Async on-prem LLM-powered structured information extraction microservice
Dirk Riemann
d0648fe01d
Runs from the Mac after every `git push server main`.
Flow: starts a tiny HTTP server on the Mac's LAN IP serving
tests/fixtures/synthetic_giro.pdf → POST /jobs with bank_statement_header
+ Paperless-style texts so text_agreement has something to check against →
poll GET /jobs/{id} until terminal → assert status=done, bank_name
non-empty, closing_balance.provenance_verified=True, text_agreement=True,
elapsed < 60 s. Non-zero exit blocks the deploy.
Uses only stdlib (http.server, urllib) — no extra deps on the Mac-side,
no test framework overhead.
Task 5.4 of MVP plan.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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| .forgejo/workflows | ||
| alembic | ||
| docs | ||
| scripts | ||
| src/ix | ||
| tests | ||
| .env.example | ||
| .gitignore | ||
| .python-version | ||
| AGENTS.md | ||
| alembic.ini | ||
| docker-compose.yml | ||
| Dockerfile | ||
| pyproject.toml | ||
| README.md | ||
| uv.lock | ||
InfoXtractor (ix)
Async, on-prem, LLM-powered structured information extraction microservice.
Given a document (PDF, image, text) and a named use case, ix returns a structured JSON result whose shape matches the use-case schema — together with per-field provenance (OCR segment IDs, bounding boxes, cross-OCR agreement flags) that let the caller decide how much to trust each extracted value.
Status: design phase. Implementation about to start.
- Full reference spec:
docs/spec-core-pipeline.md(aspirational; MVP is a strict subset) - MVP design:
docs/superpowers/specs/2026-04-18-ix-mvp-design.md - Agent / development notes:
AGENTS.md
Principles
- On-prem always. LLM = Ollama, OCR = local engines (Surya first). No OpenAI / Anthropic / Azure / AWS / cloud.
- Grounded extraction, not DB truth. ix returns best-effort fields + provenance; the caller decides what to trust.
- Transport-agnostic pipeline core. REST + Postgres-queue adapters in parallel on one job store.