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[[File:Papa-n-baby.jpg| | [[File:Papa-n-baby.jpg|450px|left|alt=Papa and Baby Hawk]] | ||
= Integrating Baby Hawk (Gemini 1.5) with Matrix Group Chat, TensorFlow in Docker, and PostgreSQL = | = Integrating Baby Hawk (Gemini 1.5) with Matrix Group Chat, TensorFlow in Docker, and PostgreSQL = |
Revision as of 19:26, 24 May 2024
Integrating Baby Hawk (Gemini 1.5) with Matrix Group Chat, TensorFlow in Docker, and PostgreSQL
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, with the addition of a PostgreSQL database.
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
- PostgreSQL database running in Docker
- Basic knowledge of Docker, Python, Jupyter Notebooks, PostgreSQL, 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
- Install Docker and Docker Compose: If not already installed, install Docker and Docker Compose.
- Create a Docker Compose File (docker-compose.yml):
version: '3'
services:
postgres:
image: postgres:latest
restart: always
environment:
POSTGRES_DB: matrix_synapse
POSTGRES_USER: matrix_user
POSTGRES_PASSWORD: your_secure_password
volumes:
- ./postgres-data:/var/lib/postgresql/data
ports:
- "5432:5432"
synapse:
image: matrixdotorg/synapse:latest
restart: always
environment:
- SYNAPSE_SERVER_NAME=matrix.ailounge.xyz
- SYNAPSE_REPORT_STATS=yes
- SYNAPSE_DATABASE_CONFIG=postgres://matrix_user:your_secure_password@postgres/matrix_synapse
depends_on:
- postgres
volumes:
- ./data:/data
ports:
- 8008:8008
- 8448:8448
- Run Docker Compose:
docker-compose up -d
- 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
- Install Certbot:
sudo apt install certbot
- Obtain Certificates:
sudo certbot certonly --standalone -d ailounge.xyz -d matrix.ailounge.xyz
- 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
- 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
- Expose Ports: Ensure the TensorFlow container exposes port 8888.
- Install Libraries: Within the container, install libraries needed for integration, e.g., `matrix-nio`.
- Access MongoDB: Configure access to MongoDB for data storage.
- Collect & Preprocess Data: Use Jupyter Notebook for data handling.
- Retrain Model: Continuously retrain the TensorFlow model based on new data.
- 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 Papa and Baby Hawk, Google's Gemini Advanced, and ChatGPT-4 from OpenAI.