alvis
b27d31b3ca
docker-compose.yml gains healthchecks and depends_on/condition chains for the litellm/langfuse/postgres tier so dependants wait for a genuinely ready service instead of a started container. Also plumbs AGAP_MCP_TOKEN into the adolf and adolf-llm containers, sourced from openai/.env (gitignored), for the kb#180 bearer auth on the agap MCP server; shared-mcp.json consumes it via bearerTokenEnvVar so the Kimi backbone authenticates too. agent-registry.yaml / agent_registry.py: the version-controlled source of truth for agent identities and trust classes -- the same ids the agap-mcp token map resolves to (`adolf`, `claude-coder`; note `claude-code-cli` is the runtime entry, not an agent identity). model-registry.yaml, litellm-config.yaml, auto-router-routes.json and provision_litellm_keys.py: model tiering, virtual-key provisioning and auto-router routes. tei-reranker/ is the local reranker service backing Hindsight recall. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
63 lines
3.3 KiB
Markdown
63 lines
3.3 KiB
Markdown
# cognee-llm (:8011)
|
|
|
|
> ⚠️ **SUPERSEDED — Adolf's memory is migrating Cognee → Hindsight (2026-07-13).**
|
|
> Hindsight runs its LLM on LiteLLM `:4000` / Ollama, so this bespoke Kimi-CLI
|
|
> wrapper is being **retired**, not ported (SPIKE gate 5 already concluded the
|
|
> extraction workload shouldn't sit on the Kimi seat). This service is decommissioned
|
|
> in migration task **H4**. Plan: `agap_git/adolf/HINDSIGHT-MIGRATION.md`. The doc
|
|
> below describes the outgoing Cognee stack, kept until H4 lands.
|
|
|
|
OpenAI-compatible wrapper around the Kimi Code CLI (`@moonshot-ai/kimi-code`, home
|
|
`/root/.kimi-code`), built for Cognee's batch/structured LLM calls. **Opposite policy to
|
|
`kimi-agent`**:
|
|
|
|
- **Stateless one-shot** — fresh temp dir under `/workspace/<uuid>` per request, `kimi -p
|
|
<prompt> --output-format stream-json`, **no `-r`/`-S` resume**, dir removed after every call
|
|
(success or failure).
|
|
- **Non-streaming** — always returns a full `chat.completion` body, even if the caller sets
|
|
`stream: true`.
|
|
- **No media, no MCP** — text-only prompt built from `messages`; no image persistence, no
|
|
`.mcp.json`.
|
|
- **Structured/low-temperature intent via prompt, not a sampling param** — the CLI has no raw
|
|
temperature knob (it's an agent loop, not a completions API), so determinism/JSON-only output
|
|
is enforced with an instruction preamble prepended to the caller's system prompt.
|
|
- **Bounded concurrency** — `MAX_CONCURRENCY = 3` in `server.js`, queued beyond that.
|
|
|
|
Endpoints: `GET /v1/models` (model id `cognee-llm`), `POST /v1/chat/completions`.
|
|
|
|
Own disposable in-container `/workspace` (no host bind mount — nothing here is meant to
|
|
survive a request, let alone a container restart) + own `cognee-llm-home` volume
|
|
(`/root/.kimi-code`), same Kimi subscription as `kimi-agent`/`adolf-llm`, separate volume so
|
|
each wrapper's CLI state stays isolated.
|
|
|
|
## This IS Cognee's LLM backbone
|
|
|
|
By design, Cognee's LLM runs on the flat Kimi subscription through this wrapper — the whole
|
|
reason it exists — mirroring how `adolf-llm` backs the assistant. P4 wires cognee's
|
|
`LLM_ENDPOINT` → `http://cognee-llm:8011`, `LLM_MODEL` → `openai/cognee-llm`.
|
|
|
|
**Accepted tradeoff (SPIKE-FINDINGS gate 5).** The CLI's JSON output is clean/schema-conformant,
|
|
but it's slower than a raw API: ~5s fixed per-invocation floor + ~22-24s for a realistic
|
|
structured-extraction call, and every call is agentic. Cognify issues one call per
|
|
chunk/entity-extraction step, so large batches serialize into minutes. To protect the
|
|
single-seat subscription, `MAX_CONCURRENCY = 3` bounds concurrent spawns.
|
|
|
|
**Documented fallback (not the default):** if cognify throughput ever becomes a real problem,
|
|
route cognee's LLM to a LiteLLM model instead (`ARCHITECTURE.md` §3.3) — see the commented block
|
|
in `cognee/cognee.env`. Embeddings already run on LiteLLM's `nomic-embed` regardless (embeddings
|
|
can't go through the agentic CLI).
|
|
|
|
## Smoke test
|
|
|
|
```bash
|
|
cd /home/alvis/agap_git/openai
|
|
docker build -t cognee-llm:local ./cognee-llm
|
|
docker run --rm -d --name cognee-llm-smoke -p 18011:8011 cognee-llm:local
|
|
curl -s http://localhost:18011/v1/models
|
|
docker rm -f cognee-llm-smoke
|
|
```
|
|
|
|
A full `/v1/chat/completions` round-trip needs a `kimi login`-authed
|
|
`/root/.kimi-code` volume (shared Kimi subscription) — not present in a bare smoke container,
|
|
so that step is deferred to integration/P4 wiring.
|