78 lines
4.1 KiB
Markdown
78 lines
4.1 KiB
Markdown
<h1 align="center">Pocket Flow - LLM Framework in 100 Lines</h1>
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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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- Install via ```pip install pocketflow```, or just copy the [source codes](pocketflow/__init__.py) (only 100 lines)
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- **💡 Pro tip!!** Build LLM apps with LLMs assistants (ChatGPT, Claude, Cursor.ai, etc.)
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<details>
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<summary><b>Use Claude to build LLM app</b></summary>
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- Create a [project](https://www.anthropic.com/news/projects) and upload the [docs](docs) to project knowledge
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- Set project custom instructions. For example:
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```
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1. check "tool.md" and "llm.md" for the required functions.
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2. design the high-level (batch) flow and nodes.
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3. design the shared memory structure: define its fields, data structures, and how they will be updated.
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Think out aloud for above first and ask users if your design makes sense.
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4. Finally, implement. Start with simple, minimalistic codes without, for example, typing.
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```
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- Ask it to build LLM app (Sonnet 3.5 strongly recommended)!
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```
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Help me build a chatbot based on a directory of PDFs.
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```
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</details>
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<details>
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<summary><b>Use ChatGPT to build LLM app</b></summary>
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- Try the [GPT assistant](https://chatgpt.com/g/g-677464af36588191b9eba4901946557b-mini-llm-flow-assistant). However, it uses older models, which are good for explaining but not good at coding.
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- For stronger coding capabilities, consider sending the [docs](docs) to more advanced models like O1.
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- Paste the docs link (https://github.com/miniLLMFlow/PocketFlow/tree/main/docs) to [Gitingest](https://gitingest.com/).
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- Then, paste the generated contents into your O1 prompt, and ask it to build LLM app.
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</details>
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Documentation: https://minillmflow.github.io/PocketFlow/
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## Why Pocket Flow?
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Pocket Flow is designed to be **the framework used by LLMs**. In the future, LLM projects will be *self-programmed* by LLMs themselves: Users specify requirements, and LLMs will design, build, and maintain. Current LLMs are:
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1. **👍 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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2. **👎 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.
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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.
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Pocket Flow is also a *learning resource*, as current frameworks abstract too much away.
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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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- To learn more details, please check out documentation: https://minillmflow.github.io/PocketFlow/
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- Beginner Tutorial: [Text summarization for Paul Graham Essay + QA agent](https://colab.research.google.com/github/miniLLMFlow/PocketFlow/blob/main/cookbook/demo.ipynb)
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- Have questions for this tutorial? Ask LLM assistants through [this prompt](https://chatgpt.com/share/676f16d2-7064-8000-b9d7-f6874346a6b5)
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- More coming soon ... Let us know you’d love to see!
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