Replace nomic-embed-text (768-d) with bge-m3 (1024-d, GPU-served via the
same :11436 ollama) as cognee's embedding model, for better multilingual
recall. cognee's Qdrant collections held only P4 smoke-test fixtures (no
real conversation data — adolf-llm's cogneeSearch/cogneeAdd are still
stubs), so the stale 768-d collections were dropped and left for cognee
to recreate at 1024-d on next write, rather than migrated.
Verified: bge-m3 returns 1024-dim vectors via ollama /api/embed; after
recreating the cognee container, a remember/recall round trip (including
Russian text) produced correctly dimensioned (1024-d) Qdrant collections
and recalled the exact fact stored, then the test dataset was deleted.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LeqyaxJF2nbRXJtae2kNB2
Resolves the 4 P4 blockers and wires cognee/cognee-mcp into the openai
compose stack:
- qdrant: container was gone (data intact under /mnt/ssd/dbs/qdrant);
brought back up, confirmed healthy on :6333.
- Embeddings: switched from a dead LiteLLM route to ollama directly
(host.docker.internal:11436, nomic-embed-text, 768-dim), using cognee's
dedicated OllamaEmbeddingEngine and its native /api/embed endpoint.
Requires extra_hosts: host.docker.internal:host-gateway since ollama
lives in a separate compose project.
- cognee-llm kimi auth: root cause was that cognee-llm had never been
started, so its kimi-agent-home-equivalent volume didn't exist yet.
Seeded cognee-llm-home from the already-authed kimi-agent-home volume
(read-only copy of config/credentials/oauth/device_id); cognee-llm now
serves real completions.
- mkdir'd cognee data/system dirs: confirmed present (done by user).
Also fixed three issues found only during a live end-to-end smoke test:
- VECTOR_DB_PROVIDER must be a real container env var, not just present in
the mounted cognee.env — the qdrant adapter's sitecustomize.py
registration hook reads os.environ directly, which pydantic-settings'
env_file parsing never populates.
- Baked the Kuzu/Ladybug JSON extension into the cognee image. This
deployment's egress to extension.ladybugdb.com is bandwidth-throttled to
~1.2 KB/s, so cognee's own runtime auto-download reliably timed out,
leaving /health permanently unhealthy and graph queries failing. Fetched
the ~827KB extension out-of-band (16-way parallel ranged GETs) and added
it to the image via COPY.
- LLM_ENDPOINT needed an explicit /v1 suffix (litellm appends
"/chat/completions" verbatim) and LLM_INSTRUCTOR_MODE=json_mode is
required since cognee-llm's Kimi wrapper is a text-only pass-through with
no real tool-calling support.
Verified with a full remember -> recall round trip through cognee-mcp's
MCP tool surface: stored a fact containing a codeword, recalled it via
GRAPH_COMPLETION search, got the exact codeword back. Exercises cognee-llm,
ollama embeddings, Qdrant, and Kuzu together.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LeqyaxJF2nbRXJtae2kNB2
