Python Agent Chatbot Server

This server implements an LLM-powered agentic chatbot with tool calls, context, and Discord/MongoDB integration. It uses Flask for the API, Celery for background tasks, Redis as the broker, and MongoDB for storage.

Features

• Flask: REST API backend
• Celery: Async tool calls
• Redis: Celery broker/result backend
• MongoDB: Candidate profile and tool call storage
• Discord: Send/receive messages via bot
• LLM Tool Calls: Agent can trigger tools in background

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Local Development Setup

1. Clone and Prepare

cd pythonserver
python3 -m venv .venv
source .venv/bin/activate

2. Install Dependencies

pip install -r requirements.txt

If requirements.txt is missing, install at least:

pip install flask celery redis pymongo openai discord.py

3. Start Local Services

• Redis:

  • Install via Homebrew: brew install redis
  • Start: redis-server

• MongoDB:

  • Install via Homebrew: brew tap mongodb/brew && brew install mongodb-community
  • Start: brew services start mongodb-community

4. Configure Environment Variables

Create a .env file or export these variables:

OPENAI_API_KEY=your-openai-key
DISCORD_TOKEN=your-discord-bot-token
DISCORD_CHANNEL_ID=your-discord-channel-id
MONGO_URI=mongodb://localhost:27017/
CELERY_BROKER_URL=redis://localhost:6379/0
CELERY_RESULT_BACKEND=redis://localhost:6379/0

5. Run the Flask Server

python app.py

6. Run the Celery Worker (in a new terminal, same venv)

celery -A celery_worker.celery_app worker --loglevel=info

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Endpoints

• /chat : Main chat endpoint for agentic conversation and tool calls.
• /health : Health check.

Troubleshooting

• Celery not connecting? Make sure Redis is running and env vars are correct.
• MongoDB errors? Ensure MongoDB is running and accessible.
• Discord issues? Make sure your bot token is correct and the bot is invited to the right server/channel.
• Async errors? All tool calls are now sync-compatible.

Customization

• Edit mongo_tool.py for MongoDB logic.
• Edit discord_tool.py for Discord bot logic.
• Edit app.py for API and agent orchestration.

Datadog RUM Integration

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  })(window,document,'script','https://www.datadoghq-browser-agent.com/us5/v6/datadog-rum.js','DD_RUM');
  window.DD_RUM.onReady(function(){
    window.DD_RUM.init({
      clientToken: 'YOUR_CLIENT_TOKEN',
      applicationId: 'YOUR_APPLICATION_ID',
      site: 'us5.datadoghq.com',
      service: 'mygithubsite',
      env: 'prod',
      sessionSampleRate: 100,
      sessionReplaySampleRate: 20,
      defaultPrivacyLevel: 'mask-user-input',
    });
  });
</script>

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