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README.md

License: MIT Docs

Pocket Flow is a 100-line minimalist LLM framework

  • Lightweight: Just 100 lines. Zero bloat, zero dependencies, zero vendor lock-in.

  • Expressive: Everything you love from large frameworks—(Multi-)Agents, Workflow, RAG, and more.

  • AI-Friendly: Let AI Agents (e.g., Cursor AI) build Agents—10x productivity boost!

  • To install, pip install pocketflowor just copy the source code (only 100 lines).

  • To learn more, check out the documentation. For an in-depth design dive, read the essay.

  • 🎉 We now have a discord!

Why Pocket Flow?

Current LLM frameworks are bloated. You only need 100 lines for LLM Framework!

Abstraction App-Specific Wrappers Vendor-Specific Wrappers Lines Size
LangChain Agent, Chain Many
(e.g., QA, Summarization)		 Many
(e.g., OpenAI, Pinecone, etc.)		 405K +166MB
LlamaIndex Agent, Graph Native for RAG
(Summarization, KG Indexing)		 Many [Optional]
(e.g., OpenAI, Pinecone, etc.)		 77K
(core-only)		 +189MB
(core-only)
CrewAI Agent, Chain Many
(e.g., FileReadTool, SerperDevTool)		 Many
(e.g., OpenAI, Anthropic, Pinecone, etc.)		 18K +173MB
Haystack Agent, Graph Many
(e.g., QA, Summarization)		 Many
(e.g., OpenAI, Anthropic, Pinecone, etc.)		 31K +195MB
SmolAgent Agent Some
(e.g., CodeAgent, VisitWebTool)		 Some
(e.g., DuckDuckGo, Hugging Face, etc.)		 8K +198MB
LangGraph Agent, Graph Some
(e.g., Semantic Search)		 Some
(e.g., PostgresStore, SqliteSaver, etc.) 		37K +51MB
AutoGen Agent Some
(e.g., Tool Agent, Chat Agent)		 Many [Optional]
(e.g., OpenAI, Pinecone, etc.)		 7K
(core-only)		 +26MB
(core-only)
PocketFlow Graph None None 100 +56KB

How does Pocket Flow work?

The 100 lines capture the core abstraction of LLM frameworks: Graph!

From there, it’s easy to implement popular design patterns like (Multi-)Agents, Workflow, RAG, etc.

How to Use Pocket Flow?

🚀 It's highly recommended to build Agents with Agents—the fastest development paradigm!

  • 😎 Humans craft the high-level requirements and system design.

  • 🤖 AI agents (e.g., Cursor AI) handle the low-level implementation.

Check out the video to see the process in action!



What can Pocket Flow build?

✨ Below are examples of LLM Apps:

Formal App Name Informal One-Liner Difficulty Learning Objectives
Ask AI Paul Graham Ask AI Paul Graham, in case you don't get in ★★☆
Medium		 RAG
Map Reduce
Text-to-Speech
Youtube Summarizer Explain YouTube Videos to you like you're 5 ★☆☆
Beginner		 Map Reduce
Cold Opener Generator Instant icebreakers that turn cold leads hot ★☆☆
Beginner		 Map Reduce
Web Search

  • Want to learn how I built these LLM Apps? Check out my YouTube!

  • Want to create your own Python project? Start with this template!