EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Sep 7·5 min read
Show HN: Engrim – A universal, local-first SQLite memory engine for AI CLIs
TL;DR
Engrim is a local-first SQLite memory engine designed for AI command-line interfaces, enabling seamless switching between models without losing project context. It addresses attention dilution by providing a curated episodic memory of 4,000 characters.
✦ Why It Matters
Start using Engrim to maintain project context and reduce costs associated with AI model interactions today.
Key Takeaways
- Implement Engrim to manage memory across multiple AI models.
- Utilize the /clear command to refresh session context without losing data.
- Capture decisions in real-time using engrim add for better project tracking.
- Run engrim setup to configure your environment automatically.
How It Works
Engrim operates by storing project-specific memories in a local SQLite database, allowing for quick retrieval and management of decisions, constraints, and project state. It employs a hybrid retrieval system that combines keyword search with vector embeddings, ensuring efficient access to relevant memories while minimizing latency.