From cc34b356727995c113754f84f9617f167d211790 Mon Sep 17 00:00:00 2001 From: prrao87 Date: Wed, 6 Nov 2024 18:43:23 -0500 Subject: [PATCH 01/27] Add graph documents via LLMGraphTransformer --- .../langchain_community/graphs/kuzu_graph.py | 160 +++++++++++++++++- 1 file changed, 157 insertions(+), 3 deletions(-) diff --git a/libs/community/langchain_community/graphs/kuzu_graph.py b/libs/community/langchain_community/graphs/kuzu_graph.py index 1f99f49fc9435..7fafbb17cff11 100644 --- a/libs/community/langchain_community/graphs/kuzu_graph.py +++ b/libs/community/langchain_community/graphs/kuzu_graph.py @@ -1,4 +1,7 @@ -from typing import Any, Dict, List +from hashlib import md5 +from typing import Any, Dict, List, Tuple + +from langchain_community.graphs.graph_document import GraphDocument, Relationship class KuzuGraph: @@ -57,7 +60,7 @@ def refresh_schema(self) -> None: if properties[property_name]["dimension"] > 0: if "shape" in properties[property_name]: for s in properties[property_name]["shape"]: - list_type_flag += "[%s]" % s + list_type_flag += f"[{s}]" else: for i in range(properties[property_name]["dimension"]): list_type_flag += "[]" @@ -71,7 +74,7 @@ def refresh_schema(self) -> None: rel_tables = self.conn._get_rel_table_names() for table in rel_tables: relationships.append( - "(:%s)-[:%s]->(:%s)" % (table["src"], table["name"], table["dst"]) + f"(:{table['src']})-[:{table['name']}]->(:{table['dst']})" ) rel_properties = [] @@ -93,3 +96,154 @@ def refresh_schema(self) -> None: f"Relationships properties: {rel_properties}\n" f"Relationships: {relationships}\n" ) + + def _create_chunk_node_table(self) -> None: + self.conn.execute( + """ + CREATE NODE TABLE IF NOT EXISTS Chunk ( + id STRING, + text STRING, + type STRING, + PRIMARY KEY(id) + ); + """ + ) + + def _create_entity_node_table(self, node_label: str) -> None: + self.conn.execute( + f""" + CREATE NODE TABLE IF NOT EXISTS {node_label} ( + id STRING, + type STRING, + PRIMARY KEY(id) + ); + """ + ) + + def _create_entity_relationship_table(self, rel: Relationship) -> None: + self.conn.execute( + f""" + CREATE REL TABLE IF NOT EXISTS {rel.type} ( + FROM {rel.source.type} TO {rel.target.type} + ); + """ + ) + + def add_graph_documents( + self, + graph_documents: List[GraphDocument], + allowed_relationships: List[Tuple[str, str, str]], + include_source: bool = False, + ) -> None: + """ + Adds a list of `GraphDocument` objects that represent nodes and relationships + in a graph to a Kùzu backend. + + Parameters: + - graph_documents (List[GraphDocument]): A list of `GraphDocument` objects + that contain the nodes and relationships to be added to the graph. Each + `GraphDocument` should encapsulate the structure of part of the graph, + including nodes, relationships, and the source document information. + + - allowed_relationships (List[Tuple[str, str, str]]): A list of allowed + relationships that exist in the graph. Each tuple contains three elements: + the source node type, the relationship type, and the target node type. + Required for Kùzu, as the names of the relationship tables that need to + pre-exist are derived from these tuples. + + - include_source (bool): If True, stores the source document + and links it to nodes in the graph using the `MENTIONS` relationship. + This is useful for tracing back the origin of data. Merges source + documents based on the `id` property from the source document metadata + if available; otherwise it calculates the MD5 hash of `page_content` + for merging process. Defaults to False. + """ + # Get unique node labels in the graph documents + node_labels = list( + {node.type for document in graph_documents for node in document.nodes} + ) + + for document in graph_documents: + # Add chunk nodes and create source document relationships if include_source + # is True + if include_source: + self._create_chunk_node_table() + if not document.source.metadata.get("id"): + # Add a unique id to each document chunk via an md5 hash + document.source.metadata["id"] = md5( + document.source.page_content.encode("utf-8") + ).hexdigest() + + self.conn.execute( + f""" + MERGE (c:Chunk {{id: $id}}) + SET c.text = $text, + c.type = "text_chunk" + """, + parameters={ + "id": document.source.metadata["id"], + "text": document.source.page_content, + }, + ) + + for node_label in node_labels: + self._create_entity_node_table(node_label) + + # Add entity nodes from data + for node in document.nodes: + self.conn.execute( + f""" + MERGE (e:{node.type} {{id: $id}}) + SET e.type = "entity" + """, + parameters={"id": node.id}, + ) + if include_source: + # If include_source is True, we need to create a relationship table + # between the chunk nodes and the entity nodes + self._create_chunk_node_table() + ddl = "CREATE REL TABLE GROUP IF NOT EXISTS MENTIONS (" + table_names = [] + for node_label in node_labels: + table_names.append(f"FROM Chunk TO {node_label}") + table_names = list(set(table_names)) + ddl += ", ".join(table_names) + # Add common properties for all the tables here + ddl += ", label STRING, triplet_source_id STRING)" + if ddl: + self.conn.execute(ddl) + + # Only allow relationships that exist in the schema + if node.type in node_labels: + self.conn.execute( + f""" + MATCH (c:Chunk {{id: $id}}), + (e:{node.type} {{id: $node_id}}) + MERGE (c)-[m:MENTIONS]->(e) + SET m.triplet_source_id = $id + """, + parameters={ + "id": document.source.metadata["id"], + "node_id": node.id, + }, + ) + + # Add entity relationships + for rel in document.relationships: + self._create_entity_relationship_table(rel) + # Create relationship + source_label = rel.source.type + source_id = rel.source.id + target_label = rel.target.type + target_id = rel.target.id + self.conn.execute( + f""" + MATCH (e1:{source_label} {{id: $source_id}}), + (e2:{target_label} {{id: $target_id}}) + MERGE (e1)-[:{rel.type}]->(e2) + """, + parameters={ + "source_id": source_id, + "target_id": target_id, + }, + ) From 59be82e0146197313315653a57a4241fcca9a7ba Mon Sep 17 00:00:00 2001 From: prrao87 Date: Wed, 6 Nov 2024 18:53:47 -0500 Subject: [PATCH 02/27] Fix ruff error --- libs/community/langchain_community/graphs/kuzu_graph.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/libs/community/langchain_community/graphs/kuzu_graph.py b/libs/community/langchain_community/graphs/kuzu_graph.py index 7fafbb17cff11..36b0608f1cd33 100644 --- a/libs/community/langchain_community/graphs/kuzu_graph.py +++ b/libs/community/langchain_community/graphs/kuzu_graph.py @@ -176,10 +176,10 @@ def add_graph_documents( self.conn.execute( f""" - MERGE (c:Chunk {{id: $id}}) + MERGE (c:Chunk {{id: $id}}) SET c.text = $text, c.type = "text_chunk" - """, + """, # noqa: F541 parameters={ "id": document.source.metadata["id"], "text": document.source.page_content, From 3d29ffe90def16df38a394879187ec15b7e6d383 Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 11 Nov 2024 20:52:16 +0530 Subject: [PATCH 03/27] Add new SQL Vector Store Langchain Integration --- .../docs/integrations/providers/microsoft.mdx | 26 + .../vectorstores/azuresqldb.ipynb | 680 ++++++++++++++++++ 2 files changed, 706 insertions(+) create mode 100644 docs/docs/integrations/vectorstores/azuresqldb.ipynb diff --git a/docs/docs/integrations/providers/microsoft.mdx b/docs/docs/integrations/providers/microsoft.mdx index a63c2fe898ffc..65128a42d40c9 100644 --- a/docs/docs/integrations/providers/microsoft.mdx +++ b/docs/docs/integrations/providers/microsoft.mdx @@ -343,6 +343,32 @@ See a [usage example](/docs/integrations/memory/postgres_chat_message_history/). Since Azure Database for PostgreSQL is open-source Postgres, you can use the [LangChain's Postgres support](/docs/integrations/vectorstores/pgvector/) to connect to Azure Database for PostgreSQL. +#### Azure SQL Database + +>[Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/sql-database-paas-overview?view=azuresql) provides a dedicated Vector data type & built-in functions that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity. +> By leveraging your current SQL Server databases for vector search, you can enhance data capabilities while minimizing expenses and avoiding the challenges of transitioning to new systems. + +##### Installation and Setup + +See [detail configuration instructions](/docs/integrations/vectorstores/azuresqldb). + +We need to install `langchain-sqlserver` python package. + +```bash +!pip install langchain-sqlserver==0.1.1 +``` + +##### Deploy Azure SQL DB on Microsoft Azure + +Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. + +[Sign Up](https://learn.microsoft.com/azure/azure-sql/database/free-offer?view=azuresql) for free to get started today. + +See a [usage example](/docs/integrations/vectorstores/azuresqldb). + +```python +from langchain_sqlserver import SQLServer_VectorStore + ### Azure AI Search diff --git a/docs/docs/integrations/vectorstores/azuresqldb.ipynb b/docs/docs/integrations/vectorstores/azuresqldb.ipynb new file mode 100644 index 0000000000000..af67698943fee --- /dev/null +++ b/docs/docs/integrations/vectorstores/azuresqldb.ipynb @@ -0,0 +1,680 @@ +{ + "metadata": { + "kernelspec": { + "name": "python3", + "display_name": "Python 3", + "language": "python" + }, + "language_info": { + "name": "python", + "version": "3.11.9", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 2, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Azure SQLDB Vector Store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", + "\n", + "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", + " \n", + "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", + "\n", + "This notebook shows you how to leverage this integrated SQL [vector database](https:\\devblogs.microsoft.com\\azure-sql\\exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database\\) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "Install the `langchain-sqlserver` python package.\n", + "\n", + "The code lives in an integration package called:[langchain-sqlserver](https://github.com/langchain-ai/langchain-azure/tree/main/libs/sqlserver)." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "!pip install langchain-sqlserver==0.1.1" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", + "\n", + "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "import pyodbc\r\n", + "import os\r\n", + "\r\n", + "#Define your SQLServer Connection String\r\n", + "_CONNECTION_STRING = (\r\n", + " 'Driver={ODBC Driver 18 for SQL Server};'\r\n", + " 'Server=.database.windows.net,1433;'\r\n", + " 'Database=test;'\r\n", + " 'TrustServerCertificate=yes;'\r\n", + " 'Connection Timeout=60;'\r\n", + " 'LongAsMax=yes;'\r\n", + ")\r\n", + "\r\n", + "# Connection string can vary:\r\n", + "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection\r\n", + "\r\n", + "" + ], + "metadata": { + "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", + "language": "python" + }, + "outputs": [], + "execution_count": 11 + }, + { + "cell_type": "markdown", + "source": [ + "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", + "\n", + "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "!pip install langchain-openai" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "#Import the necessary Libraries\r\n", + "from langchain_openai import AzureOpenAIEmbeddings\r\n", + "from langchain_openai import AzureChatOpenAI\r\n", + "\r\n", + "#Set your AzureOpenAI details \r\n", + "azure_endpoint = \"https://.openai.azure.com/\"\r\n", + "azure_deployment_name_embedding = \"text-embedding-3-small\"\r\n", + "azure_deployment_name_chatcompletion = \"chatcompletion\"\r\n", + "azure_api_version = \"2023-05-15\"\r\n", + "azure_api_key = \"YOUR_KEY\"\r\n", + "\r\n", + "\r\n", + "# Use AzureChatOpenAI for chat completions\r\n", + "llm = AzureChatOpenAI(\r\n", + " azure_endpoint=azure_endpoint,\r\n", + " azure_deployment=azure_deployment_name_chatcompletion,\r\n", + " openai_api_version=azure_api_version,\r\n", + " openai_api_key=azure_api_key\r\n", + ")\r\n", + "\r\n", + "# Use AzureOpenAIEmbeddings for embeddings\r\n", + "embeddings = AzureOpenAIEmbeddings(\r\n", + " azure_endpoint=azure_endpoint,\r\n", + " azure_deployment=azure_deployment_name_embedding, \r\n", + " openai_api_version=azure_api_version,\r\n", + " openai_api_key=azure_api_key\r\n", + ")" + ], + "metadata": { + "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", + "language": "python" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "## Creating Azure SQL DB Vector Search" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore\r\n", + "from langchain_community.vectorstores.utils import DistanceStrategy\r\n", + "\r\n", + "# Initialize the vector store \r\n", + "vector_store = SQLServer_VectorStore(\r\n", + " connection_string=_CONNECTION_STRING,\r\n", + " distance_strategy=DistanceStrategy.COSINE, #optional, if not provided, defaults to COSINE\r\n", + " embedding_function=embeddings, # you can use different embeddings provided in LangChain\r\n", + " embedding_length=1536,\r\n", + " table_name=\"langchain_test_table\" # using table with a custom name\r\n", + ")" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978" + }, + "outputs": [], + "execution_count": 15 + }, + { + "cell_type": "markdown", + "source": [ + "## Add items to vector store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "## we will use some artificial data for this example\r\n", + "query = [\r\n", + " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\r\n", + " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\r\n", + " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\r\n", + " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\r\n", + " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\r\n", + " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\r\n", + " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\r\n", + " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\r\n", + " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\r\n", + " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\r\n", + " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\r\n", + " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\r\n", + "]\r\n", + "\r\n", + "query_metadata = [\r\n", + " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\r\n", + " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\r\n", + " {\"id\": 4, \"summary\": \"stale product\"},\r\n", + " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\r\n", + " {\"id\": 5, \"summary\": \"Great for the kids!\"},\r\n", + " {\"id\": 2, \"summary\": \"yum falafel\"},\r\n", + " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\r\n", + " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\r\n", + " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\r\n", + " {\"id\": 7, \"summary\": \"This stuff is great\"},\r\n", + " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\r\n", + "]\r\n", + "" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f" + }, + "outputs": [], + "execution_count": 16 + }, + { + "cell_type": "code", + "source": [ + "vector_store.add_texts(texts=query, metadatas=query_metadata)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c" + }, + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 19, + "data": { + "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" + }, + "metadata": {} + } + ], + "execution_count": 19 + }, + { + "cell_type": "markdown", + "source": [ + "## Querying Data:\r\n", + "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", + "\r\n", + "Performing a simple similarity search can be done as follows:" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# Perform a similarity search between the embedding of the query and the embeddings of the documents\r\n", + "simsearch_result = vector_store.similarity_search(\"Good reviews\", k = 3)\r\n", + "print(simsearch_result)\r\n", + "" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" + } + ], + "execution_count": 28 + }, + { + "cell_type": "markdown", + "source": [ + "## Filtering Support:\r\n", + "\r\n", + "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# hybrid search -> filter for cases where id not equal to 1.\r\n", + "hybrid_simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}})\r\n", + "print(hybrid_simsearch_result)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" + } + ], + "execution_count": 29 + }, + { + "cell_type": "markdown", + "source": [ + "## Similarity Search with Score:\r\n", + "If you want to execute a similarity search and receive the corresponding scores you can run:" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "simsearch_with_score_result = vector_store.similarity_search_with_score(\"Not a very good product\", k=12)\r\n", + "print(simsearch_with_score_result)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", + "tags": [ + "hide_input" + ] + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" + } + ], + "execution_count": 30 + }, + { + "cell_type": "markdown", + "source": [ + "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Similarity Search when you already have embeddings you want to search on" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# if you already have embeddings you want to search on\r\n", + "simsearch_by_vector = vector_store.similarity_search_by_vector([-0.0033353185281157494, 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"text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" + } + ], + "execution_count": 32 + }, + { + "cell_type": "code", + "source": [ + "# Similarity Search with Score if you already have embeddings you want to search on \r\n", + "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, 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-0.00335560436360538, 0.004189011175185442, 0.010785267688333988, -0.021016057580709457, -0.019041575491428375, 0.023896636441349983, 0.03816429525613785, 0.020393960177898407, -0.01766214333474636, -0.001857838360592723, -0.009317929856479168, -0.009148881770670414, 0.007965545170009136, -0.02097548544406891, -0.013841656967997551, -0.014795088209211826, 0.014105372130870819, 0.026439119130373, -0.014822135679423809, 0.012597463093698025, 0.02151643857359886, -0.013104607351124287, 0.023883111774921417, -0.0065996372140944, -0.03521609678864479, -0.017621571198105812, 0.01887928880751133, 0.031185990199446678, 0.021827487275004387, 0.01129241194576025, 0.005663110408931971, 0.01722938008606434, -0.00519653782248497, 0.01737814210355282, -0.03272770717740059, -0.0006571743870154023, 0.008357737213373184, -0.007208209950476885, -0.01858176477253437, -0.0425189733505249, 0.002968484302982688, -0.003763010259717703, -0.0075530679896473885, 0.016188044100999832, 0.02570883184671402, -0.035351336002349854, 0.041004300117492676, 0.005193157121539116, -0.0031983896624296904, -0.006592874880880117, 0.005798349156975746, 0.02269301377236843, 0.017472809180617332, 0.02125948667526245, -0.03857000917196274, -0.005673253443092108, 0.0021857917308807373, -0.011623745784163475, 0.00370891485363245, -0.011245078407227993, -0.01391603797674179, -0.014186514541506767, -0.030131129547953606, 0.0072149718180298805, -0.007336686830967665, 0.0064711603336036205, 0.016701949760317802, 0.009831836447119713, 0.0070459237322211266, -0.003925296477973461, -0.013679370284080505, -0.022152060642838478, 0.02641207166016102, -0.01866290718317032, -0.010812315158545971, -0.004993680398911238, 0.015214326791465282, 0.00982507411390543, -0.04403364285826683, 0.0045981076546013355, 0.00671120872721076, -0.014308229088783264, -0.01016993261873722, -0.01616099663078785, 0.0003716944484040141, -0.005027489736676216, -0.009135358035564423, 0.016350330784916878, -0.02937379479408264, -0.008499737828969955, 0.02750750258564949, 0.031240085139870644, -0.006055301986634731, 0.0044932980090379715, -0.01913624256849289])\r\n", + "print(simsearch_by_vector_with_score)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" + } + ], + "execution_count": 34 + }, + { + "cell_type": "markdown", + "source": [ + "## Delete Row by ID" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# delete row by id\r\n", + "vector_store.delete([\"3\", \"7\"])" + ], + "metadata": { + "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", + "language": "python" + }, + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 35, + "data": { + "text/plain": "True" + }, + "metadata": {} + } + ], + "execution_count": 35 + }, + { + "cell_type": "markdown", + "source": [ + "## Drop Vector Store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# drop vectorstore\r\n", + "vector_store.drop()" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "# Load a Document from Azure Blob Storage" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", + "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "pip install azure-storage-blob" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "from langchain.document_loaders import AzureBlobStorageFileLoader\r\n", + "from langchain_core.documents import Document\r\n", + "from langchain.text_splitter import RecursiveCharacterTextSplitter\r\n", + "\r\n", + "# Define your connection string and blob details\r\n", + "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\r\n", + "container_name = \" Date: Mon, 11 Nov 2024 22:39:01 +0530 Subject: [PATCH 04/27] Fixing the link --- docs/docs/integrations/vectorstores/azuresqldb.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/vectorstores/azuresqldb.ipynb b/docs/docs/integrations/vectorstores/azuresqldb.ipynb index af67698943fee..62c3f272e45c9 100644 --- a/docs/docs/integrations/vectorstores/azuresqldb.ipynb +++ b/docs/docs/integrations/vectorstores/azuresqldb.ipynb @@ -41,7 +41,7 @@ " \n", "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", "\n", - "This notebook shows you how to leverage this integrated SQL [vector database](https:\\devblogs.microsoft.com\\azure-sql\\exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database\\) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" + "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" ], "metadata": { "language": "python", From 3dc753866afc0e9a60720013e967fcc127998312 Mon Sep 17 00:00:00 2001 From: Pooja Kamath <60406274+Pookam90@users.noreply.github.com> Date: Mon, 11 Nov 2024 23:49:17 +0530 Subject: [PATCH 05/27] Update microsoft.mdx Adding Vector Store SQL DB --- docs/docs/integrations/providers/microsoft.mdx | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/docs/docs/integrations/providers/microsoft.mdx b/docs/docs/integrations/providers/microsoft.mdx index 65128a42d40c9..8cc0dc423a6df 100644 --- a/docs/docs/integrations/providers/microsoft.mdx +++ b/docs/docs/integrations/providers/microsoft.mdx @@ -343,16 +343,17 @@ See a [usage example](/docs/integrations/memory/postgres_chat_message_history/). Since Azure Database for PostgreSQL is open-source Postgres, you can use the [LangChain's Postgres support](/docs/integrations/vectorstores/pgvector/) to connect to Azure Database for PostgreSQL. -#### Azure SQL Database +### Azure SQL Database ->[Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/sql-database-paas-overview?view=azuresql) provides a dedicated Vector data type & built-in functions that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity. -> By leveraging your current SQL Server databases for vector search, you can enhance data capabilities while minimizing expenses and avoiding the challenges of transitioning to new systems. +>[Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/sql-database-paas-overview?view=azuresql) is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It also provides a dedicated Vector data type & built-in functions that simplifies the storage and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity. + +By leveraging your current SQL Server databases for vector search, you can enhance data capabilities while minimizing expenses and avoiding the challenges of transitioning to new systems. ##### Installation and Setup See [detail configuration instructions](/docs/integrations/vectorstores/azuresqldb). -We need to install `langchain-sqlserver` python package. +We need to install the `langchain-sqlserver` python package. ```bash !pip install langchain-sqlserver==0.1.1 @@ -360,15 +361,13 @@ We need to install `langchain-sqlserver` python package. ##### Deploy Azure SQL DB on Microsoft Azure -Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. - [Sign Up](https://learn.microsoft.com/azure/azure-sql/database/free-offer?view=azuresql) for free to get started today. See a [usage example](/docs/integrations/vectorstores/azuresqldb). ```python from langchain_sqlserver import SQLServer_VectorStore - +``` ### Azure AI Search From ee113ecdc22811b220f87f7643471dfe4793088c Mon Sep 17 00:00:00 2001 From: hsm207 Date: Tue, 12 Nov 2024 18:13:21 +0100 Subject: [PATCH 06/27] remove outdated docs --- .../retrievers/weaviate-hybrid.ipynb | 297 ------------------ 1 file changed, 297 deletions(-) delete mode 100644 docs/docs/integrations/retrievers/weaviate-hybrid.ipynb diff --git a/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb b/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb deleted file mode 100644 index 9592435b918b1..0000000000000 --- a/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb +++ /dev/null @@ -1,297 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "ce0f17b9", - "metadata": {}, - "source": [ - "# Weaviate Hybrid Search\n", - "\n", - ">[Weaviate](https://weaviate.io/developers/weaviate) is an open-source vector database.\n", - "\n", - ">[Hybrid search](https://weaviate.io/blog/hybrid-search-explained) is a technique that combines multiple search algorithms to improve the accuracy and relevance of search results. It uses the best features of both keyword-based search algorithms with vector search techniques.\n", - "\n", - ">The `Hybrid search in Weaviate` uses sparse and dense vectors to represent the meaning and context of search queries and documents.