8000 GitHub - zamalali/DeepGit: Deep research agent to help you find the best GitHub repositories 🕵️!
[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to content
/ DeepGit Public

Deep research agent to help you find the best GitHub repositories 🕵️!

deepgit.vercel.app
709 stars 74 forks Branches Tags Activity
Star
Notifications You must be signed in to change notification settings

zamalali/DeepGit

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

91 Commits
.github/workflows
.github/workflows
 
 
assets
assets
 
 
docs
docs
 
 
tests
tests
 
 
themes
themes
 
 
tools
tools
 
 
.env
.env
 
 
Dockerfile
Dockerfile
 
 
README.md
README.md
 
 
agent.py
agent.py
 
 
app.py
app.py
 
 
langgraph.json
langgraph.json
 
 
requirements.txt
requirements.txt
 
 
run_tests.py
run_tests.py
 
 

Repository files navigation

DeepGit

Langgraph Workflow Diagram

DeepGit 2.0 🤯 — now hardware‑aware & ColBERT‑powered

DeepGit

DeepGit is an advanced, Langgraph-based agentic workflow designed to perform deep research across GitHub repositories. It intelligently searches, analyzes, and ranks repositories based on user intent—even uncovering less-known but highly relevant tools. DeepGit infuses hybrid dense retrieval with advanced cross-encoder re-ranking and comprehensive activity analysis into a unified, open-source platform for intelligent repository discovery

Try out the Lite version here 🧑‍🎓

DeepGit-lite is a lightweight version of DeepGit running on zero GPU on Hugging Face Space here.
It may not perform as well as the full version, but it's great for a quick first-hand preview.

The latest release makes it even deeper, smarter, and faster:

DeepGit still unifies hybrid dense retrieval, cross‑encoder re‑ranking, activity & quality analysis—but now every step is both smarter and leaner.

⚙️ How It Works — Agentic Workflow v2

When the user submits a query, the DeepGit Orchestrator Agent triggers a relay of expert tools:

  1. Query Expansion
    An LLM turns your natural‑language question into high‑signal GitHub tags for precise searching.

  2. Hardware Spec Detector
    The same pass infers your wording for hints like “GPU‑poor”, “low‑memory”, or “mobile‑only” and records the constraint.

  3. ColBERT‑v2 Semantic Retriever
    Every README & doc block is embedded with multi‑dimensional token vectors; MaxSim scoring surfaces nuanced matches.

  4. Cross‑Encoder Re‑ranker
    A lightweight BERT (MiniLM‑L‑6‑v2) re‑orders the top K results for passage‑level accuracy.

  5. Hardware‑aware Dependency Filter
    The reasoning engine inspects each repo’s requirements.txt / pyproject.toml and discards any that can’t run on your declared hardware.

  6. Community & Code Insight
    Collects stars, forks, issue cadence, commit history, plus quick code‑quality metrics.

  7. Multi‑factor Ranking & Delivery
    Merges all scores into one ranking and serves a clean table with links, similarity %, and “Runs on cpu‑only” badges where relevant.

🚀 Goals

  • Uncover Hidden Gems:
    Surface powerful but under-the-radar open-source tools. Now comes with hardware spec filter too.

  • Empower Research:
    Build an intelligent discovery layer over GitHub tailored for research-focused developers.

  • Promote Open Innovation:
    Open-source the entire workflow to foster transparency and collaboration in research.

🖥️ User Interface

DeepGit provides an intuitive interface for exploring repository recommendations. The main page where users enter raw natural language query. This is the primary interaction point for initiating deep semantic searches.

DeepGit Dashboard

Output: Showcases the tabulated results with clickable links and different threshold scores, making it easy to compare and understand the ranking criteria.

DeepGit App UI

🔧 Recommended Environment

  • Python: 3.11+ (The repo has been tested on Python 3.11.x)
  • pip: 24.0+ (Ensure you have an up-to-date pip version)

👨‍🏭 Setup Instructions

1. Clone the Repository

git clone https://github.com/zamalali/DeepGit.git
cd DeepGit

2. Create a Virtual Environment (Recommended)

python3 -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Upgrade pip (Optional but Recommended)

pip install --upgrade pip

4. Install Dependencies

pip install -r requirements.txt

5. 🚀 Running DeepGit via App

To run DeepGit locally, simply execute:

python app.py

🛠️ Troubleshooting

  • Python Version: Use Python 3.11 or higher as the repo has been tested on Python 3.11.x.
  • pip Version: Make sure you’re running pip 24.0 or later.
  • Dependency Issues: If you encounter any, try reinstalling in a new virtual environment.

🛠️ Running DeepGit

For a detailed documentation on using DeepGit, Check out here.

DeepGit leverages Langgraph for orchestration. To launch the Langsmith dashboard and start the workflow, simply run:

langgraph dev

This command opens the Langsmith dashboard where you can enter your raw queries in a JSON snippet and monitor the entire agentic workflow.

DeepGit on Docker

For instructions on using Docker with DeepGit, please refer to our Docker Documentation.

About

Deep research agent to help you find the best GitHub repositories 🕵️!

deepgit.vercel.app

Resources

Readme
Activity

Stars

709 stars

Watchers

5 watching

Forks

74 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages

0
New feature What it gives you
⚛️ Multi‑dimensional ColBERT v2 embeddings Fine‑grained token‑level similarity for nuanced matches that single‑vector embeddings miss.
🔩 Smart Hardware Filter Tell DeepGit your device specs — CPU-only, low RAM, or mobile. It filters out repos that won’t run smoothly, so you only see ones that fit your setup.