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PocketFlow

The-Pocket/PocketFlow

Minimalist 100-line LLM framework enabling Agent creation and workflow orchestration.

GraphCanon updated 2d · GitHub synced 2d · 25 views this month

11k stars1.2k forksLast push 3w Python MIT

Decision brief

PocketFlow is a minimalist 100-line Python framework designed for efficient AI agent development and deployment, offering support for multi-agent systems, workflows, and RAG with very low dependency requirements.

Good fit when

  • - When you need a lightweight solution (<100 lines) that minimizes dependencies and avoids vendor lock-in for developing LLM-based agents.
  • - If you are working on projects where simplicity and quick prototyping are key, such as in academic research or proof-of-concept development.

Avoid when

  • - Avoid if your project requires complex feature integration that typically demands a larger codebase with more extensive dependencies.
  • - Not suitable for large-scale enterprise applications requiring robust, vendor-supported solutions with comprehensive documentation and support frameworks.
Hosting:
unknown - No specific cloud or hosting requirements mentioned. Its lightweight nature makes it versatile across various deployment environments from local development to cloud-based systems.
Pricing:
freemium - Free and open-source, with no direct costs for the core framework but might require additional investment in complementary services or support for larger projects.

Observed Jul 11, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Active (21d since push)
As of 2d
Provenance
Not a fork · Organization account
As of 2d
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install PocketFlow
PyPI

How it fits your stack(9)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Alternative

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Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

PocketFlow is a lightweight, agentic AI coding platform designed for efficient agent development and deployment. It supports multi-agent systems, workflows, and RAG (Retrieval-Augmented Generation) with minimal dependencies.

Capability facts

Languages
python

Source: github.language · Aug 17, 2026

Categories

Graph entities

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

LangChain integrationLangChain

Source: README excerpt (regex_v1, Aug 17, 2026)

| LangChain | Agent, Chain | Many <br><sup><sub>(e.g., QA, Summarization)</s
Source link
Python runtimePython

Source: README excerpt (regex_v1, Aug 17, 2026)

- To install, ```pip install pocketflow```or just copy the [source code](https://github.com/The-Pocket/Pocke
Source link
Works with CursorCursor

Source: README excerpt (regex_v1, Aug 17, 2026)

uang.substack.com/p/agentic-coding-the-most-fun-way-to)**: Let AI Agents (e.g., Cursor AI) build Agents—10x productivity boost!
Source link

Tags

README

Pocket Flow – 100-line minimalist LLM framework

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

Badge image

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!

Badge image
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
S

For agents

This page has a .md twin and JSON over the API.

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