scholarbot / README.md
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---
title: Scholarbot
emoji: πŸŽ“
colorFrom: blue
colorTo: green
sdk: docker
pinned: false
---
# ScholarBot β€” Research Q&A System
**Live demo:** https://zan18a-scholarbot.hf.space/docs
A production-grade AI system that answers questions using Retrieval Augmented Generation (RAG) + a fine-tuned language model, served via a REST API.
---
## What it does
Send any question β†’ it searches 5000 documents β†’ generates a grounded answer β†’ returns JSON with sources and latency.
---
## Tech Stack
| Layer | Technology |
|---|---|
| Model | flan-t5-small (google) |
| Retrieval | ChromaDB + sentence-transformers |
| Embeddings | all-MiniLM-L6-v2 |
| API | FastAPI + uvicorn |
| Containerization | Docker |
| Deployment | HuggingFace Spaces |
| CI/CD | GitHub Actions |
| Dataset | natural-questions (5000 rows) |
---
## API Endpoints
| Method | Endpoint | Description |
|---|---|---|
| POST | /query | Ask a question, get an answer |
| GET | /health | Health check |
| GET | /docs | Swagger UI |
---
## Example Request
```bash
curl -X POST https://zan18a-scholarbot.hf.space/query \
-H "Content-Type: application/json" \
-d '{"question": "what is machine learning", "top_k": 3}'
```
## Example Response
```json
{
"answer": "Machine learning is a process used to learn from data.",
"sources": ["..."],
"model_id": "scholarbot-mistral-lora",
"latency_ms": 652.9
}
```
---
## Local Setup
```bash
git clone https://github.com/zidan18Ahd/scholarbot
cd scholarbot
python -m venv .venv && .venv\Scripts\activate
pip install -r requirements.txt
python data/download.py
python build_index.py
uvicorn api.main:app --reload --port 8000
```
---
## Author
Built by Zidan Ahmed as an end-to-end AI engineering portfolio project.