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codician-dev
988358ad1a
Implements the knowledge-graph playbook (extraction → resolution → assembly → querying + evaluation loop) as a plug & play CLI + .growmos/ JSONL store: task packets for Claude Code / Codex / Grok / Cursor / Gemini, MCP stdio server, git hooks, CI, optional headless provider mode, Apollo example corpus, 18 tests, docs and methodology. Repo dogfoods its own graph.
51 lines
2.2 KiB
Markdown
51 lines
2.2 KiB
Markdown
# Headless mode: cron, CI, overnight loops
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Agent-native mode needs no API key. When no agent is at the keyboard — a nightly job, a CI step,
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a batch backfill — growmos can call an LLM API itself. It is stdlib-only and provider-neutral.
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## Configure
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```bash
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export ANTHROPIC_API_KEY=sk-ant-… # provider auto-detected from whichever key is set
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# or
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export OPENAI_API_KEY=… # OpenAI
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export XAI_API_KEY=… # xAI Grok
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# or any OpenAI-compatible server:
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export GROWMOS_PROVIDER=openai GROWMOS_BASE_URL=http://localhost:11434/v1 GROWMOS_API_KEY=x
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# optional per-stage overrides:
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export GROWMOS_EXTRACT_MODEL=… GROWMOS_REASON_MODEL=…
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```
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Or set `provider.name / base_url / extract_model / reason_model` in `.growmos/config.json`
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(never commit an API key there — use env vars).
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Model split follows the playbook's Table IV: a fast, cheap model for high-volume extraction
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(`claude-haiku-4-5`, `gpt-4o-mini`, `grok-3-mini` by default) and a stronger reasoning model for
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resolution, summarization and answering (`claude-sonnet-5`, `gpt-4o`, `grok-3`).
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Structured outputs are requested (`output_config.format` json_schema on Anthropic,
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`response_format json_schema` on OpenAI-compatible APIs) so payloads validate by construction.
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## Run
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```bash
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growmos ingest --scan --limit 25 # extraction → resolution → hub profiles, respecting caps
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growmos query "…" --auto # grounded answer via the reasoning model
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```
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## Cron / GitHub Actions
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```yaml
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- run: pip install growmos
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- run: growmos ingest --scan
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env: { ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} }
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- run: growmos doctor && growmos eval
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- run: git add .growmos && git commit -m "growmos: overnight growth" || true
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```
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## Cost notes (from the playbook's scaling guidance)
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- Extraction dominates for large corpora — cache the fixed prompt prefix and batch when your
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provider offers it; growmos already caps documents per run.
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- Resolution is one call per entity type per block (blocks of ≤ `resolve_batch_size`), not per document.
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- Summarization is per hub node and only when its source set changed.
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- Querying cost is proportional to subgraph size — tune `--hops` and `--max-triples`.
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