jkanalakis/deep-recall

Enterprise-grade memory framework for LLMs featuring GPU-optimized inference, vector storage, and automated scaling. Enables hyper-personalized responses through efficient context retrieval and integration.

33
/ 100
Emerging

Builds on PostgreSQL with pgvector for vector storage and supports pluggable backends (FAISS, Qdrant, Milvus, Chroma) for semantic search across user interaction history. Uses a three-tier microservices architecture—Memory Service for embeddings/retrieval, Inference Service for GPU-optimized LLM inference, and an Orchestrator API gateway—deployed via Docker Compose with Kubernetes support. Includes privacy-first APIs for viewing, updating, or deleting user memories, plus comprehensive monitoring and test suites across unit, integration, and API layers.

No commits in the last 6 months.

No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 9 / 25
Maturity 7 / 25
Community 15 / 25

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Stars

90

Forks

12

Language

Python

License

Last pushed

May 03, 2025

Commits (30d)

0

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