\n", - "\n", - "This notebook shows how to use `Weaviate hybrid search` as a LangChain retriever." - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "c307b082", - "metadata": {}, - "source": [ - "Set up the retriever:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "bba863a2-977c-4add-b5f4-bfc33a80eae5", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "%pip install --upgrade --quiet weaviate-client" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "c10dd962", - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "\n", - "import weaviate\n", - "\n", - "WEAVIATE_URL = os.getenv(\"WEAVIATE_URL\")\n", - "auth_client_secret = (weaviate.AuthApiKey(api_key=os.getenv(\"WEAVIATE_API_KEY\")),)\n", - "client = weaviate.Client(\n", - " url=WEAVIATE_URL,\n", - " additional_headers={\n", - " \"X-Openai-Api-Key\": os.getenv(\"OPENAI_API_KEY\"),\n", - " },\n", - ")\n", - "\n", - "# client.schema.delete_all()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f47a2bfe", - "metadata": {}, - "outputs": [], - "source": [ - "from langchain_community.retrievers import (\n", - " WeaviateHybridSearchRetriever,\n", - ")\n", - "from langchain_core.documents import Document" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "f2eff08e", - "metadata": {}, - "outputs": [], - "source": [ - "retriever = WeaviateHybridSearchRetriever(\n", - " client=client,\n", - " index_name=\"LangChain\",\n", - " text_key=\"text\",\n", - " attributes=[],\n", - " create_schema_if_missing=True,\n", - ")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "b68debff", - "metadata": {}, - "source": [ - "Add some data:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "cd8a7b17", - "metadata": {}, - "outputs": [], - "source": [ - "docs = [\n", - " Document(\n", - " metadata={\n", - " \"title\": \"Embracing The Future: AI Unveiled\",\n", - " \"author\": \"Dr. Rebecca Simmons\",\n", - " },\n", - " page_content=\"A comprehensive analysis of the evolution of artificial intelligence, from its inception to its future prospects. Dr. Simmons covers ethical considerations, potentials, and threats posed by AI.\",\n", - " ),\n", - " Document(\n", - " metadata={\n", - " \"title\": \"Symbiosis: Harmonizing Humans and AI\",\n", - " \"author\": \"Prof. Jonathan K. Sterling\",\n", - " },\n", - " page_content=\"Prof. Sterling explores the potential for harmonious coexistence between humans and artificial intelligence. The book discusses how AI can be integrated into society in a beneficial and non-disruptive manner.\",\n", - " ),\n", - " Document(\n", - " metadata={\"title\": \"AI: The Ethical Quandary\", \"author\": \"Dr. Rebecca Simmons\"},\n", - " page_content=\"In her second book, Dr. Simmons delves deeper into the ethical considerations surrounding AI development and deployment. It is an eye-opening examination of the dilemmas faced by developers, policymakers, and society at large.\",\n", - " ),\n", - " Document(\n", - " metadata={\n", - " \"title\": \"Conscious Constructs: The Search for AI Sentience\",\n", - " \"author\": \"Dr. Samuel Cortez\",\n", - " },\n", - " page_content=\"Dr. Cortez takes readers on a journey exploring the controversial topic of AI consciousness. The book provides compelling arguments for and against the possibility of true AI sentience.\",\n", - " ),\n", - " Document(\n", - " metadata={\n", - " \"title\": \"Invisible Routines: Hidden AI in Everyday Life\",\n", - " \"author\": \"Prof. Jonathan K. Sterling\",\n", - " },\n", - " page_content=\"In his follow-up to 'Symbiosis', Prof. Sterling takes a look at the subtle, unnoticed presence and influence of AI in our everyday lives. It reveals how AI has become woven into our routines, often without our explicit realization.\",\n", - " ),\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "3c5970db", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['3a27b0a5-8dbb-4fee-9eba-8b6bc2c252be',\n", - " 'eeb9fd9b-a3ac-4d60-a55b-a63a25d3b907',\n", - " '7ebbdae7-1061-445f-a046-1989f2343d8f',\n", - " 'c2ab315b-3cab-467f-b23a-b26ed186318d',\n", - " 'b83765f2-e5d2-471f-8c02-c3350ade4c4f']" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "retriever.add_documents(docs)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "6e030694", - "metadata": {}, - "source": [ - "Do a hybrid search:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "bf7dbb98", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[Document(page_content='In her second book, Dr. Simmons delves deeper into the ethical considerations surrounding AI development and deployment. It is an eye-opening examination of the dilemmas faced by developers, policymakers, and society at large.', metadata={}),\n", - " Document(page_content='A comprehensive analysis of the evolution of artificial intelligence, from its inception to its future prospects. Dr. Simmons covers ethical considerations, potentials, and threats posed by AI.', metadata={}),\n", - " Document(page_content=\"In his follow-up to 'Symbiosis', Prof. Sterling takes a look at the subtle, unnoticed presence and influence of AI in our everyday lives. It reveals how AI has become woven into our routines, often without our explicit realization.\", metadata={}),\n", - " Document(page_content='Prof. Sterling explores the potential for harmonious coexistence between humans and artificial intelligence. The book discusses how AI can be integrated into society in a beneficial and non-disruptive manner.', metadata={})]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "retriever.invoke(\"the ethical implications of AI\")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "id": "d0c5bb4d", - "metadata": {}, - "source": [ - "Do a hybrid search with where filter:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "b2bc87c1", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[Document(page_content='Prof. Sterling explores the potential for harmonious coexistence between humans and artificial intelligence. The book discusses how AI can be integrated into society in a beneficial and non-disruptive manner.', metadata={}),\n", - " Document(page_content=\"In his follow-up to 'Symbiosis', Prof. Sterling takes a look at the subtle, unnoticed presence and influence of AI in our everyday lives. It reveals how AI has become woven into our routines, often without our explicit realization.\", metadata={})]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "retriever.invoke(\n", - " \"AI integration in society\",\n", - " where_filter={\n", - " \"path\": [\"author\"],\n", - " \"operator\": \"Equal\",\n", - " \"valueString\": \"Prof. Jonathan K. Sterling\",\n", - " },\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "5ae2899e", - "metadata": {}, - "source": [ - "Do a hybrid search with scores:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "4fffd0af", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[Document(page_content='Prof. Sterling explores the potential for harmonious coexistence between humans and artificial intelligence. The book discusses how AI can be integrated into society in a beneficial and non-disruptive manner.', metadata={'_additional': {'explainScore': '(bm25)\\n(hybrid) Document eeb9fd9b-a3ac-4d60-a55b-a63a25d3b907 contributed 0.00819672131147541 to the score\\n(hybrid) Document eeb9fd9b-a3ac-4d60-a55b-a63a25d3b907 contributed 0.00819672131147541 to the score', 'score': '0.016393442'}}),\n", - " Document(page_content=\"In his follow-up to 'Symbiosis', Prof. Sterling takes a look at the subtle, unnoticed presence and influence of AI in our everyday lives. It reveals how AI has become woven into our routines, often without our explicit realization.\", metadata={'_additional': {'explainScore': '(bm25)\\n(hybrid) Document b83765f2-e5d2-471f-8c02-c3350ade4c4f contributed 0.0078125 to the score\\n(hybrid) Document b83765f2-e5d2-471f-8c02-c3350ade4c4f contributed 0.008064516129032258 to the score', 'score': '0.015877016'}}),\n", - " Document(page_content='In her second book, Dr. Simmons delves deeper into the ethical considerations surrounding AI development and deployment. It is an eye-opening examination of the dilemmas faced by developers, policymakers, and society at large.', metadata={'_additional': {'explainScore': '(bm25)\\n(hybrid) Document 7ebbdae7-1061-445f-a046-1989f2343d8f contributed 0.008064516129032258 to the score\\n(hybrid) Document 7ebbdae7-1061-445f-a046-1989f2343d8f contributed 0.0078125 to the score', 'score': '0.015877016'}}),\n", - " Document(page_content='A comprehensive analysis of the evolution of artificial intelligence, from its inception to its future prospects. Dr. Simmons covers ethical considerations, potentials, and threats posed by AI.', metadata={'_additional': {'explainScore': '(vector) [-0.0071824766 -0.0006682752 0.001723625 -0.01897258 -0.0045127636 0.0024410256 -0.020503938 0.013768672 0.009520169 -0.037972264]... \\n(hybrid) Document 3a27b0a5-8dbb-4fee-9eba-8b6bc2c252be contributed 0.007936507936507936 to the score', 'score': '0.007936508'}})]" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "retriever.invoke(\n", - " \"AI integration in society\",\n", - " score=True,\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From dbabe41925f65cab8a1e8a19378288366eba5747 Mon Sep 17 00:00:00 2001 From: Pooja Kamath <60406274+Pookam90@users.noreply.github.com> Date: Mon, 18 Nov 2024 10:52:37 +0530 Subject: [PATCH 07/27] Update FeatureTables.js Adding SQLServer Vector Store to the Index Table --- docs/src/theme/FeatureTables.js | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/docs/src/theme/FeatureTables.js b/docs/src/theme/FeatureTables.js index 7217c245a12c9..a617395cf6d54 100644 --- a/docs/src/theme/FeatureTables.js +++ b/docs/src/theme/FeatureTables.js @@ -1115,6 +1115,19 @@ const FEATURE_TABLES = { local: true, idsInAddDocuments: false, }, + { + name: "SQLServer", + link: "azuresqldb", + deleteById: true, + filtering: true, + searchByVector: true, + searchWithScore: true, + async: false, + passesStandardTests: false, + multiTenancy: false, + local: false, + idsInAddDocuments: false, + }, { name: "Weaviate", link: "weaviate", From f2994b0be845548ea4630fcaf7f0589526046b97 Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 11:27:10 +0530 Subject: [PATCH 08/27] Adding sqlserver vectorstore --- .../vectorstores/azuresqldb.ipynb | 160 +++- .../integrations/vectorstores/sqlserver.ipynb | 834 ++++++++++++++++++ 2 files changed, 991 insertions(+), 3 deletions(-) create mode 100644 docs/docs/integrations/vectorstores/sqlserver.ipynb diff --git a/docs/docs/integrations/vectorstores/azuresqldb.ipynb b/docs/docs/integrations/vectorstores/azuresqldb.ipynb index 62c3f272e45c9..ecce9b6e2ae28 100644 --- a/docs/docs/integrations/vectorstores/azuresqldb.ipynb +++ b/docs/docs/integrations/vectorstores/azuresqldb.ipynb @@ -52,9 +52,11 @@ { "cell_type": "markdown", "source": [ + "## Setup & Installation \n", + " \n", "Install the `langchain-sqlserver` python package.\n", "\n", - "The code lives in an integration package called:[langchain-sqlserver](https://github.com/langchain-ai/langchain-azure/tree/main/libs/sqlserver)." + "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." ], "metadata": { "language": "python", @@ -74,6 +76,18 @@ "outputs": [], "execution_count": null }, + { + "cell_type": "code", + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6" + }, + "outputs": [], + "execution_count": null + }, { "cell_type": "markdown", "source": [ @@ -184,7 +198,7 @@ { "cell_type": "markdown", "source": [ - "## Creating Azure SQL DB Vector Search" + "## Manage vector store :  Creating SQL DB Vector Search" ], "metadata": { "language": "python", @@ -652,12 +666,152 @@ ], "execution_count": 46 }, + { + "cell_type": "markdown", + "source": [ + "## Usage for retrieval-augmented generation\n", + "\n", + "## Use Case 1: Q&A System based on the Story Book\n", + "\n", + "The Q&A function allows users to ask specific questions about the story, characters, and events, and get concise, context-rich answers. This not only enhances their understanding of the books but also makes them feel like they're part of the magical universe.\n", + "\n", + "### **Query by turning into retriever**\n", + "\n", + "The LangChain Vector store simplifies building sophisticated Q&A systems by enabling efficient similarity searches to find the top 10 relevant documents based on the user's query. The **retriever** is created from the **vector\\_store,** and the question-answer chain is built using the **create\\_stuff\\_documents\\_chain** function. A prompt template is crafted using the **ChatPromptTemplate** class, ensuring structured and context-rich responses. Often in Q&A applications it's important to show users the sources that were used to generate the answer. LangChain's built-in **create\\_retrieval\\_chain** will propagate retrieved source documents to the output under the \"context\" key:\n", + "\n", + "Read more about Langchain RAG tutorials & the terminologies mentioned above [here](https:\\python.langchain.com\\docs\\tutorials\\rag\\)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "13ca400b-7883-45af-9e17-75f2f622dde1" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "import pandas as pd\r\n", + "from langchain_core.prompts import ChatPromptTemplate\r\n", + "from typing import List, Tuple\r\n", + "from langchain.chains import create_retrieval_chain\r\n", + "from langchain.chains.combine_documents import create_stuff_documents_chain\r\n", + "\r\n", + "# Define the function to perform the RAG chain invocation \r\n", + "def get_answer_and_sources(user_query: str):\r\n", + " # Perform similarity search with scores\r\n", + " docs_with_score: List[Tuple[Document, float]] = vector_store.similarity_search_with_score(\r\n", + " user_query, \r\n", + " k=10, \r\n", + " )\r\n", + "\r\n", + " # Extract the context from the top results\r\n", + " context = \"\\n\".join([doc.page_content for doc, score in docs_with_score])\r\n", + "\r\n", + " # Define the system prompt\r\n", + " system_prompt = (\r\n", + " \"You are an assistant for question-answering tasks based on the story in the book. \"\r\n", + " \"Use the following pieces of retrieved context to answer the question. \"\r\n", + " \"If you don't know the answer, say that you don't know, but also suggest that the user can use the fan fiction function to generate fun stories. \"\r\n", + " \"Use 5 sentences maximum and keep the answer concise by also providing some background context of 1-2 sentences.\"\r\n", + " \"\\n\\n\"\r\n", + " \"{context}\"\r\n", + " )\r\n", + "\r\n", + " # Create the prompt template\r\n", + " prompt = ChatPromptTemplate.from_messages(\r\n", + " [\r\n", + " (\"system\", system_prompt),\r\n", + " (\"human\", \"{input}\"),\r\n", + " ]\r\n", + " )\r\n", + "\r\n", + " # Create the retriever and chains\r\n", + " retriever = vector_store.as_retriever()\r\n", + " question_answer_chain = create_stuff_documents_chain(llm, prompt)\r\n", + " rag_chain = create_retrieval_chain(retriever, question_answer_chain)\r\n", + "\r\n", + " # Define the input\r\n", + " input_data = {\"input\": user_query}\r\n", + "\r\n", + " # Invoke the RAG chain\r\n", + " response = rag_chain.invoke(input_data)\r\n", + "\r\n", + " # Print the answer\r\n", + " print(\"Answer:\", response[\"answer\"])\r\n", + "\r\n", + " \r\n", + " # Prepare the data for the table\r\n", + " data = {\r\n", + " \"Doc ID\": [doc.metadata.get(\"source\", \"N/A\").split('/')[-1] for doc in response[\"context\"]],\r\n", + " \"Content\": [doc.page_content[:50] + \"...\" if len(doc.page_content) > 100 else doc.page_content for doc in response[\"context\"]],\r\n", + " }\r\n", + "\r\n", + "\r\n", + " # Create a DataFrame\r\n", + " df = pd.DataFrame(data)\r\n", + "\r\n", + " # Print the table\r\n", + " print(\"\\nSources:\")\r\n", + " print(df.to_markdown(index=False))" + ], + "metadata": { + "azdata_cell_guid": "b60a1f0a-a767-413a-a537-61103439a26e", + "language": "python" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "# Define the user query\r\n", + "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\r\n", + "\r\n", + "# Call the function to get the answer and sources\r\n", + "get_answer_and_sources(user_query)" + ], + "metadata": { + "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", + "language": "python", + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n", + "output_type": "stream" + } + ], + "execution_count": 1 + }, + { + "cell_type": "code", + "source": [ + "# Define the user query\r\n", + "user_query = \"Did Harry have a pet? What was it\"\r\n", + "\r\n", + "# Call the function to get the answer and sources\r\n", + "get_answer_and_sources(user_query)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b" + }, + "outputs": [ + { + "name": "stdout", + "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n", + "output_type": "stream" + } + ], + "execution_count": 2 + }, { "cell_type": "markdown", "source": [ "## API reference \n", "\n", - "For detailed documentation of all \\_\\_ModuleName\\_\\_VectorStore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" + "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" ], "metadata": { "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb new file mode 100644 index 0000000000000..ecce9b6e2ae28 --- /dev/null +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -0,0 +1,834 @@ +{ + "metadata": { + "kernelspec": { + "name": "python3", + "display_name": "Python 3", + "language": "python" + }, + "language_info": { + "name": "python", + "version": "3.11.9", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 2, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Azure SQLDB Vector Store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", + "\n", + "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", + " \n", + "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", + "\n", + "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Setup & Installation \n", + " \n", + "Install the `langchain-sqlserver` python package.\n", + "\n", + "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "!pip install langchain-sqlserver==0.1.1" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", + "\n", + "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "import pyodbc\r\n", + "import os\r\n", + "\r\n", + "#Define your SQLServer Connection String\r\n", + "_CONNECTION_STRING = (\r\n", + " 'Driver={ODBC Driver 18 for SQL Server};'\r\n", + " 'Server=.database.windows.net,1433;'\r\n", + " 'Database=test;'\r\n", + " 'TrustServerCertificate=yes;'\r\n", + " 'Connection Timeout=60;'\r\n", + " 'LongAsMax=yes;'\r\n", + ")\r\n", + "\r\n", + "# Connection string can vary:\r\n", + "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection\r\n", + "\r\n", + "" + ], + "metadata": { + "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", + "language": "python" + }, + "outputs": [], + "execution_count": 11 + }, + { + "cell_type": "markdown", + "source": [ + "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", + "\n", + "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "!pip install langchain-openai" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "#Import the necessary Libraries\r\n", + "from langchain_openai import AzureOpenAIEmbeddings\r\n", + "from langchain_openai import AzureChatOpenAI\r\n", + "\r\n", + "#Set your AzureOpenAI details \r\n", + "azure_endpoint = \"https://.openai.azure.com/\"\r\n", + "azure_deployment_name_embedding = \"text-embedding-3-small\"\r\n", + "azure_deployment_name_chatcompletion = \"chatcompletion\"\r\n", + "azure_api_version = \"2023-05-15\"\r\n", + "azure_api_key = \"YOUR_KEY\"\r\n", + "\r\n", + "\r\n", + "# Use AzureChatOpenAI for chat completions\r\n", + "llm = AzureChatOpenAI(\r\n", + " azure_endpoint=azure_endpoint,\r\n", + " azure_deployment=azure_deployment_name_chatcompletion,\r\n", + " openai_api_version=azure_api_version,\r\n", + " openai_api_key=azure_api_key\r\n", + ")\r\n", + "\r\n", + "# Use AzureOpenAIEmbeddings for embeddings\r\n", + "embeddings = AzureOpenAIEmbeddings(\r\n", + " azure_endpoint=azure_endpoint,\r\n", + " azure_deployment=azure_deployment_name_embedding, \r\n", + " openai_api_version=azure_api_version,\r\n", + " openai_api_key=azure_api_key\r\n", + ")" + ], + "metadata": { + "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", + "language": "python" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "## Manage vector store :  Creating SQL DB Vector Search" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore\r\n", + "from langchain_community.vectorstores.utils import DistanceStrategy\r\n", + "\r\n", + "# Initialize the vector store \r\n", + "vector_store = SQLServer_VectorStore(\r\n", + " connection_string=_CONNECTION_STRING,\r\n", + " distance_strategy=DistanceStrategy.COSINE, #optional, if not provided, defaults to COSINE\r\n", + " embedding_function=embeddings, # you can use different embeddings provided in LangChain\r\n", + " embedding_length=1536,\r\n", + " table_name=\"langchain_test_table\" # using table with a custom name\r\n", + ")" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978" + }, + "outputs": [], + "execution_count": 15 + }, + { + "cell_type": "markdown", + "source": [ + "## Add items to vector store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "## we will use some artificial data for this example\r\n", + "query = [\r\n", + " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\r\n", + " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\r\n", + " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\r\n", + " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\r\n", + " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\r\n", + " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\r\n", + " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\r\n", + " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\r\n", + " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\r\n", + " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\r\n", + " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\r\n", + " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\r\n", + "]\r\n", + "\r\n", + "query_metadata = [\r\n", + " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\r\n", + " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\r\n", + " {\"id\": 4, \"summary\": \"stale product\"},\r\n", + " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\r\n", + " {\"id\": 5, \"summary\": \"Great for the kids!\"},\r\n", + " {\"id\": 2, \"summary\": \"yum falafel\"},\r\n", + " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\r\n", + " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\r\n", + " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\r\n", + " {\"id\": 7, \"summary\": \"This stuff is great\"},\r\n", + " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\r\n", + "]\r\n", + "" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f" + }, + "outputs": [], + "execution_count": 16 + }, + { + "cell_type": "code", + "source": [ + "vector_store.add_texts(texts=query, metadatas=query_metadata)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c" + }, + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 19, + "data": { + "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" + }, + "metadata": {} + } + ], + "execution_count": 19 + }, + { + "cell_type": "markdown", + "source": [ + "## Querying Data:\r\n", + "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", + "\r\n", + "Performing a simple similarity search can be done as follows:" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# Perform a similarity search between the embedding of the query and the embeddings of the documents\r\n", + "simsearch_result = vector_store.similarity_search(\"Good reviews\", k = 3)\r\n", + "print(simsearch_result)\r\n", + "" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" + } + ], + "execution_count": 28 + }, + { + "cell_type": "markdown", + "source": [ + "## Filtering Support:\r\n", + "\r\n", + "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# hybrid search -> filter for cases where id not equal to 1.