mirror of
https://github.com/hwchase17/langchain
synced 2024-10-29 17:07:25 +00:00
195 lines
7.7 KiB
ReStructuredText
195 lines
7.7 KiB
ReStructuredText
Welcome to LangChain
|
|
==========================
|
|
|
|
| **LangChain** is a framework for developing applications powered by language models. We believe that the most powerful and differentiated applications will not only call out to a language model, but will also be:
|
|
1. *Data-aware*: connect a language model to other sources of data
|
|
2. *Agentic*: allow a language model to interact with its environment
|
|
|
|
| The LangChain framework is designed around these principles.
|
|
|
|
| This is the Python specific portion of the documentation. For a purely conceptual guide to LangChain, see `here <https://docs.langchain.com/docs/>`_. For the JavaScript documentation, see `here <https://js.langchain.com/docs/>`_.
|
|
|
|
Getting Started
|
|
----------------
|
|
|
|
| How to get started using LangChain to create an Language Model application.
|
|
|
|
- `Quickstart Guide <./getting_started/getting_started.html>`_
|
|
|
|
| Concepts and terminology.
|
|
|
|
- `Concepts and terminology <./getting_started/concepts.html>`_
|
|
|
|
| Tutorials created by community experts and presented on YouTube.
|
|
|
|
- `Tutorials <./getting_started/tutorials.html>`_
|
|
|
|
.. toctree::
|
|
:maxdepth: 2
|
|
:caption: Getting Started
|
|
:name: getting_started
|
|
:hidden:
|
|
|
|
getting_started/getting_started.md
|
|
getting_started/concepts.md
|
|
getting_started/tutorials.md
|
|
|
|
|
|
Modules
|
|
-----------
|
|
|
|
| These modules are the core abstractions which we view as the building blocks of any LLM-powered application.
|
|
For each module LangChain provides standard, extendable interfaces. LanghChain also provides external integrations and even end-to-end implementations for off-the-shelf use.
|
|
|
|
| The docs for each module contain quickstart examples, how-to guides, reference docs, and conceptual guides.
|
|
|
|
| The modules are (from least to most complex):
|
|
|
|
- `Models <./modules/models.html>`_: Supported model types and integrations.
|
|
|
|
- `Prompts <./modules/prompts.html>`_: Prompt management, optimization, and serialization.
|
|
|
|
- `Memory <./modules/memory.html>`_: Memory refers to state that is persisted between calls of a chain/agent.
|
|
|
|
- `Indexes <./modules/indexes.html>`_: Language models become much more powerful when combined with application-specific data - this module contains interfaces and integrations for loading, querying and updating external data.
|
|
|
|
- `Chains <./modules/chains.html>`_: Chains are structured sequences of calls (to an LLM or to a different utility).
|
|
|
|
- `Agents <./modules/agents.html>`_: An agent is a Chain in which an LLM, given a high-level directive and a set of tools, repeatedly decides an action, executes the action and observes the outcome until the high-level directive is complete.
|
|
|
|
- `Callbacks <./modules/callbacks/getting_started.html>`_: Callbacks let you log and stream the intermediate steps of any chain, making it easy to observe, debug, and evaluate the internals of an application.
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Modules
|
|
:name: modules
|
|
:hidden:
|
|
|
|
./modules/models.rst
|
|
./modules/prompts.rst
|
|
./modules/indexes.md
|
|
./modules/memory.md
|
|
./modules/chains.md
|
|
./modules/agents.md
|
|
./modules/callbacks/getting_started.ipynb
|
|
|
|
Use Cases
|
|
----------
|
|
|
|
| Best practices and built-in implementations for common LangChain use cases:
|
|
|
|
- `Autonomous Agents <./use_cases/autonomous_agents.html>`_: Autonomous agents are long-running agents that take many steps in an attempt to accomplish an objective. Examples include AutoGPT and BabyAGI.
|
|
|
|
- `Agent Simulations <./use_cases/agent_simulations.html>`_: Putting agents in a sandbox and observing how they interact with each other and react to events can be an effective way to evaluate their long-range reasoning and planning abilities.
|
|
|
|
- `Personal Assistants <./use_cases/personal_assistants.html>`_: One of the primary LangChain use cases. Personal assistants need to take actions, remember interactions, and have knowledge about your data.
|
|
|
|
- `Question Answering <./use_cases/question_answering.html>`_: Another common LangChain use case. Answering questions over specific documents, only utilizing the information in those documents to construct an answer.
