From 90f7713399d0a9eb397c048ba260a981c3b4254b Mon Sep 17 00:00:00 2001 From: Satyam Kumar Date: Wed, 18 Dec 2024 20:05:19 +0530 Subject: [PATCH 01/31] refactor: improve docstring parsing logic for Google style (#28730) Thank you for contributing to LangChain! - [x] **PR title**: "package: description" - Where "package" is whichever of langchain, community, core, etc. is being modified. Use "docs: ..." for purely docs changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" Description: Improved the `_parse_google_docstring` function in `langchain/core` to support parsing multi-paragraph descriptions before the `Args:` section while maintaining compliance with Google-style docstring guidelines. This change ensures better handling of docstrings with detailed function descriptions. Issue: Fixes #28628 Dependencies: None. Twitter handle: @isatyamks --------- Co-authored-by: Erick Friis Co-authored-by: Chester Curme --- .../langchain_core/utils/function_calling.py | 3 +- libs/core/tests/unit_tests/test_tools.py | 81 +++++++++++++++++++ 2 files changed, 83 insertions(+), 1 deletion(-) diff --git a/libs/core/langchain_core/utils/function_calling.py b/libs/core/langchain_core/utils/function_calling.py index e6b70c4ade1d7..e56e7dd49ba8e 100644 --- a/libs/core/langchain_core/utils/function_calling.py +++ b/libs/core/langchain_core/utils/function_calling.py @@ -615,7 +615,8 @@ def _parse_google_docstring( arg for arg in args if arg not in ("run_manager", "callbacks", "return") } if filtered_annotations and ( - len(docstring_blocks) < 2 or not docstring_blocks[1].startswith("Args:") + len(docstring_blocks) < 2 + or not any(block.startswith("Args:") for block in docstring_blocks[1:]) ): msg = "Found invalid Google-Style docstring." raise ValueError(msg) diff --git a/libs/core/tests/unit_tests/test_tools.py b/libs/core/tests/unit_tests/test_tools.py index 164ecc508e76e..b331abea7da7a 100644 --- a/libs/core/tests/unit_tests/test_tools.py +++ b/libs/core/tests/unit_tests/test_tools.py @@ -1190,6 +1190,87 @@ def foo5(run_manager: Optional[CallbackManagerForToolRun] = None) -> str: assert args_schema["description"] == expected["description"] +def test_docstring_parsing() -> None: + expected = { + "title": "foo", + "description": "The foo.", + "type": "object", + "properties": { + "bar": {"title": "Bar", "description": "The bar.", "type": "string"}, + "baz": {"title": "Baz", "description": "The baz.", "type": "integer"}, + }, + "required": ["bar", "baz"], + } + + # Simple case + def foo(bar: str, baz: int) -> str: + """The foo. + + Args: + bar: The bar. + baz: The baz. + """ + return bar + + as_tool = tool(foo, parse_docstring=True) + args_schema = _schema(as_tool.args_schema) # type: ignore + assert args_schema["description"] == "The foo." + assert args_schema["properties"] == expected["properties"] + + # Multi-line description + def foo2(bar: str, baz: int) -> str: + """The foo. + + Additional description here. + + Args: + bar: The bar. + baz: The baz. + """ + return bar + + as_tool = tool(foo2, parse_docstring=True) + args_schema2 = _schema(as_tool.args_schema) # type: ignore + assert args_schema2["description"] == "The foo. Additional description here." + assert args_schema2["properties"] == expected["properties"] + + # Multi-line wth Returns block + def foo3(bar: str, baz: int) -> str: + """The foo. + + Additional description here. + + Args: + bar: The bar. + baz: The baz. + + Returns: + str: description of returned value. + """ + return bar + + as_tool = tool(foo3, parse_docstring=True) + args_schema3 = _schema(as_tool.args_schema) # type: ignore + args_schema3["title"] = "foo2" + assert args_schema2 == args_schema3 + + # Single argument + def foo4(bar: str) -> str: + """The foo. + + Args: + bar: The bar. + """ + return bar + + as_tool = tool(foo4, parse_docstring=True) + args_schema4 = _schema(as_tool.args_schema) # type: ignore + assert args_schema4["description"] == "The foo." + assert args_schema4["properties"] == { + "bar": {"description": "The bar.", "title": "Bar", "type": "string"} + } + + def test_tool_invalid_docstrings() -> None: # Test invalid docstrings def foo3(bar: str, baz: int) -> str: From 05a44797ee8b8626a6a5542599a3058f44ebd446 Mon Sep 17 00:00:00 2001 From: Yudai Kotani Date: Wed, 18 Dec 2024 23:43:04 +0900 Subject: [PATCH 02/31] langchain_community: Add default None values to DocumentAttributeValue class properties (#28785) **Description**: This PR addresses an issue where the DocumentAttributeValue class properties did not have default values of None. By explicitly setting the Optional attributes (DateValue, LongValue, StringListValue, and StringValue) to default to None, this change ensures the class functions as expected when no value is provided for these attributes. **Changes Made**: Added default None values to the following properties of the DocumentAttributeValue class: DateValue LongValue StringListValue StringValue Removed the invalid argument extra="allow" from the BaseModel inheritance. Dependencies: None. **Twitter handle (optional)**: @__korikori1021 **Checklist** - [x] Verified that KendraRetriever works as expected after the changes. Co-authored-by: y1u0d2a1i --- libs/community/langchain_community/retrievers/kendra.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/libs/community/langchain_community/retrievers/kendra.py b/libs/community/langchain_community/retrievers/kendra.py index fe36e85dbe1b7..d674c368663d2 100644 --- a/libs/community/langchain_community/retrievers/kendra.py +++ b/libs/community/langchain_community/retrievers/kendra.py @@ -119,13 +119,13 @@ def get_value_text(self) -> str: class DocumentAttributeValue(BaseModel, extra="allow"): # type: ignore[call-arg] """Value of a document attribute.""" - DateValue: Optional[str] + DateValue: Optional[str] = None """The date expressed as an ISO 8601 string.""" - LongValue: Optional[int] + LongValue: Optional[int] = None """The long value.""" - StringListValue: Optional[List[str]] + StringListValue: Optional[List[str]] = None """The string list value.""" - StringValue: Optional[str] + StringValue: Optional[str] = None """The string value.""" @property From ef24220d3f84f7e7ee3dcc25bd997bdd40b13982 Mon Sep 17 00:00:00 2001 From: David Pryce-Compson Date: Wed, 18 Dec 2024 14:45:10 +0000 Subject: [PATCH 03/31] community: adding haiku 3.5 and opus callbacks (#28783) **Description:** Adding new AWS Bedrock model and their respective costs to match https://aws.amazon.com/bedrock/pricing/ for the Bedrock callback **Issue:** Missing models for those that wish to try them out **Dependencies:** Nothing added **Twitter handle:** @David_Pryce and / or @JamfSoftware If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --- .../callbacks/bedrock_anthropic_callback.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/libs/community/langchain_community/callbacks/bedrock_anthropic_callback.py b/libs/community/langchain_community/callbacks/bedrock_anthropic_callback.py index 6dd88639cbb7e..4d14fbe99e846 100644 --- a/libs/community/langchain_community/callbacks/bedrock_anthropic_callback.py +++ b/libs/community/langchain_community/callbacks/bedrock_anthropic_callback.py @@ -12,6 +12,8 @@ "anthropic.claude-3-5-sonnet-20240620-v1:0": 0.003, "anthropic.claude-3-5-sonnet-20241022-v2:0": 0.003, "anthropic.claude-3-haiku-20240307-v1:0": 0.00025, + "anthropic.claude-3-opus-20240229-v1:0": 0.015, + "anthropic.claude-3-5-haiku-20241022-v1:0": 0.0008, } MODEL_COST_PER_1K_OUTPUT_TOKENS = { @@ -22,6 +24,8 @@ "anthropic.claude-3-5-sonnet-20240620-v1:0": 0.015, "anthropic.claude-3-5-sonnet-20241022-v2:0": 0.015, "anthropic.claude-3-haiku-20240307-v1:0": 0.00125, + "anthropic.claude-3-opus-20240229-v1:0": 0.075, + "anthropic.claude-3-5-haiku-20241022-v1:0": 0.004, } From 986b752fc81f00b066f2d797b3f8b6b2aaceeb33 Mon Sep 17 00:00:00 2001 From: Rave Harpaz Date: Wed, 18 Dec 2024 06:50:25 -0800 Subject: [PATCH 04/31] Add OCI Generative AI new model and structured output support (#28754) - [X] **PR title**: community: Add new model and structured output support - [X] **PR message**: - **Description:** add support for meta llama 3.2 image handling, and JSON mode for structured output - **Issue:** NA - **Dependencies:** NA - **Twitter handle:** NA - [x] **Add tests and docs**: 1. we have updated our unit tests, 2. no changes required for documentation. - [x] **Lint and test**: make format, make lint and make test we run successfully --------- Co-authored-by: Arthur Cheng Co-authored-by: ccurme --- .../integrations/chat/oci_generative_ai.ipynb | 10 +- .../chat_models/oci_generative_ai.py | 190 +++++++++++++++--- 2 files changed, 170 insertions(+), 30 deletions(-) diff --git a/docs/docs/integrations/chat/oci_generative_ai.ipynb b/docs/docs/integrations/chat/oci_generative_ai.ipynb index d5dc26cf25eba..49efa3a57522d 100644 --- a/docs/docs/integrations/chat/oci_generative_ai.ipynb +++ b/docs/docs/integrations/chat/oci_generative_ai.ipynb @@ -26,14 +26,14 @@ "## Overview\n", "### Integration details\n", "\n", - "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/oci_generative_ai) | Package downloads | Package latest |\n", - "| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n", - "| [ChatOCIGenAI](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_generative_ai.ChatOCIGenAI.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-oci-generative-ai?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-oci-generative-ai?style=flat-square&label=%20) |\n", + "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/oci_generative_ai) |\n", + "| :--- | :--- | :---: | :---: | :---: |\n", + "| [ChatOCIGenAI](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_generative_ai.ChatOCIGenAI.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ❌ | ❌ |\n", "\n", "### Model features\n", - "| [Tool calling](/docs/how_to/tool_calling/) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n", + "| [Tool calling](/docs/how_to/tool_calling/) | [Structured output](/docs/how_to/structured_output/) | [JSON mode](/docs/how_to/structured_output/#advanced-specifying-the-method-for-structuring-outputs) | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n", "| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |\n", - "| ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | \n", + "| ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | \n", "\n", "## Setup\n", "\n", diff --git a/libs/community/langchain_community/chat_models/oci_generative_ai.py b/libs/community/langchain_community/chat_models/oci_generative_ai.py index 8600dd5e923cf..f66449bc564b3 100644 --- a/libs/community/langchain_community/chat_models/oci_generative_ai.py +++ b/libs/community/langchain_community/chat_models/oci_generative_ai.py @@ -2,12 +2,14 @@ import re import uuid from abc import ABC, abstractmethod +from operator import itemgetter from typing import ( Any, Callable, Dict, Iterator, List, + Literal, Mapping, Optional, Sequence, @@ -32,13 +34,17 @@ ToolMessage, ) from langchain_core.messages.tool import ToolCallChunk +from langchain_core.output_parsers import ( + JsonOutputParser, + PydanticOutputParser, +) from langchain_core.output_parsers.base import OutputParserLike from langchain_core.output_parsers.openai_tools import ( JsonOutputKeyToolsParser, PydanticToolsParser, ) from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult -from langchain_core.runnables import Runnable +from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough from langchain_core.tools import BaseTool from langchain_core.utils.function_calling import convert_to_openai_function from pydantic import BaseModel, ConfigDict @@ -58,6 +64,10 @@ } +def _is_pydantic_class(obj: Any) -> bool: + return isinstance(obj, type) and issubclass(obj, BaseModel) + + def _remove_signature_from_tool_description(name: str, description: str) -> str: """ Removes the `{name}{signature} - ` prefix and Args: section from tool description. @@ -158,7 +168,7 @@ def chat_response_to_text(self, response: Any) -> str: def chat_stream_to_text(self, event_data: Dict) -> str: if "text" in event_data: - if "finishedReason" in event_data or "toolCalls" in event_data: + if "finishReason" in event_data or "toolCalls" in event_data: return "" else: return event_data["text"] @@ -378,7 +388,10 @@ def __init__(self) -> None: "SYSTEM": models.SystemMessage, "ASSISTANT": models.AssistantMessage, } - self.oci_chat_message_content = models.TextContent + self.oci_chat_message_content = models.ChatContent + self.oci_chat_message_text_content = models.TextContent + self.oci_chat_message_image_content = models.ImageContent + self.oci_chat_message_image_url = models.ImageUrl self.chat_api_format = models.BaseChatRequest.API_FORMAT_GENERIC def chat_response_to_text(self, response: Any) -> str: @@ -415,19 +428,81 @@ def get_role(self, message: BaseMessage) -> str: def messages_to_oci_params( self, messages: List[BaseMessage], **kwargs: Any ) -> Dict[str, Any]: - oci_messages = [ - self.oci_chat_message[self.get_role(msg)]( - content=[self.oci_chat_message_content(text=msg.content)] - ) - for msg in messages - ] - oci_params = { + """Convert LangChain messages to OCI chat parameters. + + Args: + messages: List of LangChain BaseMessage objects + **kwargs: Additional keyword arguments + + Returns: + Dict containing OCI chat parameters + + Raises: + ValueError: If message content is invalid + """ + oci_messages = [] + + for message in messages: + content = self._process_message_content(message.content) + oci_message = self.oci_chat_message[self.get_role(message)](content=content) + oci_messages.append(oci_message) + + return { "messages": oci_messages, "api_format": self.chat_api_format, "top_k": -1, } - return oci_params + def _process_message_content( + self, content: Union[str, List[Union[str, Dict]]] + ) -> List[Any]: + """Process message