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PocketFlow
PocketFlow logo

PocketFlow

Active·★ 11.3k·MIT·Updated 2026-07-26
★ Most Popular★ Essential

PocketFlow is a minimalist LLM framework whose core is just 100 lines of Python with no dependencies. Its premise is that the essential abstraction behind LLM frameworks is a graph: nodes that do work and the flow between them. On top of that abstraction you can implement agents, multi-agent systems, workflows, RAG and other patterns yourself, without vendor-specific or app-specific wrappers.

It suits developers who want to understand and fully control their agent logic, educators and learners who want to see how LLM applications work under the hood, and anyone frustrated by heavy frameworks and their dependency trees. The project also promotes "agentic coding": because the framework is so small, coding agents such as Cursor can read it entirely and build PocketFlow applications for you. Ports exist for TypeScript, Java, C++, Go and other languages, and the documentation includes design patterns and a large cookbook of examples.

Getting started: `pip install pocketflow`, or simply copy the single 100-line source file into your project. Follow the documentation's design patterns to build an agent or workflow from nodes and flows.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-24.

License
MIT
Latest release
No GitHub releases
Last commit
2026-07-26
Contributors
28
Forks
1,210
Open issues and PRs
76
First published
2024-12-24
PyPI package
pocketflow 0.0.3 · 7,873 downloads last week

Source: GitHub, npm and PyPI public APIs.

#LLM Framework#AI Agents#Python#Minimalist#Workflow Automation#Coding
$ Install
$ pip install pocketflow
↗ Visit site★ GitHub
01

Features

01Lightweight and minimalist (100 lines, zero dependencies).
02Expressive, supporting popular LLM design patterns (Agents, Workflow, RAG).
03Facilitates "Agentic Coding" for 10x productivity with AI Agents.
04Core abstraction based on Graphs for flexible LLM application building.
05Cross-language support with versions in Typescript, Java, C++, Go, Rust, and PHP.
02

Why choose it

+Tiny, dependency-free core that you can read in minutes and vendor into any project.
+No lock-in: you bring your own model calls, tools and storage.
+Excellent for learning how agent and workflow patterns work.
+Ports to several languages and an extensive cookbook; MIT licensed.
03

Trade-offs

!You implement integrations yourself: model clients, retries, tracing, memory and tool schemas are not included.
!Production concerns such as durability and observability require additional libraries.
!Development of the core repository has slowed; the last push was in July 2026.
04

Maintenance check

SlowingChecked: 2026-10-25
Last commit
2026-07-26
Commits, last 90 days
0
Releases, last 90 days
0
Latest release
v0.0.0 (2025-03-25)
Open issues
76
Recent issues with at least one comment
14/25
Commits per week, last 12 weeks
Commits per week, last 12 weeks: 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0

Oldest week on the left; the latest four weeks are orange. Source: GitHub commit activity.

Status rule: archived on GitHub = Archived; last commit within 90 days = Active; 91 to 365 days = Slowing; older = Stale. All figures come from the GitHub API on the date shown.

Most discussed open issues

  • #12 请问支持流式返回吗11 comments · 2025-03-20
  • #2 Feature Requests11 comments · 2025-01-05
  • #74 如何优雅的结束Flow10 comments · 2025-06-11
  • #119 Proposal: Create a Rust Template Repository for PocketFlow9 comments · 2025-11-05
  • #54 provide exec_res_list for batchflow?8 comments · 2025-05-09

Issue titles are quoted from GitHub. Open the link to check whether a problem still applies to the version you use.

05

Compatibility

Python
Native
Verified via docs
Typescript
Supported
Verified via docs
Java
Supported
Verified via docs
C++
Supported
Verified via docs
Go
Supported
Verified via docs
Rust
Supported
Verified via docs
06

Quick start

1
$ pip install pocketflow
07

Use cases

↳Building and orchestrating AI agents (e.g., research agents, multi-agents).
↳Implementing LLM-powered workflows (e.g., writing, batch processing, code generation).
↳Developing Retrieval-Augmented Generation (RAG) applications.
08

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On this page
01Features02Why choose it03Trade-offs04Maintenance check05Compatibility06Quick start07Use cases08Alternatives
The-Pocket /
PocketFlow
↗

100-line minimalist LLM framework with zero dependencies

11.3k1.2kMIT
Last commit3mo ago
StatusActive
CategoryMulti-Agent
Contributors28
Links
Documentation↗Discussion↗Issues↗Releases↗
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