\r\n", + "hybrid_simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}})\r\n", + "print(hybrid_simsearch_result)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" + } + ], + "execution_count": 29 + }, + { + "cell_type": "markdown", + "source": [ + "## Similarity Search with Score:\r\n", + "If you want to execute a similarity search and receive the corresponding scores you can run:" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "simsearch_with_score_result = vector_store.similarity_search_with_score(\"Not a very good product\", k=12)\r\n", + "print(simsearch_with_score_result)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", + "tags": [ + "hide_input" + ] + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" + } + ], + "execution_count": 30 + }, + { + "cell_type": "markdown", + "source": [ + "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Similarity Search when you already have embeddings you want to search on" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# if you already have embeddings you want to search on\r\n", + "simsearch_by_vector = vector_store.similarity_search_by_vector([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, -0.009446406736969948, 0.007444877177476883, -0.009277358651161194, -0.025289593264460564, -0.02119186706840992, -0.005906539969146252, -0.018906336277723312, -0.007539544254541397, -0.016066329553723335, -0.01171841286122799, -0.02093491330742836, 0.004608250688761473, 0.011042220517992973, 0.011549364775419235, -0.009541073814034462, 0.0025864355266094208, 0.0026202453300356865, -0.0036007240414619446, -0.011995651759207249, -0.02549245022237301, -0.007958783768117428, 0.015701185911893845, 0.016188044100999832, -0.005825396627187729, -0.00866878591477871, -0.00038881058571860194, -0.0006356207886710763, 0.0074110678397119045, 0.00766802066937089, -0.005419681314378977, -0.007674783002585173, 0.0086823096498847, -0.004740108270198107, -0.01406479999423027, 0.02170577272772789, -0.0029955320060253143, -0.008574118837714195, 0.005460252985358238, 0.0034130807034671307, -0.005521110258996487, 0.0045507741160690784, 0.03662257641553879, -0.004141678102314472, 0.004442583303898573, -0.0035026762634515762, 0.0021316963247954845, -0.009297644719481468, -0.032186754047870636, 0.01478156354278326, -0.0016355401603505015, -0.005835539661347866, 0.03253837302327156, -0.040301062166690826, -0.0090339295566082, -0.001611873391084373, 0.018703479319810867, -0.00610601669177413, -0.016323283314704895, 0.002358220750465989, -0.004118011333048344, 0.005784825421869755, 0.01579585298895836, 0.028886936604976654, -0.004111249465495348, 0.020475102588534355, -0.0360545739531517, 0.0018696717452257872, 0.0039658681489527225, 0.026723120361566544, -0.011177458800375462, -0.03759629279375076, 0.0012501105666160583, 0.007478686980903149, -0.03445876017212868, -0.011130125261843204, -0.019677195698022842, -0.004784060642123222, 0.01866290718317032, 0.0013667537132278085, 0.015417184680700302, -0.01467337366193533, -0.010109075345098972, 0.03976010903716087, 0.02482978254556656, -0.045196693390607834, -0.02562768943607807, -0.0017614809330552816, -0.0002624471380840987, -0.006839685142040253, 0.005757777485996485, -0.001704004593193531, 0.020650913938879967, 0.021841011941432953, 0.045845840126276016, 0.00012234854511916637, -0.0019170051673427224, 0.006082349922508001, -0.027940265834331512, 0.005524491425603628, -0.002109719906002283, 0.011393840424716473, 0.036784861236810684, 0.019257957115769386, 0.0018020524876192212, 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"text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" + } + ], + "execution_count": 32 + }, + { + "cell_type": "code", + "source": [ + "# Similarity Search with Score if you already have embeddings you want to search on \r\n", + "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, 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-0.008499737828969955, 0.02750750258564949, 0.031240085139870644, -0.006055301986634731, 0.0044932980090379715, -0.01913624256849289])\r\n", + "print(simsearch_by_vector_with_score)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" + } + ], + "execution_count": 34 + }, + { + "cell_type": "markdown", + "source": [ + "## Delete Row by ID" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# delete row by id\r\n", + "vector_store.delete([\"3\", \"7\"])" + ], + "metadata": { + "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", + "language": "python" + }, + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 35, + "data": { + "text/plain": "True" + }, + "metadata": {} + } + ], + "execution_count": 35 + }, + { + "cell_type": "markdown", + "source": [ + "## Drop Vector Store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# drop vectorstore\r\n", + "vector_store.drop()" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "# Load a Document from Azure Blob Storage" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", + "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "pip install azure-storage-blob" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "from langchain.document_loaders import AzureBlobStorageFileLoader\r\n", + "from langchain_core.documents import Document\r\n", + "from langchain.text_splitter import RecursiveCharacterTextSplitter\r\n", + "\r\n", + "# Define your connection string and blob details\r\n", + "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\r\n", + "container_name = \" 100 else doc.page_content for doc in response[\"context\"]],\r\n", + " }\r\n", + "\r\n", + "\r\n", + " # Create a DataFrame\r\n", + " df = pd.DataFrame(data)\r\n", + "\r\n", + " # Print the table\r\n", + " print(\"\\nSources:\")\r\n", + " print(df.to_markdown(index=False))" + ], + "metadata": { + "azdata_cell_guid": "b60a1f0a-a767-413a-a537-61103439a26e", + "language": "python" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "# Define the user query\r\n", + "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\r\n", + "\r\n", + "# Call the function to get the answer and sources\r\n", + "get_answer_and_sources(user_query)" + ], + "metadata": { + "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", + "language": "python", + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n", + "output_type": "stream" + } + ], + "execution_count": 1 + }, + { + "cell_type": "code", + "source": [ + "# Define the user query\r\n", + "user_query = \"Did Harry have a pet? What was it\"\r\n", + "\r\n", + "# Call the function to get the answer and sources\r\n", + "get_answer_and_sources(user_query)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b" + }, + "outputs": [ + { + "name": "stdout", + "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n", + "output_type": "stream" + } + ], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "source": [ + "## API reference \n", + "\n", + "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" + ], + "metadata": { + "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Related\r\n", + "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", + "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" + ], + "metadata": { + "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" + }, + "attachments": {} + } + ] +} \ No newline at end of file From ca91673889f5322070737299dc5463f8b120ef5c Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 11:27:40 +0530 Subject: [PATCH 09/27] Adding SQLserver vector store --- docs/docs/integrations/vectorstores/sqlserver.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index ecce9b6e2ae28..726012b071fb6 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -24,7 +24,7 @@ { "cell_type": "markdown", "source": [ - "# Azure SQLDB Vector Store" + "# SQL Server Vector Store" ], "metadata": { "language": "python", @@ -777,9 +777,9 @@ }, "outputs": [ { + "output_type": "stream", "name": "stdout", - "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n", - "output_type": "stream" + "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" } ], "execution_count": 1 @@ -799,9 +799,9 @@ }, "outputs": [ { + "output_type": "stream", "name": "stdout", - "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n", - "output_type": "stream" + "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" } ], "execution_count": 2 From ec7fee0e75660a2e4dbbfaaf359e07124fa08c3a Mon Sep 17 00:00:00 2001 From: Pooja Kamath <60406274+Pookam90@users.noreply.github.com> Date: Mon, 18 Nov 2024 11:29:24 +0530 Subject: [PATCH 10/27] Update FeatureTables.js adding sqlserver vectore store matrix --- docs/src/theme/FeatureTables.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/src/theme/FeatureTables.js b/docs/src/theme/FeatureTables.js index a617395cf6d54..134b939aa4af4 100644 --- a/docs/src/theme/FeatureTables.js +++ b/docs/src/theme/FeatureTables.js @@ -1117,7 +1117,7 @@ const FEATURE_TABLES = { }, { name: "SQLServer", - link: "azuresqldb", + link: "sqlserver", deleteById: true, filtering: true, searchByVector: true, From 3aa803307481b171d2932a9d358b80251256a430 Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 11:31:05 +0530 Subject: [PATCH 11/27] Adding SQL Server Vector store to MSFT integrations --- docs/docs/integrations/providers/microsoft.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/docs/integrations/providers/microsoft.mdx b/docs/docs/integrations/providers/microsoft.mdx index 8cc0dc423a6df..518d4869d47f2 100644 --- a/docs/docs/integrations/providers/microsoft.mdx +++ b/docs/docs/integrations/providers/microsoft.mdx @@ -351,7 +351,7 @@ By leveraging your current SQL Server databases for vector search, you can enhan ##### Installation and Setup -See [detail configuration instructions](/docs/integrations/vectorstores/azuresqldb). +See [detail configuration instructions](/docs/integrations/vectorstores/sqlserver). We need to install the `langchain-sqlserver` python package. @@ -363,7 +363,7 @@ We need to install the `langchain-sqlserver` python package. [Sign Up](https://learn.microsoft.com/azure/azure-sql/database/free-offer?view=azuresql) for free to get started today. -See a [usage example](/docs/integrations/vectorstores/azuresqldb). +See a [usage example](/docs/integrations/vectorstores/sqlserver). ```python from langchain_sqlserver import SQLServer_VectorStore From 68c6e08cbf44a27444826efa0b35d514dd2bd83f Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 11:34:03 +0530 Subject: [PATCH 12/27] Removing AzureSQL and replacing with SQLServer --- .../vectorstores/azuresqldb.ipynb | 834 ------------------ 1 file changed, 834 deletions(-) delete mode 100644 docs/docs/integrations/vectorstores/azuresqldb.ipynb diff --git a/docs/docs/integrations/vectorstores/azuresqldb.ipynb b/docs/docs/integrations/vectorstores/azuresqldb.ipynb deleted file mode 100644 index ecce9b6e2ae28..0000000000000 --- a/docs/docs/integrations/vectorstores/azuresqldb.ipynb +++ /dev/null @@ -1,834 +0,0 @@ -{ - "metadata": { - "kernelspec": { - "name": "python3", - "display_name": "Python 3", - "language": "python" - }, - "language_info": { - "name": "python", - "version": "3.11.9", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" - } - }, - "nbformat_minor": 2, - "nbformat": 4, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# Azure SQLDB Vector Store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", - "\n", - "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", - " \n", - "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", - "\n", - "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Setup & Installation \n", - " \n", - "Install the `langchain-sqlserver` python package.\n", - "\n", - "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "!pip install langchain-sqlserver==0.1.1" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "from langchain_sqlserver import SQLServer_VectorStore" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", - "\n", - "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "import pyodbc\r\n", - "import os\r\n", - "\r\n", - "#Define your SQLServer Connection String\r\n", - "_CONNECTION_STRING = (\r\n", - " 'Driver={ODBC Driver 18 for SQL Server};'\r\n", - " 'Server=.database.windows.net,1433;'\r\n", - " 'Database=test;'\r\n", - " 'TrustServerCertificate=yes;'\r\n", - " 'Connection Timeout=60;'\r\n", - " 'LongAsMax=yes;'\r\n", - ")\r\n", - "\r\n", - "# Connection string can vary:\r\n", - "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection\r\n", - "\r\n", - "" - ], - "metadata": { - "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", - "language": "python" - }, - "outputs": [], - "execution_count": 11 - }, - { - "cell_type": "markdown", - "source": [ - "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", - "\n", - "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "!pip install langchain-openai" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "#Import the necessary Libraries\r\n", - "from langchain_openai import AzureOpenAIEmbeddings\r\n", - "from langchain_openai import AzureChatOpenAI\r\n", - "\r\n", - "#Set your AzureOpenAI details \r\n", - "azure_endpoint = \"https://.openai.azure.com/\"\r\n", - "azure_deployment_name_embedding = \"text-embedding-3-small\"\r\n", - "azure_deployment_name_chatcompletion = \"chatcompletion\"\r\n", - "azure_api_version = \"2023-05-15\"\r\n", - "azure_api_key = \"YOUR_KEY\"\r\n", - "\r\n", - "\r\n", - "# Use AzureChatOpenAI for chat completions\r\n", - "llm = AzureChatOpenAI(\r\n", - " azure_endpoint=azure_endpoint,\r\n", - " azure_deployment=azure_deployment_name_chatcompletion,\r\n", - " openai_api_version=azure_api_version,\r\n", - " openai_api_key=azure_api_key\r\n", - ")\r\n", - "\r\n", - "# Use AzureOpenAIEmbeddings for embeddings\r\n", - "embeddings = AzureOpenAIEmbeddings(\r\n", - " azure_endpoint=azure_endpoint,\r\n", - " azure_deployment=azure_deployment_name_embedding, \r\n", - " openai_api_version=azure_api_version,\r\n", - " openai_api_key=azure_api_key\r\n", - ")" - ], - "metadata": { - "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", - "language": "python" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "## Manage vector store :  Creating SQL DB Vector Search" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "from langchain_sqlserver import SQLServer_VectorStore\r\n", - "from langchain_community.vectorstores.utils import DistanceStrategy\r\n", - "\r\n", - "# Initialize the vector store \r\n", - "vector_store = SQLServer_VectorStore(\r\n", - " connection_string=_CONNECTION_STRING,\r\n", - " distance_strategy=DistanceStrategy.COSINE, #optional, if not provided, defaults to COSINE\r\n", - " embedding_function=embeddings, # you can use different embeddings provided in LangChain\r\n", - " embedding_length=1536,\r\n", - " table_name=\"langchain_test_table\" # using table with a custom name\r\n", - ")" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978" - }, - "outputs": [], - "execution_count": 15 - }, - { - "cell_type": "markdown", - "source": [ - "## Add items to vector store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "## we will use some artificial data for this example\r\n", - "query = [\r\n", - " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\r\n", - " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\r\n", - " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\r\n", - " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\r\n", - " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\r\n", - " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\r\n", - " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\r\n", - " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\r\n", - " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\r\n", - " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\r\n", - " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\r\n", - " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\r\n", - "]\r\n", - "\r\n", - "query_metadata = [\r\n", - " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\r\n", - " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\r\n", - " {\"id\": 4, \"summary\": \"stale product\"},\r\n", - " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\r\n", - " {\"id\": 5, \"summary\": \"Great for the kids!\"},\r\n", - " {\"id\": 2, \"summary\": \"yum falafel\"},\r\n", - " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\r\n", - " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\r\n", - " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\r\n", - " {\"id\": 7, \"summary\": \"This stuff is great\"},\r\n", - " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\r\n", - "]\r\n", - "" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f" - }, - "outputs": [], - "execution_count": 16 - }, - { - "cell_type": "code", - "source": [ - "vector_store.add_texts(texts=query, metadatas=query_metadata)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c" - }, - "outputs": [ - { - "output_type": "execute_result", - "execution_count": 19, - "data": { - "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" - }, - "metadata": {} - } - ], - "execution_count": 19 - }, - { - "cell_type": "markdown", - "source": [ - "## Querying Data:\r\n", - "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", - "\r\n", - "Performing a simple similarity search can be done as follows:" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# Perform a similarity search between the embedding of the query and the embeddings of the documents\r\n", - "simsearch_result = vector_store.similarity_search(\"Good reviews\", k = 3)\r\n", - "print(simsearch_result)\r\n", - "" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" - } - ], - "execution_count": 28 - }, - { - "cell_type": "markdown", - "source": [ - "## Filtering Support:\r\n", - "\r\n", - "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# hybrid search -> filter for cases where id not equal to 1.\r\n", - "hybrid_simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}})\r\n", - "print(hybrid_simsearch_result)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" - } - ], - "execution_count": 29 - }, - { - "cell_type": "markdown", - "source": [ - "## Similarity Search with Score:\r\n", - "If you want to execute a similarity search and receive the corresponding scores you can run:" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "simsearch_with_score_result = vector_store.similarity_search_with_score(\"Not a very good product\", k=12)\r\n", - "print(simsearch_with_score_result)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", - "tags": [ - "hide_input" - ] - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" - } - ], - "execution_count": 30 - }, - { - "cell_type": "markdown", - "source": [ - "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Similarity Search when you already have embeddings you want to search on" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# if you already have embeddings you want to search on\r\n", - "simsearch_by_vector = vector_store.similarity_search_by_vector([-0.0033353185281157494, 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"text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" - } - ], - "execution_count": 32 - }, - { - "cell_type": "code", - "source": [ - "# Similarity Search with Score if you already have embeddings you want to search on \r\n", - "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, 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-0.008499737828969955, 0.02750750258564949, 0.031240085139870644, -0.006055301986634731, 0.0044932980090379715, -0.01913624256849289])\r\n", - "print(simsearch_by_vector_with_score)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" - } - ], - "execution_count": 34 - }, - { - "cell_type": "markdown", - "source": [ - "## Delete Row by ID" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# delete row by id\r\n", - "vector_store.delete([\"3\", \"7\"])" - ], - "metadata": { - "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", - "language": "python" - }, - "outputs": [ - { - "output_type": "execute_result", - "execution_count": 35, - "data": { - "text/plain": "True" - }, - "metadata": {} - } - ], - "execution_count": 35 - }, - { - "cell_type": "markdown", - "source": [ - "## Drop Vector Store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# drop vectorstore\r\n", - "vector_store.drop()" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "# Load a Document from Azure Blob Storage" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", - "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "pip install azure-storage-blob" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "from langchain.document_loaders import AzureBlobStorageFileLoader\r\n", - "from langchain_core.documents import Document\r\n", - "from langchain.text_splitter import RecursiveCharacterTextSplitter\r\n", - "\r\n", - "# Define your connection string and blob details\r\n", - "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\r\n", - "container_name = \" 100 else doc.page_content for doc in response[\"context\"]],\r\n", - " }\r\n", - "\r\n", - "\r\n", - " # Create a DataFrame\r\n", - " df = pd.DataFrame(data)\r\n", - "\r\n", - " # Print the table\r\n", - " print(\"\\nSources:\")\r\n", - " print(df.to_markdown(index=False))" - ], - "metadata": { - "azdata_cell_guid": "b60a1f0a-a767-413a-a537-61103439a26e", - "language": "python" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "# Define the user query\r\n", - "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\r\n", - "\r\n", - "# Call the function to get the answer and sources\r\n", - "get_answer_and_sources(user_query)" - ], - "metadata": { - "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", - "language": "python", - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n", - "output_type": "stream" - } - ], - "execution_count": 1 - }, - { - "cell_type": "code", - "source": [ - "# Define the user query\r\n", - "user_query = \"Did Harry have a pet? What was it\"\r\n", - "\r\n", - "# Call the function to get the answer and sources\r\n", - "get_answer_and_sources(user_query)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b" - }, - "outputs": [ - { - "name": "stdout", - "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n", - "output_type": "stream" - } - ], - "execution_count": 2 - }, - { - "cell_type": "markdown", - "source": [ - "## API reference \n", - "\n", - "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" - ], - "metadata": { - "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Related\r\n", - "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", - "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" - ], - "metadata": { - "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" - }, - "attachments": {} - } - ] -} \ No newline at end of file From 4ee2b8fe152e46acbe3fed05f6b55268bd1dd0bd Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 13:18:38 +0530 Subject: [PATCH 13/27] Adding sqlserver vector store with makeformat,lint --- .../integrations/vectorstores/sqlserver.ipynb | 4753 ++++++++++++++--- 1 file changed, 3922 insertions(+), 831 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index 726012b071fb6..2ae56d9e41667 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -1,834 +1,3925 @@ { - "metadata": { - "kernelspec": { - "name": "python3", - "display_name": "Python 3", - "language": "python" - }, - "language_info": { - "name": "python", - "version": "3.11.9", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" - } - }, - "nbformat_minor": 2, - "nbformat": 4, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# SQL Server Vector Store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", - "\n", - "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", - " \n", - "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", - "\n", - "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Setup & Installation \n", - " \n", - "Install the `langchain-sqlserver` python package.\n", - "\n", - "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "!pip install langchain-sqlserver==0.1.1" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "from langchain_sqlserver import SQLServer_VectorStore" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", - "\n", - "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "import pyodbc\r\n", - "import os\r\n", - "\r\n", - "#Define your SQLServer Connection String\r\n", - "_CONNECTION_STRING = (\r\n", - " 'Driver={ODBC Driver 18 for SQL Server};'\r\n", - " 'Server=.database.windows.net,1433;'\r\n", - " 'Database=test;'\r\n", - " 'TrustServerCertificate=yes;'\r\n", - " 'Connection Timeout=60;'\r\n", - " 'LongAsMax=yes;'\r\n", - ")\r\n", - "\r\n", - "# Connection string can vary:\r\n", - "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection\r\n", - "\r\n", - "" - ], - "metadata": { - "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", - "language": "python" - }, - "outputs": [], - "execution_count": 11 - }, - { - "cell_type": "markdown", - "source": [ - "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", - "\n", - "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "!pip install langchain-openai" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "#Import the necessary Libraries\r\n", - "from langchain_openai import AzureOpenAIEmbeddings\r\n", - "from langchain_openai import AzureChatOpenAI\r\n", - "\r\n", - "#Set your AzureOpenAI details \r\n", - "azure_endpoint = \"https://.openai.azure.com/\"\r\n", - "azure_deployment_name_embedding = \"text-embedding-3-small\"\r\n", - "azure_deployment_name_chatcompletion = \"chatcompletion\"\r\n", - "azure_api_version = \"2023-05-15\"\r\n", - "azure_api_key = \"YOUR_KEY\"\r\n", - "\r\n", - "\r\n", - "# Use AzureChatOpenAI for chat completions\r\n", - "llm = AzureChatOpenAI(\r\n", - " azure_endpoint=azure_endpoint,\r\n", - " azure_deployment=azure_deployment_name_chatcompletion,\r\n", - " openai_api_version=azure_api_version,\r\n", - " openai_api_key=azure_api_key\r\n", - ")\r\n", - "\r\n", - "# Use AzureOpenAIEmbeddings for embeddings\r\n", - "embeddings = AzureOpenAIEmbeddings(\r\n", - " azure_endpoint=azure_endpoint,\r\n", - " azure_deployment=azure_deployment_name_embedding, \r\n", - " openai_api_version=azure_api_version,\r\n", - " openai_api_key=azure_api_key\r\n", - ")" - ], - "metadata": { - "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", - "language": "python" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "## Manage vector store :  Creating SQL DB Vector Search" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "from langchain_sqlserver import SQLServer_VectorStore\r\n", - "from langchain_community.vectorstores.utils import DistanceStrategy\r\n", - "\r\n", - "# Initialize the vector store \r\n", - "vector_store = SQLServer_VectorStore(\r\n", - " connection_string=_CONNECTION_STRING,\r\n", - " distance_strategy=DistanceStrategy.COSINE, #optional, if not provided, defaults to COSINE\r\n", - " embedding_function=embeddings, # you can use different embeddings provided in LangChain\r\n", - " embedding_length=1536,\r\n", - " table_name=\"langchain_test_table\" # using table with a custom name\r\n", - ")" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978" - }, - "outputs": [], - "execution_count": 15 - }, - { - "cell_type": "markdown", - "source": [ - "## Add items to vector store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "## we will use some artificial data for this example\r\n", - "query = [\r\n", - " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\r\n", - " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\r\n", - " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\r\n", - " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\r\n", - " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\r\n", - " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\r\n", - " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\r\n", - " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\r\n", - " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\r\n", - " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\r\n", - " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\r\n", - " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\r\n", - "]\r\n", - "\r\n", - "query_metadata = [\r\n", - " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\r\n", - " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\r\n", - " {\"id\": 4, \"summary\": \"stale product\"},\r\n", - " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\r\n", - " {\"id\": 5, \"summary\": \"Great for the kids!