Getting Started

This guide will help you set up and run the generative AI agent project.

Prerequisites

• Python 3.10+: Install Python
• Git: Install Git
• Docker (optional): Install Docker
• Access to flexo

Quick Setup

1. Fork and clone the repository:

   # First, fork the repository on GitHub by clicking the 'Fork' button
   # Then clone your fork:
   git clone https://github.com/YOUR_USERNAME/flexo.git
   cd flexo
   

2. Create Python environment:

   # Mac/Linux
   python3 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt
   
   # Windows
   python -m venv venv
   .\venv\Scripts\activate
   pip install -r requirements.txt
   

3. Configure the project:

4. Copy .env.example to .env and update with your settings

5. Review src/configs/agent.yaml for agent configuration

6. Start the API server:

   uvicorn src.main:app --reload --host 127.0.0.1 --port 8000
   

7. Test the API using one of these methods:

A. Using cURL:

curl -X POST http://127.0.0.1:8000/v1/chat/completions \
    -H "Content-Type: application/json" \
    -d '{
          "messages": [
            {
              "role": "user",
              "content": [
                { "text": "Hello, AI!" }
              ]
            }
          ],
          "context": {
            "values": [
              { "key": "session_id", "value": "abc123" }
            ]
          },
          "include_status_updates": false,
          "stream": true
        }'

Note: Include an -H "X-API-Key: your-flexo-api-key" header when ENABLE_API_KEY=true

B. Using the Streamlit testing interface:

# Navigate to the tests directory
cd tests

# Run the Streamlit app
streamlit run test_streamlit_app.py

# This will open a browser window at http://localhost:8501 where you can interact with the agent

Docker Deployment (Optional)

# Build the container
docker build -t flexo-agent .

# Run the container
docker run -p 8000:8000 --env-file .env flexo-agent

Next Steps

• Explore configuration options in the Agent Configuration Guide
• Learn about deployment in the Deployment Guide
• Customize the agent's behavior and extend its functionality

Testing Tips

• The Streamlit interface provides a more user-friendly way to test the agent's capabilities
• The Streamlit app is looking for your local agent instance running on port 8000
• For debugging, check both the API server logs and the Streamlit app logs

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