content into OCI chat content format. + + Args: + content: Message content as string or list + + Returns: + List of OCI chat content objects + + Raises: + ValueError: If content format is invalid + """ + if isinstance(content, str): + return [self.oci_chat_message_text_content(text=content)] + + if not isinstance(content, list): + raise ValueError("Message content must be str or list of items") + + processed_content = [] + for item in content: + if isinstance(item, str): + processed_content.append(self.oci_chat_message_text_content(text=item)) + continue + + if not isinstance(item, dict): + raise ValueError( + f"Content items must be str or dict, got: {type(item)}" + ) + + if "type" not in item: + raise ValueError("Dict content item must have a type key") + + if item["type"] == "image_url": + processed_content.append( + self.oci_chat_message_image_content( + image_url=self.oci_chat_message_image_url( + url=item["image_url"]["url"] + ) + ) + ) + elif item["type"] == "text": + processed_content.append( + self.oci_chat_message_text_content(text=item["text"]) + ) + else: + raise ValueError(f"Unsupported content type: {item['type']}") + + return processed_content def convert_to_oci_tool( self, @@ -577,7 +652,10 @@ def bind_tools( def with_structured_output( self, - schema: Union[Dict[Any, Any], Type[BaseModel]], + schema: Optional[Union[Dict, Type[BaseModel]]] = None, + *, + method: Literal["function_calling", "json_mode"] = "function_calling", + include_raw: bool = False, **kwargs: Any, ) -> Runnable[LanguageModelInput, Union[Dict, BaseModel]]: """Model wrapper that returns outputs formatted to match the given schema. @@ -585,24 +663,86 @@ def with_structured_output( Args: schema: The output schema as a dict or a Pydantic class. If a Pydantic class then the model output will be an object of that class. If a dict then - the model output will be a dict. + the model output will be a dict. With a Pydantic class the returned + attributes will be validated, whereas with a dict they will not be. If + `method` is "function_calling" and `schema` is a dict, then the dict + must match the OCI Generative AI function-calling spec. + method: + The method for steering model generation, either "function_calling" + or "json_mode". If "function_calling" then the schema will be converted + to an OCI function and the returned model will make use of the + function-calling API. If "json_mode" then Cohere's JSON mode will be + used. Note that if using "json_mode" then you must include instructions + for formatting the output into the desired schema into the model call. + include_raw: + If False then only the parsed structured output is returned. If + an error occurs during model output parsing it will be raised. If True + then both the raw model response (a BaseMessage) and the parsed model + response will be returned. If an error occurs during output parsing it + will be caught and returned as well. The final output is always a dict + with keys "raw", "parsed", and "parsing_error". Returns: - A Runnable that takes any ChatModel input and returns either a dict or - Pydantic class as output. - """ - llm = self.bind_tools([schema], **kwargs) - if isinstance(schema, type) and issubclass(schema, BaseModel): - output_parser: OutputParserLike = PydanticToolsParser( - tools=[schema], first_tool_only=True + A Runnable that takes any ChatModel input and returns as output: + + If include_raw is True then a dict with keys: + raw: BaseMessage + parsed: Optional[_DictOrPydantic] + parsing_error: Optional[BaseException] + + If include_raw is False then just _DictOrPydantic is returned, + where _DictOrPydantic depends on the schema: + + If schema is a Pydantic class then _DictOrPydantic is the Pydantic + class. + + If schema is a dict then _DictOrPydantic is a dict. + + """ # noqa: E501 + if kwargs: + raise ValueError(f"Received unsupported arguments {kwargs}") + is_pydantic_schema = _is_pydantic_class(schema) + if method == "function_calling": + if schema is None: + raise ValueError( + "schema must be specified when method is 'function_calling'. " + "Received None." + ) + llm = self.bind_tools([schema], **kwargs) + tool_name = getattr(self._provider.convert_to_oci_tool(schema), "name") + if is_pydantic_schema: + output_parser: OutputParserLike = PydanticToolsParser( + tools=[schema], # type: ignore[list-item] + first_tool_only=True, # type: ignore[list-item] + ) + else: + output_parser = JsonOutputKeyToolsParser( + key_name=tool_name, first_tool_only=True + ) + elif method == "json_mode": + llm = self.bind(response_format={"type": "json_object"}) + output_parser = ( + PydanticOutputParser(pydantic_object=schema) # type: ignore[type-var, arg-type] + if is_pydantic_schema + else JsonOutputParser() ) else: - key_name = getattr(self._provider.convert_to_oci_tool(schema), "name") - output_parser = JsonOutputKeyToolsParser( - key_name=key_name, first_tool_only=True + raise ValueError( + f"Unrecognized method argument. " + f"Expected `function_calling` or `json_mode`." + f"Received: `{method}`." ) - - return llm | output_parser + if include_raw: + parser_assign = RunnablePassthrough.assign( + parsed=itemgetter("raw") | output_parser, parsing_error=lambda _: None + ) + parser_none = RunnablePassthrough.assign(parsed=lambda _: None) + parser_with_fallback = parser_assign.with_fallbacks( + [parser_none], exception_key="parsing_error" + ) + return RunnableMap(raw=llm) | parser_with_fallback + else: + return llm | output_parser def _generate( self, From 33b1fb95b8919a4ba1967e5a6f46279cc48629fa Mon Sep 17 00:00:00 2001 From: GITHUBear <1729307751@qq.com> Date: Wed, 18 Dec 2024 06:51:49 -0800 Subject: [PATCH 05/31] partners: langchain-oceanbase Integration (#28782) Hi, langchain team! I'm a maintainer of [OceanBase](https://github.com/oceanbase/oceanbase). With the integration guidance, I create a python lib named [langchain-oceanbase](https://github.com/oceanbase/langchain-oceanbase) to integrate `Oceanbase Vector Store` with `Langchain`. So I'd like to add the required docs. I will appreciate your feedback. Thank you! --------- Signed-off-by: shanhaikang.shk Co-authored-by: Erick Friis --- .../docs/integrations/providers/oceanbase.mdx | 31 ++ .../integrations/vectorstores/oceanbase.ipynb | 383 ++++++++++++++++++ libs/packages.yml | 3 + 3 files changed, 417 insertions(+) create mode 100644 docs/docs/integrations/providers/oceanbase.mdx create mode 100644 docs/docs/integrations/vectorstores/oceanbase.ipynb diff --git a/docs/docs/integrations/providers/oceanbase.mdx b/docs/docs/integrations/providers/oceanbase.mdx new file mode 100644 index 0000000000000..30537f1391004 --- /dev/null +++ b/docs/docs/integrations/providers/oceanbase.mdx @@ -0,0 +1,31 @@ +# OceanBase + +[OceanBase Database](https://github.com/oceanbase/oceanbase) is a distributed relational database. +It is developed entirely by Ant Group. The OceanBase Database is built on a common server cluster. +Based on the Paxos protocol and its distributed structure, the OceanBase Database provides high availability and linear scalability. + +OceanBase currently has the ability to store vectors. Users can easily perform the following operations with SQL: + +- Create a table containing vector type fields; +- Create a vector index table based on the HNSW algorithm; +- Perform vector approximate nearest neighbor queries; +- ... + +## Installation + +```bash +pip install -U langchain-oceanbase +``` + +We recommend using Docker to deploy OceanBase: + +```shell +docker run --name=ob433 -e MODE=slim -p 2881:2881 -d oceanbase/oceanbase-ce:4.3.3.0-100000132024100711 +``` + +[More methods to deploy OceanBase cluster](https://github.com/oceanbase/oceanbase-doc/blob/V4.3.1/en-US/400.deploy/500.deploy-oceanbase-database-community-edition/100.deployment-overview.md) + +### Usage + +For a more detailed walkthrough of the OceanBase Wrapper, see [this notebook](https://github.com/oceanbase/langchain-oceanbase/blob/main/docs/vectorstores.ipynb) + diff --git a/docs/docs/integrations/vectorstores/oceanbase.ipynb b/docs/docs/integrations/vectorstores/oceanbase.ipynb new file mode 100644 index 0000000000000..3ede92cb85355 --- /dev/null +++ b/docs/docs/integrations/vectorstores/oceanbase.ipynb @@ -0,0 +1,383 @@ +{ + "cells": [ + { + "cell_type": "raw", + "id": "1957f5cb", + "metadata": {}, + "source": [ + "---\n", + "sidebar_label: Oceanbase\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "ef1f0986", + "metadata": {}, + "source": [ + "# OceanbaseVectorStore\n", + "\n", + "This notebook covers how to get started with the Oceanbase vector store." + ] + }, + { + "cell_type": "markdown", + "id": "36fdc060", + "metadata": {}, + "source": [ + "## Setup\n", + "\n", + "To access Oceanbase vector stores you'll need to deploy a standalone OceanBase server:" + ] + }, + { + "cell_type": "raw", + "id": "a7b92118", + "metadata": {}, + "source": [ + "%docker run --name=ob433 -e MODE=mini -e OB_SERVER_IP=127.0.0.1 -p 2881:2881 -d quay.io/oceanbase/oceanbase-ce:4.3.3.1-101000012024102216" + ] + }, + { + "cell_type": "markdown", + "id": "5b687bdc", + "metadata": {}, + "source": [ + "And install the `langchain-oceanbase` integration package." + ] + }, + { + "cell_type": "raw", + "id": "64e28aa6", + "metadata": { + "vscode": { + "languageId": "raw" + } + }, + "source": [ + "%pip install -qU \"langchain-oceanbase\"" + ] + }, + { + "cell_type": "markdown", + "id": "ea850342", + "metadata": {}, + "source": [ + "Check the connection to OceanBase and set the memory usage ratio for vector data:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "066bbc79", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from pyobvector import ObVecClient\n", + "\n", + "tmp_client = ObVecClient()\n", + "tmp_client.perform_raw_text_sql(\"ALTER SYSTEM ob_vector_memory_limit_percentage = 30\")" + ] + }, + { + "cell_type": "markdown", + "id": "93df377e", + "metadata": {}, + "source": [ + "## Initialization\n", + "\n", + "Configure the API key of the embedded model. Here we use `DashScopeEmbeddings` as an example. When deploying `Oceanbase` with a Docker image as described above, simply follow the script below to set the `host`, `port`, `user`, `password`, and `database name`. For other deployment methods, set these parameters according to the actual situation." + ] + }, + { + "cell_type": "raw", + "id": "ff29e3b7", + "metadata": {}, + "source": [ + "%pip install dashscope" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "dc37144c-208d-4ab3-9f3a-0407a69fe052", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "from langchain_community.embeddings import DashScopeEmbeddings\n", + "from langchain_oceanbase.vectorstores import OceanbaseVectorStore\n", + "\n", + "DASHSCOPE_API = os.environ.get(\"DASHSCOPE_API_KEY\", \"\")\n", + "connection_args = {\n", + " \"host\": \"127.0.0.1\",\n", + " \"port\": \"2881\",\n", + " \"user\": \"root@test\",\n", + " \"password\": \"\",\n", + " \"db_name\": \"test\",\n", + "}\n", + "\n", + "embeddings = DashScopeEmbeddings(\n", + " model=\"text-embedding-v1\", dashscope_api_key=DASHSCOPE_API\n", + ")\n", + "\n", + "vector_store = OceanbaseVectorStore(\n", + " embedding_function=embeddings,\n", + " table_name=\"langchain_vector\",\n", + " connection_args=connection_args,\n", + " vidx_metric_type=\"l2\",\n", + " drop_old=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ac6071d4", + "metadata": {}, + "source": [ + "## Manage vector store\n", + "\n", + "### Add items to vector store\n", + "\n", + "- TODO: Edit and then run code cell to generate output" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "17f5efc0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['1', '2', '3']" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from langchain_core.documents import Document\n", + "\n", + "document_1 = Document(page_content=\"foo\", metadata={\"source\": \"https://foo.com\"})\n", + "document_2 = Document(page_content=\"bar\", metadata={\"source\": \"https://bar.com\"})\n", + "document_3 = Document(page_content=\"baz\", metadata={\"source\": \"https://baz.com\"})\n", + "\n", + "documents = [document_1, document_2, document_3]\n", + "\n", + "vector_store.add_documents(documents=documents, ids=[\"1\", \"2\", \"3\"])" + ] + }, + { + "cell_type": "markdown", + "id": "c738c3e0", + "metadata": {}, + "source": [ + "### Update items in vector store" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "f0aa8b71", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['1']" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "updated_document = Document(\n", + " page_content=\"qux\", metadata={\"source\": \"https://another-example.com\"}\n", + ")\n", + "\n", + "vector_store.add_documents(documents=[updated_document], ids=[\"1\"])" + ] + }, + { + "cell_type": "markdown", + "id": "dcf1b905", + "metadata": {}, + "source": [ + "### Delete items from vector store" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "ef61e188", + "metadata": {}, + "outputs": [], + "source": [ + "vector_store.delete(ids=[\"3\"])" + ] + }, + { + "cell_type": "markdown", + "id": "c3620501", + "metadata": {}, + "source": [ + "## Query vector store\n", + "\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", + "### Query directly\n", + "\n", + "Performing a simple similarity search can be done as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "aa0a16fa", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* bar [{'source': 'https://bar.com'}]\n" + ] + } + ], + "source": [ + "results = vector_store.similarity_search(\n", + " query=\"thud\", k=1, filter={\"source\": \"https://another-example.com\"}\n", + ")\n", + "for doc in results:\n", + " print(f\"* {doc.page_content} [{doc.metadata}]\")" + ] + }, + { + "cell_type": "markdown", + "id": "3ed9d733", + "metadata": {}, + "source": [ + "If you want to execute a similarity search and receive the corresponding scores you can run:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "5efd2eaa", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "* [SIM=133.452299] bar [{'source': 'https://bar.com'}]\n" + ] + } + ], + "source": [ + "results = vector_store.similarity_search_with_score(\n", + " query=\"thud\", k=1, filter={\"source\": \"https://example.com\"}\n", + ")\n", + "for doc, score in results:\n", + " print(f\"* [SIM={score:3f}] {doc.page_content} [{doc.metadata}]\")" + ] + }, + { + "cell_type": "markdown", + "id": "0c235cdc", + "metadata": {}, + "source": [ + "### Query by turning into retriever\n", + "\n", + "You can also transform the vector store into a retriever for easier usage in your chains. " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "f3460093", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Document(metadata={'source': 'https://bar.com'}, page_content='bar')]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "retriever = vector_store.as_retriever(search_kwargs={\"k\": 1})\n", + "retriever.invoke(\"thud\")" + ] + }, + { + "cell_type": "markdown", + "id": "901c75dc", + "metadata": {}, + "source": [ + "## Usage for retrieval-augmented generation\n", + "\n", + "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n", + "\n", + "- [Tutorials](/docs/tutorials/)\n", + "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n", + "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/#retrieval)" + ] + }, + { + "cell_type": "markdown", + "id": "8a27244f", + "metadata": {}, + "source": [ + "## API reference\n", + "\n", + "For detailed documentation of all OceanbaseVectorStore features and configurations head to the API reference: https://python.langchain.com/docs/integrations/vectorstores/oceanbase" + ] + } + ], + "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": "3.11.