Compare commits
No commits in common. "main" and "feat/pg-queue-adapter" have entirely different histories.
main
...
feat/pg-qu
32 changed files with 129 additions and 2374 deletions
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@ -4,11 +4,11 @@
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# the Postgres password.
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# --- Job store -----------------------------------------------------------
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IX_POSTGRES_URL=postgresql+asyncpg://infoxtractor:<password>@127.0.0.1:5431/infoxtractor
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IX_POSTGRES_URL=postgresql+asyncpg://infoxtractor:<password>@host.docker.internal:5431/infoxtractor
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# --- LLM backend ---------------------------------------------------------
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IX_OLLAMA_URL=http://127.0.0.1:11434
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IX_DEFAULT_MODEL=qwen3:14b
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IX_OLLAMA_URL=http://host.docker.internal:11434
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IX_DEFAULT_MODEL=gpt-oss:20b
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# --- OCR -----------------------------------------------------------------
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IX_OCR_ENGINE=surya
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1
.gitignore
vendored
1
.gitignore
vendored
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@ -15,7 +15,6 @@ dist/
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build/
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*.log
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/tmp/
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.claude/
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# uv
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# uv.lock is committed intentionally for reproducible builds.
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@ -4,7 +4,7 @@ Async, on-prem, LLM-powered structured information extraction microservice. Give
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Designed to be used by other on-prem services (e.g. mammon) as a reliable fallback / second opinion for format-specific deterministic parsers.
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Status: MVP deployed (2026-04-18) at `http://192.168.68.42:8994` — LAN only. Full reference spec at `docs/spec-core-pipeline.md`; MVP spec at `docs/superpowers/specs/2026-04-18-ix-mvp-design.md`; deploy runbook at `docs/deployment.md`.
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Status: design phase. Full reference spec at `docs/spec-core-pipeline.md`. MVP spec will live at `docs/superpowers/specs/`.
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## Guiding Principles
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@ -25,7 +25,7 @@ Status: MVP deployed (2026-04-18) at `http://192.168.68.42:8994` — LAN only. F
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- **Language**: Python 3.12, asyncio
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- **Web/REST**: FastAPI + uvicorn
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- **OCR (pluggable)**: Surya OCR first (GPU, shares RTX 3090 with Ollama / Immich ML)
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- **LLM**: Ollama at `192.168.68.42:11434`, structured outputs via JSON schema. Initial model candidate: `qwen2.5:32b` / `qwen3:14b`, configurable per use case
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- **LLM**: Ollama at `192.168.68.42:11434`, structured outputs via JSON schema. Initial model candidate: `qwen2.5:32b` / `gpt-oss:20b`, configurable per use case
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- **State**: Postgres on the shared `postgis` container (:5431), new `infoxtractor` database
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- **Deployment**: Docker, `git push server main` → post-receive rebuild (pattern from other apps)
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|
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69
Dockerfile
69
Dockerfile
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@ -1,69 +0,0 @@
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# InfoXtractor container image.
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#
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# Base image ships CUDA 12.4 runtime libraries so the Surya OCR client can
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# use the RTX 3090 on the deploy host. Ubuntu 22.04 is the LTS used across
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# the home-server stack (immich-ml, monitoring) so GPU drivers line up.
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FROM nvidia/cuda:12.4.0-runtime-ubuntu22.04
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ENV DEBIAN_FRONTEND=noninteractive \
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PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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PIP_NO_CACHE_DIR=1 \
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PIP_DISABLE_PIP_VERSION_CHECK=1
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# --- System deps --------------------------------------------------------
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# - python3.12 via deadsnakes PPA (pinned; Ubuntu 22.04 ships 3.10 only)
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# - libmagic1 : python-magic backend for MIME sniffing
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# - libgl1 : libGL.so needed by Pillow/OpenCV wheels used by Surya
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# - libglib2.0 : shared by Pillow/PyMuPDF headless rendering
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# - curl : post-receive hook's /healthz probe & general ops
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# - ca-certs : httpx TLS verification
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends \
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software-properties-common \
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ca-certificates \
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curl \
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gnupg \
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&& add-apt-repository -y ppa:deadsnakes/ppa \
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&& apt-get update \
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&& apt-get install -y --no-install-recommends \
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python3.12 \
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python3.12-venv \
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python3.12-dev \
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libmagic1 \
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libgl1 \
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libglib2.0-0 \
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&& ln -sf /usr/bin/python3.12 /usr/local/bin/python \
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&& ln -sf /usr/bin/python3.12 /usr/local/bin/python3 \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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# --- uv (dependency resolver used by the project) -----------------------
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# Install via the standalone installer; avoids needing a working system pip
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# (python3.12 on Ubuntu 22.04 has no `distutils`, which breaks Ubuntu pip).
