Neura Market
LangChainDart logo

LangChainDart

Free

Build powerful LLM-based Dart/Flutter applications. ![GitHub Repo stars](https://img.shields.io/github/stars/davidmigloz/langchain_dart?style=social)

FreeFree tier
Type
Open Source
Visit Website GitHub (40 stars)

About LangChainDart

LangChain.dart is an unofficial Dart port of the popular LangChain Python framework, providing a set of ready-to-use components for working with language models and a standard interface for chaining them together. It enables developers to build LLM-powered Dart/Flutter applications such as chatbots, Q&A with RAG, agents, summarization, translation, extraction, and recommendation systems. The framework includes core modules: Model I/O (unified API for LLM providers like OpenAI, Google, Mistral, Ollama, prompt templates, output parsers), Retrieval (document loaders, text splitters, embedding models, vector stores, retrievers for RAG), and Agents (LLM-driven decision making using tools like web search and calculators). Components can be composed via the LangChain Expression Language (LCEL). The ecosystem is modular with packages like langchain_core (core abstractions and LCEL) and langchain (higher-level chains, agents, and retrieval).

Key Features

Unified API for multiple LLM providers (OpenAI, Google, Mistral, Ollama, etc.)
Prompt templates and example selectors for managing model inputs
Output parsers for structuring model outputs
Document loaders, text splitters, embedding models, vector stores, and retrievers for RAG
Agent framework with tool integrations (web search, calculators, etc.)
LangChain Expression Language (LCEL) for composing components
Modular package design (langchain_core, langchain, etc.)
Support for chatbots, Q&A, summarization, translation, extraction, and recommendation systems

Pros & Cons

Pros
  • Open source and free to use
  • Brings LangChain capabilities to Dart/Flutter ecosystem
  • Supports multiple popular LLM providers
  • Modular architecture allows selective imports
  • LCEL enables flexible chaining of components
  • RAG support for grounding LLM responses in user data
  • Active development with growing community
Cons
  • Unofficial port, not maintained by LangChain team
  • Smaller community and fewer resources compared to Python/JS versions
  • Documentation and examples are still maturing
  • Limited to Dart/Flutter (not cross-platform beyond those frameworks)
  • May lag behind upstream LangChain features

Best For

Chatbots and conversational agentsQuestion answering with retrieval-augmented generation (RAG)Text summarizationLanguage translationData extraction from documentsRecommendation systemsBuilding LLM-powered Flutter mobile apps

FAQ

What is LangChain.dart?
LangChain.dart is an unofficial Dart port of the LangChain Python framework. It provides components and interfaces for building LLM-powered applications in Dart and Flutter, including model I/O, retrieval, agents, and a composition language (LCEL).
What packages are available?
The ecosystem includes langchain_core (core abstractions and LCEL) and langchain (higher-level chains, agents, and retrieval). Additional packages may be available for specific integrations.
Which LLM providers are supported?
LangChain.dart supports multiple providers including OpenAI, Google, Mistral, and Ollama, with a unified API for easy switching.
Can I use LangChain.dart with Flutter?
Yes, LangChain.dart is designed for both Dart and Flutter applications, enabling LLM-powered features in mobile apps.