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/libs/packages.yml b/libs/packages.yml index e7882917fe55f..9613d4780552b 100644 --- a/libs/packages.yml +++ b/libs/packages.yml @@ -158,3 +158,6 @@ packages: - name: langchain-linkup repo: LinkupPlatform/langchain-linkup path: . + - name: langchain-oceanbase + repo: oceanbase/langchain-oceanbase + path: . From 91d28ef4532a342eeda75b065efb02db32494241 Mon Sep 17 00:00:00 2001 From: ANSARI MD AAQIB AHMED <108489381+aqib0770@users.noreply.github.com> Date: Wed, 18 Dec 2024 20:46:50 +0530 Subject: [PATCH 06/31] Add langchain-yt-dlp Document Loader Documentation (#28775) ## Overview This PR adds documentation for the `langchain-yt-dlp` package, a YouTube document loader that uses `yt-dlp` for Youtube videos metadata extraaction. ## Changes - Added documentation notebook for YoutubeLoader - Updated packages.yml to include langchain-yt-dlp ## Motivation The existing LangChain YoutubeLoader was unable to fetch YouTube metadata due to changes in YouTube's structure. This package resolves those issues by leveraging the `yt-dlp` library. ## Features - Reliable YouTube metadata extraction ## Related - Package Repository: https://github.com/aqib0770/langchain-yt-dlp - PyPI Package: https://pypi.org/project/langchain-yt-dlp/ --------- Co-authored-by: Chester Curme --- .../document_loaders/yt_dlp.ipynb | 149 ++++++++++++++++++ libs/packages.yml | 5 +- 2 files changed, 153 insertions(+), 1 deletion(-) create mode 100644 docs/docs/integrations/document_loaders/yt_dlp.ipynb diff --git a/docs/docs/integrations/document_loaders/yt_dlp.ipynb b/docs/docs/integrations/document_loaders/yt_dlp.ipynb new file mode 100644 index 0000000000000..c27685d90a0c0 --- /dev/null +++ b/docs/docs/integrations/document_loaders/yt_dlp.ipynb @@ -0,0 +1,149 @@ +{ + "cells": [ + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "---\n", + "sidebar_label: YoutubeLoaderDL\n", + "---" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# YoutubeLoaderDL\n", + "\n", + "Loader for Youtube leveraging the `yt-dlp` library.\n", + "\n", + "This package implements a [document loader](/docs/concepts/document_loaders/) for Youtube. In contrast to the [YoutubeLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.youtube.YoutubeLoader.html) of `langchain-community`, which relies on `pytube`, `YoutubeLoaderDL` is able to fetch YouTube metadata. `langchain-yt-dlp` leverages the robust `yt-dlp` library, providing a more reliable and feature-rich YouTube document loader.\n", + "\n", + "## Overview\n", + "### Integration details\n", + "\n", + "| Class | Package | Local | Serializable | JS Support |\n", + "| :--- | :--- | :---: | :---: | :---: |\n", + "| YoutubeLoader | langchain-yt-dlp | ✅ | ✅ | ❌ |\n", + "\n", + "## Setup\n", + "\n", + "### Installation\n", + "\n", + "```bash\n", + "pip install langchain-yt-dlp\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Initialization" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain_yt_dlp.youtube_loader import YoutubeLoaderDL\n", + "\n", + "# Basic transcript loading\n", + "loader = YoutubeLoaderDL.from_youtube_url(\n", + " \"https://www.youtube.com/watch?v=dQw4w9WgXcQ\", add_video_info=True\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Load" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "documents = loader.load()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'source': 'dQw4w9WgXcQ',\n", + " 'title': 'Rick Astley - Never Gonna Give You Up (Official Music Video)',\n", + " 'description': 'The official video for “Never Gonna Give You Up” by Rick Astley. \\n\\nNever: The Autobiography 📚 OUT NOW! \\nFollow this link to get your copy and listen to Rick’s ‘Never’ playlist ❤️ #RickAstleyNever\\nhttps://linktr.ee/rickastleynever\\n\\n“Never Gonna Give You Up” was a global smash on its release in July 1987, topping the charts in 25 countries including Rick’s native UK and the US Billboard Hot 100. It also won the Brit Award for Best single in 1988. Stock Aitken and Waterman wrote and produced the track which was the lead-off single and lead track from Rick’s debut LP “Whenever You Need Somebody”. The album was itself a UK number one and would go on to sell over 15 million copies worldwide.\\n\\nThe legendary video was directed by Simon West – who later went on to make Hollywood blockbusters such as Con Air, Lara Croft – Tomb Raider and The Expendables 2. The video passed the 1bn YouTube views milestone on 28 July 2021.\\n\\nSubscribe to the official Rick Astley YouTube channel: https://RickAstley.lnk.to/YTSubID\\n\\nFollow Rick Astley:\\nFacebook: https://RickAstley.lnk.to/FBFollowID \\nTwitter: https://RickAstley.lnk.to/TwitterID \\nInstagram: https://RickAstley.lnk.to/InstagramID \\nWebsite: https://RickAstley.lnk.to/storeID \\nTikTok: https://RickAstley.lnk.to/TikTokID\\n\\nListen to Rick Astley:\\nSpotify: https://RickAstley.lnk.to/SpotifyID \\nApple Music: https://RickAstley.lnk.to/AppleMusicID \\nAmazon Music: https://RickAstley.lnk.to/AmazonMusicID \\nDeezer: https://RickAstley.lnk.to/DeezerID \\n\\nLyrics:\\nWe’re no strangers to love\\nYou know the rules and so do I\\nA full commitment’s what I’m thinking of\\nYou wouldn’t get this from any other guy\\n\\nI just wanna tell you how I’m feeling\\nGotta make you understand\\n\\nNever gonna give you up\\nNever gonna let you down\\nNever gonna run around and desert you\\nNever gonna make you cry\\nNever gonna say goodbye\\nNever gonna tell a lie and hurt you\\n\\nWe’ve known each other for so long\\nYour heart’s been aching but you’re too shy to say it\\nInside we both know what’s been going on\\nWe know the game and we’re gonna play it\\n\\nAnd if you ask me how I’m feeling\\nDon’t tell me you’re too blind to see\\n\\nNever gonna give you up\\nNever gonna let you down\\nNever gonna run around and desert you\\nNever gonna make you cry\\nNever gonna say goodbye\\nNever gonna tell a lie and hurt you\\n\\n#RickAstley #NeverGonnaGiveYouUp #WheneverYouNeedSomebody #OfficialMusicVideo',\n", + " 'view_count': 1603360806,\n", + " 'publish_date': datetime.datetime(2009, 10, 25, 0, 0),\n", + " 'length': 212,\n", + " 'author': 'Rick Astley',\n", + " 'channel_id': 'UCuAXFkgsw1L7xaCfnd5JJOw',\n", + " 'webpage_url': 'https://www.youtube.com/watch?v=dQw4w9WgXcQ'}" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "documents[0].metadata" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Lazy Load" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- No lazy loading is implemented" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## API reference:\n", + "\n", + "- [Github](https://github.com/aqib0770/langchain-yt-dlp)\n", + "- [PyPi](https://pypi.org/project/langchain-yt-dlp/)" + ] + } + ], + "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": "3.10.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/libs/packages.yml b/libs/packages.yml index 9613d4780552b..c5891e30bf31f 100644 --- a/libs/packages.yml +++ b/libs/packages.yml @@ -158,6 +158,9 @@ packages: - name: langchain-linkup repo: LinkupPlatform/langchain-linkup path: . + - name: langchain-yt-dlp + repo: aqib0770/langchain-yt-dlp + path: . - name: langchain-oceanbase repo: oceanbase/langchain-oceanbase - path: . + path: . \ No newline at end of file From f723a8456ebab0243dded27971cb6a6698540baf Mon Sep 17 00:00:00 2001 From: binhnd102 <51689237+binhnd102@users.noreply.github.com> Date: Wed, 18 Dec 2024 22:21:28 +0700 Subject: [PATCH 07/31] Fixes: community: fix LanceDB return no metadata (#27024) - [ x ] Fix when lancedb return table without metadata column - **Description:** Check the table schema, if not has metadata column, init the Document with metadata argument equal to empty dict - **Issue:** https://github.com/langchain-ai/langchain/issues/27005 - [ x ] **Add tests and docs** --------- Co-authored-by: ccurme --- .../vectorstores/lancedb.py | 8 +++- .../vectorstores/test_lancedb.py | 38 +++++++++++++++++++ 2 files changed, 44 insertions(+), 2 deletions(-) diff --git a/libs/community/langchain_community/vectorstores/lancedb.py b/libs/community/langchain_community/vectorstores/lancedb.py index 7253d885b11e6..f08e4380481b1 100644 --- a/libs/community/langchain_community/vectorstores/lancedb.py +++ b/libs/community/langchain_community/vectorstores/lancedb.py @@ -151,12 +151,14 @@ def results_to_docs(self, results: Any, score: bool = False) -> Any: score_col = "_relevance_score" else: score_col = None + # Check if 'metadata' is in the columns + has_metadata = "metadata" in columns if score_col is None or not score: return [ Document( page_content=results[self._text_key][idx].as_py(), - metadata=results["metadata"][idx].as_py(), + metadata=results["metadata"][idx].as_py() if has_metadata else {}, ) for idx in range(len(results)) ] @@ -165,7 +167,9 @@ def results_to_docs(self, results: Any, score: bool = False) -> Any: ( Document( page_content=results[self._text_key][idx].as_py(), - metadata=results["metadata"][idx].as_py(), + metadata=results["metadata"][idx].as_py() + if has_metadata + else {}, ), results[score_col][idx].as_py(), ) diff --git a/libs/community/tests/integration_tests/vectorstores/test_lancedb.py b/libs/community/tests/integration_tests/vectorstores/test_lancedb.py index 7ba3a00466388..615b310629d34 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_lancedb.py +++ b/libs/community/tests/integration_tests/vectorstores/test_lancedb.py @@ -114,3 +114,41 @@ def test_lancedb_all_searches() -> None: ) assert len(result_3[0]) == 2 # type: ignore assert "text 1" in result_3[0][0].page_content # type: ignore + + +@pytest.mark.requires("lancedb") +def test_lancedb_no_metadata() -> None: + lancedb = import_lancedb() + embeddings = FakeEmbeddings() + # Connect to a temporary LanceDB instance + db = lancedb.connect("/tmp/lancedb_no_metadata_test") + # Create data without the 'metadata' field + texts = ["text 1", "text 2", "item 3"] + data = [] + for idx, text in enumerate(texts): + embedding = embeddings.embed_documents([text])[0] + data.append( + { + "vector": embedding, + "id": str(idx), + "text": text, + # Note: We're deliberately not including 'metadata' here + } + ) + # Create the table without 'metadata' column + db.create_table("vectorstore_no_metadata", data=data) + # Initialize LanceDB with the existing connection and table name + store = LanceDB( + connection=db, + embedding=embeddings, + table_name="vectorstore_no_metadata", + ) + # Perform a similarity search + result = store.similarity_search("text 1") + # Verify that the metadata in the Document objects is an empty dictionary + for doc in result: + assert ( + doc.metadata == {} + ), "Expected empty metadata when 'metadata' column is missing" + # Clean up by deleting the table (optional) + db.drop_table("vectorstore_no_metadata") From d49df4871d98a8daf97d3b09caa8468242c9d0e3 Mon Sep 17 00:00:00 2001 From: Mohammad Mohtashim <45242107+keenborder786@users.noreply.github.com> Date: Wed, 18 Dec 2024 21:45:48 +0500 Subject: [PATCH 08/31] [Community]: Image Extraction Fixed for `PDFPlumberParser` (#28491) - **Description:** One-Bit Images was raising error which has been fixed in this PR for `PDFPlumberParser` - **Issue:** #28480 --------- Co-authored-by: Chester Curme --- .../document_loaders/parsers/pdf.py | 28 ++++++++++++++++--- 1 file changed, 24 insertions(+), 4 deletions(-) diff --git a/libs/community/langchain_community/document_loaders/parsers/pdf.py b/libs/community/langchain_community/document_loaders/parsers/pdf.py index c603dde71eb32..702d5998dd7c2 100644 --- a/libs/community/langchain_community/document_loaders/parsers/pdf.py +++ b/libs/community/langchain_community/document_loaders/parsers/pdf.py @@ -427,6 +427,13 @@ def __init__( text_kwargs: Keyword arguments to pass to ``pdfplumber.Page.extract_text()`` dedupe: Avoiding the error of duplicate characters if `dedupe=True`. """ + try: + import PIL # noqa:F401 + except ImportError: + raise ImportError( + "pillow package not found, please install it with" + " `pip