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RUN curl -LsSf https://astral.sh/uv/install.sh | sh \
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&& ln -sf /root/.local/bin/uv /usr/local/bin/uv
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WORKDIR /app
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# Copy dependency manifests + README early so the heavy `uv sync` layer
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# caches whenever only application code changes. README.md is required
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# because pyproject.toml names it as the package's readme — hatchling
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# validates it exists when resolving the editable install.
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COPY pyproject.toml uv.lock .python-version README.md ./
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# Prod + OCR extras, no dev tooling. --frozen means "must match uv.lock";
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# CI catches drift before it reaches the image.
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RUN uv sync --frozen --no-dev --extra ocr
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# --- Application code ---------------------------------------------------
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COPY src src
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COPY alembic alembic
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COPY alembic.ini ./
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EXPOSE 8994
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# Migrations are idempotent (alembic upgrade head is a no-op on a current
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# DB) so running them on every start keeps the image + DB aligned without
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# an extra orchestration step.
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CMD ["sh", "-c", "uv run alembic upgrade head && uv run uvicorn ix.app:create_app --factory --host 0.0.0.0 --port 8994"]
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45
README.md
45
README.md
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@ -4,12 +4,10 @@ Async, on-prem, LLM-powered structured information extraction microservice.
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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.
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**Status:** MVP deployed. Live on the home LAN at `http://192.168.68.42:8994`.
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**Status:** design phase. Implementation about to start.
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- Full reference spec: [`docs/spec-core-pipeline.md`](docs/spec-core-pipeline.md) (aspirational; MVP is a strict subset)
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- **MVP design:** [`docs/superpowers/specs/2026-04-18-ix-mvp-design.md`](docs/superpowers/specs/2026-04-18-ix-mvp-design.md)
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- **Implementation plan:** [`docs/superpowers/plans/2026-04-18-ix-mvp-implementation.md`](docs/superpowers/plans/2026-04-18-ix-mvp-implementation.md)
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- **Deployment runbook:** [`docs/deployment.md`](docs/deployment.md)
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- Agent / development notes: [`AGENTS.md`](AGENTS.md)
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## Principles
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@ -17,44 +15,3 @@ Given a document (PDF, image, text) and a named *use case*, ix returns a structu
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- **On-prem always.** LLM = Ollama, OCR = local engines (Surya first). No OpenAI / Anthropic / Azure / AWS / cloud.
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- **Grounded extraction, not DB truth.** ix returns best-effort fields + provenance; the caller decides what to trust.
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- **Transport-agnostic pipeline core.** REST + Postgres-queue adapters in parallel on one job store.
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||||
|
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## Submitting a job
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|
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```bash
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curl -X POST http://192.168.68.42:8994/jobs \
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-H "Content-Type: application/json" \
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-d '{
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"use_case": "bank_statement_header",
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"ix_client_id": "mammon",
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"request_id": "some-correlation-id",
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"context": {
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"files": [{
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"url": "http://paperless.local/api/documents/42/download/",
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"headers": {"Authorization": "Token …"}
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}],
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"texts": ["<Paperless Tesseract OCR content>"]
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}
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}'
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# → {"job_id":"…","ix_id":"…","status":"pending"}
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```
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Poll `GET /jobs/{job_id}` until `status` is `done` or `error`. Optionally pass `callback_url` to receive a webhook on completion (one-shot, no retry; polling stays authoritative).
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||||
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Full REST surface + provenance response shape documented in the MVP design spec.
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|
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## Running locally
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||||
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```bash
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uv sync --extra dev
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uv run pytest tests/unit -v # hermetic unit + integration suite
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IX_TEST_OLLAMA=1 uv run pytest tests/live -v # needs LAN access to Ollama + GPU
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```
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## Deploying
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||||
```bash
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git push server main # rebuilds Docker image, restarts container, /healthz deploy gate
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||||
python scripts/e2e_smoke.py # E2E acceptance against the live service
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||||
```
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See [`docs/deployment.md`](docs/deployment.md) for full runbook + rollback.
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||||
|
|
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|
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@ -1,42 +0,0 @@
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# InfoXtractor Docker Compose stack.
