AI-Memory

This project utilizes an Elasticsearch API and a GPT model to store and manage a chronological repository of information about specific topics, activities, and interactions. The GPT model functions as an extended memory system, or Retriever-Augmented Generator (RAG), to provide suggestions, manage tasks, and offer reminders.

Features

• Chronological Tracking: The model tracks the addition and modification of information, allowing it to understand the sequence of events or data entries.
• Information Retrieval: The model can efficiently retrieve information from Elasticsearch using queries that might involve specific dates, topics, or statuses.
• Decision Making: Based on retrieved data, the model generates reasoned responses that consider historical data.
• Assistant Capabilities: The model provides suggestions, manages tasks, and offers reminders.

Getting Started

This guide will help you set up and use the AI-Memory project.

1. Install Elasticsearch

To install Elasticsearch, follow the official Elasticsearch documentation. You can choose between a self-hosted solution (for free) or a cloud-managed one.

2. Create the Index

You need to create an index with the prefix index-ai-memory- and a suffix that you can set in the configuration file under the AI_MEMORY_ELASTIC_SEARCH_WRITE_INDEX_SUFFIX variable. This can be done via the Elasticsearch CLI or Kibana.

Example using Elasticsearch CLI:

curl -X PUT "localhost:9200/index-ai-memory-your_suffix?pretty"

3. Create an API Key

You need to create an API key for your Elasticsearch index. This can be done via the Elasticsearch CLI or Kibana.

Example using Elasticsearch CLI:

curl -X POST "localhost:9200/_security/api_key?pretty" -H 'Content-Type: application/json' -d'
{
  "name": "ai-memory-key",
  "role_descriptors": {
    "ai_memory_role": {
      "cluster": ["all"],
      "index": [
        {
          "names": ["index-ai-memory-*"],
          "privileges": ["all"]
        }
      ]
    }
  }
}
'

4. Configure Environment Variables

Create the conf folder and copy the gpt-values-override-conf.dist.sh file inside. Rename the copied file replacing .dist. with the ID you want. Set the needed values in the new file.

Example:

cp gpt-values-override-conf.dist.sh conf/gpt-values-override-conf.myid.sh

Edit gpt-values-override-conf.myid.sh and set your values

5. Generate Files

Run the generate-files.sh script. This will generate the necessary YAML and Markdown files for the GPT Builder. The script also checks if the environment files are not in sync with the dist file.

bash generate-files.sh

6. Use GPT Builder

Once the files have been generated under the /out folder, go to ChatGPT (a Plus subscription is needed) and use the GPT Builder. Fill the "instructions" box with the content of the generated gpt-instructions.md file and create a new action with the content of the generated gpt-schema.yml file.

7. Set API Key for the Action

Set the API key for the action using the one generated from Elasticsearch. It's important to

select

the Authentication type: ApiKey. The API key box should contain the value ApiKey <yourapikey> (the prefix ApiKey is fundamental) and the Auth should be set to Custom with the value Authorization

Using the GPT

Once everything is ready, you can use the created GPT by asking it to store or read from its memory.

Examples of Requests

• Store Information:

  Store the following information: "Meeting with John on Monday at 10 AM."

• Retrieve Information:

  What meetings do I have scheduled for Monday?

• Personal Information:

  What is my name?

• Extra Personal Information:

  What languages do I speak?

Components

• Elasticsearch API: The API is used to store and manage data.
• GPT Model: The model is used to generate responses and provide suggestions, and can be interacted with using natural language inputs.

License

This project is licensed under the MIT license.