Zep is a powerful memory layer for AI applications, allowing for effective management of conversational context and user sessions. With Relevance AI, your AI agents gain enhanced memory capabilities, making them more adept at navigating complex conversations and tasks.
Zep empowers AI agents with persistent memory management and session-based context handling. Relevance AI amplifies these capabilities, enabling intelligent interactions that adapt and learn over time.
Contextual Intelligence
Seamlessly retains and recalls past interactions to deliver more meaningful and personalized responses
Knowledge Orchestration
Efficiently organizes and retrieves relevant information across multiple conversations and data sources
Semantic Mastery
Leverages advanced vector search to understand and connect related concepts across conversations
Relevance AI enhances your workflows by integrating seamlessly with Zep, providing a robust memory layer for AI agents.
What you’ll need
You don't need to be a developer to set up this integration. Follow this simple guide to get started:
- A Relevance AI account
- An Airtable account with access to the base and table you'd like to use
- Authorization (you'll connect securely using OAuth—no sensitive info stored manually)
Security & Reliability
The Zep and Relevance AI integration provides a robust memory layer for AI applications, allowing for effective management of conversational context, user sessions, and memory persistence. This integration empowers your AI agents with long-term memory capabilities, enhancing their ability to handle complex conversations and tasks.
Key benefits include persistent memory management for AI conversations, session-based context handling, user management and metadata tracking, and flexible memory retrieval and context maintenance.
To get started, ensure you have the necessary accounts and credentials, including a Zep account with API access, a Relevance AI account, and OAuth credentials with `pipedream-zep-read-write` permissions. Your system should meet the requirements of Node.js 12.x or higher, HTTPS support for API calls, and sufficient storage for session data.
Begin by configuring OAuth authentication and initializing the base URL for API calls. You can create new users and sessions, and add memory to sessions using structured API requests. For example, creating a new user involves specifying the user ID, email, and metadata, while creating a session requires a unique session ID and associated user ID.
Common issues may arise, such as authentication errors or session creation failures. Solutions include verifying OAuth credentials, ensuring unique session IDs, and checking message formats when adding memory. Best practices suggest managing sessions uniquely, structuring messages appropriately, and optimizing performance through batch operations and error handling.
Be mindful of API rate limits and quotas based on your Zep account tier, and refer to the Zep documentation for additional support and detailed API information.
No training on your data
Your data remains private and is never utilized for model training purposes.
Security first
We never store anything we don’t need to. The inputs or outputs of your tools are never stored.
To get the most out of the Zep + Relevance AI integration without writing code:
- Start with a clear user and session structure: Use unique user IDs and session IDs to maintain organization and avoid conflicts.
- Leverage metadata: Include relevant metadata for users and sessions to enhance context tracking and improve conversation handling.
- Test your memory additions: Validate message formats and ensure sessions are active before adding memory to avoid errors.
- Monitor session activity: Regularly check for inactive sessions and close them properly to maintain optimal performance.
- Optimize for performance: Batch message additions when possible and implement error handling to manage API rate limits effectively.