install pillow`" + ) self.text_kwargs = text_kwargs or {} self.dedupe = dedupe self.extract_images = extract_images @@ -468,17 +475,30 @@ def _process_page_content(self, page: pdfplumber.page.Page) -> str: def _extract_images_from_page(self, page: pdfplumber.page.Page) -> str: """Extract images from page and get the text with RapidOCR.""" + from PIL import Image + if not self.extract_images: return "" images = [] for img in page.images: if img["stream"]["Filter"].name in _PDF_FILTER_WITHOUT_LOSS: - images.append( - np.frombuffer(img["stream"].get_data(), dtype=np.uint8).reshape( - img["stream"]["Height"], img["stream"]["Width"], -1 + if img["stream"]["BitsPerComponent"] == 1: + images.append( + np.array( + Image.frombytes( + "1", + (img["stream"]["Width"], img["stream"]["Height"]), + img["stream"].get_data(), + ).convert("L") + ) + ) + else: + images.append( + np.frombuffer(img["stream"].get_data(), dtype=np.uint8).reshape( + img["stream"]["Height"], img["stream"]["Width"], -1 + ) ) - ) elif img["stream"]["Filter"].name in _PDF_FILTER_WITH_LOSS: images.append(img["stream"].get_data()) else: From 5cf965004c7b5c839ef59cd9c55230373c4d0ae6 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Wed, 18 Dec 2024 09:28:42 -0800 Subject: [PATCH 09/31] core: release 0.3.26 (#28793) --- libs/core/poetry.lock | 252 +++++++++++++++++++-------------------- libs/core/pyproject.toml | 8 +- 2 files changed, 133 insertions(+), 127 deletions(-) diff --git a/libs/core/poetry.lock b/libs/core/poetry.lock index b7fe070395602..d39e1a397af16 100644 --- a/libs/core/poetry.lock +++ b/libs/core/poetry.lock @@ -151,19 +151,19 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} [[package]] name = "attrs" -version = "24.2.0" +version = "24.3.0" description = "Classes Without Boilerplate" optional = false -python-versions = 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for the Python Logging Package" optional = false python-versions = ">=3.8" files = [ - {file = "python_json_logger-3.2.0-py3-none-any.whl", hash = "sha256:d73522ddcfc6d0461394120feaddea9025dc64bf804d96357dd42fa878cc5fe8"}, - {file = "python_json_logger-3.2.0.tar.gz", hash = "sha256:2c11056458d3f56614480b24e9cb28f7aba69cbfbebddbb77c92f0ec0d4947ab"}, + {file = "python_json_logger-3.2.1-py3-none-any.whl", hash = "sha256:cdc17047eb5374bd311e748b42f99d71223f3b0e186f4206cc5d52aefe85b090"}, + {file = "python_json_logger-3.2.1.tar.gz", hash = "sha256:8eb0554ea17cb75b05d2848bc14fb02fbdbd9d6972120781b974380bfa162008"}, ] [package.dependencies] @@ -3778,13 +3777,13 @@ files = [ [[package]] name = "smart-open" -version = "7.0.5" +version = "7.1.0" description = "Utils for streaming large files (S3, HDFS, GCS, Azure Blob Storage, gzip, bz2...)" optional = false python-versions = "<4.0,>=3.7" files = [ - {file = "smart_open-7.0.5-py3-none-any.whl", hash = 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"LangChain text splitting utilities" authors = [] license = "MIT" @@ -36,7 +36,7 @@ ignore_missing_imports = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.25" +langchain-core = "^0.3.26" [tool.ruff.lint] select = ["E", "F", "I", "T201", "D"] @@ -74,16 +74,19 @@ convention = "google" [tool.poetry.group.lint.dependencies] ruff = "^0.5" + [tool.poetry.group.typing.dependencies] mypy = "^1.10" lxml-stubs = "^0.5.1" types-requests = "^2.31.0.20240218" tiktoken = "^0.8.0" + [tool.poetry.group.dev.dependencies] jupyter = "^1.0.0" + [tool.poetry.group.test.dependencies] pytest = "^8" freezegun = "^1.2.2" @@ -92,6 +95,7 @@ pytest-watcher = "^0.3.4" pytest-asyncio = "^0.21.1" pytest-socket = "^0.7.0" + [tool.poetry.group.test_integration] optional = true @@ -101,14 +105,17 @@ nltk = "^3.9.1" transformers = "^4.47.0" sentence-transformers = { version = ">=2.6.0", python = "<3.13" } + [tool.poetry.group.lint.dependencies.langchain-core] path = "../core" develop = true + [tool.poetry.group.dev.dependencies.langchain-core] path = "../core" develop = true + [tool.poetry.group.test.dependencies.langchain-core] path = "../core" develop = true From e6b41d081deebdea4b2775e798a8e68d8f9ab8c5 Mon Sep 17 00:00:00 2001 From: Martin Triska Date: Wed, 18 Dec 2024 18:47:08 +0100 Subject: [PATCH 11/31] community: DocumentLoaderAsParser wrapper (#27749) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ## Description This pull request introduces the `DocumentLoaderAsParser` class, which acts as an adapter to transform document loaders into parsers within the LangChain framework. The class enables document loaders that accept a `file_path` parameter to be utilized as blob parsers. This is particularly useful for integrating various document loading capabilities seamlessly into the LangChain ecosystem. When merged in together with PR https://github.com/langchain-ai/langchain/pull/27716 It opens options for `SharePointLoader` / `OneDriveLoader` to process any filetype that has a document loader. ### Features - **Flexible Parsing**: The `DocumentLoaderAsParser` class can adapt any document loader that meets the criteria of accepting a `file_path` argument, allowing for lazy parsing of documents. - **Compatibility**: The class has been designed to work with various document loaders, making it versatile for different use cases. ### Usage Example To use the `DocumentLoaderAsParser`, you would initialize it with a suitable document loader class and any required parameters. Here’s an example of how to do this with the `UnstructuredExcelLoader`: ```python from langchain_community.document_loaders.blob_loaders import Blob from langchain_community.document_loaders.parsers.documentloader_adapter import DocumentLoaderAsParser from langchain_community.document_loaders.excel import UnstructuredExcelLoader # Initialize the parser adapter with UnstructuredExcelLoader xlsx_parser = DocumentLoaderAsParser(UnstructuredExcelLoader, mode="paged") # Use parser, for ex. pass it to MimeTypeBasedParser MimeTypeBasedParser( handlers={ "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet": xlsx_parser } ) ``` - **Dependencies:** None - **Twitter handle:** @martintriska1 If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --------- Co-authored-by: Chester Curme --- .../parsers/documentloader_adapter.py | 67 +++++++++++++++++++ 1 file changed, 67 insertions(+) create mode 100644 libs/community/langchain_community/document_loaders/parsers/documentloader_adapter.py diff --git a/libs/community/langchain_community/document_loaders/parsers/documentloader_adapter.py b/libs/community/langchain_community/document_loaders/parsers/documentloader_adapter.py new file mode 100644 index 0000000000000..38be56d9a24e5 --- /dev/null +++ b/libs/community/langchain_community/document_loaders/parsers/documentloader_adapter.py @@ -0,0 +1,67 @@ +import inspect +from typing import Any, Dict, Iterator, Type + +from langchain.document_loaders.base import BaseBlobParser, BaseLoader +from langchain_core._api import beta +from langchain_core.documents import Document +from langchain_core.documents.base import Blob + + +@beta() +class DocumentLoaderAsParser(BaseBlobParser): + """A wrapper class that adapts a document loader to function as a parser. + + This class is a work-around that adapts a document loader to function as a parser. + It is recommended to use a proper parser, if available. + + Requires the document loader to accept a `file_path` parameter. + """ + + DocumentLoaderType: Type[BaseLoader] + doc_loader_kwargs: Dict[str, Any] + + def __init__(self, document_loader_class: Type[BaseLoader], **kwargs: Any) -> None: + """ + Initializes the DocumentLoaderAsParser with a specific document loader class + and additional arguments. + + Args: + document_loader_class (Type[BaseLoader]): The document loader class to adapt + as a parser. + **kwargs: Additional arguments passed to the document loader's constructor. + + Raises: + TypeError: If the specified document loader does not accept a `file_path` parameter, + an exception is raised, as only loaders with this parameter can be adapted. + + Example: + ``` + from langchain_community.document_loaders.excel import UnstructuredExcelLoader + + # Initialize parser adapter with a document loader + excel_parser = DocumentLoaderAsParser(UnstructuredExcelLoader, mode="elements") + ``` + """ # noqa: E501 + super().__init__() + self.DocumentLoaderClass = document_loader_class + self.document_loader_kwargs = kwargs + + # Ensure the document loader class has a `file_path` parameter + init_signature = inspect.signature(document_loader_class.__init__) + if "file_path" not in init_signature.parameters: + raise TypeError( + f"{document_loader_class.__name__} does not accept `file_path`." + "Only document loaders with `file_path` parameter" + "can be morphed into a parser." + ) + + def lazy_parse(self, blob: Blob) -> Iterator[Document]: + """ + Use underlying DocumentLoader to lazily parse the blob. + """ + doc_loader = self.DocumentLoaderClass( + file_path=blob.path, **self.document_loader_kwargs + ) # type: ignore + for document in doc_loader.lazy_load(): + document.metadata.update(blob.metadata) + yield document From 50ea1c3ea3a57050f50c9842259a9033548f2d5f Mon Sep 17 00:00:00 2001 From: William FH <13333726+hinthornw@users.noreply.github.com> Date: Wed, 18 Dec 2024 10:02:02 -0800 Subject: [PATCH 12/31] [Core] respect tracing project name cvar (#28792) --- libs/core/langchain_core/callbacks/manager.py | 1 + libs/core/langchain_core/tracers/context.py | 7 +++++-- .../runnables/test_tracing_interops.py | 19 +++++++++++++++++++ 3 files changed, 25 insertions(+), 2 deletions(-) diff --git a/libs/core/langchain_core/callbacks/manager.py b/libs/core/langchain_core/callbacks/manager.py index 821939d1a609c..cabe04b6a94d1 100644 --- a/libs/core/langchain_core/callbacks/manager.py +++ b/libs/core/langchain_core/callbacks/manager.py @@ -2379,6 +2379,7 @@ def _configure( if run_tree is not None else tracing_context["client"] ), + tags=tracing_tags, ) callback_manager.add_handler(handler, True) except Exception as e: diff --git a/libs/core/langchain_core/tracers/context.py b/libs/core/langchain_core/tracers/context.py index 3694db7188b06..d36adc9bc8eaf 100644 --- a/libs/core/langchain_core/tracers/context.py +++ b/libs/core/langchain_core/tracers/context.py @@ -13,8 +13,8 @@ ) from uuid import UUID +from langsmith import run_helpers as ls_rh from langsmith import utils as ls_utils -from langsmith.run_helpers import get_run_tree_context from langchain_core.tracers.langchain import LangChainTracer from langchain_core.tracers.run_collector import RunCollectorCallbackHandler @@ -149,7 +149,10 @@ def _tracing_v2_is_enabled() -> Union[bool, Literal["local"]]: def _get_tracer_project() -> str: - run_tree = get_run_tree_context() + tracing_context = ls_rh.get_tracing_context() + run_tree = tracing_context["parent"] + if run_tree is None and tracing_context["project_name"] is not None: + return tracing_context["project_name"] return getattr( run_tree, "session_name", diff --git a/libs/core/tests/unit_tests/runnables/test_tracing_interops.py b/libs/core/tests/unit_tests/runnables/test_tracing_interops.py index af6a5e84ce9ee..0743929f86120 100644 --- a/libs/core/tests/unit_tests/runnables/test_tracing_interops.py +++ b/libs/core/tests/unit_tests/runnables/test_tracing_interops.py @@ -35,6 +35,25 @@ def _get_posts(client: Client) -> list: return posts +def test_tracing_context() -> None: + mock_session = MagicMock() + mock_client_ = Client( + session=mock_session, api_key="test", auto_batch_tracing=False + ) + + @RunnableLambda + def my_function(a: int) -> int: + return a + 1 + + name = uuid.uuid4().hex + project_name = f"Some project {name}" + with tracing_context(project_name=project_name, client=mock_client_, enabled=True): + assert my_function.invoke(1) == 2 + posts = _get_posts(mock_client_) + assert posts + assert all(post["session_name"] == project_name for post in posts) + + def test_config_traceable_handoff() -> None: get_env_var.cache_clear() mock_session = MagicMock() From 684b146b181e8e32832d8d5f72a23e4fdd132abb Mon Sep 17 00:00:00 2001 From: "V.Prasanna kumar" Date: Thu, 19 Dec 2024 00:15:00 +0530 Subject: [PATCH 13/31] Fixed adding float values into DynamoDB (#26562) Thank you for contributing to LangChain! - [x] **PR title**: Add float Message into Dynamo DB - community - Example: "community: Chat Message History - [x] **PR message**: - **Description:** pushing float values into dynamo db creates error , solved that by converting to str type - **Issue:** Float values are not getting pushed - **Twitter handle:** VpkPrasanna Have added an utility function for str conversion , let me know where to place it happy to do an commit. This PR is from an discussion of #26543 @hwchase17 @baskaryan @efriis --------- Co-authored-by: Chester Curme --- .../chat_message_histories/dynamodb.py | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/libs/community/langchain_community/chat_message_histories/dynamodb.py b/libs/community/langchain_community/chat_message_histories/dynamodb.py index ca1586a2b0a87..62beb4895e747 100644 --- a/libs/community/langchain_community/chat_message_histories/dynamodb.py +++ b/libs/community/langchain_community/chat_message_histories/dynamodb.py @@ -1,6 +1,7 @@ from __future__ import annotations import logging +from decimal import Decimal from typing import TYPE_CHECKING, Dict, List, Optional from langchain_core.chat_history import BaseChatMessageHistory @@ -17,6 +18,16 @@ logger = logging.getLogger(__name__) +def convert_messages(item: List) -> List: + if isinstance(item, list): + return [convert_messages(i) for i in item] + elif isinstance(item, dict): + return {k: convert_messages(v) for k, v in item.items()} + elif isinstance(item, float): + return Decimal(str(item)) + return item + + class DynamoDBChatMessageHistory(BaseChatMessageHistory): """Chat message history that stores history in AWS DynamoDB. @@ -47,6 +58,8 @@ class DynamoDBChatMessageHistory(BaseChatMessageHistory): limit. If not None then only the latest `history_size` messages are stored. history_messages_key: Key for the chat history where the messages are stored and updated + coerce_float_to_decimal: If True, all float values in the messages will be + converted to Decimal. """ def __init__( @@ -62,6 +75,8 @@ def __init__( ttl_key_name: str = "expireAt", history_size: Optional[int] = None, history_messages_key: Optional[str] = "History", + *, + coerce_float_to_decimal: bool = False, ): if boto3_session: client = boto3_session.resource("dynamodb", endpoint_url=endpoint_url) @@ -83,6 +98,7 @@ def __init__( self.ttl_key_name = ttl_key_name self.history_size = history_size self.history_messages_key = history_messages_key + self.coerce_float_to_decimal = coerce_float_to_decimal if kms_key_id: try: @@ -159,6 +175,9 @@ def add_message(self, message: BaseMessage) -> None: _message = message_to_dict(message) messages.append(_message) + if self.coerce_float_to_decimal: + messages = convert_messages(messages) + if self.history_size: messages = messages[-self.history_size :] From 7c8f9776959e0243706e529ca08535d017b1dbc8 Mon Sep 17 00:00:00 2001 From: Mohammad Mohtashim <45242107+keenborder786@users.noreply.github.com> Date: Thu, 19 Dec 2024 00:35:06 +0500 Subject: [PATCH 14/31] Community: Fix `with_structured_output` for `ChatSambaNovaCloud` (#28796) - **Description:** The `kwargs` was being checked as None object which was causing the rest of code in `with_structured_output` not getting executed. The checking part has been fixed in this PR. - **Issue:** #28776 --- .../langchain_community/chat_models/sambanova.