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#
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# Single service. Uses host networking so the container can reach:
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# - Ollama at 127.0.0.1:11434
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||||
# - postgis at 127.0.0.1:5431 (bound to loopback only; security hardening)
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||||
# Both services are LAN-hardened on the host and never exposed publicly,
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# so host-network access stays on-prem. This matches the `goldstein`
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# container pattern on the same server.
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#
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# The GPU reservation block matches immich-ml / the shape Docker Compose
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# expects for GPU allocation on this host.
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||||
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||||
name: infoxtractor
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||||
services:
|
||||
infoxtractor:
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||||
build: .
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||||
container_name: infoxtractor
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||||
network_mode: host
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||||
restart: always
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||||
env_file: .env
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||||
deploy:
|
||||
resources:
|
||||
reservations:
|
||||
devices:
|
||||
- driver: nvidia
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||||
count: 1
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||||
capabilities: [gpu]
|
||||
volumes:
|
||||
# Persist Surya (datalab) + HuggingFace model caches so rebuilds don't
|
||||
# re-download ~1.5 GB of weights every time.
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||||
- ix_surya_cache:/root/.cache/datalab
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||||
- ix_hf_cache:/root/.cache/huggingface
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labels:
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infrastructure.web_url: "http://192.168.68.42:8994"
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||||
backup.enable: "true"
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backup.type: "postgres"
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||||
backup.name: "infoxtractor"
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||||
|
||||
volumes:
|
||||
ix_surya_cache:
|
||||
ix_hf_cache:
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|
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@ -1,153 +0,0 @@
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# Deployment
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||||
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||||
On-prem deploy to `192.168.68.42`. Push-to-deploy via a bare git repo + `post-receive` hook that rebuilds the Docker Compose stack. Pattern mirrors mammon and unified_messaging.
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||||
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||||
## Topology
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||||
|
||||
```
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||||
Mac (dev)
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||||
│ git push server main
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▼
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||||
192.168.68.42:/home/server/Public/infoxtractor/repos.git (bare)
|
||||
│ post-receive → GIT_WORK_TREE=/…/app git checkout -f main
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||||
│ docker compose up -d --build
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│ curl /healthz (60 s gate)
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▼
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Docker container `infoxtractor` (port 8994)
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├─ 127.0.0.1:11434 → Ollama (qwen3:14b; host-network mode)
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||||
└─ 127.0.0.1:5431 → postgis (database `infoxtractor`; host-network mode)
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||||
```
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||||
|
||||
## One-time server setup
|
||||
|
||||
Run **once** from the Mac. Idempotent.
|
||||
|
||||
```bash
|
||||
export IX_POSTGRES_PASSWORD=<generate-a-strong-one>
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./scripts/setup_server.sh
|
||||
```
|
||||
|
||||
The script:
|
||||
1. Creates `/home/server/Public/infoxtractor/repos.git` (bare) + `/home/server/Public/infoxtractor/app/` (worktree).
|
||||
2. Installs the `post-receive` hook (see `scripts/setup_server.sh` for the template).
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||||
3. Creates the `infoxtractor` Postgres role + database on the shared `postgis` container.
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||||
4. Writes `/home/server/Public/infoxtractor/app/.env` (mode 0600) from `.env.example` with the password substituted in.
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||||
5. Verifies `qwen3:14b` is pulled in Ollama.
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||||
6. Prints a hint to open UFW for port 8994 on the LAN subnet if it's missing.
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||||
|
||||
After the script finishes, add the deploy remote to the local repo:
|
||||
|
||||
```bash
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git remote add server ssh://server@192.168.68.42/home/server/Public/infoxtractor/repos.git
|
||||
```
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||||
|
||||
## Normal deploy workflow
|
||||
|
||||
```bash
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# after merging a feat branch into main
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||||
git push server main
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||||
|
||||
# tail the server's deploy log
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||||
ssh server@192.168.68.42 "tail -f /tmp/infoxtractor-deploy.log"
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||||
|
||||
# healthz gate (the post-receive hook also waits up to 60 s for this)
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curl http://192.168.68.42:8994/healthz
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||||
|
||||
# end-to-end smoke — this IS the real acceptance test
|
||||
python scripts/e2e_smoke.py
|
||||
```
|
||||
|
||||
If the post-receive hook exits non-zero (healthz never reaches 200), the deploy is considered failed. The previous container keeps running (the hook swaps via `docker compose up -d --build`, which first builds the new image and only swaps if the build succeeds; if the new container fails `/healthz`, it's still up but broken). Investigate with `docker compose logs --tail 200` in `${APP_DIR}` and either fix forward or revert (see below).
