LangChain - LangChain

LangChain

LangChain

Building applications with LLMs through composability.

Retrieval

TL;DR: We are adjusting our abstractions to make it easy for other retrieval methods besides the LangChain VectorDB object to be used in LangChain. This is done with the goals of (1) allowing retrievers constructed elsewhere to be used more easily in LangChain, (2) encouraging more experimentation with alternative

LangChain + Zapier Natural Language Actions (NLA)

LangChain + Zapier Natural Language Actions (NLA)

We are super excited to team up with Zapier and integrate their new Zapier NLA API into LangChain, which you can now use with your agents and chains. With this integration, you have access to the 5k+ apps and 20k+ actions on Zapier's platform through a natural language API interface.

Evaluation

Evaluation of language models, and by extension applications built on top of language models, is hard. With recent model releases (OpenAI, Anthropic, Google) evaluation is becoming a bigger and bigger issue. People are starting to try to tackle this, with OpenAI releasing OpenAI/evals - focused on evaluating OpenAI models.

LLMs and SQL

Francisco Ingham and Jon Luo are two of the community members leading the change on the SQL integrations. We’re really excited to write this blog post with them going over all the tips and tricks they’ve learned doing so. We’re even more excited to announce that we’

Origin Web Browser

Origin Web Browser

[Editor's Note]: This is the second of hopefully many guest posts. We intend to highlight novel applications building on top of LangChain. If you are interested in working with us on such a post, please reach out to harrison@langchain.dev. Authors: Parth Asawa (pgasawa@), Ayushi Batwara (ayushi.batwara@), Jason

Prompt Selectors

Prompt Selectors

One common complaint we've heard is that the default prompt templates do not work equally well for all models. This became especially pronounced this past week when OpenAI released a ChatGPT API. This new API had a completely new interface (which required new abstractions) and as a result many users

Chat Models

Last week OpenAI released a ChatGPT endpoint. It came marketed with several big improvements, most notably being 10x cheaper and a lot faster. But it also came with a completely new API endpoint. We were able to quickly write a wrapper for this endpoint to let users use it like

Using the ChatGPT API to evaluate the ChatGPT API

Using the ChatGPT API to evaluate the ChatGPT API

OpenAI released a new ChatGPT API yesterday. Lots of people were excited to try it. But how does it actually compare to the existing API? It will take some time before there is a definitive answer, but here are some initial thoughts. Because I'm lazy, I also enrolled the help

Agent Toolkits

Today, we're announcing agent toolkits, a new abstraction that allows developers to create agents designed for a particular use-case (for example, interacting with a relational database or interacting with an OpenAPI spec). We hope to continue developing different toolkits that can enable agents to do amazing feats. Toolkits are supported

TypeScript Support

TypeScript Support

It's finally here... TypeScript support for LangChain. What does this mean? It means that all your favorite prompts, chains, and agents are all recreatable in TypeScript natively. Both the Python version and TypeScript version utilize the same serializable format, meaning that artifacts can seamlessly be shared between languages. As an

Streaming Support in LangChain

Streaming Support in LangChain

We’re excited to announce streaming support in LangChain. There's been a lot of talk about the best UX for LLM applications, and we believe streaming is at its core. We’ve also updated the chat-langchain repo to include streaming and async execution. We hope that this repo can serve

LangChain + Chroma

LangChain + Chroma

Today we’re announcing LangChain's integration with Chroma, the first step on the path to the Modern A.I Stack. LangChain - The A.I-native developer toolkit We started LangChain with the intent to build a modular and flexible framework for developing A.I-native applications. Some of the use cases

Chat-Your-Data Submissions

Chat-Your-Data Submissions

Last week, we kicked off a week long competition to create a chatbot over your own data. The goal was to inspire (1) lots of document loaders for loading various types of data, (2) lots of end-to-end examples. We succeeded on both fronts! On the document loader side, we added

Async Support in LangChain

Async Support in LangChain

We’re excited to roll out initial asynchronous support in LangChain by leveraging the asyncio library. Asyncio uses uses coroutines and an event loop to perform non-blocking I/O operations; these coroutines are able to “pause” (await) while waiting on their ultimate result and let other routines run in the

Chat-Your-Data Challenge

Chat-Your-Data Challenge

ChatGPT has taken the world by storm. Millions are using it. But while it’s great for general purpose knowledge, it only knows information about what it has been trained on, which is pre-2021 generally available internet data. It doesn’t know about your private data, it doesn’t know

Tutorial: ChatGPT Over Your Data

Tutorial: ChatGPT Over Your Data

Note: See the accompanying GitHub repo for this blogpost here. ChatGPT has taken the world by storm. Millions are using it. But while it’s great for general purpose knowledge, it only knows information about what it has been trained on, which is pre-2021 generally available internet data. It doesn’

LangChain <> Unstructured

LangChain <> Unstructured

One of the core value props of LangChain is the ability to combine Large Language Models with your own text data. There are multiple (four!) different methods of doing so, and many different applications this can power. A step that sits upstream of using text data is the ability to

GPTwitter

[Editor's Note]: This is the first of hopefully many guest posts. We intend to highlight novel applications building on top of LangChain. If you are interested in working with us on such a post, please reach out to harrison@langchain.dev. This post by Akash Samant highlights an application that

Tracing

We’re excited to announce native tracing support in LangChain! By enabling tracing in your LangChain runs, you’ll be able to more effectively visualize, step through, and debug your chains and agents. Motivation Reasoning about your chain and agent executions is important for troubleshooting and debugging. However, it can

LangChainHub

We are excited to announce the launch of the LangChainHub, a place where you can find and submit commonly used prompts, chains, agents, and more! This obviously draws a lot of inspiration from Hugging Face's Hub, which we believe has done an incredible job of fostering an amazing community. Motivation

LangChain Chat

Today we’re excited to announce and showcase an open source chatbot specifically geared toward answering questions about LangChain’s documentation. Key Links * Deployed Chatbot: chat.langchain.dev * Deployed Chatbot on HuggingFace spaces: huggingface.co/spaces/hwchase17/chat-langchain * Open source repo: github.com/hwchase17/chat-langchain * Next.js frontend: github.com/