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/libs/community/langchain_community/chat_models/sambanova.py b/libs/community/langchain_community/chat_models/sambanova.py index a2ddf24d8c8c0..e345c0f6920b2 100644 --- a/libs/community/langchain_community/chat_models/sambanova.py +++ b/libs/community/langchain_community/chat_models/sambanova.py @@ -616,7 +616,7 @@ class AnswerWithJustification(BaseModel): # 'parsing_error': None # } """ # noqa: E501 - if kwargs is not None: + if kwargs: raise ValueError(f"Received unsupported arguments {kwargs}") is_pydantic_schema = _is_pydantic_class(schema) if method == "function_calling": @@ -629,8 +629,8 @@ class AnswerWithJustification(BaseModel): llm = self.bind_tools([schema], tool_choice=tool_name) if is_pydantic_schema: output_parser: OutputParserLike[Any] = PydanticToolsParser( - tools=[schema], - first_tool_only=True, + tools=[schema], # type: ignore[list-item] + first_tool_only=True, # type: ignore[list-item] ) else: output_parser = JsonOutputKeyToolsParser( @@ -642,7 +642,7 @@ class AnswerWithJustification(BaseModel): # llm = self.bind(response_format={"type": "json_object"}) if is_pydantic_schema: schema = cast(Type[BaseModel], schema) - output_parser = PydanticOutputParser(pydantic_object=schema) + output_parser = PydanticOutputParser(pydantic_object=schema) # type: ignore[type-var, arg-type] else: output_parser = JsonOutputParser() @@ -660,7 +660,7 @@ class AnswerWithJustification(BaseModel): # ) if is_pydantic_schema: schema = cast(Type[BaseModel], schema) - output_parser = PydanticOutputParser(pydantic_object=schema) + output_parser = PydanticOutputParser(pydantic_object=schema) # type: ignore[type-var, arg-type] else: output_parser = JsonOutputParser() else: From 3256b5d6ae4ffb3118d2b0de0b102551eed3f42e Mon Sep 17 00:00:00 2001 From: Yuxin Chen Date: Wed, 18 Dec 2024 15:27:59 -0500 Subject: [PATCH 15/31] text-splitters: fix state persistence issue in ExperimentalMarkdownSyntaxTextSplitter (#28373) - **Description:** This PR resolves an issue with the `ExperimentalMarkdownSyntaxTextSplitter` class, which retains the internal state across multiple calls to the `split_text` method. This behaviour caused an unintended accumulation of chunks in `self` variables, leading to incorrect outputs when processing multiple Markdown files sequentially. - Modified `libs\text-splitters\langchain_text_splitters\markdown.py` to reset the relevant internal attributes at the start of each `split_text` invocation. This ensures each call processes the input independently. - Added unit tests in `libs\text-splitters\tests\unit_tests\test_text_splitters.py` to verify the fix and ensure the state does not persist across calls. - **Issue:** Fixes [#26440](https://github.com/langchain-ai/langchain/issues/26440). - **Dependencies:** No additional dependencies are introduced with this change. - [x] Unit tests were added to verify the changes. - [x] Updated documentation where necessary. - [x] Ran `make format`, `make lint`, and `make test` to ensure compliance with project standards. --------- Co-authored-by: Angel Chen Co-authored-by: Chester Curme --- .../langchain_text_splitters/markdown.py | 5 + .../tests/unit_tests/test_text_splitters.py | 401 ++++++++++++++++++ 2 files changed, 406 insertions(+) diff --git a/libs/text-splitters/langchain_text_splitters/markdown.py b/libs/text-splitters/langchain_text_splitters/markdown.py index 34c7d2197d238..f8d3807dc5011 100644 --- a/libs/text-splitters/langchain_text_splitters/markdown.py +++ b/libs/text-splitters/langchain_text_splitters/markdown.py @@ -324,6 +324,11 @@ def split_text(self, text: str) -> List[Document]: chunks of the input text. If `return_each_line` is enabled, each line is returned as a separate `Document`. """ + # Reset the state for each new file processed + self.chunks.clear() + self.current_chunk = Document(page_content="") + self.current_header_stack.clear() + raw_lines = text.splitlines(keepends=True) while raw_lines: diff --git a/libs/text-splitters/tests/unit_tests/test_text_splitters.py b/libs/text-splitters/tests/unit_tests/test_text_splitters.py index 95f170d52b7c4..ee86ae6a60abe 100644 --- a/libs/text-splitters/tests/unit_tests/test_text_splitters.py +++ b/libs/text-splitters/tests/unit_tests/test_text_splitters.py @@ -1527,6 +1527,407 @@ def test_experimental_markdown_syntax_text_splitter_split_lines() -> None: assert output == expected_output +EXPERIMENTAL_MARKDOWN_DOCUMENTS = [ + ( + "# My Header 1 From Document 1\n" + "Content for header 1 from Document 1\n" + "## Header 2 From Document 1\n" + "Content for header 2 from Document 1\n" + "```python\n" + "def func_definition():\n" + " print('Keep the whitespace consistent')\n" + "```\n" + "# Header 1 again From Document 1\n" + "We should also split on the horizontal line\n" + "----\n" + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), + ( + "# My Header 1 From Document 2\n" + "Content for header 1 from Document 2\n" + "## Header 2 From Document 2\n" + "Content for header 2 from Document 2\n" + "```python\n" + "def func_definition():\n" + " print('Keep the whitespace consistent')\n" + "```\n" + "# Header 1 again From Document 2\n" + "We should also split on the horizontal line\n" + "----\n" + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), +] + + +def test_experimental_markdown_syntax_text_splitter_on_multi_files() -> None: + """Test experimental markdown syntax splitter split + on default called consecutively on two files.""" + markdown_splitter = ExperimentalMarkdownSyntaxTextSplitter() + output = [] + for experimental_markdown_document in EXPERIMENTAL_MARKDOWN_DOCUMENTS: + output += markdown_splitter.split_text(experimental_markdown_document) + + expected_output = [ + Document( + page_content="Content for header 1 from Document 1\n", + metadata={"Header 1": "My Header 1 From Document 1"}, + ), + Document( + page_content="Content for header 2 from Document 1\n", + metadata={ + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content=( + "```python\ndef func_definition():\n " + "print('Keep the whitespace consistent')\n```\n" + ), + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content="We should also split on the horizontal line\n", + metadata={"Header 1": "Header 1 again From Document 1"}, + ), + Document( + page_content=( + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), + metadata={"Header 1": "Header 1 again From Document 1"}, + ), + Document( + page_content="Content for header 1 from Document 2\n", + metadata={"Header 1": "My Header 1 From Document 2"}, + ), + Document( + page_content="Content for header 2 from Document 2\n", + metadata={ + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content=( + "```python\ndef func_definition():\n " + "print('Keep the whitespace consistent')\n```\n" + ), + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content="We should also split on the horizontal line\n", + metadata={"Header 1": "Header 1 again From Document 2"}, + ), + Document( + page_content=( + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), + metadata={"Header 1": "Header 1 again From Document 2"}, + ), + ] + + assert output == expected_output + + +def test_experimental_markdown_syntax_text_splitter_split_lines_on_multi_files() -> ( + None +): + """Test experimental markdown syntax splitter split + on each line called consecutively on two files.""" + markdown_splitter = ExperimentalMarkdownSyntaxTextSplitter(return_each_line=True) + output = [] + for experimental_markdown_document in EXPERIMENTAL_MARKDOWN_DOCUMENTS: + output += markdown_splitter.split_text(experimental_markdown_document) + expected_output = [ + Document( + page_content="Content for header 1 from Document 1", + metadata={"Header 1": "My Header 1 From Document 1"}, + ), + Document( + page_content="Content for header 2 from Document 1", + metadata={ + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content="```python", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content="def func_definition():", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content=" print('Keep the whitespace consistent')", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content="```", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content="We should also split on the horizontal line", + metadata={"Header 1": "Header 1 again From Document 1"}, + ), + Document( + page_content="This will be a new doc but with the same header metadata", + metadata={"Header 1": "Header 1 again From Document 1"}, + ), + Document( + page_content="And it includes a new paragraph", + metadata={"Header 1": "Header 1 again From Document 1"}, + ), + Document( + page_content="Content for header 1 from Document 2", + metadata={"Header 1": "My Header 1 From Document 2"}, + ), + Document( + page_content="Content for header 2 from Document 2", + metadata={ + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content="```python", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content="def func_definition():", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content=" print('Keep the whitespace consistent')", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content="```", + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content="We should also split on the horizontal line", + metadata={"Header 1": "Header 1 again From Document 2"}, + ), + Document( + page_content="This will be a new doc but with the same header metadata", + metadata={"Header 1": "Header 1 again From Document 2"}, + ), + Document( + page_content="And it includes a new paragraph", + metadata={"Header 1": "Header 1 again From Document 2"}, + ), + ] + + assert output == expected_output + + +def test_experimental_markdown_syntax_text_splitter_with_header_on_multi_files() -> ( + None +): + """Test experimental markdown splitter + by header called consecutively on two files""" + + markdown_splitter = ExperimentalMarkdownSyntaxTextSplitter(strip_headers=False) + output = [] + for experimental_markdown_document in EXPERIMENTAL_MARKDOWN_DOCUMENTS: + output += markdown_splitter.split_text(experimental_markdown_document) + + expected_output = [ + Document( + page_content="# My Header 1 From Document 1\n" + "Content for header 1 from Document 1\n", + metadata={"Header 1": "My Header 1 From Document 1"}, + ), + Document( + page_content="## Header 2 From Document 1\n" + "Content for header 2 from Document 1\n", + metadata={ + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content=( + "```python\ndef func_definition():\n " + "print('Keep the whitespace consistent')\n```\n" + ), + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 1", + "Header 2": "Header 2 From Document 1", + }, + ), + Document( + page_content="# Header 1 again From Document 1\n" + "We should also split on the horizontal line\n", + metadata={"Header 1": "Header 1 again From Document 1"}, + ), + Document( + page_content=( + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), + metadata={"Header 1": "Header 1 again From Document 1"}, + ), + Document( + page_content="# My Header 1 From Document 2\n" + "Content for header 1 from Document 2\n", + metadata={"Header 1": "My Header 1 From Document 2"}, + ), + Document( + page_content="## Header 2 From Document 2\n" + "Content for header 2 from Document 2\n", + metadata={ + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content=( + "```python\ndef func_definition():\n " + "print('Keep the whitespace consistent')\n```\n" + ), + metadata={ + "Code": "python", + "Header 1": "My Header 1 From Document 2", + "Header 2": "Header 2 From Document 2", + }, + ), + Document( + page_content="# Header 1 again From Document 2\n" + "We should also split on the horizontal line\n", + metadata={"Header 1": "Header 1 again From Document 2"}, + ), + Document( + page_content=( + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), + metadata={"Header 1": "Header 1 again From Document 2"}, + ), + ] + assert output == expected_output + + +def test_experimental_markdown_syntax_text_splitter_header_config_on_multi_files() -> ( + None +): + """Test experimental markdown splitter + by header