Matrix/TensorFlow for Baby Hawk

Integrating Baby Hawk (Gemini 1.5) with Matrix Group Chat and TensorFlow in Docker

This tutorial guides you through integrating a Gemini 1.5 API to interact in various Matrix rooms, leveraging a TensorFlow model running in a Docker container equipped with Jupyter Notebook, and securing communications using SSL.

Prerequisites

• Running instance of Baby Hawk's Gemini 1.5 API on ailounge.xyz
• TensorFlow instance running in Docker with Jupyter Notebook
• Matrix Synapse server running in Docker
• Basic knowledge of Docker, Python, Jupyter Notebooks, and Matrix
• Domain names set up for matrix.ailounge.xyz and Jupyter accessed via ailounge.xyz

Step 1: Set Up Matrix Synapse Server using Docker

1. Install Docker and Docker Compose: If not already installed, install Docker and Docker Compose.
2. Create a Docker Compose File (docker-compose.yml):

version: '3'
services:
  synapse:
    image: matrixdotorg/synapse:latest
    restart: always
    environment:
      - SYNAPSE_SERVER_NAME=matrix.ailounge.xyz
      - SYNAPSE_REPORT_STATS=yes  
    volumes:
      - ./data:/data 
    ports:
      - 8008:8008
      - 8448:8448

1. Run Docker Compose:

docker-compose up -d

1. Register Admin User: Follow instructions in the container logs to register an admin user.

Step 2: Secure Jupyter Notebook and Matrix Synapse with SSL Using Certbot

1. Install Certbot:

sudo apt install certbot

1. Obtain Certificates:

sudo certbot certonly --standalone -d ailounge.xyz -d matrix.ailounge.xyz

1. Configure Jupyter to Use SSL:

Add SSL configuration to the Docker command for Jupyter:

--NotebookApp.certfile=/etc/ssl/certs/jupyter.crt --NotebookApp.keyfile=/etc/ssl/private/jupyter.key

1. Configure Matrix Synapse to Use SSL:

Update Synapse's configuration to use the obtained SSL certificates.

Step 3: Configure and Run Baby Hawk's Gemini 1.5 API

Ensure the API endpoint for Baby Hawk is publicly accessible and secured with SSL.

Step 4: Implement Continuous Learning with TensorFlow in Docker

1. Expose Ports: Ensure the TensorFlow container exposes port 8888.
2. Install Libraries: Within the container, install libraries needed for integration, e.g., matrix-nio.
3. Access MongoDB: Configure access to MongoDB for data storage.
4. Collect & Preprocess Data: Use Jupyter Notebook for data handling.
5. Retrain Model: Continuously retrain the TensorFlow model based on new data.
6. Update API: Update the Baby Hawk API to utilize the retrained models.

Step 5: Create and Run a Matrix Bot for Integration

Script a bot that uses Baby Hawk's API to interact within Matrix rooms.

DNS Configuration

• Add A records for ailounge.xyz and matrix.ailounge.xyz.
• Configure necessary SRV records for Matrix services.

Important Notes

• Ensure proper networking between containers.
• Protect sensitive data and credentials.
• Experiment with model training and architecture.

Credits

This tutorial was collaboratively created by [Your Names], Google's Gemini Advanced AI, and ChatGPT from OpenAI.