\"},\r\n", - " {\"id\": 2, \"summary\": \"yum falafel\"},\r\n", - " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\r\n", - " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\r\n", - " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\r\n", - " {\"id\": 7, \"summary\": \"This stuff is great\"},\r\n", - " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\r\n", - "]\r\n", - "" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f" - }, - "outputs": [], - "execution_count": 16 - }, - { - "cell_type": "code", - "source": [ - "vector_store.add_texts(texts=query, metadatas=query_metadata)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c" - }, - "outputs": [ - { - "output_type": "execute_result", - "execution_count": 19, - "data": { - "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" - }, - "metadata": {} - } - ], - "execution_count": 19 - }, - { - "cell_type": "markdown", - "source": [ - "## Querying Data:\r\n", - "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", - "\r\n", - "Performing a simple similarity search can be done as follows:" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# Perform a similarity search between the embedding of the query and the embeddings of the documents\r\n", - "simsearch_result = vector_store.similarity_search(\"Good reviews\", k = 3)\r\n", - "print(simsearch_result)\r\n", - "" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" - } - ], - "execution_count": 28 - }, - { - "cell_type": "markdown", - "source": [ - "## Filtering Support:\r\n", - "\r\n", - "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# hybrid search -> filter for cases where id not equal to 1.\r\n", - "hybrid_simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}})\r\n", - "print(hybrid_simsearch_result)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" - } - ], - "execution_count": 29 - }, - { - "cell_type": "markdown", - "source": [ - "## Similarity Search with Score:\r\n", - "If you want to execute a similarity search and receive the corresponding scores you can run:" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "simsearch_with_score_result = vector_store.similarity_search_with_score(\"Not a very good product\", k=12)\r\n", - "print(simsearch_with_score_result)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", - "tags": [ - "hide_input" - ] - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" - } - ], - "execution_count": 30 - }, - { - "cell_type": "markdown", - "source": [ - "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Similarity Search when you already have embeddings you want to search on" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# if you already have embeddings you want to search on\r\n", - "simsearch_by_vector = vector_store.similarity_search_by_vector([-0.0033353185281157494, 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"text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" - } - ], - "execution_count": 32 - }, - { - "cell_type": "code", - "source": [ - "# Similarity Search with Score if you already have embeddings you want to search on \r\n", - "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, 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-0.008499737828969955, 0.02750750258564949, 0.031240085139870644, -0.006055301986634731, 0.0044932980090379715, -0.01913624256849289])\r\n", - "print(simsearch_by_vector_with_score)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" - } - ], - "execution_count": 34 - }, - { - "cell_type": "markdown", - "source": [ - "## Delete Row by ID" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# delete row by id\r\n", - "vector_store.delete([\"3\", \"7\"])" - ], - "metadata": { - "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", - "language": "python" - }, - "outputs": [ - { - "output_type": "execute_result", - "execution_count": 35, - "data": { - "text/plain": "True" - }, - "metadata": {} - } - ], - "execution_count": 35 - }, - { - "cell_type": "markdown", - "source": [ - "## Drop Vector Store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# drop vectorstore\r\n", - "vector_store.drop()" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "# Load a Document from Azure Blob Storage" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", - "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "pip install azure-storage-blob" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "from langchain.document_loaders import AzureBlobStorageFileLoader\r\n", - "from langchain_core.documents import Document\r\n", - "from langchain.text_splitter import RecursiveCharacterTextSplitter\r\n", - "\r\n", - "# Define your connection string and blob details\r\n", - "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\r\n", - "container_name = \" 100 else doc.page_content for doc in response[\"context\"]],\r\n", - " }\r\n", - "\r\n", - "\r\n", - " # Create a DataFrame\r\n", - " df = pd.DataFrame(data)\r\n", - "\r\n", - " # Print the table\r\n", - " print(\"\\nSources:\")\r\n", - " print(df.to_markdown(index=False))" - ], - "metadata": { - "azdata_cell_guid": "b60a1f0a-a767-413a-a537-61103439a26e", - "language": "python" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "# Define the user query\r\n", - "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\r\n", - "\r\n", - "# Call the function to get the answer and sources\r\n", - "get_answer_and_sources(user_query)" - ], - "metadata": { - "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", - "language": "python", - "tags": [] - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" - } - ], - "execution_count": 1 - }, - { - "cell_type": "code", - "source": [ - "# Define the user query\r\n", - "user_query = \"Did Harry have a pet? What was it\"\r\n", - "\r\n", - "# Call the function to get the answer and sources\r\n", - "get_answer_and_sources(user_query)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" - } - ], - "execution_count": 2 - }, - { - "cell_type": "markdown", - "source": [ - "## API reference \n", - "\n", - "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" - ], - "metadata": { - "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Related\r\n", - "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", - "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" - ], - "metadata": { - "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" - }, - "attachments": {} - } + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025", + "language": "python" + }, + "source": [ + "# SQL Server Vector Store" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f", + "language": "python" + }, + "source": [ + "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", + "\n", + "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", + " \n", + "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", + "\n", + "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d", + "language": "python" + }, + "source": [ + "## Setup & Installation \n", + " \n", + "Install the `langchain-sqlserver` python package.\n", + "\n", + "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b", + "language": "python" + }, + "outputs": [], + "source": [ + "!pip install langchain-sqlserver==0.1.1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6", + "language": "python" + }, + "outputs": [], + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3", + "language": "python" + }, + "source": [ + "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", + "\n", + "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", + "language": "python" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "import pyodbc\n", + "\n", + "# Define your SQLServer Connection String\n", + "_CONNECTION_STRING = (\n", + " \"Driver={ODBC Driver 18 for SQL Server};\"\n", + " \"Server=.database.windows.net,1433;\"\n", + " \"Database=test;\"\n", + " \"TrustServerCertificate=yes;\"\n", + " \"Connection Timeout=60;\"\n", + " \"LongAsMax=yes;\"\n", + ")\n", + "\n", + "# Connection string can vary:\n", + "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee", + "language": "python" + }, + "source": [ + "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", + "\n", + "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0", + "language": "python" + }, + "outputs": [], + "source": [ + "!pip install langchain-openai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", + "language": "python" + }, + "outputs": [], + "source": [ + "# Import the necessary Libraries\n", + "from langchain_openai import AzureChatOpenAI, AzureOpenAIEmbeddings\n", + "\n", + "# Set your AzureOpenAI details\n", + "azure_endpoint = \"https://.openai.azure.com/\"\n", + "azure_deployment_name_embedding = \"text-embedding-3-small\"\n", + "azure_deployment_name_chatcompletion = \"chatcompletion\"\n", + "azure_api_version = \"2023-05-15\"\n", + "azure_api_key = \"YOUR_KEY\"\n", + "\n", + "\n", + "# Use AzureChatOpenAI for chat completions\n", + "llm = AzureChatOpenAI(\n", + " azure_endpoint=azure_endpoint,\n", + " azure_deployment=azure_deployment_name_chatcompletion,\n", + " openai_api_version=azure_api_version,\n", + " openai_api_key=azure_api_key,\n", + ")\n", + "\n", + "# Use AzureOpenAIEmbeddings for embeddings\n", + "embeddings = AzureOpenAIEmbeddings(\n", + " azure_endpoint=azure_endpoint,\n", + " azure_deployment=azure_deployment_name_embedding,\n", + " openai_api_version=azure_api_version,\n", + " openai_api_key=azure_api_key,\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada", + "language": "python" + }, + "source": [ + "## Manage vector store :  Creating SQL DB Vector Search" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978", + "language": "python" + }, + "outputs": [], + "source": [ + "from langchain_community.vectorstores.utils import DistanceStrategy\n", + "from langchain_sqlserver import SQLServer_VectorStore\n", + "\n", + "# Initialize the vector store\n", + "vector_store = SQLServer_VectorStore(\n", + " connection_string=_CONNECTION_STRING,\n", + " distance_strategy=DistanceStrategy.COSINE, # optional, if not provided, defaults to COSINE\n", + " embedding_function=embeddings, # you can use different embeddings provided in LangChain\n", + " embedding_length=1536,\n", + " table_name=\"langchain_test_table\", # using table with a custom name\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b", + "language": "python" + }, + "source": [ + "## Add items to vector store" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f", + "language": "python" + }, + "outputs": [], + "source": [ + "## we will use some artificial data for this example\n", + "query = [\n", + " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\n", + " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\n", + " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\n", + " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\n", + " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\n", + " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\n", + " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\n", + " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\n", + " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\n", + " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\n", + " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\n", + " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\n", + "]\n", + "\n", + "query_metadata = [\n", + " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\n", + " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\n", + " {\"id\": 4, \"summary\": \"stale product\"},\n", + " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\n", + " {\"id\": 5, \"summary\": \"Great for the kids!\"},\n", + " {\"id\": 2, \"summary\": \"yum falafel\"},\n", + " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\n", + " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\n", + " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\n", + " {\"id\": 7, \"summary\": \"This stuff is great\"},\n", + " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c", + "language": "python" + }, + "outputs": [ + { + "data": { + "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vector_store.add_texts(texts=query, metadatas=query_metadata)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33", + "language": "python" + }, + "source": [ + "## Querying Data:\r\n", + "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", + "\r\n", + "Performing a simple similarity search can be done as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" + } + ], + "source": [ + "# Perform a similarity search between the embedding of the query and the embeddings of the documents\n", + "simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3)\n", + "print(simsearch_result)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0", + "language": "python" + }, + "source": [ + "## Filtering Support:\r\n", + "\r\n", + "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" + } + ], + "source": [ + "# hybrid search -> filter for cases where id not equal to 1.\n", + "hybrid_simsearch_result = vector_store.similarity_search(\n", + " \"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}}\n", + ")\n", + "print(hybrid_simsearch_result)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501", + "language": "python" + }, + "source": [ + "## Similarity Search with Score:\r\n", + "If you want to execute a similarity search and receive the corresponding scores you can run:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", + "language": "python", + "tags": [ + "hide_input" ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" + } + ], + "source": [ + "simsearch_with_score_result = vector_store.similarity_search_with_score(\n", + " \"Not a very good product\", k=12\n", + ")\n", + "print(simsearch_with_score_result)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886", + "language": "python" + }, + "source": [ + "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4", + "language": "python" + }, + "source": [ + "## Similarity Search when you already have embeddings you want to search on" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "azdata_cell_guid": "35afb4cd-0682-4525-9ba8-625fecc59bb4", + "language": "python", + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" + } + ], + "source": [ + "# if you already have embeddings you want to search on\n", + "simsearch_by_vector = vector_store.similarity_search_by_vector(\n", + " [\n", + " -0.0033353185281157494,\n", + " -0.017689190804958344,\n", + " -0.01590404286980629,\n", + " -0.01751338131725788,\n", + " -0.018054334446787834,\n", + " 0.021841011941432953,\n", + " -0.012313461862504482,\n", + " -0.02273358590900898,\n", + " -0.021286534145474434,\n", + " -0.01814900152385235,\n", + " 0.012252604588866234,\n", + " 0.038759343326091766,\n", + " 0.0015408731997013092,\n", + " -0.00691406661644578,\n", + " -0.013638799078762531,\n", + " 0.024153590202331543,\n", + " 0.039895348250865936,\n", + " 0.0012036223197355866,\n", + " 0.009372025728225708,\n", + " -0.012178223580121994,\n", + " -0.019853007048368454,\n", + " 0.006024873349815607,\n", + " 0.011319459415972233,\n", + " -0.025167878717184067,\n", + " -0.00759363966062665,\n", + " 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" -0.014308229088783264,\n", + " -0.01016993261873722,\n", + " -0.01616099663078785,\n", + " 0.0003716944484040141,\n", + " -0.005027489736676216,\n", + " -0.009135358035564423,\n", + " 0.016350330784916878,\n", + " -0.02937379479408264,\n", + " -0.008499737828969955,\n", + " 0.02750750258564949,\n", + " 0.031240085139870644,\n", + " -0.006055301986634731,\n", + " 0.0044932980090379715,\n", + " -0.01913624256849289,\n", + " ]\n", + ")\n", + "print(simsearch_by_vector)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" + } + ], + "source": [ + "# Similarity Search with Score if you already have embeddings you want to search on\n", + "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score(\n", + " [\n", + " -0.0033353185281157494,\n", + " -0.017689190804958344,\n", + " -0.01590404286980629,\n", + " -0.01751338131725788,\n", + " -0.018054334446787834,\n", + " 0.021841011941432953,\n", + " -0.012313461862504482,\n", + " -0.02273358590900898,\n", + " -0.021286534145474434,\n", + " -0.01814900152385235,\n", + " 0.012252604588866234,\n", + " 0.038759343326091766,\n", + " 0.0015408731997013092,\n", + " -0.00691406661644578,\n", + " -0.013638799078762531,\n", + " 0.024153590202331543,\n", + " 0.039895348250865936,\n", + " 0.0012036223197355866,\n", + " 0.009372025728225708,\n", + " -0.012178223580121994,\n", + " -0.019853007048368454,\n", + " 0.006024873349815607,\n", + " 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+ " 0.00982507411390543,\n", + " -0.04403364285826683,\n", + " 0.0045981076546013355,\n", + " 0.00671120872721076,\n", + " -0.014308229088783264,\n", + " -0.01016993261873722,\n", + " -0.01616099663078785,\n", + " 0.0003716944484040141,\n", + " -0.005027489736676216,\n", + " -0.009135358035564423,\n", + " 0.016350330784916878,\n", + " -0.02937379479408264,\n", + " -0.008499737828969955,\n", + " 0.02750750258564949,\n", + " 0.031240085139870644,\n", + " -0.006055301986634731,\n", + " 0.0044932980090379715,\n", + " -0.01913624256849289,\n", + " ]\n", + ")\n", + "print(simsearch_by_vector_with_score)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be", + "language": "python" + }, + "source": [ + "## Delete Row by ID" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", + "language": "python" + }, + "outputs": [ + { + "data": { + "text/plain": "True" + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# delete row by id\n", + "vector_store.delete([\"3\", \"7\"])" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389", + "language": "python" + }, + "source": [ + "## Drop Vector Store" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c", + "language": "python" + }, + "outputs": [], + "source": [ + "# drop vectorstore\n", + "vector_store.drop()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962", + "language": "python" + }, + "source": [ + "# Load a Document from Azure Blob Storage" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4", + "language": "python" + }, + "source": [ + "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", + "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294", + "language": "python" + }, + "outputs": [], + "source": [ + "pip install azure-storage-blob" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "azdata_cell_guid": "d9127900-0942-48f1-bd4d-081c7fa3fcae", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Number of split documents: 528\n" + } + ], + "source": [ + "from langchain.document_loaders import AzureBlobStorageFileLoader\n", + "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", + "from langchain_core.documents import Document\n", + "\n", + "# Define your connection string and blob details\n", + "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\n", + "container_name = \" 100\n", + " else doc.page_content\n", + " for doc in response[\"context\"]\n", + " ],\n", + " }\n", + "\n", + " # Create a DataFrame\n", + " df = pd.DataFrame(data)\n", + "\n", + " # Print the table\n", + " print(\"\\nSources:\")\n", + " print(df.to_markdown(index=False))" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", + "language": "python", + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" + } + ], + "source": [ + "# Define the user query\n", + "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\n", + "\n", + "# Call the function to get the answer and sources\n", + "get_answer_and_sources(user_query)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" + } + ], + "source": [ + "# Define the user query\n", + "user_query = \"Did Harry have a pet? What was it\"\n", + "\n", + "# Call the function to get the answer and sources\n", + "get_answer_and_sources(user_query)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" + }, + "source": [ + "## API reference \n", + "\n", + "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" + }, + "source": [ + "## Related\r\n", + "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", + "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } \ No newline at end of file From 6bbb6455a6eea7281b01c905c06ee054bd00aa37 Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 13:19:33 +0530 Subject: [PATCH 14/27] adding sqlserver vector store with format --- .../integrations/vectorstores/sqlserver.ipynb | 4753 +++-------------- 1 file changed, 831 insertions(+), 3922 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index 2ae56d9e41667..726012b071fb6 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -1,3925 +1,834 @@ { - "cells": [ - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025", - "language": "python" - }, - "source": [ - "# SQL Server Vector Store" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f", - "language": "python" - }, - "source": [ - "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", - "\n", - "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", - " \n", - "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", - "\n", - "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d", - "language": "python" - }, - "source": [ - "## Setup & Installation \n", - " \n", - "Install the `langchain-sqlserver` python package.\n", - "\n", - "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b", - "language": "python" - }, - "outputs": [], - "source": [ - "!pip install langchain-sqlserver==0.1.1" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6", - "language": "python" - }, - "outputs": [], - "source": [ - "from langchain_sqlserver import SQLServer_VectorStore" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3", - "language": "python" - }, - "source": [ - "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", - "\n", - "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", - "language": "python" - }, - "outputs": [], - "source": [ - "import os\n", - "\n", - "import pyodbc\n", - "\n", - "# Define your SQLServer Connection String\n", - "_CONNECTION_STRING = (\n", - " \"Driver={ODBC Driver 18 for SQL Server};\"\n", - " \"Server=.database.windows.net,1433;\"\n", - " \"Database=test;\"\n", - " \"TrustServerCertificate=yes;\"\n", - " \"Connection Timeout=60;\"\n", - " \"LongAsMax=yes;\"\n", - ")\n", - "\n", - "# Connection string can vary:\n", - "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee", - "language": "python" - }, - "source": [ - "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", - "\n", - "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0", - "language": "python" - }, - "outputs": [], - "source": [ - "!pip install langchain-openai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", - "language": "python" - }, - "outputs": [], - "source": [ - "# Import the necessary Libraries\n", - "from langchain_openai import AzureChatOpenAI, AzureOpenAIEmbeddings\n", - "\n", - "# Set your AzureOpenAI details\n", - "azure_endpoint = \"https://.openai.azure.com/\"\n", - "azure_deployment_name_embedding = \"text-embedding-3-small\"\n", - "azure_deployment_name_chatcompletion = \"chatcompletion\"\n", - "azure_api_version = \"2023-05-15\"\n", - "azure_api_key = \"YOUR_KEY\"\n", - "\n", - "\n", - "# Use AzureChatOpenAI for chat completions\n", - "llm = AzureChatOpenAI(\n", - " azure_endpoint=azure_endpoint,\n", - " azure_deployment=azure_deployment_name_chatcompletion,\n", - " openai_api_version=azure_api_version,\n", - " openai_api_key=azure_api_key,\n", - ")\n", - "\n", - "# Use AzureOpenAIEmbeddings for embeddings\n", - "embeddings = AzureOpenAIEmbeddings(\n", - " azure_endpoint=azure_endpoint,\n", - " azure_deployment=azure_deployment_name_embedding,\n", - " openai_api_version=azure_api_version,\n", - " openai_api_key=azure_api_key,\n", - ")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada", - "language": "python" - }, - "source": [ - "## Manage vector store :  Creating SQL DB Vector Search" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978", - "language": "python" - }, - "outputs": [], - "source": [ - "from langchain_community.vectorstores.utils import DistanceStrategy\n", - "from langchain_sqlserver import SQLServer_VectorStore\n", - "\n", - "# Initialize the vector store\n", - "vector_store = SQLServer_VectorStore(\n", - " connection_string=_CONNECTION_STRING,\n", - " distance_strategy=DistanceStrategy.COSINE, # optional, if not provided, defaults to COSINE\n", - " embedding_function=embeddings, # you can use different embeddings provided in LangChain\n", - " embedding_length=1536,\n", - " table_name=\"langchain_test_table\", # using table with a custom name\n", - ")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b", - "language": "python" - }, - "source": [ - "## Add items to vector store" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f", - "language": "python" - }, - "outputs": [], - "source": [ - "## we will use some artificial data for this example\n", - "query = [\n", - " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\n", - " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\n", - " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\n", - " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\n", - " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\n", - " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\n", - " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\n", - " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\n", - " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\n", - " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\n", - " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\n", - " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\n", - "]\n", - "\n", - "query_metadata = [\n", - " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\n", - " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\n", - " {\"id\": 4, \"summary\": \"stale product\"},\n", - " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\n", - " {\"id\": 5, \"summary\": \"Great for the kids!