What is PocketPaw's new semantic memory?

Hybrid setup: vectors for similarity search, graphs for entity links. Ditches flat files for smarter recall.

How do I enable vector memory in PocketPaw?

Set `POCKETPAW_MEMORY_BACKEND=vector` and pick store like `chromadb`. Falls back to files if needed.

Does PocketPaw's graph use external services?

Nope—local-first with Ollama embeddings, SQLite/NetworkX. No cloud unless you opt in.

PocketPaw Swaps Dumb Text Files for a Brain That Actually Connects Dots

PocketPaw's agents used to forget everything without exact keywords. Now, with vectors and graphs, they link 'Project X uses React' to breaking changes—finally acting like they have a memory.

theAIcatchup Apr 10, 2026 3 min read

Diagram showing PocketPaw's ingest and retrieval pipelines with vectors and graph DB

⚡ Key Takeaways

PocketPaw upgrades from lexical file dumps to vector+graph memory for semantic, relational recall. 𝕏
Local-first design with fallbacks keeps it reliable and private. 𝕏
Graphs fix vector limits, enabling queries like 'Python projects'—but watch for LLM extraction noise. 𝕏

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theAIcatchup

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#PocketPaw #knowledge graph #semantic memory #vector database

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Originally reported by dev.to

⚡ Key Takeaways

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theAIcatchup

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