Setting Up Ollama with AWS RDS: The Ultimate Guide to Running Your Own LLM

What is Ollama?

Why Choose AWS RDS?

Prerequisites

• An active AWS account. If you don’t have one, sign up for AWS.
• Basic knowledge of AWS Console.
• Familiarity with databases, specifically PostgreSQL, would be helpful!

Step 1: Launching PostgreSQL on AWS RDS

1. Sign into your AWS Console and go to the RDS service.
2. Click on Create database.
3. Select Standard Create and choose PostgreSQL as your engine.
4. Choose the version of PostgreSQL to use.
5. Choose a DB instance class based on your performance requirements. A general-purpose class will typically suffice for development.
6. Set up your storage preferences. Here, you can choose between General Purpose or Provisioned IOPS storage.
7. Configure DB instance identifier, Master username, and Master password. Remember these credentials, as you will use them to connect to your database.
8. Adjust VPC security groups to allow traffic on the relevant ports. You might want to set this to allow connections from your application server’s IP.
9. Review your settings, and click on Create database. You’ll need to wait a few minutes for AWS to launch your database instance.

Step 2: Configuration for Ollama

1. Download Ollama via the official Ollama website. This will give you the CLI tool needed to run your models.
2. After installing Ollama, ensure it can access your PostgreSQL database by configuring it properly. You'll need to provide connection details, including hostname, port, database name, username, and password.
   1 2 bash ollama db --hostname <your-db-instance-endpoint> --port 5432 --dbname <your-db-name> --username <your-username> --password <your-password>
3. You may need to modify your pg_hba.conf file (if you’re using a custom setup) on your database to allow the Ollama server to access the database properly. This file controls client authentication, and you should ensure it allows your network’s IP addresses.

Step 3: Pulling and Running Models

1. Use the Ollama CLI to pull a model. For example, if you want to pull the Llama model, you can run:
   1 2 bash ollama pull llama2
2. After the model has been downloaded, you can run it:
   1 2 bash ollama run llama2
3. To utilize the database for training or inference, you must configure Ollama to connect to your RDS instance during these operations.

Step 4: Integrating Ollama with AWS RDS

• Implementing SQL Queries: Use Ollama's extensive capabilities to run SQL queries directly within your application to fetch or update records based on your LLM tasks.
• Embedding Data Creation: Ollama can embed data from RDS into its models for training purposes. Suppose you have customer queries that you'd like to train your model on, you could create embeddings using Ollama and save them to your RDS instance.

Step 5: Leveraging Arsturn for Enhanced Engagement

Step 6: Testing Your Setup

1. Use tools like Postman or simply curl to send requests from your application to the Ollama models and check if they're responding accurately.
2. Review the logs in your RDS instance to ensure that it’s handling queries properly and not hitting any resource limits.
3. Evaluate the model outputs to refine the training process if needed. Refine prompts, tweak model parameters, and iterate based on your evaluations.

Conclusion