Dynamic Context

Dynamic Context: Enhance Your AI Agent or Project Folder with Live Data

When creating an AI agent or setting up a project, Dynamic Context enables you to pull in real-time information from an API and integrate it into your agent's or project's system prompt. This feature is perfect for adding live data or leveraging Retrieval-Augmented Generation (RAG) from your own databases (e.g., vector store).

Use Cases:

• Integrate with a vector store: Use this feature to pull the most relevant content from your database and inject it into the AI's context, improving response accuracy and relevance.

• Dynamic content injection: Add up-to-date information like the latest newsletter, blog posts, or even social media updates (e.g., pulling in the last 10 tweets from your account).

How It Works:

For AI Agents:

1. Go to the AI Agents section and either create or edit an existing agent.

2. Set up Dynamic Context by connecting to your API for live data retrieval.

For Project Folders:

1. Create a new project folder.

2. Go to Project Settings and set up Dynamic Context to link to your API.

Process:

• Once set up, whenever the user interacts with the AI agent or starts a conversation in a project, the API will be called.

• The API’s response will be injected into the agent’s or project’s context and instructions, enhancing the AI's ability to provide more relevant and timely responses.

Dynamic Context vs. Knowledge Base:

Unlike a knowledge base, which requires the AI to perform a lookup to retrieve relevant information, Dynamic Context allows the AI to have instant access to live data without delay.

• Pros: Instant access to contextual information at all times.

• Cons: The context length will increase with the additional data.

Flexibility and Customization:

• Customize the request headers and body to include variables like chat ID, AI agent ID, and the last user message.

• Set up cache policies to avoid repeated API calls for every message.

• You can configure the Dynamic Context endpoint to point to a private server or any API you have access to.

Limitations:

• The API response is added directly to the system prompt, which can increase the context length. Ensure your API responses are concise.

• The maximum allowed API response length is 15% of the model’s token context limit. Responses exceeding this limit will be truncated.

• Recommended response formats: JSON (formatted, not minified) or Markdown.

Troubleshooting:

• macOS users: For security reasons, the API endpoint must be served over HTTPS. If you're using a local setup, consider using an SSL proxy to handle the request.

• CORS issues: Ensure your API endpoint allows requests from Trueseek's official web and app sources. You may need to specify allowed origins based on your platform (e.g., web app, macOS app, self-hosted version).

Available Variables:

These variables can be used in the request header or body and will be replaced dynamically when the API is called:

• {chatID}: Unique ID for the current chat.

• {characterID}: Unique ID for the AI agent the user is interacting with.

• {lastUserMessage}: The most recent message from the user.

• {userID}: (For Trueseek Custom) The ID of the currently logged-in user.