From 397cd899889a009d9cff9b60342effa648bf508b Mon Sep 17 00:00:00 2001 From: Mason Daugherty Date: Wed, 13 Aug 2025 18:19:38 -0400 Subject: [PATCH] docs: update outdated `README.md` content (#32540) --- libs/core/README.md | 12 +++++------- libs/langchain/README.md | 17 +++++------------ libs/langchain_v1/README.md | 17 +++++------------ libs/standard-tests/README.md | 6 ------ libs/text-splitters/README.md | 4 +--- 5 files changed, 16 insertions(+), 40 deletions(-) diff --git a/libs/core/README.md b/libs/core/README.md index fb09de946ec..50b9ebf27aa 100644 --- a/libs/core/README.md +++ b/libs/core/README.md @@ -21,13 +21,13 @@ For full documentation see the [API reference](https://python.langchain.com/api_ ## 1️⃣ Core Interface: Runnables -The concept of a Runnable is central to LangChain Core – it is the interface that most LangChain Core components implement, giving them +The concept of a `Runnable` is central to LangChain Core – it is the interface that most LangChain Core components implement, giving them -- a common invocation interface (invoke, batch, stream, etc.) +- a common invocation interface (`invoke()`, `batch()`, `stream()`, etc.) - built-in utilities for retries, fallbacks, schemas and runtime configurability -- easy deployment with [LangServe](https://github.com/langchain-ai/langserve) +- easy deployment with [LangGraph](https://github.com/langchain-ai/langgraph) -For more check out the [runnable docs](https://python.langchain.com/docs/expression_language/interface). Examples of components that implement the interface include: LLMs, Chat Models, Prompts, Retrievers, Tools, Output Parsers. +For more check out the [runnable docs](https://python.langchain.com/docs/concepts/runnables/). Examples of components that implement the interface include: LLMs, Chat Models, Prompts, Retrievers, Tools, Output Parsers. You can use LangChain Core objects in two ways: @@ -51,7 +51,7 @@ LangChain Expression Language (LCEL) is a _declarative language_ for composing L LangChain Core compiles LCEL sequences to an _optimized execution plan_, with automatic parallelization, streaming, tracing, and async support. -For more check out the [LCEL docs](https://python.langchain.com/docs/expression_language/). +For more check out the [LCEL docs](https://python.langchain.com/docs/concepts/lcel/). ![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](https://raw.githubusercontent.com/langchain-ai/langchain/master/docs/static/svg/langchain_stack_112024.svg "LangChain Framework Overview") @@ -59,8 +59,6 @@ For more advanced use cases, also check out [LangGraph](https://github.com/langc ## 📕 Releases & Versioning -`langchain-core` is currently on version `0.1.x`. - As `langchain-core` contains the base abstractions and runtime for the whole LangChain ecosystem, we will communicate any breaking changes with advance notice and version bumps. The exception for this is anything in `langchain_core.beta`. The reason for `langchain_core.beta` is that given the rate of change of the field, being able to move quickly is still a priority, and this module is our attempt to do so. Minor version increases will occur for: diff --git a/libs/langchain/README.md b/libs/langchain/README.md index ec2870ae6cf..a1fd0a5e7d7 100644 --- a/libs/langchain/README.md +++ b/libs/langchain/README.md @@ -3,28 +3,21 @@ ⚡ Building applications with LLMs through composability ⚡ [![Release Notes](https://img.shields.io/github/release/langchain-ai/langchain)](https://github.com/langchain-ai/langchain/releases) -[![lint](https://github.com/langchain-ai/langchain/actions/workflows/lint.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/lint.yml) -[![test](https://github.com/langchain-ai/langchain/actions/workflows/test.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/test.yml) [![Downloads](https://static.pepy.tech/badge/langchain/month)](https://pepy.tech/project/langchain) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI)](https://twitter.com/langchainai) [![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain) [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/langchain-ai/langchain) [![GitHub star chart](https://img.shields.io/github/stars/langchain-ai/langchain?style=social)](https://star-history.com/#langchain-ai/langchain) -[![Dependency Status](https://img.shields.io/librariesio/github/langchain-ai/langchain)](https://libraries.io/github/langchain-ai/langchain) -[![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langchain)](https://github.com/langchain-ai/langchain/issues) Looking for the JS/TS version? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs). To help you ship LangChain apps to production faster, check out [LangSmith](https://smith.langchain.com). [LangSmith](https://smith.langchain.com) is a unified developer platform for building, testing, and monitoring LLM applications. -Fill out [this form](https://www.langchain.com/contact-sales) to speak with our sales team. ## Quick Install `pip install langchain` -or -`pip install langsmith && conda install langchain -c conda-forge` ## 🤔 What is this? @@ -34,22 +27,22 @@ This library aims to assist in the development of those types of applications. C **❓ Question answering with RAG** -- [Documentation](https://python.langchain.com/docs/use_cases/question_answering/) +- [Documentation](https://python.langchain.com/docs/tutorials/rag/) - End-to-end Example: [Chat LangChain](https://chat.langchain.com) and [repo](https://github.com/langchain-ai/chat-langchain) **🧱 Extracting structured output** -- [Documentation](https://python.langchain.com/docs/use_cases/extraction/) +- [Documentation](https://python.langchain.com/docs/tutorials/extraction/) - End-to-end Example: [SQL Llama2 Template](https://github.com/langchain-ai/langchain-extract/) **🤖 