PocketFlow

The-PocketMIT活跃维护

100 行代码的极简 LLM 框架,用图编排 Agent 工作流,让 Agent 自己搭建 Agent,适合想快速上手又不想被重型框架绑住的场景。

Pocket Flow: 100-line LLM framework. Let Agents build Agents!

v0.0.0发布于 2025-03-25 14:01 UTC11,315star +8 / 7 天1,214fork同步于 2026-11-10 17:29 UTC

怎么上手

由 README 提炼,执行前请确认
pip install pocketflow
硬件要求按 README 说明

README 未说明

下载:源码 zip·GitHub Releases(安装包)本站不镜像安装包

项目说明

由 README 自动翻译提炼

100 行极简 LLM 框架,用 Graph 抽象搭 Agent 和工作流,零依赖零厂商锁定

100 行代码的极简 LLM 框架,用图编排 Agent 工作流,让 Agent 自己搭建 Agent,适合想快速上手又不想被重型框架绑住的场景。

核心能力

  • 仅 100 行源码,零依赖、零厂商锁定
  • 以 Graph 为核心抽象实现 Agent、Workflow、RAG 等模式
  • 可直接复制源码或 pip 安装,无额外封装层
  • 提供多语言版本:TypeScript、Java、C++、Go、Rust、PHP
  • cookbook 覆盖流式输出、多 Agent、并行、HITL 等示例

容易踩的坑

框架本身不含 LLM 调用封装,需自行接入模型 SDK;示例 cookbook 可能需要额外依赖和 API Key

内容由模型根据 README 生成,可能不完整或不准确,以官方文档为准。看原文 README

最近发版

1 个版本v0.0.0
  1. v0.0.0pre-release最新正式版2025-03-25 · 2025-03-25 14:01 UTC

    这个版本没有写更新说明。

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    README 原文

    未翻译

    English | 中文 | Español | 日本語 | Deutsch | Русский | Português | Français | 한국어

    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—(Multi-)Agents, Workflow, RAG, and more.

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

    Get started with Pocket Flow:

    Why Pocket Flow?

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

    AbstractionApp-Specific WrappersVendor-Specific WrappersLinesSize
    LangChainAgent, ChainMany (e.g., QA, Summarization)Many (e.g., OpenAI, Pinecone, etc.)405K+166MB
    CrewAIAgent, ChainMany (e.g., FileReadTool, SerperDevTool)Many (e.g., OpenAI, Anthropic, Pinecone, etc.)18K+173MB
    SmolAgentAgentSome (e.g., CodeAgent, VisitWebTool)Some (e.g., DuckDuckGo, Hugging Face, etc.)8K+198MB
    LangGraphAgent, GraphSome (e.g., Semantic Search)Some (e.g., PostgresStore, SqliteSaver, etc.) 37K+51MB
    AutoGenAgentSome (e.g., Tool Agent, Chat Agent)Many [Optional] (e.g., OpenAI, Pinecone, etc.)7K (core-only)+26MB (core-only)
    PocketFlowGraphNoneNone100+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.