|
||||
|
||||
## Rollback
|
||||
|
||||
Never force-push `main`. Rollbacks happen as **forward commits** via `git revert`:
|
||||
|
||||
```bash
|
||||
git revert HEAD # creates a revert commit for the last change
|
||||
git push forgejo main
|
||||
git push server main
|
||||
```
|
||||
|
||||
## First deploy
|
||||
|
||||
- **Date:** 2026-04-18
|
||||
- **Commit:** `fix/ollama-extract-json` (#36, the last of several Docker/ops follow-ups after PR #27 shipped the initial Dockerfile)
|
||||
- **`/healthz`:** all three probes (`postgres`, `ollama`, `ocr`) green. First-pass took ~7 min for the fresh container because Surya's recognition (1.34 GB) + detection (73 MB) models download from HuggingFace on first run; subsequent rebuilds reuse the named volumes declared in `docker-compose.yml` and come up in <30 s.
|
||||
- **E2E extraction:** `bank_statement_header` against `tests/fixtures/synthetic_giro.pdf` with Paperless-style texts:
|
||||
- Pipeline completes in **35 s**.
|
||||
- Extracted: `bank_name=DKB`, `account_iban=DE89370400440532013000`, `currency=EUR`, `opening_balance=1234.56`, `closing_balance=1450.22`, `statement_date=2026-03-31`, `statement_period_end=2026-03-31`, `statement_period_start=2026-03-01`, `account_type=null`.
|
||||
- Provenance: 8 / 9 leaf fields have sources; 7 / 8 `provenance_verified` and `text_agreement` are True. `statement_period_start` shows up in the OCR but normalisation fails (dateutil picks a different interpretation of the cited day); to be chased in a follow-up.
|
||||
|
||||
### Docker-ops follow-ups that landed during the first deploy
|
||||
|
||||
All small, each merged as its own PR. In commit order after the scaffold (#27):
|
||||
|
||||
- **#31** `fix(docker): uv via standalone installer` — Python 3.12 on Ubuntu 22.04 drops `distutils`; Ubuntu's pip needed it. Switched to the `uv` standalone installer, which has no pip dependency.
|
||||
- **#32** `fix(docker): include README.md in the uv sync COPY` — `hatchling` validates the readme file exists when resolving the editable project install.
|
||||
- **#33** `fix(compose): drop runtime: nvidia` — the deploy host's Docker daemon doesn't register a named `nvidia` runtime; `deploy.resources.devices` is sufficient and matches immich-ml.
|
||||
- **#34** `fix(deploy): network_mode: host` — `postgis` is bound to `127.0.0.1` on the host (security hardening T12). `host.docker.internal` points at the bridge gateway, not loopback, so the container couldn't reach postgis. Goldstein uses the same pattern.
|
||||
- **#35** `fix(deps): pin surya-ocr ^0.17` — earlier cu124 torch pin had forced surya to 0.14.1, which breaks our `surya.foundation` import and needs a transformers version that lacks `QuantizedCacheConfig`.
|
||||
- **#36** `fix(genai): drop Ollama format flag; extract trailing JSON` — Ollama 0.11.8 segfaults on Pydantic JSON Schemas (`$ref`, `anyOf`, `pattern`), and `format="json"` terminates reasoning models (qwen3) at `{}` because their `<think>…</think>` chain-of-thought isn't valid JSON. Omit the flag, inject the schema into the system prompt, extract the outermost `{…}` balanced block from the response.
|
||||
- **volumes** — named `ix_surya_cache` + `ix_hf_cache` mount `/root/.cache/datalab` + `/root/.cache/huggingface` so rebuilds don't re-download ~1.5 GB of model weights.
|
||||
|
||||
Production notes:
|
||||
|
||||
- `IX_DEFAULT_MODEL=qwen3:14b` (already pulled on the host). Spec listed `gpt-oss:20b` as a concrete example; swapped to keep the deploy on-prem without an extra `ollama pull`.
|
||||
- Torch 2.11 default cu13 wheels fall back to CPU against the host's CUDA 12.4 driver — Surya runs on CPU. Expected inference times: seconds per page. Upgrading the NVIDIA driver (or pinning a cu12-compatible torch wheel newer than 2.7) will unlock GPU with no code changes.
|
||||
|
||||
## E2E smoke test (`scripts/e2e_smoke.py`)
|
||||
|
||||
What it does (from the Mac):
|
||||
|
||||
1. Checks `/healthz`.
|
||||
2. Starts a tiny HTTP server on the Mac's LAN IP serving `tests/fixtures/synthetic_giro.pdf`.
|
||||
3. Submits a `POST /jobs` with `use_case=bank_statement_header`, the fixture URL in `context.files`, and a Paperless-style OCR text in `context.texts` (to exercise the `text_agreement` cross-check).