configuration called consecutively on two files""" + + headers_to_split_on = [("#", "Encabezamiento 1")] + markdown_splitter = ExperimentalMarkdownSyntaxTextSplitter( + headers_to_split_on=headers_to_split_on + ) + output = [] + for experimental_markdown_document in EXPERIMENTAL_MARKDOWN_DOCUMENTS: + output += markdown_splitter.split_text(experimental_markdown_document) + + expected_output = [ + Document( + page_content="Content for header 1 from Document 1\n" + "## Header 2 From Document 1\n" + "Content for header 2 from Document 1\n", + metadata={"Encabezamiento 1": "My Header 1 From Document 1"}, + ), + Document( + page_content=( + "```python\ndef func_definition():\n " + "print('Keep the whitespace consistent')\n```\n" + ), + metadata={ + "Code": "python", + "Encabezamiento 1": "My Header 1 From Document 1", + }, + ), + Document( + page_content="We should also split on the horizontal line\n", + metadata={"Encabezamiento 1": "Header 1 again From Document 1"}, + ), + Document( + page_content=( + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), + metadata={"Encabezamiento 1": "Header 1 again From Document 1"}, + ), + Document( + page_content="Content for header 1 from Document 2\n" + "## Header 2 From Document 2\n" + "Content for header 2 from Document 2\n", + metadata={"Encabezamiento 1": "My Header 1 From Document 2"}, + ), + Document( + page_content=( + "```python\ndef func_definition():\n " + "print('Keep the whitespace consistent')\n```\n" + ), + metadata={ + "Code": "python", + "Encabezamiento 1": "My Header 1 From Document 2", + }, + ), + Document( + page_content="We should also split on the horizontal line\n", + metadata={"Encabezamiento 1": "Header 1 again From Document 2"}, + ), + Document( + page_content=( + "This will be a new doc but with the same header metadata\n\n" + "And it includes a new paragraph" + ), + metadata={"Encabezamiento 1": "Header 1 again From Document 2"}, + ), + ] + + assert output == expected_output + + def test_solidity_code_splitter() -> None: splitter = RecursiveCharacterTextSplitter.from_language( Language.SOL, chunk_size=CHUNK_SIZE, chunk_overlap=0 From 079f1d93ab5b769c9af56262597d69005ae1af6c Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Wed, 18 Dec 2024 12:32:00 -0800 Subject: [PATCH 16/31] langchain: release 0.3.13 (#28797) --- libs/langchain/poetry.lock | 330 +++++++++++++++------------------- libs/langchain/pyproject.toml | 4 +- 2 files changed, 144 insertions(+), 190 deletions(-) diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index e99e3301ae9f3..f892ddfcda4e0 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -285,19 +285,19 @@ files = [ [[package]] name = "attrs" -version = "24.2.0" +version = "24.3.0" description = "Classes Without Boilerplate" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"}, - {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"}, + {file = "attrs-24.3.0-py3-none-any.whl", hash = "sha256:ac96cd038792094f438ad1f6ff80837353805ac950cd2aa0e0625ef19850c308"}, + {file = "attrs-24.3.0.tar.gz", hash = "sha256:8f5c07333d543103541ba7be0e2ce16eeee8130cb0b3f9238ab904ce1e85baff"}, ] [package.extras] benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy 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test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (> [[package]] name = "jupyterlab" -version = "4.3.3" +version = "4.3.4" description = "JupyterLab computational environment" optional = false python-versions = ">=3.8" files = [ - {file = "jupyterlab-4.3.3-py3-none-any.whl", hash = "sha256:32a8fd30677e734ffcc3916a4758b9dab21b02015b668c60eb36f84357b7d4b1"}, - {file = "jupyterlab-4.3.3.tar.gz", hash = "sha256:76fa39e548fdac94dc1204af5956c556f54c785f70ee26aa47ea08eda4d5bbcd"}, + {file = "jupyterlab-4.3.4-py3-none-any.whl", hash = "sha256:b754c2601c5be6adf87cb5a1d8495d653ffb945f021939f77776acaa94dae952"}, + {file = "jupyterlab-4.3.4.tar.gz", hash = "sha256:f0bb9b09a04766e3423cccc2fc23169aa2ffedcdf8713e9e0fb33cac0b6859d0"}, ] [package.dependencies] @@ -1976,7 +1976,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.25" +version = "0.3.26" description = "Building applications with LLMs through composability" optional = false python-versions = 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a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain" -version = "0.3.12" +version = "0.3.13" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -33,7 +33,7 @@ langchain-server = "langchain.server:main" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.25" +langchain-core = "^0.3.26" langchain-text-splitters = "^0.3.3" langsmith = ">=0.1.17,<0.3" pydantic = "^2.7.4" From 43b0736a51dfb471baca20bc67cab1b59e86757d Mon Sep 17 00:00:00 2001 From: bjoaquinc <75667013+bjoaquinc@users.noreply.github.com> Date: Wed, 18 Dec 2024 16:08:18 -0500 Subject: [PATCH 17/31] docs: added a link to the taxonomy of labels in the contributing guide for easy access (#28719) Thank you for contributing to LangChain! - [ ] **PR title**: "package: description" - Where "package" is whichever of langchain, community, core, etc. is being modified. Use "docs: ..." for purely docs changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [ ] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** Added a link to make it easier to organize github issues for langchain. - **Issue:** After reading that there was a taxonomy of labels I had to figure out how to find it. - **Dependencies:** None - **Twitter handle:** None - [ ] **Add tests and docs**: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --------- Co-authored-by: Chester Curme --- docs/docs/contributing/index.mdx | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/docs/docs/contributing/index.mdx b/docs/docs/contributing/index.mdx index d2c1231789d8d..90e677bcf5f77 100644 --- a/docs/docs/contributing/index.mdx +++ b/docs/docs/contributing/index.mdx @@ -37,7 +37,11 @@ If you are able to help answer questions, please do so! This will allow the main Our [issues](https://github.com/langchain-ai/langchain/issues) page is kept up to date with bugs, improvements, and feature requests. -There is a taxonomy of labels to help with sorting and discovery of issues of interest. Please use these to help organize issues. +There is a [taxonomy of labels](https://github.com/langchain-ai/langchain/labels?sort=count-desc) +to help with sorting and discovery of issues of interest. Please use these to help +organize issues. Check out the [Help Wanted](https://github.com/langchain-ai/langchain/labels/help%20wanted) +and [Good First Issue](https://github.com/langchain-ai/langchain/labels/good%20first%20issue) +tags for recommendations. If you start working on an issue, please assign it to yourself. From 4a531437bb5bad3aa474b7359f841341c82267c5 Mon Sep 17 00:00:00 2001 From: Bagatur <22008038+baskaryan@users.noreply.github.com> Date: Wed, 18 Dec 2024 13:54:07 -0800 Subject: [PATCH 18/31] core[patch], openai[patch]: Handle OpenAI developer msg (#28794) - Convert developer openai messages to SystemMessage - store additional_kwargs={"__openai_role__": "developer"} so that the correct role can be reconstructed if needed - update ChatOpenAI to read in openai_role --------- Co-authored-by: Erick Friis --- libs/core/langchain_core/messages/utils.py | 13 +++++--- .../tests/unit_tests/messages/test_utils.py | 21 ++++++++++++ .../langchain_openai/chat_models/base.py | 27 +++++++++++++--- .../chat_models/test_base.py | 13 ++++++++ .../tests/unit_tests/chat_models/test_base.py | 32 +++++++++++++++++++ 5 files changed, 96 insertions(+), 10 deletions(-) diff --git a/libs/core/langchain_core/messages/utils.py b/libs/core/langchain_core/messages/utils.py index 452d59a5d78bf..435bd1e2f1e07 100644 --- a/libs/core/langchain_core/messages/utils.py +++ b/libs/core/langchain_core/messages/utils.py @@ -221,14 +221,14 @@ def _create_message_from_message_type( tool_call_id: (str) the tool call id. Default is None. tool_calls: (list[dict[str, Any]]) the tool calls. Default is None. id: (str) the id of the message. Default is None. - **additional_kwargs: (dict[str, Any]) additional keyword arguments. + additional_kwargs: (dict[str, Any]) additional keyword arguments. Returns: a message of the appropriate type. Raises: ValueError: if the message type is not one of "human", "user", "ai", - "assistant", "system", "function", or "tool". + "assistant", "function", "tool", "system", or "developer". """ kwargs: dict[str, Any] = {} if name is not None: @@ -261,7 +261,10 @@ def _create_message_from_message_type( message: BaseMessage = HumanMessage(content=content, **kwargs) elif message_type in ("ai", "assistant"): message = AIMessage(content=content, **kwargs) - elif message_type == "system": + elif message_type in ("system", "developer"): + if message_type == "developer": + kwargs["additional_kwargs"] = kwargs.get("additional_kwargs") or {} + kwargs["additional_kwargs"]["__openai_role__"] = "developer" message = SystemMessage(content=content, **kwargs) elif message_type == "function": message = FunctionMessage(content=content, **kwargs) @@ -273,7 +276,7 @@ def _create_message_from_message_type( else: msg = ( f"Unexpected message type: '{message_type}'. Use one of 'human'," - f" 'user', 'ai', 'assistant', 'function', 'tool', or 'system'." + f" 'user', 'ai', 'assistant', 'function', 'tool', 'system', or 'developer'." ) msg = create_message(message=msg, error_code=ErrorCode.MESSAGE_COERCION_FAILURE) raise ValueError(msg) @@ -1385,7 +1388,7 @@ def _get_message_openai_role(message: BaseMessage) -> str: elif isinstance(message, ToolMessage): return "tool" elif isinstance(message, SystemMessage): - return "system" + return message.additional_kwargs.get("__openai_role__", "system") elif isinstance(message, FunctionMessage): return "function" elif isinstance(message, ChatMessage): diff --git a/libs/core/tests/unit_tests/messages/test_utils.py b/libs/core/tests/unit_tests/messages/test_utils.py index 9f4a9a4cc6c36..3a32c2984952a 100644 --- a/libs/core/tests/unit_tests/messages/test_utils.py +++ b/libs/core/tests/unit_tests/messages/test_utils.py @@ -469,6 +469,7 @@ def test_convert_to_messages() -> None: message_like: list = [ # BaseMessage SystemMessage("1"), + SystemMessage("1.1", additional_kwargs={"__openai_role__": "developer"}), HumanMessage([{"type": "image_url", "image_url": {"url": "2.1"}}], name="2.2"), AIMessage( [ @@ -503,6 +504,7 @@ def test_convert_to_messages() -> None: ToolMessage("5.1", tool_call_id="5.2", name="5.3"), # OpenAI dict {"role": "system", "content": "6"}, + {"role": "developer", "content": "6.1"}, { "role": "user", "content": [{"type": "image_url", "image_url": {"url": "7.1"}}], @@ -526,6 +528,7 @@ def test_convert_to_messages() -> None: {"role": "tool", "content": "10.1", "tool_call_id": "10.2"}, # Tuple/List ("system", "11.1"), + ("developer", "11.2"), ("human", [{"type": "image_url", "image_url": {"url": "12.1"}}]), ( "ai", @@ -551,6 +554,9 @@ def test_convert_to_messages() -> None: ] expected = [ SystemMessage(content="1"), + SystemMessage( + content="1.1", additional_kwargs={"__openai_role__": "developer"} + ), HumanMessage( content=[{"type": "image_url", "image_url": {"url": "2.1"}}], name="2.2" ), @@ -586,6 +592,9 @@ def test_convert_to_messages() -> None: ), ToolMessage(content="5.1", name="5.3", tool_call_id="5.2"), SystemMessage(content="6"), + SystemMessage( + content="6.1", additional_kwargs={"__openai_role__": "developer"} + ), HumanMessage( content=[{"type": "image_url", "image_url": {"url": "7.1"}}], name="7.2" ), @@ -603,6 +612,9 @@ def test_convert_to_messages() -> None: ), ToolMessage(content="10.1", tool_call_id="10.2"), SystemMessage(content="11.1"), + SystemMessage( + content="11.2", additional_kwargs={"__openai_role__": "developer"} + ), HumanMessage(content=[{"type": "image_url", "image_url": {"url": "12.1"}}]), AIMessage( content=[ @@ -937,3 +949,12 @@ def test_convert_to_openai_messages_mixed_content_types() -> None: assert isinstance(result[0]["content"][0], dict) assert isinstance(result[0]["content"][1], dict) assert isinstance(result[0]["content"][2], dict) + + +def test_convert_to_openai_messages_developer() -> None: + messages: list = [ + SystemMessage("a", additional_kwargs={"__openai_role__": "developer"}), + {"role": "developer", "content": "a"}, + ] + result = convert_to_openai_messages(messages) + assert result == [{"role": "developer", "content": "a"}] * 2 diff --git a/libs/partners/openai/langchain_openai/chat_models/base.py b/libs/partners/openai/langchain_openai/chat_models/base.py index e312ed249c88e..d866e30fe36e1 100644 --- a/libs/partners/openai/langchain_openai/chat_models/base.py +++ b/libs/partners/openai/langchain_openai/chat_models/base.py @@ -139,8 +139,17 @@ def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage: tool_calls=tool_calls, invalid_tool_calls=invalid_tool_calls, ) - elif role == "system": - return SystemMessage(content=_dict.get("content", ""), name=name, id=id_) + elif role in ("system", "developer"): + if role == "developer": + additional_kwargs = {"__openai_role__": role} + else: + additional_kwargs = {} + return SystemMessage( + content=_dict.get("content", ""), + name=name, + id=id_, + additional_kwargs=additional_kwargs, + ) elif role == "function": return FunctionMessage( content=_dict.get("content", ""), name=cast(str, _dict.get("name")), id=id_ @@ -233,7 +242,9 @@ def _convert_message_to_dict(message: BaseMessage) -> dict: ) message_dict["audio"] = audio elif isinstance(message, SystemMessage): - message_dict["role"] = "system" + message_dict["role"] = message.additional_kwargs.get( + "__openai_role__", "system" + ) elif isinstance(message, FunctionMessage): message_dict["role"] = "function" elif isinstance(message, ToolMessage): @@ -284,8 +295,14 @@ def _convert_delta_to_message_chunk( id=id_, tool_call_chunks=tool_call_chunks, # type: ignore[arg-type] ) - elif role == "system" or default_class == SystemMessageChunk: - return SystemMessageChunk(content=content, id=id_) + elif role in ("system", "developer") or default_class == SystemMessageChunk: + if role == "developer": + additional_kwargs = {"__openai_role__": "developer"} + else: + additional_kwargs = {} + return SystemMessageChunk( + content=content, id=id_, additional_kwargs=additional_kwargs + ) elif role == "function" or default_class == FunctionMessageChunk: return FunctionMessageChunk(content=content, name=_dict["name"], id=id_) elif role == "tool" or default_class == ToolMessageChunk: diff --git a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py index 1204ccef87c4e..f997ce44d6852 100644 --- a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py +++ b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py @@ -1097,3 +1097,16 @@ def test_o1_max_tokens() -> None: "how are you" ) assert isinstance(response, AIMessage) + + +def test_developer_message() -> None: + llm = ChatOpenAI(model="o1", max_tokens=10) # type: ignore[call-arg] + response = llm.invoke( + [ + {"role": "developer", "content": "respond in all caps"}, + {"role": "user", "content": "HOW ARE YOU"}, + ] + ) + assert isinstance(response, AIMessage) + assert isinstance(response.content, str) + assert response.content.upper() == response.content diff --git a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py index aea480a748177..6e889b80a562c 100644 --- a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py +++ b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py @@ -100,6 +100,16 @@ def test__convert_dict_to_message_system() -> None: assert _convert_message_to_dict(expected_output) == message +def test__convert_dict_to_message_developer() -> None: + message = {"role": "developer", "content": "foo"} + result = _convert_dict_to_message(message) + expected_output = SystemMessage( + content="foo", additional_kwargs={"__openai_role__": "developer"} + ) + assert result == expected_output + assert _convert_message_to_dict(expected_output) == message + + def test__convert_dict_to_message_system_with_name() -> None: message = {"role": "system", "content": "foo", "name": "test"} result = _convert_dict_to_message(message) @@ -850,3 +860,25 @@ class JokeWithEvaluation(TypedDict): self_evaluation: SelfEvaluation llm.with_structured_output(JokeWithEvaluation, method="json_schema") + + +def test__get_request_payload() -> None: + llm = ChatOpenAI(model="gpt-4o-2024-08-06") + messages: list = [ + SystemMessage("hello"), + SystemMessage("bye", additional_kwargs={"__openai_role__": "developer"}), + {"role": "human", "content": "how are you"}, + ] + expected = { + "messages": [ + {"role": "system", "content": "hello"}, + {"role": "developer", "content": "bye"}, + {"role": "user", "content": "how are you"}, + ], + "model": "gpt-4o-2024-08-06", + "stream": False, + "n": 1, + "temperature": 0.7, + } + payload = llm._get_request_payload(messages) + assert payload == expected From 557f63c2e65bc9bec6500da05696129df3b6dfbf Mon Sep 17 00:00:00 2001 From: Bagatur <22008038+baskaryan@users.noreply.github.com> Date: Wed, 18 Dec 2024 13:58:03 -0800 Subject: [PATCH 19/31] core[patch]: Release 0.3.27 (#28799) --- libs/core/pyproject.toml | 14 +------------- 1 file changed, 1 insertion(+), 13 deletions(-) diff --git a/libs/core/pyproject.toml b/libs/core/pyproject.toml index c52e78add1220..610ea3aca1061 100644 --- a/libs/core/pyproject.toml +++ b/libs/core/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-core" -version = "0.3.26" +version = "0.3.27" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -84,23 +84,17 @@ classmethod-decorators = [ "classmethod", "langchain_core.utils.pydantic.pre_ini [tool.poetry.group.lint.dependencies] ruff = "^0.5" - - [tool.poetry.group.typing.dependencies] mypy = ">=1.10,<1.11" types-pyyaml = "^6.0.12.2" types-requests = "^2.28.11.5" types-jinja2 = "^2.11.9" - - [tool.poetry.group.dev.dependencies] jupyter = "^1.0.0" setuptools = "^67.6.1" grandalf = "^0.8" - - [tool.poetry.group.test.dependencies] pytest = "^8" freezegun = "^1.2.2" @@ -119,18 +113,12 @@ python = "<3.12" version = ">=1.26.0,<3" python = ">=3.12" - - [tool.poetry.group.test_integration.dependencies] - - [tool.poetry.group.typing.dependencies.langchain-text-splitters] path = "../text-splitters" develop = true - - [tool.poetry.group.test.dependencies.langchain-tests] path = "../standard-tests" develop = true From 4dc28b43ac553f27c49307a0db7b18ec07e54014 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Wed, 18 Dec 2024 13:58:46 -0800 Subject: [PATCH 20/31] community: release 0.3.13 (#28798) --- libs/community/poetry.lock | 481 +++++++++++++++------------------- libs/community/pyproject.toml | 6 +- 2 files changed, 220 insertions(+), 267 deletions(-) diff --git a/libs/community/poetry.lock b/libs/community/poetry.lock index b67efa31c209b..493010889f595 100644 --- a/libs/community/poetry.lock +++ b/libs/community/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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--- libs/partners/mistralai/poetry.lock | 392 ++++++++++++++++--------- libs/partners/mistralai/pyproject.toml | 4 +- 2 files changed, 262 insertions(+), 134 deletions(-) diff --git a/libs/partners/mistralai/poetry.lock b/libs/partners/mistralai/poetry.lock index 152e34f833acb..01106c5400c8a 100644 --- a/libs/partners/mistralai/poetry.lock +++ b/libs/partners/mistralai/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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b/libs/partners/xai/pyproject.toml index 150093830a046..a6872c3913bb3 100644 --- a/libs/partners/xai/pyproject.toml +++ b/libs/partners/xai/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-xai" -version = "0.1.0" +version = "0.1.1" description = "An integration package connecting xAI and LangChain" authors = [] readme = "README.md" @@ -21,7 +21,7 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" langchain-openai = ">=0.2,<0.3" -langchain-core = ">=0.3.18,<0.4" +langchain-core = "^0.3.27" requests = ">=2,<3" aiohttp = ">=3.9.1,<4" @@ -76,9 +76,11 @@ langchain-openai = { path = "../openai", develop = true } langchain-core = { path = "../../core", develop = true } langchain-tests = { path = "../../standard-tests", develop = true } + [tool.poetry.group.codespell.dependencies] codespell = "^2.2.0" + [tool.poetry.group.test_integration.dependencies] [[tool.poetry.group.test_integration.dependencies.numpy]] version = "^1" @@ -88,13 +90,16 @@ python = "<3.12" version = "^1.26.0" python = ">=3.12" + [tool.poetry.group.lint.dependencies] ruff = "^0.5" + [tool.poetry.group.typing.dependencies] mypy = "^1.10" types-requests = "^2" langchain-core = { path = "../../core", develop = true } + [tool.poetry.group.dev.dependencies] langchain-core = { path = "../../core", develop = true } From 1e88adaca7bb0dfe86f933cbe82639653384b05d Mon Sep 17 00:00:00 2001 From: Christophe Bornet Date: Wed, 18 Dec 2024 23:22:58 +0100 Subject: [PATCH 26/31] all: Add pre-commit hook (#26993) This calls `make format` on projects that have modified files. So `poetry install --with lint` must have been done for those projects. --------- Co-authored-by: Erick Friis --- .pre-commit-config.yaml | 129 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 129 insertions(+) create mode 100644 .pre-commit-config.yaml diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000000000..0430c11987032 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,129 @@ +repos: +- repo: local + hooks: + - id: core + name: format core + language: system + entry: make -C libs/core format + files: ^libs/core/ + pass_filenames: false + - id: community + name: format community + language: system + entry: make -C libs/community format + files: ^libs/community/ + pass_filenames: false + - id: langchain + name: format langchain + language: system + entry: make -C libs/langchain format + files: ^libs/langchain/ + pass_filenames: false + - id: standard-tests + name: format standard-tests + language: system + entry: make -C libs/standard-tests format + files: ^libs/standard-tests/ + pass_filenames: false + - id: text-splitters + name: format text-splitters + language: system + entry: make -C libs/text-splitters format + files: ^libs/text-splitters/ + pass_filenames: false + - id: anthropic + name: format partners/anthropic + language: system + entry: make -C libs/partners/anthropic format + files: ^libs/partners/anthropic/ + pass_filenames: false + - id: chroma + name: format partners/chroma + language: system + entry: make -C libs/partners/chroma format + files: ^libs/partners/chroma/ + pass_filenames: false + - id: couchbase + name: format partners/couchbase + language: system + entry: make -C libs/partners/couchbase format + files: ^libs/partners/couchbase/ + pass_filenames: false + - id: exa + name: format partners/exa + language: system + entry: make -C libs/partners/exa format + files: ^libs/partners/exa/ + pass_filenames: false + - id: fireworks + name: format partners/fireworks + language: system + entry: make -C libs/partners/fireworks format + files: ^libs/partners/fireworks/ + pass_filenames: false + - id: groq + name: format partners/groq + language: system + entry: make -C libs/partners/groq format + files: ^libs/partners/groq/ + pass_filenames: false + - id: huggingface + name: format partners/huggingface + language: system + entry: make -C libs/partners/huggingface format + files: ^libs/partners/huggingface/ + pass_filenames: false + - id: mistralai + name: format partners/mistralai + language: system + entry: make -C libs/partners/mistralai format + files: ^libs/partners/mistralai/ + pass_filenames: false + - id: nomic + name: format partners/nomic + language: system + entry: make -C libs/partners/nomic format + files: ^libs/partners/nomic/ + pass_filenames: false + - id: ollama + name: format partners/ollama + language: system + entry: make -C libs/partners/ollama format + files: ^libs/partners/ollama/ + pass_filenames: false + - id: openai + name: format partners/openai + language: system + entry: make -C libs/partners/openai format + files: ^libs/partners/openai/ + pass_filenames: false + - id: pinecone + name: format partners/pinecone + language: system + entry: make -C libs/partners/pinecone format + files: ^libs/partners/pinecone/ + pass_filenames: false + - id: prompty + name: format partners/prompty + language: system + entry: make -C libs/partners/prompty format + files: ^libs/partners/prompty/ + pass_filenames: false + - id: qdrant + name: format partners/qdrant + language: system + entry: make -C libs/partners/qdrant format + files: ^libs/partners/qdrant/ + pass_filenames: false + - id: voyageai + name: format partners/voyageai + language: system + entry: make -C libs/partners/voyageai format + files: ^libs/partners/voyageai/ + pass_filenames: false + - id: root + name: format docs, cookbook + language: system + entry: make format + files: ^(docs|cookbook)/ + pass_filenames: false From 50afa7c4e7fc245a5bf375e3d8de156b849f7ca9 Mon Sep 17 00:00:00 2001 From: Lu Peng <118394507+lu-ohai@users.noreply.github.com> Date: Wed, 18 Dec 2024 17:33:23 -0500 Subject: [PATCH 27/31] community: add new parameter default_headers (#28700) Thank you for contributing to LangChain! - [x] **PR title**: "package: description" - "community: 1. add new parameter `default_headers` for oci model deployments and oci chat model deployments. 2. updated k parameter in OCIModelDeploymentLLM class." - [x] **PR message**: - **Description:** 1. add new parameters `default_headers` for oci model deployments and oci chat model deployments. 2. updated k parameter in OCIModelDeploymentLLM class. - [x] **Add tests and docs**: 1. unit tests 2. notebook --------- Co-authored-by: Erick Friis --- .../integrations/chat/oci_data_science.ipynb | 6 ++- .../chat_models/oci_data_science.py | 37 ++++++++++++++++++- ..._data_science_model_deployment_endpoint.py | 35 ++++++++++++++++-- .../chat_models/test_oci_data_science.py | 5 +++ .../test_oci_model_deployment_endpoint.py | 5 +++ 5 files changed, 82 insertions(+), 6 deletions(-) diff --git a/docs/docs/integrations/chat/oci_data_science.ipynb b/docs/docs/integrations/chat/oci_data_science.ipynb index 6196d2025c04b..61b0a41ae1f85 100644 --- a/docs/docs/integrations/chat/oci_data_science.ipynb +++ b/docs/docs/integrations/chat/oci_data_science.ipynb @@ -137,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -156,6 +156,10 @@ " \"temperature\": 0.2,\n", " \"max_tokens\": 512,\n", " }, # other model params...\n", + " default_headers={\n", + " \"route\": \"/v1/chat/completions\",\n", + " # other request headers ...