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Get your Graph RAG Chatbot running in 5 minutes!
## Prerequisites
- Groq API Key (free at https://console.groq.com)
- One of: Docker, Python 3.8+, or Hugging Face account
---
## π Fastest Way: Docker Compose (Recommended)
### 1. Get API Key
1. Visit https://console.groq.com
2. Sign up/Login
3. Click "API Keys" β Create new API key
4. Copy the key
### 2. Configure
```bash
cd /path/to/project
cp .env.example .env
# Edit .env and paste your API key:
# GROQ_API_KEY=your_actual_key_here
```
### 3. Launch
```bash
docker-compose up -d
```
### 4. Access
Open browser: http://localhost:7860
β
**Done!** Your app is running.
---
## Alternative: Local Python Setup
### 1. Create environment
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
### 2. Install dependencies
```bash
pip install -r requirements.txt
```
### 3. Set API key
```bash
export GROQ_API_KEY="your_api_key_here" # On Windows: set GROQ_API_KEY=...
```
### 4. Run app
```bash
python app.py
```
### 5. Access
Open: http://localhost:7860
---
## Alternative: Hugging Face Spaces (No local setup!)
### 1. Create Space
1. Go to https://huggingface.co/spaces
2. Click "Create new Space"
3. Select "Docker" SDK
4. Fill in details β Create
### 2. Upload files
```bash
git clone https://huggingface.co/spaces/YOUR_USERNAME/graph-rag-chatbot
cd graph-rag-chatbot
cp /path/to/app.py .
cp /path/to/Dockerfile .
cp /path/to/requirements.txt .
cp -r /path/to/templates .
cp /path/to/.dockerignore .
git add -A
git commit -m "Initial upload"
git push
```
### 3. Add API key
In Space Settings β Repository secrets:
- Name: `GROQ_API_KEY`
- Value: your_api_key
β
**Done!** App deploys automatically
---
## Using the Application
### Upload Documents
1. Click the upload area (or drag & drop)
2. Select PDF, CSV, or TXT file
3. Watch the progress bar
4. Status changes: queued β processing β ready
### View Knowledge Graph
1. Click "π View Full Graph" (appears when ready)
2. Or go to "Knowledge Graph" tab
3. Select document from dropdown
### Chat with Your Document
1. Select document from dropdown
2. Type your question
3. Click "Send" (or press Enter)
4. Read the answer!
---
## Test Files
### Quick CSV Test
Create `test.csv`:
```csv
Name,Role,Salary
Alice,Engineer,120000
Bob,Manager,110000
Carol,Designer,100000
```
Upload it and try asking:
- "Who is the highest paid?"
- "How many employees?"
- "What roles are in the data?"
---
## Troubleshooting
### "GROQ_API_KEY not found"
```bash
# Linux/Mac
echo "GROQ_API_KEY=your_key" >> .env
# Windows
echo GROQ_API_KEY=your_key >> .env
```
### Port 7860 in use?
```bash
# Find what's using it
lsof -i :7860 # Mac/Linux
netstat -ano | findstr :7860 # Windows
# Use different port
PORT=8000 python app.py
```
### Docker build fails?
```bash
# Clean and rebuild
docker-compose down
docker system prune -a
docker-compose up -d
```
### Model download slow?
The embedding model (~400MB) downloads once on first run. This is normal and can take 2-3 minutes. Subsequent runs are instant.
---
## Common Commands
```bash
# View logs
docker-compose logs -f
# Stop app
docker-compose down
# Restart
docker-compose restart
# See what's running
docker-compose ps
# Check file storage
ls -la data/
```
---
## Feature Overview
| Feature | Status | Notes |
|---|---|---|
| PDF Upload | β
| Up to 50MB |
| CSV Upload | β
| Auto-detected |
| TXT Upload | β
| Plain text |
| Knowledge Graph | β
| Auto-visualized |
| RAG Chat | β
| Uses Groq Mixtral |
| Real-time Updates | β
| Every 1.5s |
| Mobile UI | β
| Responsive |
| Multi-document | β
| Process in parallel |
| API Access | β
| JSON endpoints |
---
## API Quick Reference
```bash
# Upload file
curl -F "files=@document.pdf" http://localhost:7860/api/upload
# Get documents
curl http://localhost:7860/api/documents
# Query document
curl -X POST -H "Content-Type: application/json" \
-d '{"query":"What is...?","document":"doc.pdf"}' \
http://localhost:7860/api/query
# Delete document
curl -X DELETE http://localhost:7860/api/delete/doc.pdf
```
---
## Next Steps
1. β
App running locally? Perfect!
2. π€ Upload a test document
3. π View the knowledge graph
4. π¬ Try asking a question
5. π Deploy to production (HF Spaces)
---
## Need Help?
1. Check `README.md` for detailed docs
2. See `TESTING.md` for test cases
3. Review `space_config.md` for HF deployment
4. Check logs: `docker-compose logs -f`
---
**You're all set! π Start exploring!**
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