LiteChain
FreeLightweight alternative to LangChain for composing LLMs
FreeFree tier
Inputs: textOutputs: text
About LiteChain
LangStream (formerly LiteChain) is a lightweight, open-source framework for building LLM applications with a focus on composability. It provides a single small core based on 'Streams' (async generators) instead of complex chains, making it easy to learn, adapt, and extend. LangStream is fully typed, well-documented, and supports composition functions such as and_then, map, collect, join, and gather. It integrates with OpenAI and other models via contrib modules, enabling developers to build chatbots, translation pipelines, and multi-step AI workflows with streaming output.
Key Features
Stream-based architecture using Python AsyncGenerator for true composability
Small core with minimal abstractions — easy to learn and adapt
Composition functions: `and_then`, `map`, `collect`, `join`, `gather`
Fully typed and well-documented (documentation and reference available)
Built-in contrib modules for OpenAI chat streams (OpenAIChatStream)
Async streaming output for real-time token generation
Lightweight alternative to LangChain's larger feature set
Pros & Cons
Pros
- Extremely lightweight and minimalistic compared to LangChain
- True composability via Stream abstraction — streams can be combined arbitrarily
- Async-native design for efficient streaming and real-time responses
- Fully typed (Python type hints) for better IDE support and error checking
- Well-documented with guides and reference API
- Free and open-source (MIT license implied by GitHub repository)
Cons
- Smaller community and fewer integrations compared to established frameworks like LangChain
- Limited built-in tooling (e.g., no extensive vector store or agent abstractions by default)
- Requires manual composition for complex workflows (no high-level pipeline DSL)
Best For
Building chatbots that respond in specific formats (e.g., emoji-only)Creating multi-step translation pipelines (e.g., emoji to plain English)Developing composable LLM applications with streaming outputsRapid prototyping of AI workflows with minimal boilerplate
FAQ
What happened to LiteChain?
LiteChain was renamed to LangStream. For more details, refer to the project's GitHub repository issue #4.
How do I install LangStream?
LangStream can be installed via pip: `pip install langstream openai` (the OpenAI integration is separate).
What is the main concept behind LangStream?
LangStream uses 'Streams' as the fundamental building block. An LLM is a Stream, an output parser is a Stream, and groups of Streams can be composed into another Stream — it's Streams all the way down.
Does LangStream support streaming output?
Yes, everything in LangStream is an async stream using Python's AsyncGenerator, allowing real-time token-by-token output.