Chatbots** -- [Documentation](https://python.langchain.com/docs/use_cases/chatbots) +- [Documentation](https://python.langchain.com/docs/tutorials/chatbot/) - End-to-end Example: [Web LangChain (web researcher chatbot)](https://weblangchain.vercel.app) and [repo](https://github.com/langchain-ai/weblangchain) ## 📖 Documentation -Please see [here](https://python.langchain.com) for full documentation on: +Please see [our full documentation](https://python.langchain.com) on: - Getting started (installation, setting up the environment, simple examples) - How-To examples (demos, integrations, helper functions) @@ -79,7 +72,7 @@ Agents involve an LLM making decisions about which Actions to take, taking that **🧐 Evaluation:** -[BETA] Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this. +Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this. For more information on these concepts, please see our [full documentation](https://python.langchain.com). diff --git a/libs/langchain_v1/README.md b/libs/langchain_v1/README.md index ec2870ae6cf..a1fd0a5e7d7 100644 --- a/libs/langchain_v1/README.md +++ b/libs/langchain_v1/README.md @@ -3,28 +3,21 @@ ⚡ Building applications with LLMs through composability ⚡ [![Release Notes](https://img.shields.io/github/release/langchain-ai/langchain)](https://github.com/langchain-ai/langchain/releases) -[![lint](https://github.com/langchain-ai/langchain/actions/workflows/lint.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/lint.yml) -[![test](https://github.com/langchain-ai/langchain/actions/workflows/test.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/test.yml) [![Downloads](https://static.pepy.tech/badge/langchain/month)](https://pepy.tech/project/langchain) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI)](https://twitter.com/langchainai) [![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain) [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/langchain-ai/langchain) [![GitHub star chart](https://img.shields.io/github/stars/langchain-ai/langchain?style=social)](https://star-history.com/#langchain-ai/langchain) -[![Dependency Status](https://img.shields.io/librariesio/github/langchain-ai/langchain)](https://libraries.io/github/langchain-ai/langchain) -[![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langchain)](https://github.com/langchain-ai/langchain/issues) Looking for the JS/TS version? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs). To help you ship LangChain apps to production faster, check out [LangSmith](https://smith.langchain.com). [LangSmith](https://smith.langchain.com) is a unified developer platform for building, testing, and monitoring LLM applications. -Fill out [this form](https://www.langchain.com/contact-sales) to speak with our sales team. ## Quick Install `pip install langchain` -or -`pip install langsmith && conda install langchain -c conda-forge` ## 🤔 What is this? @@ -34,22 +27,22 @@ This library aims to assist in the development of those types of applications. C **❓ Question answering with RAG** -- [Documentation](https://python.langchain.com/docs/use_cases/question_answering/) +- [Documentation](https://python.langchain.com/docs/tutorials/rag/) - End-to-end Example: [Chat LangChain](https://chat.langchain.com) and [repo](https://github.com/langchain-ai/chat-langchain) **🧱 Extracting structured output** -- [Documentation](https://python.langchain.com/docs/use_cases/extraction/) +- [Documentation](https://python.langchain.com/docs/tutorials/extraction/) - End-to-end Example: [SQL Llama2 Template](https://github.com/langchain-ai/langchain-extract/) **🤖 Chatbots** -- [Documentation](https://python.langchain.com/docs/use_cases/chatbots) +- [Documentation](https://python.langchain.com/docs/tutorials/chatbot/) - End-to-end Example: [Web LangChain (web researcher chatbot)](https://weblangchain.vercel.app) and [repo](https://github.com/langchain-ai/weblangchain) ## 📖 Documentation -Please see [here](https://python.langchain.com) for full documentation on: +Please see [our full documentation](https://python.langchain.com) on: - Getting started (installation, setting up the environment, simple examples) - How-To examples (demos, integrations, helper functions) @@ -79,7 +72,7 @@ Agents involve an LLM making decisions about which Actions to take, taking that **🧐 Evaluation:** -[BETA] Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this. +Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this. For more information on these concepts, please see our [full documentation](https://python.langchain.com). diff --git a/libs/standard-tests/README.md b/libs/standard-tests/README.md index fe34759e3ac..b30f9fdbf2c 100644 --- a/libs/standard-tests/README.md +++ b/libs/standard-tests/README.md @@ -18,12 +18,6 @@ Pip: pip install -U langchain-tests ``` -Poetry: - -```bash -poetry add langchain-tests -``` - uv: ```bash diff --git a/libs/text-splitters/README.md b/libs/text-splitters/README.md index fbbfc34f5d6..4c1a04785ae 100644 --- a/libs/text-splitters/README.md +++ b/libs/text-splitters/README.md @@ -14,12 +14,10 @@ pip install langchain-text-splitters LangChain Text Splitters contains utilities for splitting into chunks a wide variety of text documents. For full documentation see the [API reference](https://python.langchain.com/api_reference/text_splitters/index.html) -and the [Text Splitters](https://python.langchain.com/docs/modules/data_connection/document_transformers/) module in the main docs. +and the [Text Splitters](https://python.langchain.com/docs/how_to/#text-splitters) module in the main docs. ## 📕 Releases & Versioning -`langchain-text-splitters` is currently on version `0.0.x`. - Minor version increases will occur for: - Breaking changes for any public interfaces NOT marked `beta`