Odoo Technical Support Agent

An AI-powered voice assistant for Odoo technical support with screen sharing capabilities and MCP (Model Context Protocol) integration.

Features

• Voice Interaction: Natural voice conversations using LiveKit and OpenAI Realtime API
• Odoo Integration: Direct access to Odoo instance via XML-RPC
• MCP Support: Model Context Protocol for standardized AI tool interactions
• Screen Sharing: Visual troubleshooting capabilities
• Railway Ready: Optimized for easy deployment on Railway
• No Video Avatar: Lightweight voice-only interface

Capabilities

The agent can help with:

• Module installation, updates, and management
• User account creation and password resets
• Database queries and operations
• Error diagnosis and log analysis
• Configuration and troubleshooting
• Best practices and guidance

Architecture

technical-support-agent/
├── backend/
│   ├── agent/          # LiveKit voice agent
│   ├── api/            # FastAPI server
│   └── mcp/            # MCP server for Odoo
├── frontend/           # Next.js UI
└── docs/              # Documentation

Prerequisites

• Python 3.11+
• Node.js 20+
• pnpm (recommended) or npm
• LiveKit server (cloud or self-hosted)
• OpenAI API key
• Odoo instance (accessible via XML-RPC)

Quick Start

1. Clone the repository

git clone <your-repo-url>
cd technical-support-agent

2. Set up environment variables

cp .env.example .env

Edit .env with your credentials:

# LiveKit Configuration
LIVEKIT_URL=wss://your-livekit-server.livekit.cloud
LIVEKIT_API_KEY=your-api-key
LIVEKIT_API_SECRET=your-api-secret

# OpenAI Configuration
OPENAI_API_KEY=your-openai-api-key

# Odoo Configuration
ODOO_HOST=your-odoo-instance.com
ODOO_PORT=8069
ODOO_DB=your-database-name
ODOO_USERNAME=admin
ODOO_PASSWORD=your-admin-password

3. Run with Docker Compose

docker-compose up --build

The services will be available at:

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000

4. Run locally (development)

Backend:

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

# Start API server
python -m uvicorn api.main:app --reload --port 8000

# In another terminal, start the agent
python -m agent.agent

Frontend:

cd frontend
pnpm install
pnpm dev

Deploying to Railway

Option 1: Using Railway CLI

1. Install Railway CLI:

npm i -g @railway/cli

2. Login and initialize:

railway login
railway init

3. Create two services (backend and frontend):

Backend:

railway up --service backend

Frontend:

cd frontend
railway up --service frontend

4. Set environment variables in Railway dashboard for each service

Option 2: Using Railway Dashboard

1. Create a new project in Railway

2. Add services:

   • Backend Service:

     • Root directory: /backend
     • Build command: pip install -r requirements.txt
     • Start command: uvicorn api.main:app --host 0.0.0.0 --port $PORT

   • Agent Service:

     • Root directory: /backend
     • Build command: pip install -r requirements.txt
     • Start command: python -m agent.agent

   • Frontend Service:

     • Root directory: /frontend
     • Build command: pnpm install && pnpm build
     • Start command: pnpm start

3. Configure environment variables in each service

4. Deploy!

MCP Server Usage

The MCP server provides standardized tools for Odoo operations:

cd backend
python -m mcp.server

Available MCP tools:

• list_modules: List all Odoo modules
• get_module_info: Get module details
• list_users: List all users
• get_user_details: Get user information
• search_records: Search any Odoo model
• get_database_info: Get database info
• get_company_info: Get company details
• check_module_dependencies: Check module dependencies

Environment Variables

Backend

Variable	Description	Required
LIVEKIT_URL	LiveKit server WebSocket URL	Yes
LIVEKIT_API_KEY	LiveKit API key	Yes
LIVEKIT_API_SECRET	LiveKit API secret	Yes
OPENAI_API_KEY	OpenAI API key	Yes
ODOO_HOST	Odoo instance host	Yes
ODOO_PORT	Odoo instance port	Yes
ODOO_DB	Odoo database name	Yes
ODOO_USERNAME	Odoo admin username	Yes
ODOO_PASSWORD	Odoo admin password	Yes
ODOO_LOG_FILE	Path to Odoo log file	No
PORT	API server port	No (default: 8000)

Frontend

Variable	Description	Required
NEXT_PUBLIC_API_URL	Backend API URL	Yes
NEXT_PUBLIC_LIVEKIT_URL	LiveKit server URL	Yes

Development

Adding New Odoo Tools

1. Add the tool method in backend/agent/tools.py:

@llm.ai_callable(description="Your tool description")
async def your_tool(
    self,
    param: Annotated[str, llm.TypeInfo(description="Parameter description")]
) -> str:
    # Your implementation
    pass

2. Register it in backend/agent/agent.py:

tools=[
    # ... existing tools
    self.tools.your_tool,
]

Adding MCP Tools

1. Implement the method in backend/mcp/odoo_tools.py
2. Register it in backend/mcp/server.py in the list_tools() function
3. Handle the call in call_tool() function

Troubleshooting

Connection Issues

• Verify LiveKit credentials are correct
• Check that Odoo instance is accessible
• Ensure firewall allows WebSocket connections

Voice Not Working

• Check browser microphone permissions
• Verify OpenAI API key is valid
• Check LiveKit server status

Odoo Connection Failed

• Verify Odoo credentials
• Check network connectivity to Odoo instance
• Ensure Odoo XML-RPC is enabled

Security Considerations

• Never commit .env file with credentials
• Use Railway secrets for production credentials
• Implement rate limiting for API endpoints
• Use HTTPS/WSS in production
• Restrict Odoo user permissions to minimum required

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues and questions, please open an issue on GitHub.