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<h1 align="center">Pocket Flow - LLM Framework in 100 Lines</h1>
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<h1 align="center">Pocket Flow - LLM Framework in 100 Lines</h1>
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[](https://minillmflow.github.io/PocketFlow/)
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[](https://minillmflow.github.io/PocketFlow/)
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<div align="center">
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<img src="/assets/minillmflow.jpg" width="400"/>
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</div>
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<br>
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A [100-line](pocketflow/__init__.py) minimalist LLM framework for ([Multi-](https://minillmflow.github.io/PocketFlow/multi_agent.html))[Agents](https://minillmflow.github.io/PocketFlow/agent.html), [task decomposition](https://minillmflow.github.io/PocketFlow/decomp.html), [RAG](https://minillmflow.github.io/PocketFlow/rag.html), etc.
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A [100-line](pocketflow/__init__.py) minimalist LLM framework for ([Multi-](https://minillmflow.github.io/PocketFlow/multi_agent.html))[Agents](https://minillmflow.github.io/PocketFlow/agent.html), [task decomposition](https://minillmflow.github.io/PocketFlow/decomp.html), [RAG](https://minillmflow.github.io/PocketFlow/rag.html), etc.
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- Install via ```pip install pocketflow```, or just copy the [source codes](pocketflow/__init__.py) (only 100 lines)
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- Install via ```pip install pocketflow```, or just copy the [source codes](pocketflow/__init__.py) (only 100 lines)
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@ -43,10 +51,6 @@ The ideal framework for LLMs should (1) **strip away low-level implementation de
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Pocket Flow is also a *learning resource*, as current frameworks abstract too much away.
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Pocket Flow is also a *learning resource*, as current frameworks abstract too much away.
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<div align="center">
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<img src="/assets/minillmflow.jpg" width="400"/>
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</div>
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## How Does it Work?
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## How Does it Work?
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The [100 lines](minillmflow/__init__.py) 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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The [100 lines](minillmflow/__init__.py) 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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