feat: Add Weaviate vector backend#236
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- PRD: Programmable Memory & Learning Layer - DocType designs: Memory Record, Policy, Profile - Tech specs: Capture/Retrieval, Storage Architecture - Profiles: Travel Planning, Programming, Documentation - Implementation plan and project tracking
Implement WeaviateBackend with the following features: - Self-hosted (Docker) and Weaviate Cloud support - Hybrid search (vector + BM25 keyword search) - Schema auto-creation and management - Full CRUD operations with metadata filtering - Health check and statistics Includes: - weaviate_backend.py: Main backend implementation - factory.py: BackendFactory for registration and caching - test_weaviate_backend.py: Comprehensive test suite Refs: kimi/vector-store-weaviate-backend
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Summary
Adds Weaviate vector backend using LlamaIndex adapter.
Implementation
Files
Dependencies
Optional: llama-index-vector-stores-weaviate
Related
Tier 1 backend for SaaS builders needing hybrid search.