\"},\n", - " {\"id\": 2, \"summary\": \"yum falafel\"},\n", - " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\n", - " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\n", - " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\n", - " {\"id\": 7, \"summary\": \"This stuff is great\"},\n", - " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c", - "language": "python" - }, - "outputs": [ - { - "data": { - "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "vector_store.add_texts(texts=query, metadatas=query_metadata)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33", - "language": "python" - }, - "source": [ - "## Querying Data:\r\n", - "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", - "\r\n", - "Performing a simple similarity search can be done as follows:" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf", - "language": "python" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" - } - ], - "source": [ - "# Perform a similarity search between the embedding of the query and the embeddings of the documents\n", - "simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3)\n", - "print(simsearch_result)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0", - "language": "python" - }, - "source": [ - "## Filtering Support:\r\n", - "\r\n", - "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": { - "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa", - "language": "python" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" - } - ], - "source": [ - "# hybrid search -> filter for cases where id not equal to 1.\n", - "hybrid_simsearch_result = vector_store.similarity_search(\n", - " \"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}}\n", - ")\n", - "print(hybrid_simsearch_result)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501", - "language": "python" - }, - "source": [ - "## Similarity Search with Score:\r\n", - "If you want to execute a similarity search and receive the corresponding scores you can run:" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": { - "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", - "language": "python", - "tags": [ - "hide_input" + "metadata": { + "kernelspec": { + "name": "python3", + "display_name": "Python 3", + "language": "python" + }, + "language_info": { + "name": "python", + "version": "3.11.9", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 2, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# SQL Server Vector Store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", + "\n", + "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", + " \n", + "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", + "\n", + "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Setup & Installation \n", + " \n", + "Install the `langchain-sqlserver` python package.\n", + "\n", + "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "!pip install langchain-sqlserver==0.1.1" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", + "\n", + "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "import pyodbc\r\n", + "import os\r\n", + "\r\n", + "#Define your SQLServer Connection String\r\n", + "_CONNECTION_STRING = (\r\n", + " 'Driver={ODBC Driver 18 for SQL Server};'\r\n", + " 'Server=.database.windows.net,1433;'\r\n", + " 'Database=test;'\r\n", + " 'TrustServerCertificate=yes;'\r\n", + " 'Connection Timeout=60;'\r\n", + " 'LongAsMax=yes;'\r\n", + ")\r\n", + "\r\n", + "# Connection string can vary:\r\n", + "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\r\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection\r\n", + "\r\n", + "" + ], + "metadata": { + "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", + "language": "python" + }, + "outputs": [], + "execution_count": 11 + }, + { + "cell_type": "markdown", + "source": [ + "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", + "\n", + "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "!pip install langchain-openai" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "#Import the necessary Libraries\r\n", + "from langchain_openai import AzureOpenAIEmbeddings\r\n", + "from langchain_openai import AzureChatOpenAI\r\n", + "\r\n", + "#Set your AzureOpenAI details \r\n", + "azure_endpoint = \"https://.openai.azure.com/\"\r\n", + "azure_deployment_name_embedding = \"text-embedding-3-small\"\r\n", + "azure_deployment_name_chatcompletion = \"chatcompletion\"\r\n", + "azure_api_version = \"2023-05-15\"\r\n", + "azure_api_key = \"YOUR_KEY\"\r\n", + "\r\n", + "\r\n", + "# Use AzureChatOpenAI for chat completions\r\n", + "llm = AzureChatOpenAI(\r\n", + " azure_endpoint=azure_endpoint,\r\n", + " azure_deployment=azure_deployment_name_chatcompletion,\r\n", + " openai_api_version=azure_api_version,\r\n", + " openai_api_key=azure_api_key\r\n", + ")\r\n", + "\r\n", + "# Use AzureOpenAIEmbeddings for embeddings\r\n", + "embeddings = AzureOpenAIEmbeddings(\r\n", + " azure_endpoint=azure_endpoint,\r\n", + " azure_deployment=azure_deployment_name_embedding, \r\n", + " openai_api_version=azure_api_version,\r\n", + " openai_api_key=azure_api_key\r\n", + ")" + ], + "metadata": { + "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", + "language": "python" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "## Manage vector store :  Creating SQL DB Vector Search" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore\r\n", + "from langchain_community.vectorstores.utils import DistanceStrategy\r\n", + "\r\n", + "# Initialize the vector store \r\n", + "vector_store = SQLServer_VectorStore(\r\n", + " connection_string=_CONNECTION_STRING,\r\n", + " distance_strategy=DistanceStrategy.COSINE, #optional, if not provided, defaults to COSINE\r\n", + " embedding_function=embeddings, # you can use different embeddings provided in LangChain\r\n", + " embedding_length=1536,\r\n", + " table_name=\"langchain_test_table\" # using table with a custom name\r\n", + ")" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978" + }, + "outputs": [], + "execution_count": 15 + }, + { + "cell_type": "markdown", + "source": [ + "## Add items to vector store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "## we will use some artificial data for this example\r\n", + "query = [\r\n", + " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\r\n", + " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\r\n", + " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\r\n", + " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\r\n", + " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\r\n", + " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\r\n", + " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\r\n", + " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\r\n", + " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\r\n", + " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\r\n", + " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\r\n", + " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\r\n", + "]\r\n", + "\r\n", + "query_metadata = [\r\n", + " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\r\n", + " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\r\n", + " {\"id\": 4, \"summary\": \"stale product\"},\r\n", + " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\r\n", + " {\"id\": 5, \"summary\": \"Great for the kids!\"},\r\n", + " {\"id\": 2, \"summary\": \"yum falafel\"},\r\n", + " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\r\n", + " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\r\n", + " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\r\n", + " {\"id\": 7, \"summary\": \"This stuff is great\"},\r\n", + " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\r\n", + "]\r\n", + "" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f" + }, + "outputs": [], + "execution_count": 16 + }, + { + "cell_type": "code", + "source": [ + "vector_store.add_texts(texts=query, metadatas=query_metadata)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c" + }, + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 19, + "data": { + "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" + }, + "metadata": {} + } + ], + "execution_count": 19 + }, + { + "cell_type": "markdown", + "source": [ + "## Querying Data:\r\n", + "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", + "\r\n", + "Performing a simple similarity search can be done as follows:" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# Perform a similarity search between the embedding of the query and the embeddings of the documents\r\n", + "simsearch_result = vector_store.similarity_search(\"Good reviews\", k = 3)\r\n", + "print(simsearch_result)\r\n", + "" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" + } + ], + "execution_count": 28 + }, + { + "cell_type": "markdown", + "source": [ + "## Filtering Support:\r\n", + "\r\n", + "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# hybrid search -> filter for cases where id not equal to 1.\r\n", + "hybrid_simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}})\r\n", + "print(hybrid_simsearch_result)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" + } + ], + "execution_count": 29 + }, + { + "cell_type": "markdown", + "source": [ + "## Similarity Search with Score:\r\n", + "If you want to execute a similarity search and receive the corresponding scores you can run:" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "simsearch_with_score_result = vector_store.similarity_search_with_score(\"Not a very good product\", k=12)\r\n", + "print(simsearch_with_score_result)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", + "tags": [ + "hide_input" + ] + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" + } + ], + "execution_count": 30 + }, + { + "cell_type": "markdown", + "source": [ + "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Similarity Search when you already have embeddings you want to search on" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# if you already have embeddings you want to search on\r\n", + "simsearch_by_vector = vector_store.similarity_search_by_vector([-0.0033353185281157494, 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"text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" + } + ], + "execution_count": 32 + }, + { + "cell_type": "code", + "source": [ + "# Similarity Search with Score if you already have embeddings you want to search on \r\n", + "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, 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-0.008499737828969955, 0.02750750258564949, 0.031240085139870644, -0.006055301986634731, 0.0044932980090379715, -0.01913624256849289])\r\n", + "print(simsearch_by_vector_with_score)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" + } + ], + "execution_count": 34 + }, + { + "cell_type": "markdown", + "source": [ + "## Delete Row by ID" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# delete row by id\r\n", + "vector_store.delete([\"3\", \"7\"])" + ], + "metadata": { + "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", + "language": "python" + }, + "outputs": [ + { + "output_type": "execute_result", + "execution_count": 35, + "data": { + "text/plain": "True" + }, + "metadata": {} + } + ], + "execution_count": 35 + }, + { + "cell_type": "markdown", + "source": [ + "## Drop Vector Store" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "# drop vectorstore\r\n", + "vector_store.drop()" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "markdown", + "source": [ + "# Load a Document from Azure Blob Storage" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", + "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4" + }, + "attachments": {} + }, + { + "cell_type": "code", + "source": [ + "pip install azure-storage-blob" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "from langchain.document_loaders import AzureBlobStorageFileLoader\r\n", + "from langchain_core.documents import Document\r\n", + "from langchain.text_splitter import RecursiveCharacterTextSplitter\r\n", + "\r\n", + "# Define your connection string and blob details\r\n", + "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\r\n", + "container_name = \" 100 else doc.page_content for doc in response[\"context\"]],\r\n", + " }\r\n", + "\r\n", + "\r\n", + " # Create a DataFrame\r\n", + " df = pd.DataFrame(data)\r\n", + "\r\n", + " # Print the table\r\n", + " print(\"\\nSources:\")\r\n", + " print(df.to_markdown(index=False))" + ], + "metadata": { + "azdata_cell_guid": "b60a1f0a-a767-413a-a537-61103439a26e", + "language": "python" + }, + "outputs": [], + "execution_count": null + }, + { + "cell_type": "code", + "source": [ + "# Define the user query\r\n", + "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\r\n", + "\r\n", + "# Call the function to get the answer and sources\r\n", + "get_answer_and_sources(user_query)" + ], + "metadata": { + "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", + "language": "python", + "tags": [] + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" + } + ], + "execution_count": 1 + }, + { + "cell_type": "code", + "source": [ + "# Define the user query\r\n", + "user_query = \"Did Harry have a pet? What was it\"\r\n", + "\r\n", + "# Call the function to get the answer and sources\r\n", + "get_answer_and_sources(user_query)" + ], + "metadata": { + "language": "python", + "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" + } + ], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "source": [ + "## API reference \n", + "\n", + "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" + ], + "metadata": { + "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" + }, + "attachments": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Related\r\n", + "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", + "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" + ], + "metadata": { + "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" + }, + "attachments": {} + } ] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" - } - ], - "source": [ - "simsearch_with_score_result = vector_store.similarity_search_with_score(\n", - " \"Not a very good product\", k=12\n", - ")\n", - "print(simsearch_with_score_result)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886", - "language": "python" - }, - "source": [ - "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4", - "language": "python" - }, - "source": [ - "## Similarity Search when you already have embeddings you want to search on" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": { - "azdata_cell_guid": "35afb4cd-0682-4525-9ba8-625fecc59bb4", - "language": "python", - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" - } - ], - "source": [ - "# if you already have embeddings you want to search on\n", - "simsearch_by_vector = vector_store.similarity_search_by_vector(\n", - " [\n", - " -0.0033353185281157494,\n", - " -0.017689190804958344,\n", - " -0.01590404286980629,\n", - " -0.01751338131725788,\n", - " -0.018054334446787834,\n", - " 0.021841011941432953,\n", - " -0.012313461862504482,\n", - " -0.02273358590900898,\n", - " -0.021286534145474434,\n", - " -0.01814900152385235,\n", - " 0.012252604588866234,\n", - " 0.038759343326091766,\n", - " 0.0015408731997013092,\n", - " -0.00691406661644578,\n", - " -0.013638799078762531,\n", - " 0.024153590202331543,\n", - " 0.039895348250865936,\n", - " 0.0012036223197355866,\n", - " 0.009372025728225708,\n", - " -0.012178223580121994,\n", - " -0.019853007048368454,\n", - " 0.006024873349815607,\n", - " 0.011319459415972233,\n", - " -0.025167878717184067,\n", - " -0.00759363966062665,\n", - " 0.010284884832799435,\n", - " 0.009831836447119713,\n", - " -0.008492975495755672,\n", - " -0.005639444105327129,\n", - " -0.009446406736969948,\n", - " 0.007444877177476883,\n", - " -0.009277358651161194,\n", - " -0.025289593264460564,\n", - " -0.02119186706840992,\n", - " -0.005906539969146252,\n", - " -0.018906336277723312,\n", - " -0.007539544254541397,\n", - " -0.016066329553723335,\n", - " -0.01171841286122799,\n", - " -0.02093491330742836,\n", - " 0.004608250688761473,\n", - " 0.011042220517992973,\n", - " 0.011549364775419235,\n", - " -0.009541073814034462,\n", - " 0.0025864355266094208,\n", - " 0.0026202453300356865,\n", - " -0.0036007240414619446,\n", - " -0.011995651759207249,\n", - " -0.02549245022237301,\n", - " -0.007958783768117428,\n", - " 0.015701185911893845,\n", - " 0.016188044100999832,\n", - " -0.005825396627187729,\n", - " -0.00866878591477871,\n", - " -0.00038881058571860194,\n", - " -0.0006356207886710763,\n", - " 0.0074110678397119045,\n", - " 0.00766802066937089,\n", - " -0.005419681314378977,\n", - " -0.007674783002585173,\n", - " 0.0086823096498847,\n", - " -0.004740108270198107,\n", - " -0.01406479999423027,\n", - " 0.02170577272772789,\n", - " -0.0029955320060253143,\n", - " -0.008574118837714195,\n", - " 0.005460252985358238,\n", - " 0.0034130807034671307,\n", - " -0.005521110258996487,\n", - " 0.0045507741160690784,\n", - " 0.03662257641553879,\n", - " -0.004141678102314472,\n", - " 0.004442583303898573,\n", - " -0.0035026762634515762,\n", - " 0.0021316963247954845,\n", - " -0.009297644719481468,\n", - " -0.032186754047870636,\n", - " 0.01478156354278326,\n", - " -0.0016355401603505015,\n", - " -0.005835539661347866,\n", - " 0.03253837302327156,\n", - " -0.040301062166690826,\n", - " -0.0090339295566082,\n", - " -0.001611873391084373,\n", - " 0.018703479319810867,\n", - " -0.00610601669177413,\n", - " -0.016323283314704895,\n", - " 0.002358220750465989,\n", - " -0.004118011333048344,\n", - " 0.005784825421869755,\n", - " 0.01579585298895836,\n", - " 0.028886936604976654,\n", - " -0.004111249465495348,\n", - " 0.020475102588534355,\n", - " -0.0360545739531517,\n", - " 0.0018696717452257872,\n", - " 0.0039658681489527225,\n", - " 0.026723120361566544,\n", - " -0.011177458800375462,\n", - " -0.03759629279375076,\n", - " 0.0012501105666160583,\n", - " 0.007478686980903149,\n", - " -0.03445876017212868,\n", - " -0.011130125261843204,\n", - " -0.019677195698022842,\n", - " -0.004784060642123222,\n", - " 0.01866290718317032,\n", - " 0.0013667537132278085,\n", - " 0.015417184680700302,\n", - " -0.01467337366193533,\n", - " -0.010109075345098972,\n", - " 0.03976010903716087,\n", - " 0.02482978254556656,\n", - " -0.045196693390607834,\n", - " -0.02562768943607807,\n", - " -0.0017614809330552816,\n", - " -0.0002624471380840987,\n", - " -0.006839685142040253,\n", - " 0.005757777485996485,\n", - " -0.001704004593193531,\n", - " 0.020650913938879967,\n", - " 0.021841011941432953,\n", - " 0.045845840126276016,\n", - " 0.00012234854511916637,\n", - " -0.0019170051673427224,\n", - " 0.006082349922508001,\n", - " -0.027940265834331512,\n", - " 0.005524491425603628,\n", - " -0.002109719906002283,\n", - " 0.011393840424716473,\n", - " 0.036784861236810684,\n", - " 0.019257957115769386,\n", - " 0.0018020524876192212,\n", - " 0.006051921285688877,\n", - " -0.01858176477253437,\n", - " 0.021584058180451393,\n", - " -0.0070459237322211266,\n", - " 0.00785735435783863,\n", - " -0.00133378931786865,\n", - " -0.028048457577824593,\n", - " -0.006944495253264904,\n", - " 0.019744815304875374,\n", - " -0.025587117299437523,\n", - " -0.020556246861815453,\n", - " 0.00877697579562664,\n", - " 0.03251132741570473,\n", - " 0.01059593353420496,\n", - " 0.00782354548573494,\n", - " 0.009493740275502205,\n", - " 0.008236022666096687,\n", - " 0.002108029555529356,\n", - " -0.007999354973435402,\n", - " 0.012692130170762539,\n", - " -0.02217910811305046,\n", - " 0.0018848860636353493,\n", - " 0.021178342401981354,\n", - " 0.00394896324723959,\n", - " 0.02273358590900898,\n", - " -0.006907304283231497,\n", - " 0.014754516072571278,\n", - " 0.007830306887626648,\n", - " 0.012090318836271763,\n", - " -0.0025661499239504337,\n", - " 0.0011884080013260245,\n", - " -0.005483919754624367,\n", - " 0.03640619292855263,\n", - " 0.022192630916833878,\n", - " 0.00766802066937089,\n", - " -0.004368202295154333,\n", - " -0.0065353987738490105,\n", - " -0.002111410489305854,\n", - " 0.02401835098862648,\n", - " 0.0008110081544145942,\n", - " 0.012225557118654251,\n", - " -0.01879814639687538,\n", - " 0.020258720964193344,\n", - " -0.009148881770670414,\n", - " 0.00009382168354932219,\n", - " -0.0399494431912899,\n", - " -0.009764216840267181,\n", - " -0.009656026028096676,\n", - " -0.0017800763016566634,\n", - " 0.03110484592616558,\n", - " 0.029617223888635635,\n", - " 0.0030479368288069963,\n", - " -0.0005232038092799485,\n", - " 0.017242904752492905,\n", - " -0.02500559203326702,\n", - " 0.01663433015346527,\n", - " -0.0012703962856903672,\n", - " 0.0030428653117269278,\n", - " 0.010237551294267178,\n", - 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" 0.00982507411390543,\n", - " -0.04403364285826683,\n", - " 0.0045981076546013355,\n", - " 0.00671120872721076,\n", - " -0.014308229088783264,\n", - " -0.01016993261873722,\n", - " -0.01616099663078785,\n", - " 0.0003716944484040141,\n", - " -0.005027489736676216,\n", - " -0.009135358035564423,\n", - " 0.016350330784916878,\n", - " -0.02937379479408264,\n", - " -0.008499737828969955,\n", - " 0.02750750258564949,\n", - " 0.031240085139870644,\n", - " -0.006055301986634731,\n", - " 0.0044932980090379715,\n", - " -0.01913624256849289,\n", - " ]\n", - ")\n", - "print(simsearch_by_vector)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": { - "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178", - "language": "python" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" - } - ], - "source": [ - "# Similarity Search with Score if you already have embeddings you want to search on\n", - "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score(\n", - " [\n", - " -0.0033353185281157494,\n", - " -0.017689190804958344,\n", - " -0.01590404286980629,\n", - " -0.01751338131725788,\n", - " -0.018054334446787834,\n", - " 0.021841011941432953,\n", - " -0.012313461862504482,\n", - " -0.02273358590900898,\n", - " -0.021286534145474434,\n", - " -0.01814900152385235,\n", - " 0.012252604588866234,\n", - " 0.038759343326091766,\n", - " 0.0015408731997013092,\n", - " -0.00691406661644578,\n", - " -0.013638799078762531,\n", - " 0.024153590202331543,\n", - " 0.039895348250865936,\n", - " 0.0012036223197355866,\n", - " 0.009372025728225708,\n", - " -0.012178223580121994,\n", - " -0.019853007048368454,\n", - " 0.006024873349815607,\n", - " 0.011319459415972233,\n", - 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" 0.020393960177898407,\n", - " -0.01766214333474636,\n", - " -0.001857838360592723,\n", - " -0.009317929856479168,\n", - " -0.009148881770670414,\n", - " 0.007965545170009136,\n", - " -0.02097548544406891,\n", - " -0.013841656967997551,\n", - " -0.014795088209211826,\n", - " 0.014105372130870819,\n", - " 0.026439119130373,\n", - " -0.014822135679423809,\n", - " 0.012597463093698025,\n", - " 0.02151643857359886,\n", - " -0.013104607351124287,\n", - " 0.023883111774921417,\n", - " -0.0065996372140944,\n", - " -0.03521609678864479,\n", - " -0.017621571198105812,\n", - " 0.01887928880751133,\n", - " 0.031185990199446678,\n", - " 0.021827487275004387,\n", - " 0.01129241194576025,\n", - " 0.005663110408931971,\n", - " 0.01722938008606434,\n", - " -0.00519653782248497,\n", - " 0.01737814210355282,\n", - " -0.03272770717740059,\n", - " -0.0006571743870154023,\n", - " 0.008357737213373184,\n", - " -0.007208209950476885,\n", - " -0.01858176477253437,\n", - " -0.0425189733505249,\n", - " 0.002968484302982688,\n", - " -0.003763010259717703,\n", - " -0.0075530679896473885,\n", - " 0.016188044100999832,\n", - " 0.02570883184671402,\n", - " -0.035351336002349854,\n", - " 0.041004300117492676,\n", - " 0.005193157121539116,\n", - " -0.0031983896624296904,\n", - " -0.006592874880880117,\n", - " 0.005798349156975746,\n", - " 0.02269301377236843,\n", - " 0.017472809180617332,\n", - " 0.02125948667526245,\n", - " -0.03857000917196274,\n", - " -0.005673253443092108,\n", - " 0.0021857917308807373,\n", - " -0.011623745784163475,\n", - " 0.00370891485363245,\n", - " -0.011245078407227993,\n", - " -0.01391603797674179,\n", - " -0.014186514541506767,\n", - " -0.030131129547953606,\n", - " 0.0072149718180298805,\n", - " -0.007336686830967665,\n", - " 0.0064711603336036205,\n", - " 0.016701949760317802,\n", - " 0.009831836447119713,\n", - " 0.0070459237322211266,\n", - " -0.003925296477973461,\n", - " -0.013679370284080505,\n", - " -0.022152060642838478,\n", - " 0.02641207166016102,\n", - " -0.01866290718317032,\n", - " -0.010812315158545971,\n", - " -0.004993680398911238,\n", - " 0.015214326791465282,\n", - " 0.00982507411390543,\n", - " -0.04403364285826683,\n", - " 0.0045981076546013355,\n", - " 0.00671120872721076,\n", - " -0.014308229088783264,\n", - " -0.01016993261873722,\n", - " -0.01616099663078785,\n", - " 0.0003716944484040141,\n", - " -0.005027489736676216,\n", - " -0.009135358035564423,\n", - " 0.016350330784916878,\n", - " -0.02937379479408264,\n", - " -0.008499737828969955,\n", - " 0.02750750258564949,\n", - " 0.031240085139870644,\n", - " -0.006055301986634731,\n", - " 0.0044932980090379715,\n", - " -0.01913624256849289,\n", - " ]\n", - ")\n", - "print(simsearch_by_vector_with_score)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be", - "language": "python" - }, - "source": [ - "## Delete Row by ID" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": { - "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", - "language": "python" - }, - "outputs": [ - { - "data": { - "text/plain": "True" - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# delete row by id\n", - "vector_store.delete([\"3\", \"7\"])" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389", - "language": "python" - }, - "source": [ - "## Drop Vector Store" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c", - "language": "python" - }, - "outputs": [], - "source": [ - "# drop vectorstore\n", - "vector_store.drop()" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962", - "language": "python" - }, - "source": [ - "# Load a Document from Azure Blob Storage" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4", - "language": "python" - }, - "source": [ - "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", - "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294", - "language": "python" - }, - "outputs": [], - "source": [ - "pip install azure-storage-blob" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": { - "azdata_cell_guid": "d9127900-0942-48f1-bd4d-081c7fa3fcae", - "language": "python" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "Number of split documents: 528\n" - } - ], - "source": [ - "from langchain.document_loaders import AzureBlobStorageFileLoader\n", - "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", - "from langchain_core.documents import Document\n", - "\n", - "# Define your connection string and blob details\n", - "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\n", - "container_name = \" 100\n", - " else doc.page_content\n", - " for doc in response[\"context\"]\n", - " ],\n", - " }\n", - "\n", - " # Create a DataFrame\n", - " df = pd.DataFrame(data)\n", - "\n", - " # Print the table\n", - " print(\"\\nSources:\")\n", - " print(df.to_markdown(index=False))" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", - "language": "python", - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" - } - ], - "source": [ - "# Define the user query\n", - "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\n", - "\n", - "# Call the function to get the answer and sources\n", - "get_answer_and_sources(user_query)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b", - "language": "python" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" - } - ], - "source": [ - "# Define the user query\n", - "user_query = \"Did Harry have a pet? What was it\"\n", - "\n", - "# Call the function to get the answer and sources\n", - "get_answer_and_sources(user_query)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" - }, - "source": [ - "## API reference \n", - "\n", - "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" - }, - "source": [ - "## Related\r\n", - "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", - "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.9" - } - }, - "nbformat": 4, - "nbformat_minor": 2 } \ No newline at end of file From 8f107d00d3882ca1695629339a7149caab95d5b9 Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 14:07:32 +0530 Subject: [PATCH 15/27] adding SQLserver vector store after format/lint --- .../integrations/vectorstores/sqlserver.ipynb | 4753 ++++++++++++++--- 1 file changed, 3922 insertions(+), 831 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index 726012b071fb6..2ae56d9e41667 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -1,834 +1,3925 @@ { - "metadata": { - "kernelspec": { - "name": "python3", - "display_name": "Python 3", - "language": "python" - }, - "language_info": { - "name": "python", - "version": "3.11.9", - "mimetype": "text/x-python", - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "pygments_lexer": "ipython3", - "nbconvert_exporter": "python", - "file_extension": ".py" - } - }, - "nbformat_minor": 2, - "nbformat": 4, - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# SQL Server Vector Store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", - "\n", - "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", - " \n", - "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", - "\n", - "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Setup & Installation \n", - " \n", - "Install the `langchain-sqlserver` python package.\n", - "\n", - "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "!pip install langchain-sqlserver==0.1.1" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "from langchain_sqlserver import SQLServer_VectorStore" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", - "\n", - "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "import pyodbc\r\n", - "import os\r\n", - "\r\n", - "#Define your SQLServer Connection String\r\n", - "_CONNECTION_STRING = (\r\n", - " 'Driver={ODBC Driver 18 for SQL Server};'\r\n", - " 'Server=.database.windows.net,1433;'\r\n", - " 'Database=test;'\r\n", - " 'TrustServerCertificate=yes;'\r\n", - " 'Connection Timeout=60;'\r\n", - " 'LongAsMax=yes;'\r\n", - ")\r\n", - "\r\n", - "# Connection string can vary:\r\n", - "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\r\n", - "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection\r\n", - "\r\n", - "" - ], - "metadata": { - "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", - "language": "python" - }, - "outputs": [], - "execution_count": 11 - }, - { - "cell_type": "markdown", - "source": [ - "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", - "\n", - "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "!pip install langchain-openai" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "#Import the necessary Libraries\r\n", - "from langchain_openai import AzureOpenAIEmbeddings\r\n", - "from langchain_openai import AzureChatOpenAI\r\n", - "\r\n", - "#Set your AzureOpenAI details \r\n", - "azure_endpoint = \"https://.openai.azure.com/\"\r\n", - "azure_deployment_name_embedding = \"text-embedding-3-small\"\r\n", - "azure_deployment_name_chatcompletion = \"chatcompletion\"\r\n", - "azure_api_version = \"2023-05-15\"\r\n", - "azure_api_key = \"YOUR_KEY\"\r\n", - "\r\n", - "\r\n", - "# Use AzureChatOpenAI for chat completions\r\n", - "llm = AzureChatOpenAI(\r\n", - " azure_endpoint=azure_endpoint,\r\n", - " azure_deployment=azure_deployment_name_chatcompletion,\r\n", - " openai_api_version=azure_api_version,\r\n", - " openai_api_key=azure_api_key\r\n", - ")\r\n", - "\r\n", - "# Use AzureOpenAIEmbeddings for embeddings\r\n", - "embeddings = AzureOpenAIEmbeddings(\r\n", - " azure_endpoint=azure_endpoint,\r\n", - " azure_deployment=azure_deployment_name_embedding, \r\n", - " openai_api_version=azure_api_version,\r\n", - " openai_api_key=azure_api_key\r\n", - ")" - ], - "metadata": { - "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", - "language": "python" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "## Manage vector store :  Creating SQL DB Vector Search" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "from langchain_sqlserver import SQLServer_VectorStore\r\n", - "from langchain_community.vectorstores.utils import DistanceStrategy\r\n", - "\r\n", - "# Initialize the vector store \r\n", - "vector_store = SQLServer_VectorStore(\r\n", - " connection_string=_CONNECTION_STRING,\r\n", - " distance_strategy=DistanceStrategy.COSINE, #optional, if not provided, defaults to COSINE\r\n", - " embedding_function=embeddings, # you can use different embeddings provided in LangChain\r\n", - " embedding_length=1536,\r\n", - " table_name=\"langchain_test_table\" # using table with a custom name\r\n", - ")" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978" - }, - "outputs": [], - "execution_count": 15 - }, - { - "cell_type": "markdown", - "source": [ - "## Add items to vector store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "## we will use some artificial data for this example\r\n", - "query = [\r\n", - " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\r\n", - " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\r\n", - " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\r\n", - " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\r\n", - " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\r\n", - " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\r\n", - " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\r\n", - " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\r\n", - " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\r\n", - " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\r\n", - " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\r\n", - " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\r\n", - "]\r\n", - "\r\n", - "query_metadata = [\r\n", - " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\r\n", - " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\r\n", - " {\"id\": 4, \"summary\": \"stale product\"},\r\n", - " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\r\n", - " {\"id\": 5, \"summary\": \"Great for the kids!\"},\r\n", - " {\"id\": 2, \"summary\": \"yum falafel\"},\r\n", - " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\r\n", - " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\r\n", - " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\r\n", - " {\"id\": 7, \"summary\": \"This stuff is great\"},\r\n", - " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\r\n", - "]\r\n", - "" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f" - }, - "outputs": [], - "execution_count": 16 - }, - { - "cell_type": "code", - "source": [ - "vector_store.add_texts(texts=query, metadatas=query_metadata)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c" - }, - "outputs": [ - { - "output_type": "execute_result", - "execution_count": 19, - "data": { - "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" - }, - "metadata": {} - } - ], - "execution_count": 19 - }, - { - "cell_type": "markdown", - "source": [ - "## Querying Data:\r\n", - "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", - "\r\n", - "Performing a simple similarity search can be done as follows:" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# Perform a similarity search between the embedding of the query and the embeddings of the documents\r\n", - "simsearch_result = vector_store.similarity_search(\"Good reviews\", k = 3)\r\n", - "print(simsearch_result)\r\n", - "" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" - } - ], - "execution_count": 28 - }, - { - "cell_type": "markdown", - "source": [ - "## Filtering Support:\r\n", - "\r\n", - "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# hybrid search -> filter for cases where id not equal to 1.\r\n", - "hybrid_simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}})\r\n", - "print(hybrid_simsearch_result)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" - } - ], - "execution_count": 29 - }, - { - "cell_type": "markdown", - "source": [ - "## Similarity Search with Score:\r\n", - "If you want to execute a similarity search and receive the corresponding scores you can run:" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "simsearch_with_score_result = vector_store.similarity_search_with_score(\"Not a very good product\", k=12)\r\n", - "print(simsearch_with_score_result)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", - "tags": [ - "hide_input" - ] - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" - } - ], - "execution_count": 30 - }, - { - "cell_type": "markdown", - "source": [ - "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Similarity Search when you already have embeddings you want to search on" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# if you already have embeddings you want to search on\r\n", - "simsearch_by_vector = vector_store.similarity_search_by_vector([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, -0.009446406736969948, 0.007444877177476883, -0.009277358651161194, -0.025289593264460564, -0.02119186706840992, -0.005906539969146252, -0.018906336277723312, -0.007539544254541397, -0.016066329553723335, -0.01171841286122799, -0.02093491330742836, 0.004608250688761473, 0.011042220517992973, 0.011549364775419235, -0.009541073814034462, 0.0025864355266094208, 0.0026202453300356865, -0.0036007240414619446, -0.011995651759207249, -0.02549245022237301, -0.007958783768117428, 0.015701185911893845, 0.016188044100999832, -0.005825396627187729, -0.00866878591477871, -0.00038881058571860194, -0.0006356207886710763, 0.0074110678397119045, 0.00766802066937089, -0.005419681314378977, -0.007674783002585173, 0.0086823096498847, -0.004740108270198107, -0.01406479999423027, 0.02170577272772789, -0.0029955320060253143, -0.008574118837714195, 0.005460252985358238, 0.0034130807034671307, -0.005521110258996487, 0.0045507741160690784, 0.03662257641553879, -0.004141678102314472, 0.004442583303898573, -0.0035026762634515762, 0.0021316963247954845, -0.009297644719481468, -0.032186754047870636, 0.01478156354278326, -0.0016355401603505015, -0.005835539661347866, 0.03253837302327156, -0.040301062166690826, -0.0090339295566082, -0.001611873391084373, 0.018703479319810867, -0.00610601669177413, -0.016323283314704895, 0.002358220750465989, -0.004118011333048344, 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"text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" - } - ], - "execution_count": 32 - }, - { - "cell_type": "code", - "source": [ - "# Similarity Search with Score if you already have embeddings you want to search on \r\n", - "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score([-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, -0.01751338131725788, -0.018054334446787834, 0.021841011941432953, -0.012313461862504482, -0.02273358590900898, -0.021286534145474434, -0.01814900152385235, 0.012252604588866234, 0.038759343326091766, 0.0015408731997013092, -0.00691406661644578, -0.013638799078762531, 0.024153590202331543, 0.039895348250865936, 0.0012036223197355866, 0.009372025728225708, -0.012178223580121994, -0.019853007048368454, 0.006024873349815607, 0.011319459415972233, -0.025167878717184067, -0.00759363966062665, 0.010284884832799435, 0.009831836447119713, -0.008492975495755672, -0.005639444105327129, 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-0.008499737828969955, 0.02750750258564949, 0.031240085139870644, -0.006055301986634731, 0.0044932980090379715, -0.01913624256849289])\r\n", - "print(simsearch_by_vector_with_score)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" - } - ], - "execution_count": 34 - }, - { - "cell_type": "markdown", - "source": [ - "## Delete Row by ID" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# delete row by id\r\n", - "vector_store.delete([\"3\", \"7\"])" - ], - "metadata": { - "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", - "language": "python" - }, - "outputs": [ - { - "output_type": "execute_result", - "execution_count": 35, - "data": { - "text/plain": "True" - }, - "metadata": {} - } - ], - "execution_count": 35 - }, - { - "cell_type": "markdown", - "source": [ - "## Drop Vector Store" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "# drop vectorstore\r\n", - "vector_store.drop()" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "markdown", - "source": [ - "# Load a Document from Azure Blob Storage" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", - "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4" - }, - "attachments": {} - }, - { - "cell_type": "code", - "source": [ - "pip install azure-storage-blob" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "from langchain.document_loaders import AzureBlobStorageFileLoader\r\n", - "from langchain_core.documents import Document\r\n", - "from langchain.text_splitter import RecursiveCharacterTextSplitter\r\n", - "\r\n", - "# Define your connection string and blob details\r\n", - "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\r\n", - "container_name = \" 100 else doc.page_content for doc in response[\"context\"]],\r\n", - " }\r\n", - "\r\n", - "\r\n", - " # Create a DataFrame\r\n", - " df = pd.DataFrame(data)\r\n", - "\r\n", - " # Print the table\r\n", - " print(\"\\nSources:\")\r\n", - " print(df.to_markdown(index=False))" - ], - "metadata": { - "azdata_cell_guid": "b60a1f0a-a767-413a-a537-61103439a26e", - "language": "python" - }, - "outputs": [], - "execution_count": null - }, - { - "cell_type": "code", - "source": [ - "# Define the user query\r\n", - "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\r\n", - "\r\n", - "# Call the function to get the answer and sources\r\n", - "get_answer_and_sources(user_query)" - ], - "metadata": { - "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", - "language": "python", - "tags": [] - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" - } - ], - "execution_count": 1 - }, - { - "cell_type": "code", - "source": [ - "# Define the user query\r\n", - "user_query = \"Did Harry have a pet? What was it\"\r\n", - "\r\n", - "# Call the function to get the answer and sources\r\n", - "get_answer_and_sources(user_query)" - ], - "metadata": { - "language": "python", - "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" - } - ], - "execution_count": 2 - }, - { - "cell_type": "markdown", - "source": [ - "## API reference \n", - "\n", - "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" - ], - "metadata": { - "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" - }, - "attachments": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Related\r\n", - "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", - "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" - ], - "metadata": { - "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" - }, - "attachments": {} - } + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "3fe4f4a9-8810-428c-90cb-147ad8563025", + "language": "python" + }, + "source": [ + "# SQL Server Vector Store" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f791e7da-9710-4f15-93f0-6ea61840a25f", + "language": "python" + }, + "source": [ + "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", + "\n", + "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", + " \n", + "Read more on using [Intelligent applications with Azure SQL Database](https://learn.microsoft.com/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql)\n", + "\n", + "This notebook shows you how to leverage this integrated SQL [vector database](https://devblogs.microsoft.com/azure-sql/exciting-announcement-public-preview-of-native-vector-support-in-azure-sql-database/) to store documents and perform vector search queries using Cosine (cosine distance), L2 (Euclidean distance), and IP (inner product) to locate documents close to the query vectors" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "320f08b1-2fac-46fe-8e3a-273b6bf6ca8d", + "language": "python" + }, + "source": [ + "## Setup & Installation \n", + " \n", + "Install the `langchain-sqlserver` python package.\n", + "\n", + "The code lives in an integration package called:[langchain-sqlserver](https:\\github.com\\langchain-ai\\langchain-azure\\tree\\main\\libs\\sqlserver)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "5fa6ff09-79d5-4023-9005-91a217f91a5b", + "language": "python" + }, + "outputs": [], + "source": [ + "!pip install langchain-sqlserver==0.1.1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "4113da9c-b0fe-4e01-bc06-cafe05634fb6", + "language": "python" + }, + "outputs": [], + "source": [ + "from langchain_sqlserver import SQLServer_VectorStore" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "458deaef-f985-4efe-957c-7840509fdfa3", + "language": "python" + }, + "source": [ + "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", + "\n", + "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "azdata_cell_guid": "d3439463-899e-48aa-88a1-ba6bdedbdc9d", + "language": "python" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "import pyodbc\n", + "\n", + "# Define your SQLServer Connection String\n", + "_CONNECTION_STRING = (\n", + " \"Driver={ODBC Driver 18 for SQL Server};\"\n", + " \"Server=.database.windows.net,1433;\"\n", + " \"Database=test;\"\n", + " \"TrustServerCertificate=yes;\"\n", + " \"Connection Timeout=60;\"\n", + " \"LongAsMax=yes;\"\n", + ")\n", + "\n", + "# Connection string can vary:\n", + "# \"mssql+pyodbc://:/?driver=ODBC+Driver+18+for+SQL+Server\" -> With Username and Password specified\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=yes\" -> Uses Trusted connection\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server\" -> Uses EntraID connection\n", + "# \"mssql+pyodbc:///?driver=ODBC+Driver+18+for+SQL+Server&Trusted_connection=no\" -> Uses EntraID connection" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "dcbdafc3-71ec-4e73-b768-ffb49dae2aee", + "language": "python" + }, + "source": [ + "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", + "\n", + "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "a65110ff-cfa4-498c-bb7a-d937c04872c0", + "language": "python" + }, + "outputs": [], + "source": [ + "!pip install langchain-openai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "3bd306b1-f346-4c01-93f4-039827e4f2e6", + "language": "python" + }, + "outputs": [], + "source": [ + "# Import the necessary Libraries\n", + "from langchain_openai import AzureChatOpenAI, AzureOpenAIEmbeddings\n", + "\n", + "# Set your AzureOpenAI details\n", + "azure_endpoint = \"https://.openai.azure.com/\"\n", + "azure_deployment_name_embedding = \"text-embedding-3-small\"\n", + "azure_deployment_name_chatcompletion = \"chatcompletion\"\n", + "azure_api_version = \"2023-05-15\"\n", + "azure_api_key = \"YOUR_KEY\"\n", + "\n", + "\n", + "# Use AzureChatOpenAI for chat completions\n", + "llm = AzureChatOpenAI(\n", + " azure_endpoint=azure_endpoint,\n", + " azure_deployment=azure_deployment_name_chatcompletion,\n", + " openai_api_version=azure_api_version,\n", + " openai_api_key=azure_api_key,\n", + ")\n", + "\n", + "# Use AzureOpenAIEmbeddings for embeddings\n", + "embeddings = AzureOpenAIEmbeddings(\n", + " azure_endpoint=azure_endpoint,\n", + " azure_deployment=azure_deployment_name_embedding,\n", + " openai_api_version=azure_api_version,\n", + " openai_api_key=azure_api_key,\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f1f10145-06db-4cab-853f-9eb3b6fa8ada", + "language": "python" + }, + "source": [ + "## Manage vector store :  Creating SQL DB Vector Search" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "azdata_cell_guid": "c4033f67-bea2-4859-af4d-b41f3b929978", + "language": "python" + }, + "outputs": [], + "source": [ + "from langchain_community.vectorstores.utils import DistanceStrategy\n", + "from langchain_sqlserver import SQLServer_VectorStore\n", + "\n", + "# Initialize the vector store\n", + "vector_store = SQLServer_VectorStore(\n", + " connection_string=_CONNECTION_STRING,\n", + " distance_strategy=DistanceStrategy.COSINE, # optional, if not provided, defaults to COSINE\n", + " embedding_function=embeddings, # you can use different embeddings provided in LangChain\n", + " embedding_length=1536,\n", + " table_name=\"langchain_test_table\", # using table with a custom name\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "525f611b-2bd5-4fd4-9192-93d588c5ad0b", + "language": "python" + }, + "source": [ + "## Add items to vector store" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "azdata_cell_guid": "6410813d-0ff1-44dd-b6bb-32fd74772e4f", + "language": "python" + }, + "outputs": [], + "source": [ + "## we will use some artificial data for this example\n", + "query = [\n", + " \"I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.\",\n", + " \"The candy is just red , No flavor . Just plan and chewy . I would never buy them again\",\n", + " \"Arrived in 6 days and were so stale i could not eat any of the 6 bags!!\",\n", + " \"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\",\n", + " \"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\",\n", + " \"We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.\",\n", + " \"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\",\n", + " \"Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.\",\n", + " \"The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2\"\n", + " \" smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.\",\n", + " \"I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!\",\n", + " \"Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.\",\n", + "]\n", + "\n", + "query_metadata = [\n", + " {\"id\": 1, \"summary\": \"Good Quality Dog Food\"},\n", + " {\"id\": 8, \"summary\": \"Nasty No flavor\"},\n", + " {\"id\": 4, \"summary\": \"stale product\"},\n", + " {\"id\": 11, \"summary\": \"Great value and convenient ramen\"},\n", + " {\"id\": 5, \"summary\": \"Great for the kids!\"},\n", + " {\"id\": 2, \"summary\": \"yum falafel\"},\n", + " {\"id\": 9, \"summary\": \"Nearly killed the cats\"},\n", + " {\"id\": 6, \"summary\": \"Price cannot be correct\"},\n", + " {\"id\": 3, \"summary\": \"Taste is neutral, quantity is DECEITFUL!\"},\n", + " {\"id\": 7, \"summary\": \"This stuff is great\"},\n", + " {\"id\": 10, \"summary\": \"The reviews don't lie\"},\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "azdata_cell_guid": "03e8161a-6cdd-415d-8261-b6b99982726c", + "language": "python" + }, + "outputs": [ + { + "data": { + "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vector_store.add_texts(texts=query, metadatas=query_metadata)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "a2838ad1-64a1-409e-b97d-7883b42a0b33", + "language": "python" + }, + "source": [ + "## Querying Data:\r\n", + "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", + "\r\n", + "Performing a simple similarity search can be done as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "azdata_cell_guid": "1baa2857-167e-4873-ad9c-e67649ef39bf", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" + } + ], + "source": [ + "# Perform a similarity search between the embedding of the query and the embeddings of the documents\n", + "simsearch_result = vector_store.similarity_search(\"Good reviews\", k=3)\n", + "print(simsearch_result)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f92f0a1b-19aa-46d1-ad1a-c2e52f9114d0", + "language": "python" + }, + "source": [ + "## Filtering Support:\r\n", + "\r\n", + "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "azdata_cell_guid": "24fabd60-0b29-4ed9-9d5e-38c68fe05dfa", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" + } + ], + "source": [ + "# hybrid search -> filter for cases where id not equal to 1.