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(Created page with "thumb|left|alt=Papa and Baby Hawk == Integrating Baby Hawk (Gemini 1.5) with Matrix Group Chat and TensorFlow in Docker == This tutorial will guide you through setting up a Gemini 1.5 API to interact in various Matrix rooms, while leveraging TensorFlow model running in a Docker container with Jupyter Notebook. === Prerequisites === * Running instance of Baby Hawk's Gemini 1.5 API on `ailounge.xyz` * TensorFlow instance running in Docker with J...")
 
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[[File:Papa-n-baby.jpg|thumb|left|alt=Papa and Baby Hawk]]
[[File:Papa-n-baby.jpg|thumb|left|alt=Papa and Baby Hawk]]


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


This tutorial will guide you through setting up a Gemini 1.5 API to interact in various Matrix rooms, while leveraging TensorFlow model running in a Docker container with Jupyter Notebook.
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 ===
== Prerequisites ==
* Running instance of Baby Hawk's Gemini 1.5 API on `ailounge.xyz`
* Running instance of Baby Hawk's Gemini 1.5 API on ailounge.xyz
* TensorFlow instance running in Docker with Jupyter Notebook
* TensorFlow instance running in Docker with Jupyter Notebook
* Matrix Synapse server running in Docker
* Matrix Synapse server running in Docker
* Basic knowledge of Docker, Python, Jupyter Notebooks, and Matrix
* 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 ===
== Step 1: Set Up Matrix Synapse Server using Docker ==
 
# '''Install Docker and Docker Compose:''' If not already installed, install Docker and Docker Compose.
1. **Install Docker and Docker Compose:** If you don't have them already, install Docker and Docker Compose.
# '''Create a Docker Compose File (docker-compose.yml):'''
2. **Create Docker Compose File (docker-compose.yml):**
<source lang="yaml">
 
```yaml
version: '3'
version: '3'
services:
services:
Line 30: Line 29:
       - 8008:8008
       - 8008:8008
       - 8448:8448
       - 8448:8448
      - 8009:8009
</source>
      - 8449:8449
# '''Run Docker Compose:'''
```
<source lang="bash">
 
3. **Run Docker Compose:**  Start the container:
 
```bash
docker-compose up -d
docker-compose up -d
```
</source>
 
# '''Register Admin User:''' Follow instructions in the container logs to register an admin user.
4. **Register Admin User:** Follow the instructions in the container logs to register an initial admin user.
 
=== Step 2: Prepare Baby Hawk's Gemini 1.5 API ===
 
Ensure that the API endpoint for Baby Hawk is publicly accessible (e.g., `https://ailounge.xyz/chat_with_baby_hawk`) and that any necessary authentication mechanisms are in place.
 
=== Step 3: Create and Configure the Matrix Bot (babyhawk_bot.py) ===
 
```python
from nio import AsyncClient, MatrixRoom, RoomMessageText
import requests
import asyncio
 
async def message_callback(room: MatrixRoom, event: RoomMessageText) -> None:
    if event.body.startswith("!babyhawk"):
        api_url = "https://ailounge.xyz/chat_with_baby_hawk"
        payload = {"message": event.body[9:]} 
 
        response = requests.post(api_url, json=payload)
        response.raise_for_status()
        message = response.json()["response"]
 
        await client.room_send(room.room_id, message_type="m.room.message", content={"msgtype": "m.text", "body": message})
 
async def main() -> None:
    client = AsyncClient("https://matrix.ailounge.xyz", "babyhawk_bot_user_id") # Replace with actual user ID
    await client.login("bot_password") 
 
    client.add_event_callback(message_callback, RoomMessageText)
 
    # Join Rooms
    public_room_id = "!public_room_id:matrix.ailounge.xyz" 
    family_room_id = "!family_room_id:matrix.ailounge.xyz"
    private_room_id = "!private_room_id:matrix.ailounge.xyz"
    await client.join(public_room_id)
    await client.join(family_room_id)
    await client.join(private_room_id)
 
    await client.sync_forever(timeout=30000)
 
# ... (rest of the code remains the same)
```
**Replace the placeholders with the actual room IDs.**
 
=== Step 4: Run the Bot and Invite to Room ===
 
1. **Start the Bot:** Run `python babyhawk_bot.py`.
2. **Create Rooms:** Create the three Matrix rooms (public, family, private).
3. **Invite the Bot:** Invite the bot user to each room.


=== Step 5: Implement Continuous Learning with TensorFlow in Docker ===
== Step 2: Secure Jupyter Notebook and Matrix Synapse with SSL Using Certbot ==
# '''Install Certbot:'''
<source lang="bash">
sudo apt install certbot
</source>
# '''Obtain Certificates:'''
<source lang="bash">
sudo certbot certonly --standalone -d ailounge.xyz -d matrix.ailounge.xyz
</source>
# '''Configure Jupyter to Use SSL:'''
Add SSL configuration to the Docker command for Jupyter:
<source lang="bash">
--NotebookApp.certfile=/etc/ssl/certs/jupyter.crt --NotebookApp.keyfile=/etc/ssl/private/jupyter.key
</source>
# '''Configure Matrix Synapse to Use SSL:'''
Update Synapse's configuration to use the obtained SSL certificates.


1. **Expose Ports:** Ensure your TensorFlow container exposes port 8888 (or the port your Jupyter Notebook is running on).
== Step 3: Configure and Run Baby Hawk's Gemini 1.5 API ==
2. **Install Libraries:** Install `matrix-nio` within the container.
Ensure the API endpoint for Baby Hawk is publicly accessible and secured with SSL.
3. **Access MongoDB:** Either mount the MongoDB data directory or use the connection string.
4. **Collect & Preprocess Data:**  Use Jupyter Notebook to collect and clean conversation data.
5. **Retrain Model:** Retrain your TensorFlow model in Jupyter Notebook.
6. **Update API:** Update your Baby Hawk API to use the newly trained model.


=== Step 6: DNS Configuration ===
== 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.


* Add an A record for `matrix.ailounge.xyz` to your server's IP address.
== Step 5: Create and Run a Matrix Bot for Integration ==
* Add an SRV record (optional):
Script a bot that uses Baby Hawk's API to interact within Matrix rooms.
  ```
  _matrix._tcp.matrix.ailounge.xyz. 86400 IN SRV 10 50 8448 matrix.ailounge.xyz.
  ```


=== Important Notes ===
== DNS Configuration ==
* Add A records for ailounge.xyz and matrix.ailounge.xyz.
* Configure necessary SRV records for Matrix services.


* **Container Networking:** Ensure the TensorFlow container can communicate with MongoDB and Matrix Synapse.
== Important Notes ==
* **Security:** Protect API credentials, bot password, and database access.
* Ensure proper networking between containers.
* **Experimentation:**  Feel free to experiment with different model architectures and training techniques.
* Protect sensitive data and credentials.
* Experiment with model training and architecture.


=== Credits ===
== Credits ==
This tutorial was created with the help of Google's Gemini Advanced AI ([https://gemini.google.com/](https://gemini.google.com/)).
This tutorial was collaboratively created by [Your Names], Google's Gemini Advanced AI, and ChatGPT from OpenAI.

Revision as of 17:02, 24 May 2024

Papa and 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.

Retrieved from "https://alt-web.xyz/wiki/index.php?title=Matrix/TensorFlow_for_Baby_Hawk&oldid=58"