langchain 0.0.1-dev.5

Build powerful LLM-based Dart/Flutter applications.

🦜️🔗 LangChain.dart

Build powerful LLM-based Dart/Flutter applications.

🚧 Early Stage of Development 🚧	📢 Call for Collaborators 📢
Please note that this project is in a very early stage of development. We are still working on the initial version and there may be bugs and incomplete features.	We are looking for collaborators to join the core group of maintainers.

What is LangChain.dart?

LangChain.dart is a Dart port of LangChain.

Motivation

Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP), serving as essential components in a wide range of applications, such as question answering, summarization, translation, and text generation.

Notably, most libraries and tools designed to support LLMs have been predominantly developed for the Python and JavaScript ecosystems. As a result, the number of Python and JavaScript applications leveraging LLMs has grown exponentially.

In contrast, the Dart / Flutter ecosystem has not experienced similar growth, which can likely be attributed to the scarcity of Dart and Flutter libraries that streamline the complexities associated with working with LLMs.

Flutter provides a unique technology that enables the rapid development of high-quality, natively compiled applications for mobile, web, desktop, and embedded devices from a single codebase, making it an ideal choice for building these types of applications.

LangChain.dart aims to fill this gap by abstracting the complexities of working with LLMs in Dart, enabling developers to harness the combined potential of both Flutter and LLMs effectively.

Packages

LangChain.dart has a modular design where the core langchain package provides the LangChain API and each integration with a model provider, data store, etc. is provided by a separate package.

Package	Version	Description	Models	Doc. loaders	Memory	Tools
langchain		The core package that provides the LangChain API.	🟢	🟢	🟢	🟢
langchain_amazon		Integration with Amazon.
langchain_anthropic		Integration with Anthropic.
langchain_chroma		Integration with Chroma.
langchain_cohere		Integration with Cohere.
langchain_google		Integration with Google.
langchain_huggingface		Integration with Hugging Face.
langchain_microsoft		Integration with Microsoft.
langchain_openai		Integration with OpenAI.	✅
langchain_pinecone		Integration with Pinecone.
langchain_supabase		Integration with Supabase.
langchain_weaviate		Integration with Weaviate.
langchain_wikipedia		Integration with Wikipedia.
langchain_wolfram		Integration with Wolfram Research.
langchain_zapier		Integration with Zapier.

Getting started

To start using LangChain.dart, add langchain as a dependency to your pubspec.yaml file. Also, include the dependencies for the specific integrations you want to use (e.g.langchain_openai):

dependencies:
  langchain: { version }
  langchain_openai: { version }

The most basic building block of LangChain is calling an LLM on some input:

final llm = OpenAI(apiKey: openaiApiKey, temperature: 0.9);
final result = await llm('Hello world!');

Docs

You can find the full documentation at langchaindart.com.

• Getting started (installation, setting up the environment, simple examples)
• How-To examples (demos, integrations, helper functions)
• Reference (full API docs)
• Resources (high-level explanation of core concepts)

Contribute

TODO

Related projects

• LangChain: The official Python LangChain project.
• LangChain.js: A JavaScript port of LangChain.
• LangChain.go: A Go port of LangChain.
• LangChain.rb: A Ruby port of LangChain.

License

LangChain.dart is licensed under the MIT License.