docs: integrations reference updates 16 (#26059)

Added missed provider pages and links. Fixed inconsistent formatting. Co-authored-by: Erick Friis <[email protected]>
langchain-ai · Sep 8, 2024 · 2f80d67 · 2f80d67
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diff --git a/docs/docs/integrations/platforms/microsoft.mdx b/docs/docs/integrations/platforms/microsoft.mdx
@@ -436,6 +436,8 @@ See a [usage example](/docs/integrations/tools/azure_ai_services).
 from langchain_community.agent_toolkits import azure_ai_services
 ```
 
+#### Azure AI Services individual tools
+
 The `azure_ai_services` toolkit includes the following tools:
 
 - Image Analysis: [AzureAiServicesImageAnalysisTool](https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.azure_ai_services.image_analysis.AzureAiServicesImageAnalysisTool.html)
@@ -460,6 +462,23 @@ See a [usage example](/docs/integrations/tools/office365).
 from langchain_community.agent_toolkits import O365Toolkit
 ```
 
+#### Office 365 individual tools
+
+You can use individual tools from the Office 365 Toolkit:
+- `O365CreateDraftMessage`: tool for creating a draft email in Office 365
+- `O365SearchEmails`: tool for searching email messages in Office 365
+- `O365SearchEvents`: tool for searching calendar events in Office 365
+- `O365SendEvent`: tool for sending calendar events in Office 365
+- `O365SendMessage`: tool for sending an email in Office 365
+
+```python
+from langchain_community.tools.office365 import O365CreateDraftMessage
+from langchain_community.tools.office365 import O365SearchEmails
+from langchain_community.tools.office365 import O365SearchEvents
+from langchain_community.tools.office365 import O365SendEvent
+from langchain_community.tools.office365 import O365SendMessage
+```
+
 ### Microsoft Azure PowerBI
 
