forked from Archives/langchain
improve docs (#1351)
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@ -41,6 +41,14 @@
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c16161de",
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"metadata": {},
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"source": [
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"This example was created by [John Wiseman](https://twitter.com/lemonodor/status/1628270074074398720?s=20)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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@ -91,6 +99,14 @@
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"agent_executor.run(\"What is the 10th fibonacci number?\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7caa30de",
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"metadata": {},
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"source": [
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"This example was created by [Samee Ur Rehman](https://twitter.com/sameeurehman/status/1630130518133207046?s=20)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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@ -202,7 +218,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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"version": "3.9.1"
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}
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},
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"nbformat": 4,
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@ -1,6 +1,15 @@
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How-To Guides
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=============
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There are three types of examples in this section:
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1. Agent Overview: how-to-guides for generic agent functionality
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2. Agent Toolkits: how-to-guides for specific agent toolkits (agents optimized for interacting with a certain resource)
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3. Agent Types: how-to-guides for working with the different agent types
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Agent Overview
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---------------
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The first category of how-to guides here cover specific parts of working with agents.
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`Load From Hub <./examples/load_from_hub.html>`_: This notebook covers how to load agents from `LangChainHub <https://github.com/hwchase17/langchain-hub>`_.
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@ -21,7 +30,44 @@ The first category of how-to guides here cover specific parts of working with ag
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`Asynchronous <./examples/async_agent.html>`_: Covering asynchronous functionality.
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The next set of examples are all end-to-end example of different agent types.
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.. toctree::
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:maxdepth: 1
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:glob:
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:hidden:
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./examples/*
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Agent Toolkits
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---------------
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The next set of examples covers agents with toolkits.
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As opposed to the examples above, these examples are not intended to show off an agent `type`,
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but rather to show off an agent applied to particular use case.
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`SQLDatabase Agent <./agent_toolkits/sql_database.html>`_: This notebook covers how to interact with an arbitrary SQL database using an agent.
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`JSON Agent <./agent_toolkits/json.html>`_: This notebook covers how to interact with a JSON dictionary using an agent.
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`OpenAPI Agent <./agent_toolkits/openapi.html>`_: This notebook covers how to interact with an arbitrary OpenAPI endpoint using an agent.
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`VectorStore Agent <./agent_toolkits/vectorstore.html>`_: This notebook covers how to interact with VectorStores using an agent.
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`Python Agent <./agent_toolkits/python.html>`_: This notebook covers how to produce and execute python code using an agent.
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.. toctree::
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:maxdepth: 1
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:glob:
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:hidden:
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./agent_toolkits/*
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Agent Types
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---------------
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The final set of examples are all end-to-end example of different agent types.
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In all examples there is an Agent with a particular set of tools.
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- Tools: A tool can be anything that takes in a string and returns a string. This means that you can use both the primitives AND the chains found in `this <../chains.html>`_ documentation. LangChain also provides a list of easily loadable tools. For detailed information on those, please see `this documentation <./tools.html>`_
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@ -50,26 +96,8 @@ In all examples there is an Agent with a particular set of tools.
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- `Example Notebook <./implementations/react.html>`_
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The final set of examples covers agents with toolkits.
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As opposed to the examples above, these examples are not intended to show off an agent `type`,
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but rather to show off an agent applied to particular use case.
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`SQLDatabase Agent <./agent_toolkits/sql_database.html>`_: This notebook covers how to interact with an arbitrary SQL database using an agent.
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`JSON Agent <./agent_toolkits/json.html>`_: This notebook covers how to interact with a JSON dictionary using an agent.
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`OpenAPI Agent <./agent_toolkits/openapi.html>`_: This notebook covers how to interact with an arbitrary OpenAPI endpoint using an agent.
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`VectorStore Agent <./agent_toolkits/vectorstore.html>`_: This notebook covers how to interact with VectorStores using an agent.
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`Python Agent <./agent_toolkits/python.html>`_: This notebook covers how to produce and execute python code using an agent.
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.. toctree::
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:maxdepth: 1
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:glob:
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:hidden:
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./examples/*
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.. toctree::
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:maxdepth: 1
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@ -77,3 +105,5 @@ but rather to show off an agent applied to particular use case.
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:hidden:
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./implementations/*
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@ -8,3 +8,8 @@ For more detailed information on agents, and different types of agents in LangCh
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Tools are functions that agents can use to interact with the world.
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These tools can be generic utilities (e.g. search), other chains, or even other agents.
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For more detailed information on tools, and different types of tools in LangChain, see [this documentation](tools.md).
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## ToolKits
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Toolkits are groups of tools that are best used together.
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They allow you to logically group and initialize a set of tools that share a particular resource (such as a database connection or json object).
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They can be used to construct an agent for a specific use-case.
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