Hugging Research

Hugging Research is a lightweight CodeAgent‑based research assistant for the Hugging Face Hub (models, datasets, Spaces, users, collections, papers). It gathers links via dedicated tools and organizes them for easy review.

What it does

• Finds relevant models/datasets/Spaces/papers on the Hub
• Uses domain‑restricted search for tutorials and docs
• Avoids hallucinated links (only cites tool‑returned URLs)
• Organizes the found links into a simple, categorized view in the Report view

Quick start

1. Clone and install

git clone https://github.com/mcdaqc/hugging-research
cd hugging-research
python -m venv venv
venv\Scripts\activate  # Windows
pip install -r requirements.txt

2. Configure your environment

cp .env.template .env
# Edit .env and set:
# HF_TOKEN=hf_xxx                # only for the inference model
# MODEL_ID=Qwen/Qwen3-Coder-480B-A35B-Instruct  # optional

3. Run the app

python app.py
# open http://localhost:7860

4. Use the app

• Enter your Hugging Face API key in the sidebar
• Click a Basic/Medium/Advanced example, or type your query in natural language
• Review the organized links in the Report view

Configuration

• HF_TOKEN: used for the inference model (agent). Tools are anonymous/read‑only.
• MODEL_ID: default Qwen/Qwen3-Coder-480B-A35B-Instruct.