|
||||
4. Polls `GET /jobs/{id}` every 2 s until terminal or 120 s timeout.
|
||||
5. Asserts: `status=="done"`, `bank_name` non-empty, `provenance.fields["result.closing_balance"].provenance_verified=True`, `text_agreement=True`, total elapsed `< 60s`.
|
||||
|
||||
Non-zero exit means the deploy is not healthy. Roll back via `git revert HEAD`.
|
||||
|
||||
## Operational checklists
|
||||
|
||||
### After `ollama pull` on the host
|
||||
|
||||
The `IX_DEFAULT_MODEL` env var on the server's `.env` must match something in `ollama list`. Changing the default means:
|
||||
|
||||
1. Edit `/home/server/Public/infoxtractor/app/.env` → `IX_DEFAULT_MODEL=<new>`.
|
||||
2. `docker compose --project-directory /home/server/Public/infoxtractor/app restart`.
|
||||
3. `curl http://192.168.68.42:8994/healthz` → confirm `ollama: ok`.
|
||||
|
||||
### If `/healthz` shows `ollama: degraded`
|
||||
|
||||
`qwen3:14b` (or the configured default) is not pulled. On the host:
|
||||
```bash
|
||||
ssh server@192.168.68.42 "docker exec ollama ollama pull qwen3:14b"
|
||||
```
|
||||
|
||||
### If `/healthz` shows `ocr: fail`
|
||||
|
||||
Surya couldn't initialize (model missing, CUDA unavailable, OOM). First run can be slow — models download on first call. Check container logs:
|
||||
```bash
|
||||
ssh server@192.168.68.42 "docker logs infoxtractor --tail 200"
|
||||
```
|
||||
|
||||
### If the container fails to start
|
||||
|
||||
```bash
|
||||
ssh server@192.168.68.42 "tail -100 /tmp/infoxtractor-deploy.log"
|
||||
ssh server@192.168.68.42 "docker compose -f /home/server/Public/infoxtractor/app/docker-compose.yml logs --tail 200"
|
||||
```
|
||||
|
||||
## Monitoring
|
||||
|
||||
- Monitoring dashboard auto-discovers via the `infrastructure.web_url` label on the container: `http://192.168.68.42:8001` → "infoxtractor" card.
|
||||
- Backup opt-in via `backup.enable=true` + `backup.type=postgres` + `backup.name=infoxtractor` labels. The daily backup script picks up the `infoxtractor` Postgres database automatically.
|
||||
|
||||
## Ports
|
||||
|
||||
| Port | Direction | Source | Service |
|
||||
|------|-----------|--------|---------|
|
||||
| 8994/tcp | ALLOW | 192.168.68.0/24 | ix REST + healthz (LAN only; not publicly exposed) |
|
||||
|
||||
No VPS Caddy entry; no `infrastructure.docs_url` label — this is an internal service.
|
||||
|
|
@ -1,8 +1,6 @@
|
|||
[project]
|
||||
name = "infoxtractor"
|
||||
version = "0.1.0"
|
||||
# Released 2026-04-18 with the first live deploy of the MVP. See
|
||||
# docs/deployment.md §"First deploy" for the commit + /healthz times.
|
||||
description = "Async on-prem LLM-powered structured information extraction microservice"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.12"
|
||||
|
|
@ -33,12 +31,10 @@ dependencies = [
|
|||
|
||||
[project.optional-dependencies]
|
||||
ocr = [
|
||||
# Real OCR engine. Kept optional so CI (no GPU) can install the base
|
||||
# package without the model deps.
|
||||
# surya >= 0.17 is required: the client code uses the
|
||||
# `surya.foundation` module, which older releases don't expose.
|
||||
"surya-ocr>=0.17,<0.18",
|
||||
"torch>=2.7",
|
||||
# Real OCR engine — pulls torch + CUDA wheels. Kept optional so CI
|
||||
# (no GPU) can install the base package without the model deps.
|
||||
"surya-ocr>=0.9",
|
||||
"torch>=2.4",
|
||||
]
|
||||
dev = [
|
||||
"pytest>=8.3",
|
||||
|
|
@ -48,11 +44,6 @@ dev = [
|
|||
"mypy>=1.13",
|
||||
]
|
||||
|
||||
# Note: the default pypi torch ships cu13 wheels, which emit a
|
||||
# UserWarning and fall back to CPU against the deploy host's CUDA 12.4
|
||||
# driver. Surya then runs on CPU — slower but correct for MVP. A future
|
||||
# driver upgrade unlocks GPU Surya with no code changes.
|
||||
|
||||
[build-system]
|
||||
requires = ["hatchling"]
|
||||
build-backend = "hatchling.build"
|
||||
|
|
|
|||
|
|
@ -1,210 +0,0 @@
|
|||
"""End-to-end smoke test against the deployed infoxtractor service.
