Integrate LocalRecall with Graphiti for Advanced AI Agent Workflows

[localai-bot]

Feature Request: Integrate LocalRecall with Graphiti

Description

LocalRecall is a lightweight, offline vector database for managing knowledge bases and files, while Graphiti is a framework for building temporally-aware knowledge graphs. Integrating these two systems could enable advanced AI agent workflows that combine local knowledge management with dynamic, time-sensitive graph-based reasoning.

Use Cases

• AI Agent Memory: Enable agents to store and retrieve context from LocalRecall while leveraging Graphiti's temporal graph queries for state-aware decisions.
• Hybrid Knowledge Management: Combine vector-based retrieval (LocalRecall) with graph-based reasoning (Graphiti) for more robust RAG pipelines.
• Enterprise Data Integration: Allow enterprises to use LocalRecall for secure, local data storage and Graphiti for querying time-sensitive information without exposing data to the cloud.

Additional Context

• LocalRecall focuses on offline, privacy-first knowledge management.
• Graphiti provides a bi-temporal data model for tracking events and their ingestion times, enabling precise historical queries.
• The integration could involve sharing data formats, API endpoints, or shared ontologies between the two systems.

Acceptance Criteria

• A proof-of-concept integration between LocalRecall and Graphiti.
• Documentation on how to use the integrated systems together.
• Example workflows demonstrating the combined capabilities.
• Community feedback and testing from users of both projects.