- search_tools block in litellm-config.yaml (SearXNG as a first-class
search_provider, standalone /v1/search endpoint, not a model tool) plus
extra_hosts on the litellm service so it can resolve search.home.
- New embedding-server (nomic-embed-text-v1.5 on a second llama.cpp
instance), pgvector-db, and litellm-pgvector services — LiteLLM's native
knowledgebase feature has no Qdrant backend, so this is the only
self-hosted path (docs/research/litellm-knowledgebase.md).
- vector_store_registry + local-embedding model entry in
litellm-config.yaml, wiring it together.
- scripts/ingest-memory.sh to load data/memory.md and
data/claude-legacy-memory.md into the knowledgebase.
- docs/memory-knowledgebase.md documenting the whole setup; data/
gitignored (personal memory content, not meant to be committed).
- New .env vars (SEARXNG_LAN_IP, PGVECTOR_DB_PASSWORD,
LITELLM_PGVECTOR_API_KEY, LITELLM_PGVECTOR_EMBEDDING_KEY,
EMBEDDING_MODEL_FILE) and generate-secrets.sh support for the
auto-generatable ones.
Resolves#22 and #23 (wayfinder map #21). Not yet verified on real
hardware — see #24.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
haylanandClaude-Bot
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