|
||||
|
||||
Uploads a synthetic bank-statement fixture, polls for completion, and asserts
|
||||
the provenance flags per spec §12 E2E. Intended to run from the Mac after
|
||||
every `git push server main` as the deploy gate.
|
||||
|
||||
Prerequisites:
|
||||
- The service is running and reachable at --base-url (default
|
||||
http://192.168.68.42:8994).
|
||||
- The fixture `tests/fixtures/synthetic_giro.pdf` is present.
|
||||
- The Mac and the server are on the same LAN (the server must be able to
|
||||
reach the Mac to download the fixture).
|
||||
|
||||
Exit codes:
|
||||
0 all assertions passed within the timeout
|
||||
1 at least one assertion failed
|
||||
2 the job never reached a terminal state in time
|
||||
3 the service was unreachable or returned an unexpected error
|
||||
|
||||
Usage:
|
||||
python scripts/e2e_smoke.py
|
||||
python scripts/e2e_smoke.py --base-url http://localhost:8994
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import http.server
|
||||
import json
|
||||
import socket
|
||||
import socketserver
|
||||
import sys
|
||||
import threading
|
||||
import time
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
import uuid
|
||||
from pathlib import Path
|
||||
|
||||
DEFAULT_BASE_URL = "http://192.168.68.42:8994"
|
||||
FIXTURE = Path(__file__).parent.parent / "tests" / "fixtures" / "synthetic_giro.pdf"
|
||||
TIMEOUT_SECONDS = 120
|
||||
POLL_INTERVAL_SECONDS = 2
|
||||
|
||||
|
||||
def find_lan_ip() -> str:
|
||||
"""Return the Mac's LAN IP that the server can reach."""
|
||||
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
|
||||
try:
|
||||
# 192.168.68.42 is the server; getting the default route towards it
|
||||
# yields the NIC with the matching subnet.
|
||||
s.connect(("192.168.68.42", 80))
|
||||
return s.getsockname()[0]
|
||||
finally:
|
||||
s.close()
|
||||
|
||||
|
||||
def serve_fixture_in_background(fixture: Path) -> tuple[str, threading.Event]:
|
||||
"""Serve the fixture on a temporary HTTP server; return the URL and a stop event."""
|
||||
if not fixture.exists():
|
||||
print(f"FIXTURE MISSING: {fixture}", file=sys.stderr)
|
||||
sys.exit(3)
|
||||
|
||||
directory = fixture.parent
|
||||
filename = fixture.name
|
||||
lan_ip = find_lan_ip()
|
||||
|
||||
class Handler(http.server.SimpleHTTPRequestHandler):
|
||||
def __init__(self, *args, **kwargs):
|
||||
super().__init__(*args, directory=str(directory), **kwargs)
|
||||
|
||||
def log_message(self, format: str, *args) -> None: # quiet
|
||||
pass
|
||||
|
||||
# Pick any free port.
|
||||
httpd = socketserver.TCPServer((lan_ip, 0), Handler)
|
||||
port = httpd.server_address[1]
|
||||
url = f"http://{lan_ip}:{port}/{filename}"
|
||||
stop = threading.Event()
|
||||
|
||||
def _serve():
|
||||
try:
|
||||
while not stop.is_set():
|
||||
httpd.handle_request()
|
||||
finally:
|
||||
httpd.server_close()
|
||||
|
||||
# Run in a thread. Use a loose timeout so handle_request returns when stop is set.
|
||||
httpd.timeout = 0.5
|
||||
t = threading.Thread(target=_serve, daemon=True)
|
||||
t.start()
|
||||
return url, stop
|
||||
|
||||
|
||||
def post_job(base_url: str, file_url: str, client_id: str, request_id: str) -> dict:
