Merge pull request opea-project#56 from cld2labs/cld2labs/MultiAgentQnA

cld2labs/MultiAgentQnA

Author: psurabh

sample_solutions/MultiAgentQnA/.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+env/
+venv/
+ENV/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+*.log
+
+# Node
+node_modules/
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+.pnpm-debug.log*
+package-lock.json
+dist/
+.cache/
+
+# Environment
+.env
+.env.local
+.env.*.local
+
+# IDEs
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Build
+build/
+*.so
+
+# Testing
+.coverage
+.pytest_cache/
+htmlcov/
+
+# Application specific
+rag_index/
+

sample_solutions/MultiAgentQnA/QUICKSTART.md

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+# Quick Start Guide
+
+Get up and running with the Multi-Agent Q&A application in 5 minutes!
+
+## Prerequisites
+
+- Docker and Docker Compose installed
+- Valid enterprise-inference API credentials
+
+## Step-by-Step Setup
+
+### 1. Configure Environment Variables
+
+Create the API environment file:
+
+```bash
+cd MultiAgentQnA
+cp api/env.example api/.env
+```
+
+Edit `api/.env` with your credentials:
+
+```env
+BASE_URL=https://your-enterprise-inference-url.com
+KEYCLOAK_CLIENT_ID=your_client_id
+KEYCLOAK_CLIENT_SECRET=your_client_secret
+EMBEDDING_MODEL_ENDPOINT=bge-base-en-v1.5
+INFERENCE_MODEL_ENDPOINT=Llama-3.1-8B-Instruct
+EMBEDDING_MODEL_NAME=bge-base-en-v1.5
+INFERENCE_MODEL_NAME=meta-llama/Llama-3.1-8B-Instruct
+```
+
+### 2. Start with Docker Compose
+
+```bash
+cd MultiAgentQnA
+docker-compose up --build
+```
+
+Wait for both services to start:
+- Backend API on http://localhost:5001
+- Frontend UI on http://localhost:3000
+
+### 3. Access the Application
+
+Open your browser and navigate to:
+
+```
+http://localhost:3000
+```
+
+You should see the Multi-Agent Q&A interface!
+
+## Alternative: Local Development
+
+### Backend
+
+```bash
+cd MultiAgentQnA/api
+
+# Create virtual environment (recommended)
+python -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+
+# Install dependencies
+pip install -r requirements.txt
+
+# Run the server
+uvicorn server:app --reload --host 0.0.0.0 --port 5001
+```
+
+### Frontend
+
+```bash
+cd MultiAgentQnA/ui
+
+# Install dependencies
+npm install
+
+# Run development server
+npm run dev
+```
+
+## Testing the Application
+
+### Test the Chat Interface
+
+1. Navigate to the Chat page
+2. Type a question, for example:
+   - **Code**: "How do I create a Python function?"
+   - **RAG**: "Find information about machine learning"
+   - **General**: "What is the weather like?"
+
+3. The system will automatically route your question to the appropriate agent
+
+### Test the Settings
+
+1. Click on "Settings" in the header
+2. Modify agent configurations:
+   - Change roles, goals, or backstories
+   - Adjust max iterations
+   - Toggle verbose mode
+3. Click "Save Configuration"
+4. Test with new questions
+
+## Verify Everything Works
+
+### Check API Health
+
+```bash
+curl http://localhost:5001/health
+```
+
+Expected response:
+```json
+{
+  "status": "healthy",
+  "api_configured": true
+}
+```
+
+### Test Chat Endpoint
+
+```bash
+curl -X POST http://localhost:5001/chat \
+  -H "Content-Type: application/json" \
+  -d '{"message": "Hello!"}'
+```
+
+Expected response:
+```json
+{
+  "response": "Response from agent...",
+  "agent": "normal_agent"
+}
+```
+
+## Common First-Time Issues
+
+### Port Already in Use
+
+**Error**: `Address already in use`
+
+**Solution**:
+```bash
+# Find and kill process on port 5001
+lsof -ti:5001 | xargs kill -9
+
+# Find and kill process on port 3000
+lsof -ti:3000 | xargs kill -9
+
+# Or change ports in docker-compose.yml
+```
+
+### Cannot Connect to Enterprise API
+
+**Error**: `Authentication failed`
+
+**Solution**:
+1. Double-check your `.env` credentials
+2. Verify BASE_URL is correct
+3. Ensure network access to enterprise-inference API
+
+### UI Shows "Failed to get response"
+
+**Solution**:
+1. Check backend logs: `docker logs multiagent-qna-backend`
+2. Verify API is running: `curl http://localhost:5001/health`
+3. Check browser console for errors
+
+## Next Steps
+
+- Read the [README.md](README.md) for detailed documentation
+- Check [TROUBLESHOOTING.md](TROUBLESHOOTING.md) for more help
+- Customize agent configurations in the Settings page
+- Integrate with your own knowledge bases or APIs
+
+## Architecture Overview
+
+```
+User Query
+    ↓
+Orchestration Agent (routes to appropriate specialist)
+    ↓
+┌─────────────────────────────────────────┐
+│                                         │
+├─ Code Agent ─── For programming Q&A     │
+├─ RAG Agent ──── For document retrieval  │
+└─ Normal Agent ── For general questions  │
+```
+
+The system automatically detects query type and routes to the best agent!
+
+## Need Help?
+
+- Check logs: `docker logs multiagent-qna-backend`
+- Review [TROUBLESHOOTING.md](TROUBLESHOOTING.md)
+- Verify environment variables are set correctly
+
+Happy chatting! 🚀
+