\n", + "hybrid_simsearch_result = vector_store.similarity_search(\n", + " \"Good reviews\", k=3, filter={\"id\": {\"$ne\": 1}}\n", + ")\n", + "print(hybrid_simsearch_result)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "449c4cde-e303-4856-8deb-6e6ad56f9501", + "language": "python" + }, + "source": [ + "## Similarity Search with Score:\r\n", + "If you want to execute a similarity search and receive the corresponding scores you can run:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "azdata_cell_guid": "382fa5d4-6da1-46c1-987f-6d0ec050be99", + "language": "python", + "tags": [ + "hide_input" ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" + } + ], + "source": [ + "simsearch_with_score_result = vector_store.similarity_search_with_score(\n", + " \"Not a very good product\", k=12\n", + ")\n", + "print(simsearch_with_score_result)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "620e29bd-02f8-4dc7-91a2-52537cb08886", + "language": "python" + }, + "source": [ + "For a full list of the different searches you can execute on a Azure SQL vector store, please refer to the [API reference](https://python.langchain.com/api_reference/sqlserver/index.html)." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "ff48b371-b94f-4a3a-bd66-cce856baf6c4", + "language": "python" + }, + "source": [ + "## Similarity Search when you already have embeddings you want to search on" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "azdata_cell_guid": "35afb4cd-0682-4525-9ba8-625fecc59bb4", + "language": "python", + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" + } + ], + "source": [ + "# if you already have embeddings you want to search on\n", + "simsearch_by_vector = vector_store.similarity_search_by_vector(\n", + " [\n", + " -0.0033353185281157494,\n", + " -0.017689190804958344,\n", + " -0.01590404286980629,\n", + " -0.01751338131725788,\n", + " -0.018054334446787834,\n", + " 0.021841011941432953,\n", + " -0.012313461862504482,\n", + " -0.02273358590900898,\n", + " -0.021286534145474434,\n", + " -0.01814900152385235,\n", + " 0.012252604588866234,\n", + " 0.038759343326091766,\n", + " 0.0015408731997013092,\n", + " -0.00691406661644578,\n", + " -0.013638799078762531,\n", + " 0.024153590202331543,\n", + " 0.039895348250865936,\n", + " 0.0012036223197355866,\n", + " 0.009372025728225708,\n", + " -0.012178223580121994,\n", + " -0.019853007048368454,\n", + " 0.006024873349815607,\n", + " 0.011319459415972233,\n", + " -0.025167878717184067,\n", + " -0.00759363966062665,\n", + " 0.010284884832799435,\n", + " 0.009831836447119713,\n", + " -0.008492975495755672,\n", + " -0.005639444105327129,\n", + " -0.009446406736969948,\n", + " 0.007444877177476883,\n", + " -0.009277358651161194,\n", + " -0.025289593264460564,\n", + " -0.02119186706840992,\n", + " -0.005906539969146252,\n", + " -0.018906336277723312,\n", + " -0.007539544254541397,\n", + " -0.016066329553723335,\n", + " -0.01171841286122799,\n", + " -0.02093491330742836,\n", + " 0.004608250688761473,\n", + " 0.011042220517992973,\n", + " 0.011549364775419235,\n", + " -0.009541073814034462,\n", + " 0.0025864355266094208,\n", + " 0.0026202453300356865,\n", + " -0.0036007240414619446,\n", + " -0.011995651759207249,\n", + " -0.02549245022237301,\n", + " -0.007958783768117428,\n", + " 0.015701185911893845,\n", + " 0.016188044100999832,\n", + " -0.005825396627187729,\n", + " -0.00866878591477871,\n", + " -0.00038881058571860194,\n", + " -0.0006356207886710763,\n", + " 0.0074110678397119045,\n", + " 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" -0.014308229088783264,\n", + " -0.01016993261873722,\n", + " -0.01616099663078785,\n", + " 0.0003716944484040141,\n", + " -0.005027489736676216,\n", + " -0.009135358035564423,\n", + " 0.016350330784916878,\n", + " -0.02937379479408264,\n", + " -0.008499737828969955,\n", + " 0.02750750258564949,\n", + " 0.031240085139870644,\n", + " -0.006055301986634731,\n", + " 0.0044932980090379715,\n", + " -0.01913624256849289,\n", + " ]\n", + ")\n", + "print(simsearch_by_vector)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" + } + ], + "source": [ + "# Similarity Search with Score if you already have embeddings you want to search on\n", + "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score(\n", + " [\n", + " -0.0033353185281157494,\n", + " -0.017689190804958344,\n", + " -0.01590404286980629,\n", + " -0.01751338131725788,\n", + " -0.018054334446787834,\n", + " 0.021841011941432953,\n", + " -0.012313461862504482,\n", + " -0.02273358590900898,\n", + " -0.021286534145474434,\n", + " -0.01814900152385235,\n", + " 0.012252604588866234,\n", + " 0.038759343326091766,\n", + " 0.0015408731997013092,\n", + " -0.00691406661644578,\n", + " -0.013638799078762531,\n", + " 0.024153590202331543,\n", + " 0.039895348250865936,\n", + " 0.0012036223197355866,\n", + " 0.009372025728225708,\n", + " -0.012178223580121994,\n", + " -0.019853007048368454,\n", + " 0.006024873349815607,\n", + " 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+ " 0.00982507411390543,\n", + " -0.04403364285826683,\n", + " 0.0045981076546013355,\n", + " 0.00671120872721076,\n", + " -0.014308229088783264,\n", + " -0.01016993261873722,\n", + " -0.01616099663078785,\n", + " 0.0003716944484040141,\n", + " -0.005027489736676216,\n", + " -0.009135358035564423,\n", + " 0.016350330784916878,\n", + " -0.02937379479408264,\n", + " -0.008499737828969955,\n", + " 0.02750750258564949,\n", + " 0.031240085139870644,\n", + " -0.006055301986634731,\n", + " 0.0044932980090379715,\n", + " -0.01913624256849289,\n", + " ]\n", + ")\n", + "print(simsearch_by_vector_with_score)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "01f30a69-76cb-4137-bb80-1061abc095be", + "language": "python" + }, + "source": [ + "## Delete Row by ID" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "azdata_cell_guid": "1b42828c-0850-4d89-a1b5-a463bae0f143", + "language": "python" + }, + "outputs": [ + { + "data": { + "text/plain": "True" + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# delete row by id\n", + "vector_store.delete([\"3\", \"7\"])" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "51b9a47e-a17a-4427-8abe-90d87fd63389", + "language": "python" + }, + "source": [ + "## Drop Vector Store" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "cc9a281a-d204-4830-83d0-fcdd890c7f9c", + "language": "python" + }, + "outputs": [], + "source": [ + "# drop vectorstore\n", + "vector_store.drop()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "2d1b942b-f1ca-4fb5-abb7-bb2855631962", + "language": "python" + }, + "source": [ + "# Load a Document from Azure Blob Storage" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "cab89a29-e5e3-44b6-8f29-b4470d26f5d4", + "language": "python" + }, + "source": [ + "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", + "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "azdata_cell_guid": "6cff6a17-89b6-4d73-a92d-cf289dea4294", + "language": "python" + }, + "outputs": [], + "source": [ + "pip install azure-storage-blob" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "azdata_cell_guid": "d9127900-0942-48f1-bd4d-081c7fa3fcae", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Number of split documents: 528\n" + } + ], + "source": [ + "from langchain.document_loaders import AzureBlobStorageFileLoader\n", + "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", + "from langchain_core.documents import Document\n", + "\n", + "# Define your connection string and blob details\n", + "conn_str = \"DefaultEndpointsProtocol=https;AccountName=;AccountKey===;EndpointSuffix=core.windows.net\"\n", + "container_name = \" 100\n", + " else doc.page_content\n", + " for doc in response[\"context\"]\n", + " ],\n", + " }\n", + "\n", + " # Create a DataFrame\n", + " df = pd.DataFrame(data)\n", + "\n", + " # Print the table\n", + " print(\"\\nSources:\")\n", + " print(df.to_markdown(index=False))" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "azdata_cell_guid": "3cab0661-2351-4164-952f-67670addd99b", + "language": "python", + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" + } + ], + "source": [ + "# Define the user query\n", + "user_query = \"How did Harry feel when he first learnt that he was a Wizard?\"\n", + "\n", + "# Call the function to get the answer and sources\n", + "get_answer_and_sources(user_query)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "azdata_cell_guid": "1e1939d8-671f-4063-906c-89ee6813f12b", + "language": "python" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" + } + ], + "source": [ + "# Define the user query\n", + "user_query = \"Did Harry have a pet? What was it\"\n", + "\n", + "# Call the function to get the answer and sources\n", + "get_answer_and_sources(user_query)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "d1f01a01-1e1d-4af6-95a3-82bad34419fe" + }, + "source": [ + "## API reference \n", + "\n", + "For detailed documentation of SQLServer Vectorstore features and configurations head to the API reference: [https://python.langchain.com/api\\_reference/sqlserver/index.html](https:\\python.langchain.com\\api_reference\\sqlserver\\index.html)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": { + "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" + }, + "source": [ + "## Related\r\n", + "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", + "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } \ No newline at end of file From 7add9f428d5f422837faf8590aff8ee21595e53f Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 15:08:13 +0530 Subject: [PATCH 16/27] "Fixing missing headers for sqlserver vectorstore" --- .../integrations/vectorstores/sqlserver.ipynb | 115 ++++++++++++++---- 1 file changed, 91 insertions(+), 24 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index 2ae56d9e41667..2b50b5255087f 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -36,7 +36,7 @@ "language": "python" }, "source": [ - "## Setup & Installation \n", + "## Initialization\n", " \n", "Install the `langchain-sqlserver` python package.\n", "\n", @@ -180,7 +180,7 @@ "language": "python" }, "source": [ - "## Manage vector store :  Creating SQL DB Vector Search" + "## Query vector store  " ] }, { @@ -266,7 +266,9 @@ "outputs": [ { "data": { - "text/plain": "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" + "text/plain": [ + "[1, 8, 4, 11, 5, 2, 9, 6, 3, 7, 10]" + ] }, "execution_count": 19, "metadata": {}, @@ -285,9 +287,9 @@ "language": "python" }, "source": [ - "## Querying Data:\r\n", - "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\r\n", - "\r\n", + "## Querying Data:\n", + "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\n", + "\n", "Performing a simple similarity search can be done as follows:" ] }, @@ -302,7 +304,9 @@ { "name": "stdout", "output_type": "stream", - "text": "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" + "text": [ + "[Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\")]\n" + ] } ], "source": [ @@ -319,8 +323,8 @@ "language": "python" }, "source": [ - "## Filtering Support:\r\n", - "\r\n", + "## Filtering Support:\n", + "\n", "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." ] }, @@ -335,7 +339,9 @@ { "name": "stdout", "output_type": "stream", - "text": "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" + "text": [ + "[Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.')]\n" + ] } ], "source": [ @@ -354,7 +360,7 @@ "language": "python" }, "source": [ - "## Similarity Search with Score:\r\n", + "## Similarity Search with Score:\n", "If you want to execute a similarity search and receive the corresponding scores you can run:" ] }, @@ -372,7 +378,9 @@ { "name": "stdout", "output_type": "stream", - "text": "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" + "text": [ + "[(Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.651870006770711), (Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.6908952973052638), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.7360955776468822), (Document(metadata={'id': 1, 'summary': 'Good Quality Dog Food'}, page_content='I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a processed meat and it smells better. My Labrador is finicky and she appreciates this product better than most.'), 0.7408823529514486), (Document(metadata={'id': 9, 'summary': 'Nearly killed the cats'}, page_content=\"Too much of a good thing? We worked this kibble in over time, slowly shifting the percentage of Felidae to national junk-food brand until the bowl was all natural. By this time, the cats couldn't keep it in or down. What a mess. We've moved on.\"), 0.782995248991772), (Document(metadata={'id': 7, 'summary': 'This stuff is great'}, page_content='I have used this product in smoothies for my son and he loves it. Additionally, I use this oil in the shower as a skin conditioner and it has made my skin look great. Some of the stretch marks on my belly has disappeared quickly. Highly recommend!!!'), 0.7912681479906212), (Document(metadata={'id': 2, 'summary': 'yum falafel'}, page_content='We had trouble finding this locally - delivery was fast, no more hunting up and down the flour aisle at our local grocery stores.'), 0.809213468778896), (Document(metadata={'id': 10, 'summary': \"The reviews don't lie\"}, page_content='Been taking Coconut Oil for YEARS. This is the best on the retail market. I wish it was in glass, but this is the one.'), 0.8281482301097155), (Document(metadata={'id': 5, 'summary': 'Great for the kids!'}, page_content=\"If you are looking for a less messy version of licorice for the children, then be sure to try these! They're soft, easy to chew, and they don't get your hands all sticky and gross in the car, in the summer, at the beach, etc. We love all the flavos and sometimes mix these in with the chocolate to have a very nice snack! Great item, great price too, highly recommend!\"), 0.8283754326400574), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.8323967822635847), (Document(metadata={'id': 11, 'summary': 'Great value and convenient ramen'}, page_content=\"Got these on sale for roughly 25 cents per cup, which is half the price of my local grocery stores, plus they rarely stock the spicy flavors. These things are a GREAT snack for my office where time is constantly crunched and sometimes you can't escape for a real meal. This is one of my favorite flavors of Instant Lunch and will be back to buy every time it goes on sale.\"), 0.8387189489406939)]\n" + ] } ], "source": [ @@ -416,7 +424,9 @@ { "name": "stdout", "output_type": "stream", - "text": "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" + "text": [ + "[Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.')]\n" + ] } ], "source": [ @@ -1975,7 +1985,9 @@ { "name": "stdout", "output_type": "stream", - "text": "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" + "text": [ + "[(Document(metadata={'id': 8, 'summary': 'Nasty No flavor'}, page_content='The candy is just red , No flavor . Just plan and chewy . I would never buy them again'), 0.9648153551769503), (Document(metadata={'id': 4, 'summary': 'stale product'}, page_content='Arrived in 6 days and were so stale i could not eat any of the 6 bags!!'), 0.9655108580341948), (Document(metadata={'id': 3, 'summary': 'Taste is neutral, quantity is DECEITFUL!'}, page_content='The taste of these white cheddar flat breads is like a regular cracker - which is not bad, except that I bought them because I wanted a cheese taste.

What was a HUGE disappointment? How misleading the packaging of the box is. The photo on the box (I bought these in store) makes it look like it is full of long flatbreads (expanding the length and width of the box). Wrong! The plastic tray that holds the crackers is about 2 smaller all around - leaving you with about 15 or so small flatbreads.

What is also bad about this is that the company states they use biodegradable and eco-friendly packaging. FAIL! They used a HUGE box for a ridiculously small amount of crackers. Not ecofriendly at all.

Would I buy these again? No - I feel ripped off. The other crackers (like Sesame Tarragon) give you a little
more bang for your buck and have more flavor.'), 0.9840511208615808), (Document(metadata={'id': 6, 'summary': 'Price cannot be correct'}, page_content='Hey, the description says 360 grams - that is roughly 13 ounces at under $4.00 per can. No way - that is the approximate price for a 100 gram can.'), 0.9915737524649991)]\n" + ] } ], "source": [ @@ -3544,7 +3556,9 @@ "outputs": [ { "data": { - "text/plain": "True" + "text/plain": [ + "True" + ] }, "execution_count": 35, "metadata": {}, @@ -3599,7 +3613,7 @@ "language": "python" }, "source": [ - "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\r\n", + "Below is example of loading a file from Azure Blob Storage container into the SQL Vector store after splitting the document into chunks.\n", "[Azure Blog Storage](https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction) is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. " ] }, @@ -3626,7 +3640,9 @@ { "name": "stdout", "output_type": "stream", - "text": "Number of split documents: 528\n" + "text": [ + "Number of split documents: 528\n" + ] } ], "source": [ @@ -3676,7 +3692,9 @@ { "name": "stdout", "output_type": "stream", - "text": "Documents added to the vector store successfully!\n" + "text": [ + "Documents added to the vector store successfully!\n" + ] } ], "source": [ @@ -3707,7 +3725,34 @@ { "name": "stdout", "output_type": "stream", - "text": "------------------------------------------------------------\nScore: 0.3626232679001803\nThe Dursleys had everything they wanted, but they also had a secret, and their greatest fear was that somebody would discover it. They didn’t think they could bear it if anyone found out about the Potters. Mrs. Potter was Mrs. Dursley’s sister, but they hadn’t met for several years; in fact, Mrs. Dursley pretended she didn’t have a sister, because her sister and her good-for-nothing husband were as unDursleyish as it was possible to be. The Dursleys shuddered to think what the neighbors would say if the Potters arrived in the street. The Dursleys knew that the Potters had a small son, too, but they had never even seen him. This boy was another good reason for keeping the Potters away; they didn’t want Dudley mixing with a child like that.\n------------------------------------------------------------\n------------------------------------------------------------\nScore: 0.44752797298657554\nThe Dursleys’ house had four bedrooms: one for Uncle Vernon and Aunt Petunia, one for visitors (usually Uncle Vernon’s sister, Marge), one where Dudley slept, and one where Dudley kept all the toys and things that wouldn’t fit into his first bedroom. It only took Harry one trip upstairs to move everything he owned from the cupboard to this room. He sat down on the bed and stared around him. Nearly everything in here was broken. The month-old video camera was lying on top of a small, working tank Dudley had once driven over the next door neighbor’s dog; in the corner was Dudley’s first-ever television set, which he’d put his foot through when his favorite program had been canceled; there was a large birdcage, which had once held a parrot that Dudley had swapped at school for a real air rifle, which was up on a shelf with the end all bent because Dudley had sat on it. Other shelves were full of books. They were the only things in the room that looked as though they’d never been touched.\n------------------------------------------------------------\n------------------------------------------------------------\nScore: 0.4652486419877385\nM r. and Mrs. Dursley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much. They were the last people you’d expect to be involved in anything strange or mysterious, because they just didn’t hold with such nonsense.\n\nMr. Dursley was the director of a firm called Grunnings, which made drills. He was a big, beefy man with hardly any neck, although he did have a very large mustache. Mrs. Dursley was thin and blonde and had nearly twice the usual amount of neck, which came in very useful as she spent so much of her time craning over garden fences, spying on the neighbors. The Dursleys had a small son called Dudley and in their opinion there was no finer boy anywhere.\n------------------------------------------------------------\n------------------------------------------------------------\nScore: 0.4739086301927252\nHagrid was watching him sadly.\n\n“Took yeh from the ruined house myself, on Dumbledore’s orders. Brought yeh ter this lot….”\n\n“Load of old tosh,” said Uncle Vernon. Harry jumped; he had almost forgotten that the Dursleys were there. Uncle Vernon certainly seemed to have got back his courage. He was glaring at Hagrid and his fists were clenched.\n\n“Now, you listen here, boy,” he snarled, “I accept there’s something strange about you, probably nothing a good beating wouldn’t have cured — and as for all this about your parents, well, they were weirdoes, no denying it, and the world’s better off without them in my opinion — asked for all they got, getting mixed up with these wizarding types — just what I expected, always knew they’d come to a sticky end —”\n\nBut at that moment, Hagrid leapt from the sofa and drew a battered pink umbrella from inside his coat. Pointing this at Uncle Vernon like a sword, he said, “I’m warning you, Dursley — I’m warning you — one more word….”\n------------------------------------------------------------\n" + "text": [ + "------------------------------------------------------------\n", + "Score: 0.3626232679001803\n", + "The Dursleys had everything they wanted, but they also had a secret, and their greatest fear was that somebody would discover it. They didn’t think they could bear it if anyone found out about the Potters. Mrs. Potter was Mrs. Dursley’s sister, but they hadn’t met for several years; in fact, Mrs. Dursley pretended she didn’t have a sister, because her sister and her good-for-nothing husband were as unDursleyish as it was possible to be. The Dursleys shuddered to think what the neighbors would say if the Potters arrived in the street. The Dursleys knew that the Potters had a small son, too, but they had never even seen him. This boy was another good reason for keeping the Potters away; they didn’t want Dudley mixing with a child like that.\n", + "------------------------------------------------------------\n", + "------------------------------------------------------------\n", + "Score: 0.44752797298657554\n", + "The Dursleys’ house had four bedrooms: one for Uncle Vernon and Aunt Petunia, one for visitors (usually Uncle Vernon’s sister, Marge), one where Dudley slept, and one where Dudley kept all the toys and things that wouldn’t fit into his first bedroom. It only took Harry one trip upstairs to move everything he owned from the cupboard to this room. He sat down on the bed and stared around him. Nearly everything in here was broken. The month-old video camera was lying on top of a small, working tank Dudley had once driven over the next door neighbor’s dog; in the corner was Dudley’s first-ever television set, which he’d put his foot through when his favorite program had been canceled; there was a large birdcage, which had once held a parrot that Dudley had swapped at school for a real air rifle, which was up on a shelf with the end all bent because Dudley had sat on it. Other shelves were full of books. They were the only things in the room that looked as though they’d never been touched.\n", + "------------------------------------------------------------\n", + "------------------------------------------------------------\n", + "Score: 0.4652486419877385\n", + "M r. and Mrs. Dursley, of number four, Privet Drive, were proud to say that they were perfectly normal, thank you very much. They were the last people you’d expect to be involved in anything strange or mysterious, because they just didn’t hold with such nonsense.\n", + "\n", + "Mr. Dursley was the director of a firm called Grunnings, which made drills. He was a big, beefy man with hardly any neck, although he did have a very large mustache. Mrs. Dursley was thin and blonde and had nearly twice the usual amount of neck, which came in very useful as she spent so much of her time craning over garden fences, spying on the neighbors. The Dursleys had a small son called Dudley and in their opinion there was no finer boy anywhere.\n", + "------------------------------------------------------------\n", + "------------------------------------------------------------\n", + "Score: 0.4739086301927252\n", + "Hagrid was watching him sadly.\n", + "\n", + "“Took yeh from the ruined house myself, on Dumbledore’s orders. Brought yeh ter this lot….”\n", + "\n", + "“Load of old tosh,” said Uncle Vernon. Harry jumped; he had almost forgotten that the Dursleys were there. Uncle Vernon certainly seemed to have got back his courage. He was glaring at Hagrid and his fists were clenched.\n", + "\n", + "“Now, you listen here, boy,” he snarled, “I accept there’s something strange about you, probably nothing a good beating wouldn’t have cured — and as for all this about your parents, well, they were weirdoes, no denying it, and the world’s better off without them in my opinion — asked for all they got, getting mixed up with these wizarding types — just what I expected, always knew they’d come to a sticky end —”\n", + "\n", + "But at that moment, Hagrid leapt from the sofa and drew a battered pink umbrella from inside his coat. Pointing this at Uncle Vernon like a sword, he said, “I’m warning you, Dursley — I’m warning you — one more word….”