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README.md
Mini LLM Flow - LLM Framework in 100 Lines
An 100-line minimalist LLM framework for agents, task decomposition, RAG, etc.
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Install via
pip install minillmflow, or just copy the source (only 100 lines) -
Pro tip: Build LLM apps with LLMs assistants (ChatGPT, Claude, Cursor.ai, etc.)
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ChatGPT: Check out GPT assistant
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Claude: Create a project, dump the docs, and ask it to write LLM workflow!
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Documentation: https://minillmflow.github.io/miniLLMFlow/
Why Mini LLM Flow?
Mini LLM Flow is designed to be the framework used by LLMs. In the future, LLM projects will self-programmed by LLMs themselves: Users specify requirements, and LLMs will design, build, and maintain. Current LLMs are:
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👍 Good at Low-level Details: LLMs can handle details like wrappers, tools, and prompts, which don't belong in a framework. Current frameworks are over-engineered, making them hard for humans (and LLMs) to maintain.
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👎 Bad at High-level Paradigms: While paradigms like MapReduce, task decomposition, and agents are powerful, LLMs still struggle to design them elegantly. These high-level concepts should be emphasized in frameworks.
The ideal framework for LLMs should (1) strip away low-level implementation details, and (2) keep high-level programming paradigms. Hence, we provide this minimal (100-line) framework that allows LLMs to focus on what matters.
Mini LLM Flow is also a learning resource, as current frameworks abstract too much away.
How Does it Work?
The 100 lines capture what we see as the core abstraction of most LLM frameworks: a nested directed graph that breaks down tasks into multiple (LLM) steps, with branching and recursion for agent-like decision-making. From there, it’s easy to layer on more complex features.
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To learn more details, please check out documentation: https://minillmflow.github.io/miniLLMFlow/
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Beginner Tutorial: Text summarization for Paul Graham Essay + QA agent
- Have questions for this tutorial? Ask LLM assistants through this prompt
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More coming soon ... Let us know you’d love to see!