|
|
|
|
- `Chatbots <./use_cases/chatbots.html>`_: Language models love to chat, making this a very natural use of them.
|
|
|
|
- `Querying Tabular Data <./use_cases/tabular.html>`_: Recommended reading if you want to use language models to query structured data (CSVs, SQL, dataframes, etc).
|
|
|
|
- `Code Understanding <./use_cases/code.html>`_: Recommended reading if you want to use language models to analyze code.
|
|
|
|
- `Interacting with APIs <./use_cases/apis.html>`_: Enabling language models to interact with APIs is extremely powerful. It gives them access to up-to-date information and allows them to take actions.
|
|
|
|
- `Extraction <./use_cases/extraction.html>`_: Extract structured information from text.
|
|
|
|
- `Summarization <./use_cases/summarization.html>`_: Compressing longer documents. A type of Data-Augmented Generation.
|
|
|
|
- `Evaluation <./use_cases/evaluation.html>`_: Generative models are hard to evaluate with traditional metrics. One promising approach is to use language models themselves to do the evaluation.
|
|
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Use Cases
|
|
:name: use_cases
|
|
:hidden:
|
|
|
|
./use_cases/autonomous_agents.md
|
|
./use_cases/agent_simulations.md
|
|
./use_cases/personal_assistants.md
|
|
./use_cases/question_answering.md
|
|
./use_cases/chatbots.md
|
|
./use_cases/tabular.rst
|
|
./use_cases/code.md
|
|
./use_cases/apis.md
|
|
./use_cases/summarization.md
|
|
./use_cases/extraction.md
|
|
./use_cases/evaluation.rst
|
|
|
|
|
|
Reference Docs
|
|
---------------
|
|
|
|
| Full documentation on all methods, classes, installation methods, and integration setups for LangChain.
|
|
|
|
|
|
- `Reference Documentation <./reference.html>`_
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Reference
|
|
:name: reference
|
|
:hidden:
|
|
|
|
./reference/installation.md
|
|
./reference/integrations.md
|
|
./reference.rst
|
|
|
|
|
|
LangChain Ecosystem
|
|
-------------------
|
|
|
|
| Guides for how other companies/products can be used with LangChain.
|
|
|
|
- `LangChain Ecosystem <./ecosystem.html>`_
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:glob:
|
|
:caption: Ecosystem
|
|
:name: ecosystem
|
|
:hidden:
|
|
|
|
./ecosystem.rst
|
|
|
|
|
|
Additional Resources
|
|
---------------------
|
|
|
|
| Additional resources we think may be useful as you develop your application!
|
|
|
|
- `LangChainHub <https://github.com/hwchase17/langchain-hub>`_: The LangChainHub is a place to share and explore other prompts, chains, and agents.
|
|
|
|
- `Gallery <./gallery.html>`_: A collection of our favorite projects that use LangChain. Useful for finding inspiration or seeing how things were done in other applications.
|
|
|
|
- `Deployments <./deployments.html>`_: A collection of instructions, code snippets, and template repositories for deploying LangChain apps.
|
|
|
|
- `Tracing <./tracing.html>`_: A guide on using tracing in LangChain to visualize the execution of chains and agents.
|
|
|
|
- `Model Laboratory <./model_laboratory.html>`_: Experimenting with different prompts, models, and chains is a big part of developing the best possible application. The ModelLaboratory makes it easy to do so.
|
|
|
|
- `Discord <https://discord.gg/6adMQxSpJS>`_: Join us on our Discord to discuss all things LangChain!
|
|
|
|
- `YouTube <./youtube.html>`_: A collection of the LangChain tutorials and videos.
|
|
|
|
- `Production Support <https://forms.gle/57d8AmXBYp8PP8tZA>`_: As you move your LangChains into production, we'd love to offer more comprehensive support. Please fill out this form and we'll set up a dedicated support Slack channel.
|
|
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:caption: Additional Resources
|
|
:name: resources
|
|
:hidden:
|
|
|
|
LangChainHub <https://github.com/hwchase17/langchain-hub>
|
|
./glossary.md
|
|
./gallery.rst
|
|
./deployments.md
|
|
./tracing.md
|
|
./use_cases/model_laboratory.ipynb
|
|
Discord <https://discord.gg/6adMQxSpJS>
|
|
./youtube.md
|
|
Production Support <https://forms.gle/57d8AmXBYp8PP8tZA>
|