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Top 23 Python llm-framework Projects
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LLM / agentic frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, MCP, RAG. (Fiddler and Razorpay both list these. "Hands-on counts, not just awareness," as Razorpay puts it.)
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My exploration of LLM-based tools for code understanding started with DeepWiki, which I have been using since its early release. As my interest shifted toward analyzing private repositories and experimenting more deeply with the underlying mechanics, I began looking for open-source alternatives. This led me to deepwiki-rs and later OpenDeepWiki. After starring OpenDeepWiki on GitHub, one of the authors of Davia reached out, which introduced me to a different, more collaborative approach to AI-assisted documentation. I later encountered PocketFlow Tutorial Codebase Knowledge through a technical report, and finally Google Code Wiki when it was publicly announced, which I followed closely given its enterprise positioning.
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git submodule add https://github.com/The-Pocket/PocketFlow.git vendor/pocketflow
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I ran into this question when thinking about the approach for a recent project. Yes CLI coding tools are good agents for interactive use, but if you are building a product then you do need an agent abstraction.
You could package Claude Code into the product (via agents-sdk or Claude -p) and have it use the API key (with metered billing) but in my case I didn’t find it ergonomic enough for my needs, so I ended up using my own agent framework Langroid for this.
https://github.com/langroid/langroid
(No it’s not based on that similarly named other framework, it’s a clean, minimal, extensible framework with good dx)
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Project mention: What is an AI SRE? Definition, Capabilities, and 2026 Buyer's Lens | dev.to | 2026-05-21
Infrastructure tool execution. The agent reads from kubectl, cloud SDKs, observability backends, and ticket systems. Some agents also write, with guardrails. HolmesGPT documents read-only access with RBAC respect. Aurora documents sandboxed execution into an isolated namespace. K8sGPT documents Kubernetes-only diagnostics with anonymisation before any AI backend call.
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LLMStack
No-code multi-agent framework to build LLM Agents, workflows and applications with your data
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code-act
Official Repo for ICML 2024 paper "Executable Code Actions Elicit Better LLM Agents" by Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, Heng Ji.
The source code and datasets are available on GitHub.
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edsl
Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.
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Project mention: Show HN: Realizing Karpathy's Prediction for Natural Language Programming | news.ycombinator.com | 2025-10-21
Andrej Karpathy's posted in early 2023 (https://x.com/karpathy/status/1617979122625712128) -
> "The hottest new programming language is English"
I've built a Natural Language Programming stack for building AI Agents. I think it is the first true Software 3.0 stack.
The core idea: Use LLMs as CPUs! You can finally step debug through your prompts and get reliable, verifiable execution. The stack includes a new language, compiler, developer tooling like VSCode extension.
Programs are written as markdown. H1 tags are agents, H2 tags are natural language playbooks (i.e. functions), python playbooks. All playbooks in an agents run on the same call stack. NL and python playbooks can call each other.
Quick intro video: https://www.youtube.com/watch?v=ZX2L453km6s
Github: https://github.com/playbooks-ai/playbooks (MIT license)
Documentation: https://playbooks-ai.github.io/playbooks-docs/getting-starte...
Project website: runplaybooks.ai
Example Playbooks program -
# Country facts agent -
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Project mention: Show HN: SyGra – Graph-oriented Synthetic data generation Pipeline for LLMs | news.ycombinator.com | 2025-09-23
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Kite
Production-ready agentic AI framework. High-performance, lightweight, simple. Built-in safety, memory, and 4 reasoning patterns. Ships to production fast. (by thienzz)
Project mention: Ask HN: When should you stop building an open-source AI agent framework? | news.ycombinator.com | 2026-02-05Hi HN,
I've been building an open-source Python framework for production-ready AI agents (lightweight, with built-in circuit breakers, multi-LLM support including Ollama, ReAct/ReWOO/ToT reasoning, and safety features like guardrails/idempotency).
Repo: https://github.com/thienzz/Kite (just released v0.1.0 on PyPI: pip install kite-agent)
My questions:
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SynapseKit
Async-native Python framework for building LLM applications — RAG pipelines, tool-using agents, and graph workflows. Streaming-first, transparent API, 2 hard deps. 27 providers · 43 tools · 26 loaders · 9 vector stores.
Project mention: Why I Modelled My LLM Pipeline as a DAG Instead of a Chain — and What I Found Out | dev.to | 2026-04-16SynapseKit is the framework I built around this model: https://github.com/SynapseKit/SynapseKit API Doc: https://synapsekit.github.io/synapsekit-docs/
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python llm-framework discussion
Python llm-framework related posts
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Porting from PocketFlow to Ambler TS
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Paperclip AI Review: I Tried to Build a Zero-Human Company in a Weekend [2026]
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What Is Multi-Agent Orchestration? A Technical Guide for 2026
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Ask HN: When should you stop building an open-source AI agent framework?
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Show HN: Sovereign GraphGuard – Atomic Persistence for AutoGen Agents
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How to Actually Start Contributing to Open Source AI Projects (A Step-by-Step Guide)
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Show HN: SyGra – Graph-oriented Synthetic data generation Pipeline for LLMs
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A note from our sponsor - SaaSHub
www.saashub.com | 11 Jun 2026
Index
What are some of the best open-source llm-framework projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | autogen | 58,700 |
| 2 | PocketFlow-Tutorial-Codebase-Knowledge | 12,377 |
| 3 | PocketFlow | 10,713 |
| 4 | langroid | 4,029 |
| 5 | holmesgpt | 2,577 |
| 6 | LLMStack | 2,301 |
| 7 | contextgem | 1,844 |
| 8 | LLMCompiler | 1,835 |
| 9 | code-act | 1,656 |
| 10 | edsl | 464 |
| 11 | LLMtuner | 248 |
| 12 | spelltest | 136 |
| 13 | playbooks | 90 |
| 14 | DataJourney | 89 |
| 15 | SyGra | 85 |
| 16 | GoalChain | 69 |
| 17 | geniusrise | 62 |
| 18 | sql-sidekick | 27 |
| 19 | Kite | 9 |
| 20 | SynapseKit | 8 |
| 21 | geniusrise-prompt-actions | 4 |
| 22 | listeners | 2 |
| 23 | geniusrise-openai | 2 |
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