\n", + "------------------------------------------------------------\n" + ] } ], "source": [ @@ -3843,7 +3888,18 @@ { "name": "stdout", "output_type": "stream", - "text": "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n\n" + "text": [ + "Answer: When Harry first learned that he was a wizard, he felt quite sure there had been a horrible mistake. He struggled to believe it because he had spent his life being bullied and mistreated by the Dursleys. If he was really a wizard, he wondered why he hadn't been able to use magic to defend himself. This disbelief and surprise were evident when he gasped, “I’m a what?”\n", + "\n", + "Sources:\n", + "| Doc ID | Content |\n", + "|:--------------------------------------------|:------------------------------------------------------|\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | Harry was wondering what a wizard did once he’d fi... |\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | Harry realized his mouth was open and closed it qu... |\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | “Most of us reckon he’s still out there somewhere ... |\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | “Ah, go boil yer heads, both of yeh,” said Hagrid.... |\n", + "\n" + ] } ], "source": [ @@ -3865,7 +3921,18 @@ { "name": "stdout", "output_type": "stream", - "text": "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n\nSources:\n| Doc ID | Content |\n|:--------------------------------------------|:------------------------------------------------------|\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n\n" + "text": [ + "Yes, Harry had a pet owl named Hedwig. He decided to call her Hedwig after finding the name in a book titled *A History of Magic*.\n", + "\n", + "Sources:\n", + "| Doc ID | Content |\n", + "|:--------------------------------------------|:------------------------------------------------------|\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | Harry sank down next to the bowl of peas. “What di... |\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | Harry kept to his room, with his new owl for compa... |\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | As the snake slid swiftly past him, Harry could ha... |\n", + "| 01 Harry Potter and the Sorcerers Stone.txt | Ron reached inside his jacket and pulled out a fat... |\n", + "\n" + ] } ], "source": [ @@ -3895,8 +3962,8 @@ "azdata_cell_guid": "f04dd9d6-d4f2-4425-9c6c-2275ff65c594" }, "source": [ - "## Related\r\n", - "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\r\n", + "## Related\n", + "- Vector store [conceptual guide](https://python.langchain.com/docs/concepts/vectorstores/)\n", "- Vector store [how-to guides](https://python.langchain.com/docs/how_to/#vector-stores)" ] } @@ -3922,4 +3989,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} \ No newline at end of file +} From e269a7bc33eb4556d7c53a7cd06e1b61b92676cb Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 15:23:51 +0530 Subject: [PATCH 17/27] "updating sqlserver vector store documentation" --- .../integrations/vectorstores/sqlserver.ipynb | 71 +++++++++++++++---- 1 file changed, 56 insertions(+), 15 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index 2b50b5255087f..bdab8146e937d 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -8,7 +8,7 @@ "language": "python" }, "source": [ - "# SQL Server Vector Store" + "# SQLServer " ] }, { @@ -19,7 +19,7 @@ "language": "python" }, "source": [ - "Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", + ">Azure SQL provides a dedicated [Vector data type](https:\\learn.microsoft.com\\sql\\t-sql\\data-types\\vector-data-type?view=azuresqldb-current&viewFallbackFrom=sql-server-ver16&tabs=csharp-sample) that simplifies the creation, storage, and querying of vector embeddings directly within a relational database. This eliminates the need for separate vector databases and related integrations, increasing the security of your solutions while reducing the overall complexity.\n", "\n", "Azure SQL is a robust service that combines scalability, security, and high availability, providing all the benefits of a modern database solution. It leverages a sophisticated query optimizer and enterprise features to perform vector similarity searches alongside traditional SQL queries, enhancing data analysis and decision-making. \n", " \n", @@ -36,7 +36,7 @@ "language": "python" }, "source": [ - "## Initialization\n", + "## Setup\n", " \n", "Install the `langchain-sqlserver` python package.\n", "\n", @@ -55,6 +55,33 @@ "!pip install langchain-sqlserver==0.1.1" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Credentials\n", + "\n", + "There are no credentials needed to run this notebook, just make sure you downloaded the `langchain_sqlserver` package\n", + "If you want to get best in-class automated tracing of your model calls you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n", + "# os.environ[\"LANGSMITH_TRACING\"] = \"true\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Initialization" + ] + }, { "cell_type": "code", "execution_count": null, @@ -180,7 +207,7 @@ "language": "python" }, "source": [ - "## Query vector store  " + "## Manage vector store  " ] }, { @@ -213,7 +240,7 @@ "language": "python" }, "source": [ - "## Add items to vector store" + "### Add items to vector store" ] }, { @@ -287,7 +314,7 @@ "language": "python" }, "source": [ - "## Querying Data:\n", + "## Query Vector Store:\n", "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\n", "\n", "Performing a simple similarity search can be done as follows:" @@ -323,7 +350,7 @@ "language": "python" }, "source": [ - "## Filtering Support:\n", + "### Filtering Support:\n", "\n", "The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.This feature enables developers and data analysts to refine their queries, ensuring that the search results are accurately aligned with their needs. By applying filters based on specific metadata attributes, users can limit the scope of their searches, concentrating only on the most relevant data subsets." ] @@ -360,7 +387,7 @@ "language": "python" }, "source": [ - "## Similarity Search with Score:\n", + "### Similarity Search with Score:\n", "If you want to execute a similarity search and receive the corresponding scores you can run:" ] }, @@ -409,7 +436,7 @@ "language": "python" }, "source": [ - "## Similarity Search when you already have embeddings you want to search on" + "### Similarity Search when you already have embeddings you want to search on" ] }, { @@ -3535,6 +3562,13 @@ "print(simsearch_by_vector_with_score)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Delete items from vector store" + ] + }, { "attachments": {}, "cell_type": "markdown", @@ -3543,7 +3577,7 @@ "language": "python" }, "source": [ - "## Delete Row by ID" + "### Delete Row by ID" ] }, { @@ -3578,7 +3612,7 @@ "language": "python" }, "source": [ - "## Drop Vector Store" + "### Drop Vector Store" ] }, { @@ -3602,7 +3636,7 @@ "language": "python" }, "source": [ - "# Load a Document from Azure Blob Storage" + "## Load a Document from Azure Blob Storage" ] }, { @@ -3714,6 +3748,13 @@ "print(\"Documents added to the vector store successfully!\")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Query Directly" + ] + }, { "cell_type": "code", "execution_count": 46, @@ -3781,15 +3822,15 @@ "source": [ "## Usage for retrieval-augmented generation\n", "\n", - "## Use Case 1: Q&A System based on the Story Book\n", + "#### Use Case 1: Q&A System based on the Story Book\n", "\n", "The Q&A function allows users to ask specific questions about the story, characters, and events, and get concise, context-rich answers. This not only enhances their understanding of the books but also makes them feel like they're part of the magical universe.\n", "\n", - "### **Query by turning into retriever**\n", + "## **Query by turning into retriever**\n", "\n", "The LangChain Vector store simplifies building sophisticated Q&A systems by enabling efficient similarity searches to find the top 10 relevant documents based on the user's query. The **retriever** is created from the **vector\\_store,** and the question-answer chain is built using the **create\\_stuff\\_documents\\_chain** function. A prompt template is crafted using the **ChatPromptTemplate** class, ensuring structured and context-rich responses. Often in Q&A applications it's important to show users the sources that were used to generate the answer. LangChain's built-in **create\\_retrieval\\_chain** will propagate retrieved source documents to the output under the \"context\" key:\n", "\n", - "Read more about Langchain RAG tutorials & the terminologies mentioned above [here](https:\\python.langchain.com\\docs\\tutorials\\rag\\)" + "Read more about Langchain RAG tutorials & the terminologies mentioned above [here](https:/python.langchain.com/docs/tutorials/rag)" ] }, { From e0ab27ee312aede6b0a7dd88edf6213019bcf10f Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 15:28:23 +0530 Subject: [PATCH 18/27] "Updating sqlserver vector store with template" --- docs/docs/integrations/vectorstores/sqlserver.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index bdab8146e937d..47360ae8604ba 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -314,7 +314,7 @@ "language": "python" }, "source": [ - "## Query Vector Store:\n", + "## Query vector Store:\n", "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\n", "\n", "Performing a simple similarity search can be done as follows:" @@ -3752,7 +3752,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Query Directly" + "## Query directly" ] }, { From 3720e267bb504a032c53388206fcd8b7835f2a0d Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 15:31:38 +0530 Subject: [PATCH 19/27] fixing typos sqlserver vectorstore --- docs/docs/integrations/vectorstores/sqlserver.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index 47360ae8604ba..b251b67cf354b 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -314,7 +314,7 @@ "language": "python" }, "source": [ - "## Query vector Store:\n", + "## Query vector Store\n", "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\n", "\n", "Performing a simple similarity search can be done as follows:" @@ -3826,7 +3826,7 @@ "\n", "The Q&A function allows users to ask specific questions about the story, characters, and events, and get concise, context-rich answers. This not only enhances their understanding of the books but also makes them feel like they're part of the magical universe.\n", "\n", - "## **Query by turning into retriever**\n", + "## Query by turning into retriever\n", "\n", "The LangChain Vector store simplifies building sophisticated Q&A systems by enabling efficient similarity searches to find the top 10 relevant documents based on the user's query. The **retriever** is created from the **vector\\_store,** and the question-answer chain is built using the **create\\_stuff\\_documents\\_chain** function. A prompt template is crafted using the **ChatPromptTemplate** class, ensuring structured and context-rich responses. Often in Q&A applications it's important to show users the sources that were used to generate the answer. LangChain's built-in **create\\_retrieval\\_chain** will propagate retrieved source documents to the output under the \"context\" key:\n", "\n", From fc70b7613b09a33704b3561c0feca65860a47a43 Mon Sep 17 00:00:00 2001 From: pookam90 Date: Mon, 18 Nov 2024 15:35:05 +0530 Subject: [PATCH 20/27] fixing typos --- docs/docs/integrations/vectorstores/sqlserver.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index b251b67cf354b..d77af5369ab43 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -314,7 +314,7 @@ "language": "python" }, "source": [ - "## Query vector Store\n", + "## Query vector store\n", "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\n", "\n", "Performing a simple similarity search can be done as follows:" From 2943402e6f9899d48829e056d6c09bab617985f1 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Mon, 9 Dec 2024 17:37:34 -0800 Subject: [PATCH 21/27] x --- .../integrations/vectorstores/sqlserver.ipynb | 3078 +---------------- docs/src/theme/FeatureTables.js | 24 +- 2 files changed, 16 insertions(+), 3086 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index d77af5369ab43..ef8101c4dec79 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -441,7 +441,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "metadata": { "azdata_cell_guid": "35afb4cd-0682-4525-9ba8-625fecc59bb4", "language": "python", @@ -463,1539 +463,7 @@ " -0.0033353185281157494,\n", " -0.017689190804958344,\n", " -0.01590404286980629,\n", - " -0.01751338131725788,\n", - " -0.018054334446787834,\n", - " 0.021841011941432953,\n", - " -0.012313461862504482,\n", - " -0.02273358590900898,\n", - " -0.021286534145474434,\n", - " -0.01814900152385235,\n", - " 0.012252604588866234,\n", - " 0.038759343326091766,\n", - " 0.0015408731997013092,\n", - " -0.00691406661644578,\n", - " -0.013638799078762531,\n", - " 0.024153590202331543,\n", - " 0.039895348250865936,\n", - " 0.0012036223197355866,\n", - " 0.009372025728225708,\n", - " -0.012178223580121994,\n", - " -0.019853007048368454,\n", - " 0.006024873349815607,\n", - " 0.011319459415972233,\n", - " -0.025167878717184067,\n", - " -0.00759363966062665,\n", - " 0.010284884832799435,\n", - " 0.009831836447119713,\n", - " -0.008492975495755672,\n", - 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" 0.005193157121539116,\n", - " -0.0031983896624296904,\n", - " -0.006592874880880117,\n", - " 0.005798349156975746,\n", - " 0.02269301377236843,\n", - " 0.017472809180617332,\n", - " 0.02125948667526245,\n", - " -0.03857000917196274,\n", - " -0.005673253443092108,\n", - " 0.0021857917308807373,\n", - " -0.011623745784163475,\n", - " 0.00370891485363245,\n", - " -0.011245078407227993,\n", - " -0.01391603797674179,\n", - " -0.014186514541506767,\n", - " -0.030131129547953606,\n", - " 0.0072149718180298805,\n", - " -0.007336686830967665,\n", - " 0.0064711603336036205,\n", - " 0.016701949760317802,\n", - " 0.009831836447119713,\n", - " 0.0070459237322211266,\n", - " -0.003925296477973461,\n", - " -0.013679370284080505,\n", - " -0.022152060642838478,\n", - " 0.02641207166016102,\n", - " -0.01866290718317032,\n", - " -0.010812315158545971,\n", - " -0.004993680398911238,\n", - " 0.015214326791465282,\n", - " 0.00982507411390543,\n", - " -0.04403364285826683,\n", - " 0.0045981076546013355,\n", - " 0.00671120872721076,\n", - " -0.014308229088783264,\n", - " -0.01016993261873722,\n", - " -0.01616099663078785,\n", - " 0.0003716944484040141,\n", - " -0.005027489736676216,\n", - " -0.009135358035564423,\n", - " 0.016350330784916878,\n", - " -0.02937379479408264,\n", - " -0.008499737828969955,\n", - " 0.02750750258564949,\n", - " 0.031240085139870644,\n", - " -0.006055301986634731,\n", - " 0.0044932980090379715,\n", - " -0.01913624256849289,\n", + " ...\n", " ]\n", ")\n", "print(simsearch_by_vector)" @@ -2003,7 +471,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": { "azdata_cell_guid": "8a7083fd-ddb2-4187-a315-744b7a623178", "language": "python" @@ -2018,1545 +486,7 @@ } ], "source": [ - "# Similarity Search with Score if you already have embeddings you want to search on\n", - "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score(\n", - " [\n", - " -0.0033353185281157494,\n", - " -0.017689190804958344,\n", - 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" 0.02750750258564949,\n", - " 0.031240085139870644,\n", - " -0.006055301986634731,\n", - " 0.0044932980090379715,\n", - " -0.01913624256849289,\n", + ".\n", " ]\n", ")\n", "print(simsearch_by_vector_with_score)" diff --git a/docs/src/theme/FeatureTables.js b/docs/src/theme/FeatureTables.js index 4149d8abd2207..74b3a4525e10e 100644 --- a/docs/src/theme/FeatureTables.js +++ b/docs/src/theme/FeatureTables.js @@ -1127,31 +1127,31 @@ const FEATURE_TABLES = { idsInAddDocuments: false, }, { - name: "SQLServer", - link: "sqlserver", + name: "Weaviate", + link: "weaviate", deleteById: true, filtering: true, searchByVector: true, searchWithScore: true, - async: false, + async: true, passesStandardTests: false, - multiTenancy: false, - local: false, + multiTenancy: true, + local: true, idsInAddDocuments: false, - }, + }, { - name: "Weaviate", - link: "weaviate", + name: "SQLServer", + link: "sqlserver", deleteById: true, filtering: true, searchByVector: true, searchWithScore: true, - async: true, + async: false, passesStandardTests: false, - multiTenancy: true, - local: true, + multiTenancy: false, + local: false, idsInAddDocuments: false, - } + }, ], } }; From 165cfe587b89615af132b53cd55584f68d7fc3cd Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Mon, 9 Dec 2024 17:46:21 -0800 Subject: [PATCH 22/27] x --- docs/docs/integrations/vectorstores/sqlserver.ipynb | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index ef8101c4dec79..5a8b22853e5dd 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -459,12 +459,7 @@ "source": [ "# if you already have embeddings you want to search on\n", "simsearch_by_vector = vector_store.similarity_search_by_vector(\n", - " [\n", - " -0.0033353185281157494,\n", - " -0.017689190804958344,\n", - " -0.01590404286980629,\n", - " ...\n", - " ]\n", + " [-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, ...]\n", ")\n", "print(simsearch_by_vector)" ] @@ -486,8 +481,9 @@ } ], "source": [ - ".\n", - " ]\n", + "# Similarity Search with Score if you already have embeddings you want to search on\n", + "simsearch_by_vector_with_score = vector_store.similarity_search_by_vector_with_score(\n", + " [-0.0033353185281157494, -0.017689190804958344, -0.01590404286980629, ...]\n", ")\n", "print(simsearch_by_vector_with_score)" ] From 976d5e2ef4b21d0fb4547af3611cb87d402e605f Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Mon, 9 Dec 2024 18:50:39 -0800 Subject: [PATCH 23/27] x --- docs/docs/integrations/vectorstores/sqlserver.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index 5a8b22853e5dd..de70f50b50362 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -102,7 +102,7 @@ "language": "python" }, "source": [ - "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", + "Find your Azure SQL DB connection string in the Azure portal under your database settings\n", "\n", "For more info: [Connect to Azure SQL DB - Python](https:\\learn.microsoft.com\\en-us\\azure\\azure-sql\\database\\connect-query-python?view=azuresql)" ] From 3c106764e4350d4d3107c91021ff0610c272c008 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Mon, 9 Dec 2024 18:50:59 -0800 Subject: [PATCH 24/27] x --- docs/docs/integrations/vectorstores/sqlserver.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/vectorstores/sqlserver.ipynb b/docs/docs/integrations/vectorstores/sqlserver.ipynb index de70f50b50362..2e6ee2a33c950 100644 --- a/docs/docs/integrations/vectorstores/sqlserver.ipynb +++ b/docs/docs/integrations/vectorstores/sqlserver.ipynb @@ -147,7 +147,7 @@ "source": [ "In this example we use Azure OpenAI to generate embeddings , however you can use different embeddings provided in LangChain.\n", "\n", - "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." + "You can deploy a version of Azure OpenAI instance on Azure Portal following this [guide](https:\\learn.microsoft.com\\en-us\\azure\\ai-services\\openai\\how-to\\create-resource?pivots=web-portal). Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the \"Keys and Endpoint\" section of your instance." ] }, { From 4176f8e8561ba77c533eaec28eeae5b221b2224f Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Mon, 9 Dec 2024 18:56:42 -0800 Subject: [PATCH 25/27] x --- docs/vercel.json | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/vercel.json b/docs/vercel.json index f91844dda1265..942c198bb6dc4 100644 --- a/docs/vercel.json +++ b/docs/vercel.json @@ -121,6 +121,10 @@ { "source": "/docs/contributing/:path((?:faq|repo_structure|review_process)/?)", "destination": "/docs/contributing/reference/:path" + }, + { + "source": "/docs/integrations/retrievers/weaviate-hybrid/?", + "destination": "/docs/integrations/vectorstores/weaviate/#search-mechanism" } ] } From 8b713ba5540bf8fd66f4ca3b96c2863a966f6563 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Mon, 9 Dec 2024 19:06:09 -0800 Subject: [PATCH 26/27] x --- .../langchain_community/graphs/kuzu_graph.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/libs/community/langchain_community/graphs/kuzu_graph.py b/libs/community/langchain_community/graphs/kuzu_graph.py index 36b0608f1cd33..3fe3d60c283c2 100644 --- a/libs/community/langchain_community/graphs/kuzu_graph.py +++ b/libs/community/langchain_community/graphs/kuzu_graph.py @@ -19,7 +19,19 @@ class KuzuGraph: See https://python.langchain.com/docs/security for more information. """ - def __init__(self, db: Any, database: str = "kuzu") -> None: + def __init__( + self, db: Any, database: str = "kuzu", allow_dangerous_requests: bool = False + ) -> None: + """Initializes the Kùzu graph database connection.""" + + if allow_dangerous_requests is not True: + raise ValueError( + "The KuzuGraph class is a powerful tool that can be used to execute " + "arbitrary queries on the database. To enable this functionality, " + "set the `allow_dangerous_requests` parameter to `True` when " + "constructing the KuzuGraph object." + ) + try: import kuzu except ImportError: From 8f52d2f5d94501b6fad37bfe4deda9b24347ee91 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Mon, 9 Dec 2024 19:07:20 -0800 Subject: [PATCH 27/27] x --- .../retrievers/weaviate-hybrid.ipynb | 297 ++++++++++++++++++ docs/vercel.json | 4 - 2 files changed, 297 insertions(+), 4 deletions(-) create mode 100644 docs/docs/integrations/retrievers/weaviate-hybrid.ipynb diff --git a/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb b/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb new file mode 100644 index 0000000000000..9592435b918b1 --- /dev/null +++ b/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb @@ -0,0 +1,297 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ce0f17b9", + "metadata": {}, + "source": [ + "# Weaviate Hybrid Search\n", + "\n", + ">[Weaviate](https://weaviate.io/developers/weaviate) is an open-source vector database.\n", + "\n", + ">[Hybrid search](https://weaviate.io/blog/hybrid-search-explained) is a technique that combines multiple search algorithms to improve the accuracy and relevance of search results. It uses the best features of both keyword-based search algorithms with vector search techniques.\n", + "\n", + ">The `Hybrid search in Weaviate` uses sparse and dense vectors to represent the meaning and context of search queries and documents.\n", + "\n", + "This notebook shows how to use `Weaviate hybrid search` as a LangChain retriever." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "c307b082", + "metadata": {}, + "source": [ + "Set up the retriever:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "bba863a2-977c-4add-b5f4-bfc33a80eae5", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%pip install --upgrade --quiet weaviate-client" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "c10dd962", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "import weaviate\n", + "\n", + "WEAVIATE_URL = os.getenv(\"WEAVIATE_URL\")\n", + "auth_client_secret = (weaviate.AuthApiKey(api_key=os.getenv(\"WEAVIATE_API_KEY\")),)\n", + "client = weaviate.Client(\n", + " url=WEAVIATE_URL,\n", + " additional_headers={\n", + " \"X-Openai-Api-Key\": os.getenv(\"OPENAI_API_KEY\"),\n", + " },\n", + ")\n", + "\n", + "# client.schema.delete_all()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f47a2bfe", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_community.retrievers import (\n", + " WeaviateHybridSearchRetriever,\n", + ")\n", + "from langchain_core.documents import Document" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "f2eff08e", + "metadata": {}, + "outputs": [], + "source": [ + "retriever = WeaviateHybridSearchRetriever(\n", + " client=client,\n", + " index_name=\"LangChain\",\n", + " text_key=\"text\",\n", + " attributes=[],\n", + " create_schema_if_missing=True,\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "b68debff", + "metadata": {}, + "source": [ + "Add some data:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "cd8a7b17", + "metadata": {}, + "outputs": [], + "source": [ + "docs = [\n", + " Document(\n", + " metadata={\n", + " \"title\": \"Embracing The Future: AI Unveiled\",\n", + " \"author\": \"Dr. Rebecca Simmons\",\n", + " },\n", + " page_content=\"A comprehensive analysis of the evolution of artificial intelligence, from its inception to its future prospects. Dr. Simmons covers ethical considerations, potentials, and threats posed by AI.\",\n", + " ),\n", + " Document(\n", + " metadata={\n", + " \"title\": \"Symbiosis: Harmonizing Humans and AI\",\n", + " \"author\": \"Prof. Jonathan K. Sterling\",\n", + " },\n", + " page_content=\"Prof. Sterling explores the potential for harmonious coexistence between humans and artificial intelligence. The book discusses how AI can be integrated into society in a beneficial and non-disruptive manner.\",\n", + " ),\n", + " Document(\n", + " metadata={\"title\": \"AI: The Ethical Quandary\", \"author\": \"Dr. Rebecca Simmons\"},\n", + " page_content=\"In her second book, Dr. Simmons delves deeper into the ethical considerations surrounding AI development and deployment. It is an eye-opening examination of the dilemmas faced by developers, policymakers, and society at large.\",\n", + " ),\n", + " Document(\n", + " metadata={\n", + " \"title\": \"Conscious Constructs: The Search for AI Sentience\",\n", + " \"author\": \"Dr. Samuel Cortez\",\n", + " },\n", + " page_content=\"Dr. Cortez takes readers on a journey exploring the controversial topic of AI consciousness. The book provides compelling arguments for and against the possibility of true AI sentience.\",\n", + " ),\n", + " Document(\n", + " metadata={\n", + " \"title\": \"Invisible Routines: Hidden AI in Everyday Life\",\n", + " \"author\": \"Prof. Jonathan K. Sterling\",\n", + " },\n", + " page_content=\"In his follow-up to 'Symbiosis', Prof. Sterling takes a look at the subtle, unnoticed presence and influence of AI in our everyday lives. 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