    NameDifficultyDescription
    Chat☆☆☆ DummyA basic chat bot with conversation history
    Structured Output☆☆☆ DummyExtracting structured data from resumes by prompting
    Workflow☆☆☆ DummyA writing workflow that outlines, writes content, and applies styling
    Agent☆☆☆ DummyA research agent that can search the web and answer questions
    RAG☆☆☆ DummyA simple Retrieval-augmented Generation process
    Batch☆☆☆ DummyA batch processor that translates markdown into multiple languages
    Streaming☆☆☆ DummyA real-time LLM streaming demo with user interrupt capability
    Chat Guardrail☆☆☆ DummyA travel advisor chatbot that only processes travel-related queries
    Majority Vote☆☆☆ DummyImprove reasoning accuracy by aggregating multiple solution attempts
    Map-Reduce☆☆☆ DummyBatch resume qualification using map-reduce pattern
    CLI HITL☆☆☆ DummyA command-line joke generator with human-in-the-loop feedback
    Multi-Agent★☆☆ BeginnerA Taboo word game for async communication between 2 agents
    Supervisor★☆☆ BeginnerResearch agent is getting unreliable... Let's build a supervision process
    Parallel★☆☆ BeginnerA parallel execution demo that shows 3x speedup
    Parallel Flow★☆☆ BeginnerA parallel image processing showing 8x speedup
    Thinking★☆☆ BeginnerSolve complex reasoning problems through Chain-of-Thought
    Memory★☆☆ BeginnerA chat bot with short-term and long-term memory
    Text2SQL★☆☆ BeginnerConvert natural language to SQL queries with an auto-debug loop
    Code Generator★☆☆ BeginnerGenerate test cases, implement solutions, and iteratively improve code
    MCP★☆☆ BeginnerAgent using Model Context Protocol for numerical operations
    Agent Skills★☆☆ BeginnerRoute requests to reusable markdown skills and apply them in an agent flow
    A2A★☆☆ BeginnerAgent wrapped with A2A protocol for inter-agent communication
    Streamlit FSM★☆☆ BeginnerStreamlit app with finite state machine for HITL image generation
    FastAPI WebSocket★☆☆ BeginnerReal-time chat interface with streaming LLM responses via WebSocket
    FastAPI Background★☆☆ BeginnerFastAPI app with background jobs and real-time progress via SSE
    Voice Chat★☆☆ BeginnerAn interactive voice chat application with VAD, STT, LLM, and TTS.
    Judge★☆☆ BeginnerLLM-as-Judge evaluator-optimizer loop for iterative content refinement
    Debate★☆☆ BeginnerAdversarial reasoning with two advocates and an impartial judge
    Agentic RAG★☆☆ BeginnerAgent-driven RAG that decides which documents to read
    Self-Healing Mermaid★☆☆ BeginnerGenerate Mermaid diagrams with automatic error recovery
    Heartbeat★☆☆ BeginnerClawBot-like always-on periodic monitoring with nested flows
    Lead Generation★★☆ IntermediateSales pipeline: scrape, enrich, score, and personalize emails
    Newsletter★★☆ IntermediateAI newsletter curation: search, filter, summarize, and format
    Invoice Processing★★☆ IntermediateExtract and validate invoice data from PDFs using vision
    NotebookLM★★☆ IntermediateTurn documents into a podcast with two AI hosts
    Deep Research★★☆ IntermediateRecursive map-reduce research with iterative refinement
    Coding Agent★★★ AdvancedProduction coding agent with 6 tools, memory, and patch-as-subflow

    👀 Want to see other tutorials for dummies? Create an issue!

    How to Use Pocket Flow?

    🚀 Through Agentic Coding—the fastest LLM App development paradigm-where humans design and agents code!

    ✨ Below are examples of more complex LLM Apps:

    App NameDifficultyTopicsHuman DesignAgent Code
    Website Chatbot Turn your website into a 24/7 customer support genius★★☆ MediumAgent RAGDesign DocFlow Code
    Danganronpa Simulator Forget the Turing test. Danganronpa, the ultimate AI experiment!★★★ AdvancedWorkflow AgentDesign DocFlow Code
    Codebase Knowledge Builder Life's too short to stare at others' code in confusion★★☆ MediumWorkflowDesign DocFlow Code
    Build Cursor with Cursor We'll reach the singularity soon ...★★★ AdvancedAgentDesign DocFlow Code
    Ask AI Paul Graham Ask AI Paul Graham, in case you don't get in★★☆ MediumRAG Map Reduce TTSDesign DocFlow Code
    Youtube Summarizer Explain YouTube Videos to you like you're 5 ★☆☆ BeginnerMap ReduceDesign DocFlow Code
    Cold Opener Generator Instant icebreakers that turn cold leads hot ★☆☆ BeginnerMap Reduce Web SearchDesign DocFlow Code
    • Want to learn Agentic Coding?

      • Check out my YouTube for video tutorial on how some apps above are made!

      • Want to build your own LLM App? Read this post! Start with this template!