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Top 23 Python Research Projects
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qlib
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
After researching different AI models in Qlib (a quantitative finance platform), here's what I learned:
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khoj
Your AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research. Turn any online or local LLM into your personal, autonomous AI (gpt, claude, gemini, llama, qwen, mistral). Get started - free.
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I spent a weekend studying GPT-Researcher, an open-source project with 24,000+ GitHub stars. It builds an autonomous research agent that generates comprehensive reports with citations. The architecture is elegant: multiple specialized agents coordinate through LangGraph, parallel execution speeds up research, and quality gates ensure reliable output.
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RD-Agent
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report
# 克隆仓库 git clone https://github.com/microsoft/RD-Agent.git cd RD-Agent # 创建开发环境 conda create -n rdagent-dev python=3.10 conda activate rdagent-dev # 安装开发依赖 make dev # 或者手动安装 pip install -e . pip install -r requirements/dev.txt
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Project mention: GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents | news.ycombinator.com | 2026-05-05
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local-deep-research
~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.
Project mention: Local Deep Research: Run Your Own AI Research Assistant, Fully Private | dev.to | 2026-05-06Local Deep Research is a self-hosted AI research assistant. You give it a question. It searches across multiple sources — web, arXiv, PubMed, Wikipedia, GitHub, your own local documents — iterates on what it finds, and produces a structured report with citations.
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mlfinlab
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
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habitat-lab
A modular high-level library to train embodied AI agents across a variety of tasks and environments.
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Project mention: Computer vision papers reimplemented with minimal PyTorch code | news.ycombinator.com | 2026-01-22
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Cod...
I’d be interested in feedback from people who have implemented or reviewed these methods, particularly where this minimal approach oversimplifies important details.
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diamond
DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model. NeurIPS 2024 Spotlight.
I’ve thought an interesting outcome might be that it’s not even that there’s a binary generated. It’s just user input -> machine code LLM -> CPU. Like the only binary would be the LLM itself and it’s essentially mimicking software live. The paper “Diffusion as a Model of Environment Dream” (DIAMOND) is close to what I’m thinking, where they have a diffusion model generate frames of a game, updating with user input, but there’s no actual “game” code it’s just the model.
https://diamond-wm.github.io/
Like you’d have a machine code LLM that behaves like software but instead of a static binary being executed it’s just the LLM itself “executing” on inputs and precious state. I’m horrible at communicating this idea but hopefully the gist is there.
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WFGY
Verification-first reasoning engine for LLMs, with reproducible demos and audit-oriented specifications. Includes WFGY 3.0 Singularity Demo (public spec) and engineering failure maps for real systems.
Project mention: Show HN: A text-only reasoning core for LLMs (MIT, system prompt and self-test) | news.ycombinator.com | 2026-02-13 -
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tldw_server
tl/dw (Too Long, Didn't Watch): Your Personal Research Multi-Tool - a naive attempt at 'A Young Lady's Illustrated Primer' (Open Source NotebookLM)
Project mention: Show HN: OpenBrief – Local-first video downloader/summarizer | news.ycombinator.com | 2026-05-25Cool project! I built something similar a while back and then kept adding to it: https://github.com/rmusser01/tldw_server
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apple-silicon-accelerometer
reading the undocumented mems accelerometer + gyroscope on apple silicon macbooks via iokit hid
Project mention: Show HN: Mech keyboard sounds driven by a hidden accelerometer in MacBooks | news.ycombinator.com | 2026-03-17I built this after discovering and open-sourcing the accelerometer signal in Apple Silicon MacBooks (https://github.com/olvvier/apple-silicon-accelerometer).
The sensor reads impact force and vibration data in real time. Haptyk maps that to different sound intensities: soft taps play a quieter click, hard presses play a louder clack.
Would love to hear what you think.
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PyGame-Learning-Environment
PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.
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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 Research discussion
Python Research related posts
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I Built a CLI to Search 800M+ Academic Papers From Your Terminal
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Computer vision papers reimplemented with minimal PyTorch code
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1500 Lines of Markdown vs 15000 Lines of Python.
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Improving KAN with CDF normalization to quantiles
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A note from our sponsor - SaaSHub
www.saashub.com | 13 Jun 2026
Index
What are some of the best open-source Research projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | qlib | 44,098 |
| 2 | khoj | 35,097 |
| 3 | gpt-researcher | 27,645 |
| 4 | RD-Agent | 13,425 |
| 5 | UI-TARS | 10,926 |
| 6 | local-deep-research | 8,457 |
| 7 | software-papers | 6,496 |
| 8 | MegaTTS3 | 6,086 |
| 9 | mlfinlab | 4,628 |
| 10 | acme | 3,996 |
| 11 | scenic | 3,806 |
| 12 | catalyst | 3,377 |
| 13 | habitat-lab | 3,011 |
| 14 | lingvo | 2,864 |
| 15 | Papers-in-100-Lines-of-Code | 2,808 |
| 16 | diamond | 2,055 |
| 17 | WFGY | 1,752 |
| 18 | SALMONN | 1,449 |
| 19 | tldw_server | 1,404 |
| 20 | yacs | 1,335 |
| 21 | apple-silicon-accelerometer | 1,163 |
| 22 | PyGame-Learning-Environment | 1,058 |
| 23 | dreamerv2 | 1,031 |
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