diff --git a/README.md b/README.md index fc9bfa7..d6672db 100644 --- a/README.md +++ b/README.md @@ -17,92 +17,77 @@ A [100-line](pocketflow/__init__.py) minimalist LLM framework for ([Multi-](http - If the 100 lines feel terse and you’d prefer a friendlier intro, [check this out](https://chatgpt.com/share/678564bd-1ba4-8000-98e4-a6ffe363c1b8) -- **💡 Pro tip!!** Build LLM apps with LLMs assistants (ChatGPT, Claude, Cursor.ai, etc.) - -
- (🫵 Click to expand) Use Claude to build LLM apps - - - Create a [project](https://www.anthropic.com/news/projects) and upload the [docs](docs) to project knowledge - - - Set project custom instructions. For example: - ``` - 1. check "tool.md" and "llm.md" for the required functions. - 2. design the high-level (batch) flow and nodes in artifact using mermaid - 3. design the shared memory structure: define its fields, data structures, and how they will be updated. - Think out aloud for above first and ask users if your design makes sense. - 4. Finally, implement. Start with simple, minimalistic codes without, for example, typing. Write the codes in artifact. - ``` - - Ask it to build LLM apps (Sonnet 3.5 strongly recommended)! - ``` - Help me build a chatbot based on a directory of PDFs. - ``` - -
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- (🫵 Click to expand) Use ChatGPT to build LLM apps - - - 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 that good at coding. - -
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- - - For stronger coding capabilities, consider sending the [docs](docs) to more advanced models like O1. - - - Paste the docs link (https://github.com/the-pocket/PocketFlow/tree/main/docs) to [Gitingest](https://gitingest.com/). - - - Then, paste the generated contents into your O1 prompt, and ask it to build LLM apps. - - -
- - Documentation: https://the-pocket.github.io/PocketFlow/ ## Why Pocket Flow? -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: +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. +To build LLM projects with LLMs assistants (ChatGPT, Claude, Cursor.ai, etc.): -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. +
+ (🫵 Click to expand) Use Claude to build LLM apps -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. + - Create a [project](https://www.anthropic.com/news/projects) and upload the [docs](docs) to project knowledge -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. + - Set project custom instructions. For example: + ``` + 1. check "tool.md" and "llm.md" for the required functions. + 2. design the high-level (batch) flow and nodes in artifact using mermaid + 3. design the shared memory structure: define its fields, data structures, and how they will be updated. + Think out aloud for above first and ask users if your design makes sense. + 4. Finally, implement. Start with simple, minimalistic codes without, for example, typing. Write the codes in artifact. + ``` + - Ask it to build LLM apps (Sonnet 3.5 strongly recommended)! + ``` + Help me build a chatbot based on a directory of PDFs. + ``` -Pocket Flow is also a *learning resource*, as current frameworks abstract too much away. +
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-| Framework | Computation Models | Communication Models | App-Specific Models | Vendor-Specific Models | Lines Of Codes | Package + Dependency Size | -|:--------------:|:------------------:|:--------------------:|:-------------------------------------------------------:|:--------------------------------------------------------:|:-----------------:|:---------------------------:| -| LangChain | Agent, Chain | Message | Many | Many | *405K* | *+166MB* | -| CrewAI | Agent, Chain | Message, Shared | Many | Many | *18K* | *+173MB* | -| SmolAgent | Agent | Message | Some | Some | *8K* | *+198MB* | -| LangGraph | Agent, Graph | Message, Shared | Some | Some | *37K* | *+51MB* | -| AutoGen | Agent | Message | Some | Many | *7K* | *+26MB* | -| **PocketFlow** | **Graph** | **Shared** | **None** | **None** | **100** | **+56KB** | +
+ (🫵 Click to expand) Use ChatGPT to build LLM apps + + - 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 that good at coding. + +
+ +
+ + - For stronger coding capabilities, consider sending the [docs](docs) to more advanced models like O1. + + - Paste the docs link (https://github.com/the-pocket/PocketFlow/tree/main/docs) to [Gitingest](https://gitingest.com/). + + - Then, paste the generated contents into your O1 prompt, and ask it to build LLM apps. + + +
-## How Does it Work? -The [100 lines](pocketflow/__init__.py) capture what we see as the core abstraction of most LLM frameworks: **Nested Directed Graph** that breaks down tasks into multiple (LLM) steps, with branching and recursion for agent-like decision-making. +## How does it work? + +The [100 lines](pocketflow/__init__.py) capture what we see as the core abstraction of LLM frameworks: a **Graph** that breaks down tasks into multiple (LLM) steps, with branching and recursion for agent-like decision-making, and a **Shared Store** that communicates across graph nodes. + +
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-From there, it’s easy to layer on more complex features like ([Multi-](https://the-pocket.github.io/PocketFlow/multi_agent.html))[Agents](https://the-pocket.github.io/PocketFlow/agent.html), [Prompt Chaining](https://the-pocket.github.io/PocketFlow/decomp.html), [RAG](https://the-pocket.github.io/PocketFlow/rag.html), etc. +From there, it’s easy to implement popular design patterns ike ([Multi-](https://the-pocket.github.io/PocketFlow/multi_agent.html))[Agents](https://the-pocket.github.io/PocketFlow/agent.html), [Prompt Chaining](https://the-pocket.github.io/PocketFlow/decomp.html), [RAG](https://the-pocket.github.io/PocketFlow/rag.html), etc. +
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+ +- To learn more details, please check out the [documentation](https://the-pocket.github.io/PocketFlow/) +- For a more in-depth dive on the design choices, check out the [essay](https://github.com/The-Pocket/.github/blob/main/profile/pocketflow.mdb) -- To learn more details, please check out documentation: https://the-pocket.github.io/PocketFlow/ - -- Beginner Tutorial: [Text summarization for Paul Graham Essay + QA agent](https://colab.research.google.com/github/the-pocket/PocketFlow/blob/main/cookbook/demo.ipynb) - -- More coming soon ... Let us know you’d love to see!