 We need to install `azure-identity` python package.
@@ -475,6 +494,20 @@ from langchain_community.agent_toolkits import PowerBIToolkit
 from langchain_community.utilities.powerbi import PowerBIDataset
 ```
 
+#### PowerBI individual tools
+
+You can use individual tools from the Azure PowerBI Toolkit:
+- `InfoPowerBITool`: tool for getting metadata about a PowerBI Dataset
+- `ListPowerBITool`: tool for getting tables names
+- `QueryPowerBITool`: tool for querying a PowerBI Dataset
+
+```python
+from langchain_community.tools.powerbi.tool import InfoPowerBITool
+from langchain_community.tools.powerbi.tool import ListPowerBITool
+from langchain_community.tools.powerbi.tool import QueryPowerBITool
+```
+
+
 ### PlayWright Browser Toolkit
 
 >[Playwright](https://github.com/microsoft/playwright) is an open-source automation tool 

diff --git a/docs/docs/integrations/providers/apache.mdx b/docs/docs/integrations/providers/apache.mdx
@@ -0,0 +1,63 @@
+# Apache Software Foundation
+
+>[The Apache Software Foundation (Wikipedia)](https://en.wikipedia.org/wiki/The_Apache_Software_Foundation) 
+> is a decentralized open source community of developers. The software they 
+> produce is distributed under the terms of the Apache License, a permissive 
+> open-source license for free and open-source software (FOSS). The Apache projects 
+> are characterized by a collaborative, consensus-based development process 
+> and an open and pragmatic software license, which is to say that it 
+> allows developers, who receive the software freely, to redistribute 
+> it under non-free terms. Each project is managed by a self-selected 
+> team of technical experts who are active contributors to the project.
+
+## Apache AGE
+
+>[Apache AGE](https://age.apache.org/) is a `PostgreSQL` extension that provides 
+> graph database functionality. `AGE` is an acronym for `A Graph Extension`, and 
+> is inspired by Bitnine’s fork of `PostgreSQL 10`, `AgensGraph`, which is 
+> a multimodal database. The goal of the project is to create single 
+> storage that can handle both relational and graph model data so that users 
+> can use standard ANSI SQL along with `openCypher`, the Graph query language. 
+> The data elements `Apache AGE` stores are nodes, edges connecting them, and 
+> attributes of nodes and edges.
+ 
+See more about [integrating with Apache AGE](/docs/integrations/graphs/apache_age).
+
+## Apache Cassandra
+
+>[Apache Cassandra](https://cassandra.apache.org/) is a NoSQL, row-oriented, 
+> highly scalable and highly available database. Starting with version 5.0, 
+> the database ships with vector search capabilities.
+ 
+See more about [integrating with Apache Cassandra](/docs/integrations/providers/cassandra/).
+
+## Apache Doris
+
+>[Apache Doris](https://doris.apache.org/) is a modern data warehouse for 
+> real-time analytics. It delivers lightning-fast analytics on real-time data at scale.
+>
+>Usually `Apache Doris` is categorized into OLAP, and it has showed excellent 
+> performance in ClickBench — a Benchmark For Analytical DBMS. Since it has 
+> a super-fast vectorized execution engine, it could also be used as a fast vectordb.
+ 
+See more about [integrating with Apache Doris](/docs/integrations/providers/apache_doris/).
+
+## Apache Kafka
+
+>[Apache Kafka](https://github.com/apache/kafka) is a distributed messaging system 
+> that is used to publish and subscribe to streams of records.
+ 
+See more about [integrating with Apache Kafka](/docs/integrations/memory/kafka_chat_message_history).
+
+
+## Apache Spark
+
+>[Apache Spark](https://spark.apache.org/) is a unified analytics engine for 
+> large-scale data processing. It provides high-level APIs in Scala, Java, 
+> Python, and R, and an optimized engine that supports general computation 
+> graphs for data analysis. It also supports a rich set of higher-level 
+> tools including `Spark SQL` for SQL and DataFrames, `pandas API on Spark` 
+> for pandas workloads, `MLlib` for machine learning, 
+> `GraphX` for graph processing, and `Structured Streaming` for stream processing.
+
+See more about [integrating with Apache Spark](/docs/integrations/providers/spark).
diff --git a/docs/docs/integrations/providers/spark.mdx b/docs/docs/integrations/providers/spark.mdx
@@ -0,0 +1,49 @@
+# Spark
+
+>[Apache Spark](https://spark.apache.org/) is a unified analytics engine for 
+> large-scale data processing. It provides high-level APIs in Scala, Java, 
+> Python, and R, and an optimized engine that supports general computation 
+> graphs for data analysis. It also supports a rich set of higher-level 
+> tools including `Spark SQL` for SQL and DataFrames, `pandas API on Spark` 
+> for pandas workloads, `MLlib` for machine learning, 
+> `GraphX` for graph processing, and `Structured Streaming` for stream processing.
+
+## Document loaders
+
+### PySpark
+
+It loads data from a `PySpark` DataFrame.
+
+See a [usage example](/docs/integrations/document_loaders/pyspark_dataframe).
+
+```python
+from langchain_community.document_loaders import PySparkDataFrameLoader
+```
+
+## Tools/Toolkits
+
+### Spark SQL toolkit
+
+Toolkit for interacting with `Spark SQL`.
+
+See a [usage example](/docs/integrations/tools/spark_sql).
+
+```python
+from langchain_community.agent_toolkits import SparkSQLToolkit, create_spark_sql_agent
+from langchain_community.utilities.spark_sql import SparkSQL
+```
+
+#### Spark SQL individual tools
+
+You can use individual tools from the Spark SQL Toolkit:
+- `InfoSparkSQLTool`: tool for getting metadata about a Spark SQL
+- `ListSparkSQLTool`: tool for getting tables names
+- `QueryCheckerTool`: tool uses an LLM to check if a query is correct
+- `QuerySparkSQLTool`: tool for querying a Spark SQL
+
+```python
+from langchain_community.tools.spark_sql.tool import InfoSparkSQLTool
+from langchain_community.tools.spark_sql.tool import ListSparkSQLTool
+from langchain_community.tools.spark_sql.tool import QueryCheckerTool
+from langchain_community.tools.spark_sql.tool import QuerySparkSQLTool
+```
diff --git a/docs/docs/integrations/providers/sparkllm.mdx b/docs/docs/integrations/providers/sparkllm.mdx
@@ -4,11 +4,26 @@
 It has cross-domain knowledge and language understanding ability by learning a large amount of texts, codes and images.
 It can understand and perform tasks based on natural dialogue.
 
-## SparkLLM LLM Model
-An example is available at [example](/docs/integrations/llms/sparkllm).
+## Chat models
 
-## SparkLLM Chat Model
-An example is available at [example](/docs/integrations/chat/sparkllm).
+See a [usage example](/docs/integrations/chat/sparkllm).
 
-## SparkLLM Text Embedding Model
-An example is available at [example](/docs/integrations/text_embedding/sparkllm)
+```python
+from langchain_community.chat_models import ChatSparkLLM
+```
+
+## LLMs
+
+See a [usage example](/docs/integrations/llms/sparkllm).
+
+```python
+from langchain_community.llms import SparkLLM
+```
+
+## Embedding models
+
+See a [usage example](/docs/integrations/text_embedding/sparkllm)
+
+```python
+from langchain_community.embeddings import SparkLLMTextEmbeddings
+```