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docs: added community
modules descriptions (#17827)
API Reference: Several `community` modules (like [adapter](https://api.python.langchain.com/en/latest/community_api_reference.html#module-langchain_community.adapters) module) are missing descriptions. It happens when langchain was split to the core, langchain and community packages. - Copied module descriptions from other packages - Fixed several descriptions to the consistent format.
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"""**Adapters** are used to adapt LangChain models to other APIs.
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LangChain integrates with many model providers.
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While LangChain has its own message and model APIs,
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LangChain has also made it as easy as
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possible to explore other models by exposing an **adapter** to adapt LangChain
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models to the other APIs, as to the OpenAI API.
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"""
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"""Agent toolkits contain integrations with various resources and services.
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LangChain has a large ecosystem of integrations with various external resources
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like local and remote file systems, APIs and databases.
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These integrations allow developers to create versatile applications that combine the
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power of LLMs with the ability to access, interact with and manipulate external
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resources.
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When developing an application, developers should inspect the capabilities and
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permissions of the tools that underlie the given agent toolkit, and determine
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whether permissions of the given toolkit are appropriate for the application.
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See [Security](https://python.langchain.com/docs/security) for more information.
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"""**Toolkits** are sets of tools that can be used to interact with
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various services and APIs.
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"""
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from langchain_community.agent_toolkits.ainetwork.toolkit import AINetworkToolkit
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from langchain_community.agent_toolkits.amadeus.toolkit import AmadeusToolkit
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"""**Chat message history** stores a history of the message interactions in a chat.
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**Class hierarchy:**
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.. code-block::
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BaseChatMessageHistory --> <name>ChatMessageHistory # Examples: FileChatMessageHistory, PostgresChatMessageHistory
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**Main helpers:**
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.. code-block::
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AIMessage, HumanMessage, BaseMessage
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""" # noqa: E501
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from langchain_community.chat_message_histories.astradb import (
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AstraDBChatMessageHistory,
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)
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"""Logic for selecting examples to include in prompts."""
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"""**Example selector** implements logic for selecting examples to include them
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in prompts.
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This allows us to select examples that are most relevant to the input.
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There could be multiple strategies for selecting examples. For example, one could
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select examples based on the similarity of the input to the examples. Another
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strategy could be to select examples based on the diversity of the examples.
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"""
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from langchain_community.example_selectors.ngram_overlap import (
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NGramOverlapExampleSelector,
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ngram_overlap_score,
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"""**Index** is used to avoid writing duplicated content
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into the vectostore and to avoid over-writing content if it's unchanged.
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Indexes also :
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* Create knowledge graphs from data.
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* Support indexing workflows from LangChain data loaders to vectorstores.
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Importantly, Index keeps on working even if the content being written is derived
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via a set of transformations from some source content (e.g., indexing children
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documents that were derived from parent documents by chunking.)
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"""
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"""Implementations of key-value stores and storage helpers.
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"""**Storage** is an implementation of key-value store.
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Module provides implementations of various key-value stores that conform
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Storage module provides implementations of various key-value stores that conform
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to a simple key-value interface.
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The primary goal of these storages is to support implementation of caching.
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"""
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The primary goal of these storages is to support caching.
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**Class hierarchy:**
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.. code-block::
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BaseStore --> <name>Store # Examples: MongoDBStore, RedisStore
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""" # noqa: E501
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from langchain_community.storage.astradb import (
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AstraDBByteStore,
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"""Code to support various indexing workflows.
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"""**Index** is used to avoid writing duplicated content
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into the vectostore and to avoid over-writing content if it's unchanged.
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Provides code to:
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Indexes also :
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* Create knowledge graphs from data.
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* Support indexing workflows from LangChain data loaders to vectorstores.
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For indexing workflows, this code is used to avoid writing duplicated content
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into the vectostore and to avoid over-writing content if it's unchanged.
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Importantly, this keeps on working even if the content being written is derived
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Importantly, Index keeps on working even if the content being written is derived
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via a set of transformations from some source content (e.g., indexing children
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documents that were derived from parent documents by chunking.)
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"""
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