srush/MiniChain

Health v2 · maintenance only

Adoption not part of the score

1232 stars · 74 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MiniChain is a tiny Python library for building applications with large language models by annotating Python functions that call LLMs and chaining them together. It builds a graph of all LLM and tool calls (like PyTorch) for debugging, with support for OpenAI, Hugging Face, search, Python, and Bash backends.

Use cases

• build retrieval-augmented QA pipelines
• chain LLM calls with a Python interpreter for math problems
• create chatbots with memory
• extract structured information from text with LLMs
• implement chain-of-thought or self-ask prompting patterns
• prototype LLM apps without heavyweight frameworks like LangChain

When to choose

• you want a minimal, hackable alternative to LangChain
• you prefer prompts separated from code via Jinja templates
• you need a call graph for debugging chained LLM invocations
• you want to mix LLM calls with Python or Bash execution

When to avoid

• you need production-grade features like streaming, agents, or extensive integrations
• you want a large ecosystem of loaders, vector stores, and memory modules
• you need actively developed features or long-term support

Facets

library · maturity maintenance

llm-inference prompt-engineering rag agent-framework chatbot large-language-models artificial-intelligence developer-tools python cross-platform prompt-chaining llm-orchestration jinja-templates langchain-alternative minimalist natural-language-processing

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