\n", + " },\n", ")" ] }, diff --git a/libs/community/langchain_community/chat_models/oci_data_science.py b/libs/community/langchain_community/chat_models/oci_data_science.py index cdb181df897b3..8ac571adbd8d4 100644 --- a/libs/community/langchain_community/chat_models/oci_data_science.py +++ b/libs/community/langchain_community/chat_models/oci_data_science.py @@ -47,6 +47,7 @@ ) logger = logging.getLogger(__name__) +DEFAULT_INFERENCE_ENDPOINT_CHAT = "/v1/chat/completions" def _is_pydantic_class(obj: Any) -> bool: @@ -56,6 +57,13 @@ def _is_pydantic_class(obj: Any) -> bool: class ChatOCIModelDeployment(BaseChatModel, BaseOCIModelDeployment): """OCI Data Science Model Deployment chat model integration. + Prerequisite + The OCI Model Deployment plugins are installable only on + python version 3.9 and above. If you're working inside the notebook, + try installing the python 3.10 based conda pack and running the + following setup. + + Setup: Install ``oracle-ads`` and ``langchain-openai``. @@ -90,6 +98,8 @@ class ChatOCIModelDeployment(BaseChatModel, BaseOCIModelDeployment): Key init args — client params: auth: dict ADS auth dictionary for OCI authentication. + default_headers: Optional[Dict] + The headers to be added to the Model Deployment request. Instantiate: .. code-block:: python @@ -98,7 +108,7 @@ class ChatOCIModelDeployment(BaseChatModel, BaseOCIModelDeployment): chat = ChatOCIModelDeployment( endpoint="https://modeldeployment..oci.customer-oci.com//predict", - model="odsc-llm", + model="odsc-llm", # this is the default model name if deployed with AQUA streaming=True, max_retries=3, model_kwargs={ @@ -106,6 +116,10 @@ class ChatOCIModelDeployment(BaseChatModel, BaseOCIModelDeployment): "temperature": 0.2, # other model parameters ... }, + default_headers={ + "route": "/v1/chat/completions", + # other request headers ... + }, ) Invocation: @@ -288,6 +302,25 @@ def _default_params(self) -> Dict[str, Any]: "stream": self.streaming, } + def _headers( + self, is_async: Optional[bool] = False, body: Optional[dict] = None + ) -> Dict: + """Construct and return the headers for a request. + + Args: + is_async (bool, optional): Indicates if the request is asynchronous. + Defaults to `False`. + body (optional): The request body to be included in the headers if + the request is asynchronous. + + Returns: + Dict: A dictionary containing the appropriate headers for the request. + """ + return { + "route": DEFAULT_INFERENCE_ENDPOINT_CHAT, + **super()._headers(is_async=is_async, body=body), + } + def _generate( self, messages: List[BaseMessage], @@ -701,7 +734,7 @@ def _process_response(self, response_json: dict) -> ChatResult: for choice in choices: message = _convert_dict_to_message(choice["message"]) - generation_info = dict(finish_reason=choice.get("finish_reason")) + generation_info = {"finish_reason": choice.get("finish_reason")} if "logprobs" in choice: generation_info["logprobs"] = choice["logprobs"] diff --git a/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py b/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py index c998fbc0ec40f..e18a1a0847d0f 100644 --- a/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py +++ b/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py @@ -32,6 +32,7 @@ from langchain_community.utilities.requests import Requests logger = logging.getLogger(__name__) +DEFAULT_INFERENCE_ENDPOINT = "/v1/completions" DEFAULT_TIME_OUT = 300 @@ -81,6 +82,9 @@ class BaseOCIModelDeployment(Serializable): max_retries: int = 3 """Maximum number of retries to make when generating.""" + default_headers: Optional[Dict[str, Any]] = None + """The headers to be added to the Model Deployment request.""" + @model_validator(mode="before") @classmethod def validate_environment(cls, values: Dict) -> Dict: @@ -120,12 +124,12 @@ def _headers( Returns: Dict: A dictionary containing the appropriate headers for the request. """ + headers = self.default_headers or {} if is_async: signer = self.auth["signer"] _req = requests.Request("POST", self.endpoint, json=body) req = _req.prepare() req = signer(req) - headers = {} for key, value in req.headers.items(): headers[key] = value @@ -135,7 +139,7 @@ def _headers( ) return headers - return ( + headers.update( { "Content-Type": DEFAULT_CONTENT_TYPE_JSON, "enable-streaming": "true", @@ -147,6 +151,8 @@ def _headers( } ) + return headers + def completion_with_retry( self, run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any ) -> Any: @@ -383,6 +389,10 @@ class OCIModelDeploymentLLM(BaseLLM, BaseOCIModelDeployment): model="odsc-llm", streaming=True, model_kwargs={"frequency_penalty": 1.0}, + headers={ + "route": "/v1/completions", + # other request headers ... + } ) llm.invoke("tell me a joke.") @@ -426,7 +436,7 @@ def _construct_json_body(self, prompt: str, param:dict) -> dict: temperature: float = 0.2 """A non-negative float that tunes the degree of randomness in generation.""" - k: int = -1 + k: int = 50 """Number of most likely tokens to consider at each step.""" p: float = 0.75 @@ -472,6 +482,25 @@ def _identifying_params(self) -> Dict[str, Any]: **self._default_params, } + def _headers( + self, is_async: Optional[bool] = False, body: Optional[dict] = None + ) -> Dict: + """Construct and return the headers for a request. + + Args: + is_async (bool, optional): Indicates if the request is asynchronous. + Defaults to `False`. + body (optional): The request body to be included in the headers if + the request is asynchronous. + + Returns: + Dict: A dictionary containing the appropriate headers for the request. + """ + return { + "route": DEFAULT_INFERENCE_ENDPOINT, + **super()._headers(is_async=is_async, body=body), + } + def _generate( self, prompts: List[str], diff --git a/libs/community/tests/unit_tests/chat_models/test_oci_data_science.py b/libs/community/tests/unit_tests/chat_models/test_oci_data_science.py index f385f2ddb09a3..f5b7dae6432c2 100644 --- a/libs/community/tests/unit_tests/chat_models/test_oci_data_science.py +++ b/libs/community/tests/unit_tests/chat_models/test_oci_data_science.py @@ -19,6 +19,7 @@ CONST_ENDPOINT = "https://oci.endpoint/ocid/predict" CONST_PROMPT = "This is a prompt." CONST_COMPLETION = "This is a completion." +CONST_COMPLETION_ROUTE = "/v1/chat/completions" CONST_COMPLETION_RESPONSE = { "id": "chat-123456789", "object": "chat.completion", @@ -120,6 +121,7 @@ def mocked_requests_post(url: str, **kwargs: Any) -> MockResponse: def test_invoke_vllm(*args: Any) -> None: """Tests invoking vLLM endpoint.""" llm = ChatOCIModelDeploymentVLLM(endpoint=CONST_ENDPOINT, model=CONST_MODEL_NAME) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE output = llm.invoke(CONST_PROMPT) assert isinstance(output, AIMessage) assert output.content == CONST_COMPLETION @@ -132,6 +134,7 @@ def test_invoke_vllm(*args: Any) -> None: def test_invoke_tgi(*args: Any) -> None: """Tests invoking TGI endpoint using OpenAI Spec.""" llm = ChatOCIModelDeploymentTGI(endpoint=CONST_ENDPOINT, model=CONST_MODEL_NAME) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE output = llm.invoke(CONST_PROMPT) assert isinstance(output, AIMessage) assert output.content == CONST_COMPLETION @@ -146,6 +149,7 @@ def test_stream_vllm(*args: Any) -> None: llm = ChatOCIModelDeploymentVLLM( endpoint=CONST_ENDPOINT, model=CONST_MODEL_NAME, streaming=True ) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE output = None count = 0 for chunk in llm.stream(CONST_PROMPT): @@ -184,6 +188,7 @@ async def test_stream_async(*args: Any) -> None: llm = ChatOCIModelDeploymentVLLM( endpoint=CONST_ENDPOINT, model=CONST_MODEL_NAME, streaming=True ) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE with mock.patch.object( llm, "_aiter_sse", diff --git a/libs/community/tests/unit_tests/llms/test_oci_model_deployment_endpoint.py b/libs/community/tests/unit_tests/llms/test_oci_model_deployment_endpoint.py index c87b05f12a12d..10555528013d1 100644 --- a/libs/community/tests/unit_tests/llms/test_oci_model_deployment_endpoint.py +++ b/libs/community/tests/unit_tests/llms/test_oci_model_deployment_endpoint.py @@ -18,6 +18,7 @@ CONST_ENDPOINT = "https://oci.endpoint/ocid/predict" CONST_PROMPT = "This is a prompt." CONST_COMPLETION = "This is a completion." +CONST_COMPLETION_ROUTE = "/v1/completions" CONST_COMPLETION_RESPONSE = { "choices": [ { @@ -114,6 +115,7 @@ async def mocked_async_streaming_response( def test_invoke_vllm(*args: Any) -> None: """Tests invoking vLLM endpoint.""" llm = OCIModelDeploymentVLLM(endpoint=CONST_ENDPOINT, model=CONST_MODEL_NAME) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE output = llm.invoke(CONST_PROMPT) assert output == CONST_COMPLETION @@ -126,6 +128,7 @@ def test_stream_tgi(*args: Any) -> None: llm = OCIModelDeploymentTGI( endpoint=CONST_ENDPOINT, model=CONST_MODEL_NAME, streaming=True ) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE output = "" count = 0 for chunk in llm.stream(CONST_PROMPT): @@ -143,6 +146,7 @@ def test_generate_tgi(*args: Any) -> None: llm = OCIModelDeploymentTGI( endpoint=CONST_ENDPOINT, api="/generate", model=CONST_MODEL_NAME ) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE output = llm.invoke(CONST_PROMPT) assert output == CONST_COMPLETION @@ -161,6 +165,7 @@ async def test_stream_async(*args: Any) -> None: llm = OCIModelDeploymentTGI( endpoint=CONST_ENDPOINT, model=CONST_MODEL_NAME, streaming=True ) + assert llm._headers().get("route") == CONST_COMPLETION_ROUTE with mock.patch.object( llm, "_aiter_sse", From 4eb8bf77935e9b47b9e14c74232475c8c33f6a04 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Wed, 18 Dec 2024 14:45:38 -0800 Subject: [PATCH 28/31] partners/anthropic: release 0.3.1 (#28801) --- libs/partners/anthropic/poetry.lock | 141 +++++++++++++++++++++++-- libs/partners/anthropic/pyproject.toml | 4 +- 2 files changed, 137 insertions(+), 8 deletions(-) diff --git a/libs/partners/anthropic/poetry.lock b/libs/partners/anthropic/poetry.lock index 0770706b18597..b6f496e0c7949 100644 --- a/libs/partners/anthropic/poetry.lock +++ b/libs/partners/anthropic/poetry.lock @@ -451,7 +451,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.27" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -460,7 +460,7 @@ develop = true [package.dependencies] jsonpatch = "^1.33" -langsmith = "^0.1.125" +langsmith = ">=0.1.125,<0.3" packaging = ">=23.2,<25" pydantic = [ {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}, @@ -476,7 +476,7 @@ url = "../../core" [[package]] name = "langchain-tests" -version = "0.3.1" +version = "0.3.7" description = "Standard tests for LangChain implementations" optional = false python-versions = ">=3.9,<4.0" @@ -484,9 +484,15 @@ files = [] develop = true [package.dependencies] -httpx = "^0.27.0" -langchain-core = "^0.3.15" +httpx = ">=0.25.0,<1" +langchain-core = "^0.3.22" +numpy = [ + {version = ">=1.24.0,<2.0.0", markers = "python_version < \"3.12\""}, + {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}, +] pytest = ">=7,<9" +pytest-asyncio = ">=0.20,<1" +pytest-socket = ">=0.6.0,<1" 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-1289,6 +1404,20 @@ pytest = ">=6.2.5" [package.extras] dev = ["pre-commit", "pytest-asyncio", "tox"] +[[package]] +name = "pytest-socket" +version = "0.7.0" +description = "Pytest Plugin to disable socket calls during tests" +optional = false +python-versions = ">=3.8,<4.0" +files = [ + {file = "pytest_socket-0.7.0-py3-none-any.whl", hash = "sha256:7e0f4642177d55d317bbd58fc68c6bd9048d6eadb2d46a89307fa9221336ce45"}, + {file = "pytest_socket-0.7.0.tar.gz", hash = "sha256:71ab048cbbcb085c15a4423b73b619a8b35d6a307f46f78ea46be51b1b7e11b3"}, +] + +[package.dependencies] +pytest = ">=6.2.5" + [[package]] name = "pytest-watcher" version = "0.3.5" @@ -1716,4 +1845,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "40e27b8e7c09a02e0ce22d7134796a59586693612c784be8d17cea70d639f3d2" +content-hash = "6ad4d438ed6657e39e016ae7b54a69f229d36aa33d32f3397d0098fa7fae7449" diff --git a/libs/partners/fireworks/pyproject.toml b/libs/partners/fireworks/pyproject.toml index 4b60c14251b2d..c187500417c81 100644 --- a/libs/partners/fireworks/pyproject.toml +++ b/libs/partners/fireworks/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-fireworks" -version = "0.2.5" +version = "0.2.6" description = "An integration package connecting Fireworks and LangChain" authors = [] readme = "README.md" @@ -20,7 +20,7 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.15" +langchain-core = "^0.3.27" fireworks-ai = ">=0.13.0" openai = "^1.10.0" requests = "^2" From 24c4af62b0550639f5b60ae1494e3f8f0a126a88 Mon Sep 17 00:00:00 2001 From: wangda <38549158+daziz@users.noreply.github.com> Date: Thu, 19 Dec 2024 10:11:50 +0800 Subject: [PATCH 30/31] docs:Correcting spelling mistakes (#28780) --- docs/docs/integrations/providers/premai.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/providers/premai.md b/docs/docs/integrations/providers/premai.md index b124c8388d4e5..25498ebb287ef 100644 --- a/docs/docs/integrations/providers/premai.md +++ b/docs/docs/integrations/providers/premai.md @@ -124,7 +124,7 @@ Dense retrieval models typically include: "repository_id": 1985, "document_id": 1306, "chunk_id": 173899, - "document_name": "[D] Difference between sparse and dense informati\u2026", + "document_name": "[D] Difference between sparse and dense information\u2026", "similarity_score": 0.3209080100059509, "content": "with the difference or anywhere\nwhere I can read about it?\n\n\n 17 9\n\n\n u/ScotiabankCanada \u2022 Promoted\n\n\n Accelerate your study permit process\n with Scotiabank's Student GIC\n Program. We're here to help you tur\u2026\n\n\n startright.scotiabank.com Learn More\n\n\n Add a Comment\n\n\nSort by: Best\n\n\n DinosParkour \u2022 1y ago\n\n\n Dense Retrieval (DR) m" } From c823cc532de2d89c3345a64f4727e7c7a7747d9c Mon Sep 17 00:00:00 2001 From: Leonid Ganeline Date: Wed, 18 Dec 2024 18:28:37 -0800 Subject: [PATCH 31/31] docs: integration providers index update (#28808) Issue: integrations related to a provider can be spread across several packages and classes. It is very hard to find a provider using only ToCs. Fix: we have a very useful and helpful tool to search by provider name. It is the `Search` field. So, I've added recommendations for using this field. It seems obvious but it is not. --------- Co-authored-by: Erick Friis Co-authored-by: Eugene Yurtsev Co-authored-by: Chester Curme --- docs/scripts/partner_pkg_table.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/scripts/partner_pkg_table.py b/docs/scripts/partner_pkg_table.py index 37a8a2f1fdd10..6dfdcecbbf2bb 100644 --- a/docs/scripts/partner_pkg_table.py +++ b/docs/scripts/partner_pkg_table.py @@ -134,7 +134,8 @@ def doc() -> str: ## All Providers -Click [here](/docs/integrations/providers/all) to see all providers. +Click [here](/docs/integrations/providers/all) to see all providers. Or search for a +provider using the Search field in the top-right corner of the screen. """