|
||||
# Include a Paperless-style OCR of the fixture as context.texts so the
|
||||
# text_agreement cross-check has something to compare against.
|
||||
paperless_text = (
|
||||
"DKB\n"
|
||||
"DE89370400440532013000\n"
|
||||
"Statement period: 01.03.2026 - 31.03.2026\n"
|
||||
"Opening balance: 1234.56 EUR\n"
|
||||
"Closing balance: 1450.22 EUR\n"
|
||||
"31.03.2026\n"
|
||||
)
|
||||
payload = {
|
||||
"use_case": "bank_statement_header",
|
||||
"ix_client_id": client_id,
|
||||
"request_id": request_id,
|
||||
"context": {
|
||||
"files": [file_url],
|
||||
"texts": [paperless_text],
|
||||
},
|
||||
}
|
||||
req = urllib.request.Request(
|
||||
f"{base_url}/jobs",
|
||||
data=json.dumps(payload).encode("utf-8"),
|
||||
headers={"Content-Type": "application/json"},
|
||||
method="POST",
|
||||
)
|
||||
with urllib.request.urlopen(req, timeout=10) as resp:
|
||||
return json.loads(resp.read().decode("utf-8"))
|
||||
|
||||
|
||||
def get_job(base_url: str, job_id: str) -> dict:
|
||||
req = urllib.request.Request(f"{base_url}/jobs/{job_id}")
|
||||
with urllib.request.urlopen(req, timeout=10) as resp:
|
||||
return json.loads(resp.read().decode("utf-8"))
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--base-url", default=DEFAULT_BASE_URL)
|
||||
parser.add_argument("--timeout", type=int, default=TIMEOUT_SECONDS)
|
||||
args = parser.parse_args()
|
||||
|
||||
# Sanity-check the service is up.
|
||||
try:
|
||||
with urllib.request.urlopen(f"{args.base_url}/healthz", timeout=5) as resp:
|
||||
health = json.loads(resp.read().decode("utf-8"))
|
||||
print(f"healthz: {health}")
|
||||
except urllib.error.URLError as e:
|
||||
print(f"service unreachable: {e}", file=sys.stderr)
|
||||
return 3
|
||||
|
||||
fixture_url, stop_server = serve_fixture_in_background(FIXTURE)
|
||||
print(f"serving fixture at {fixture_url}")
|
||||
|
||||
try:
|
||||
client_id = "e2e_smoke"
|
||||
request_id = f"smoke-{uuid.uuid4().hex[:8]}"
|
||||
submit = post_job(args.base_url, fixture_url, client_id, request_id)
|
||||
job_id = submit["job_id"]
|
||||
print(f"submitted job_id={job_id}")
|
||||
|
||||
started = time.monotonic()
|
||||
last_status = None
|
||||
job = None
|
||||
while time.monotonic() - started < args.timeout:
|
||||
job = get_job(args.base_url, job_id)
|
||||
if job["status"] != last_status:
|
||||
print(f"[{time.monotonic() - started:5.1f}s] status={job['status']}")
|
||||
last_status = job["status"]
|
||||
if job["status"] in ("done", "error"):
|
||||
break
|
||||
time.sleep(POLL_INTERVAL_SECONDS)
|
||||
else:
|
||||
print(f"FAIL: timed out after {args.timeout}s", file=sys.stderr)
|
||||
return 2
|
||||
|
||||
assert job is not None
|
||||
failed = []
|
||||
|
||||
if job["status"] != "done":
|
||||
failed.append(f"status={job['status']!r} (want 'done')")
|
||||
|
||||
response = job.get("response") or {}
|
||||
if response.get("error"):
|
||||
failed.append(f"response.error={response['error']!r}")
|
||||
|
||||
result = (response.get("ix_result") or {}).get("result") or {}
|
||||
bank = result.get("bank_name")
|
||||
if not isinstance(bank, str) or not bank.strip():
|
||||
failed.append(f"bank_name={bank!r} (want non-empty string)")
|
||||
|
||||
fields = (response.get("provenance") or {}).get("fields") or {}
|
||||
closing = fields.get("result.closing_balance") or {}
|
||||
if not closing.get("provenance_verified"):
|
||||
failed.append(f"closing_balance.provenance_verified={closing.get('provenance_verified')!r}")
|
||||
if closing.get("text_agreement") is not True:
|
||||
failed.append(f"closing_balance.text_agreement={closing.get('text_agreement')!r} (Paperless-style text submitted)")
|
||||
|
||||
elapsed = time.monotonic() - started
|
||||
if elapsed >= 60:
|
||||
failed.append(f"elapsed={elapsed:.1f}s (≥ 60s; slow path)")
|
||||
|
||||
print(json.dumps(result, indent=2, default=str))
|
||||
|
||||
if failed:
|
||||
print("\n".join(f"FAIL: {f}" for f in failed), file=sys.stderr)
|
||||
return 1
|
||||
|
||||
print(f"\nPASS in {elapsed:.1f}s")
|
||||
return 0
|
||||
finally:
|
||||
stop_server.set()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
|
|
@ -1,127 +0,0 @@
|
|||
#!/usr/bin/env bash
|
||||
# One-shot server setup for InfoXtractor. Idempotent: safe to re-run.
|
||||
#
|
||||
# Run from the Mac:
|
||||
# IX_POSTGRES_PASSWORD=<pw> ./scripts/setup_server.sh
|
||||
#
|
||||
# What it does on 192.168.68.42:
|
||||
# 1. Creates the bare git repo `/home/server/Public/infoxtractor/repos.git` if missing.
|
||||
# 2. Writes the post-receive hook (or updates it) and makes it executable.
|
||||
# 3. Creates the Postgres role + database on the shared `postgis` container.
|
||||
# 4. Writes `/home/server/Public/infoxtractor/app/.env` (0600) from .env.example.
|
||||
# 5. Verifies `qwen3:14b` is pulled in Ollama.
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
SERVER="${IX_SERVER:-server@192.168.68.42}"
|
||||
APP_BASE="/home/server/Public/infoxtractor"
|
||||
REPOS_GIT="${APP_BASE}/repos.git"
|
||||
APP_DIR="${APP_BASE}/app"
|
||||
DB_NAME="infoxtractor"
|
||||
DB_USER="infoxtractor"
|
||||
|
||||
if [ -z "${IX_POSTGRES_PASSWORD:-}" ]; then
|
||||
read -r -s -p "Postgres password for role '${DB_USER}': " IX_POSTGRES_PASSWORD
|
||||
echo
|
||||
fi
|
||||
|
||||
if [ -z "${IX_POSTGRES_PASSWORD}" ]; then
|
||||
echo "IX_POSTGRES_PASSWORD is required." >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
echo "==> 1/5 Ensuring bare repo + post-receive hook on ${SERVER}"
|
||||
ssh "${SERVER}" bash -s <<EOF
|
||||
set -euo pipefail
|
||||
mkdir -p "${REPOS_GIT}" "${APP_DIR}"
|
||||
if [ ! -f "${REPOS_GIT}/HEAD" ]; then
|
||||
git init --bare "${REPOS_GIT}"
|
||||
fi
|
||||
|
||||
cat >"${REPOS_GIT}/hooks/post-receive" <<'HOOK'
|
||||
#!/usr/bin/env bash
|
||||
set -eo pipefail
|
||||
|
||||
APP_DIR="${APP_DIR}"
|
||||
LOG="/tmp/infoxtractor-deploy.log"
|
||||
|
||||
echo "[\$(date -u '+%FT%TZ')] post-receive start" >> "\$LOG"
|
||||
|
||||
mkdir -p "\$APP_DIR"
|
||||
GIT_WORK_TREE="\$APP_DIR" git --git-dir="${REPOS_GIT}" checkout -f main >> "\$LOG" 2>&1
|
||||
|
||||
cd "\$APP_DIR"
|
||||
docker compose up -d --build >> "\$LOG" 2>&1
|
||||
|
||||
# Deploy gate: /healthz must return 200 within 60 s.
|
||||
for i in \$(seq 1 30); do
|
||||
if curl -fsS http://localhost:8994/healthz > /dev/null 2>&1; then
|
||||
echo "[\$(date -u '+%FT%TZ')] healthz OK" >> "\$LOG"
|
||||
exit 0
|
||||
fi
|
||||
sleep 2
|
||||
done
|
||||
|
||||
echo "[\$(date -u '+%FT%TZ')] healthz never reached OK" >> "\$LOG"
|
||||
docker compose logs --tail 100 >> "\$LOG" 2>&1 || true
|
||||
exit 1
|
||||
HOOK
|
||||
|
||||
chmod +x "${REPOS_GIT}/hooks/post-receive"
|
||||
EOF
|
||||
|
||||
echo "==> 2/5 Verifying Ollama has qwen3:14b pulled"
|
||||
if ! ssh "${SERVER}" "docker exec ollama ollama list | awk '{print \$1}' | grep -qx 'qwen3:14b'"; then
|
||||
echo "FAIL: qwen3:14b not found in Ollama. Run: ssh ${SERVER} 'docker exec ollama ollama pull qwen3:14b'" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
echo "==> 3/5 Creating Postgres role '${DB_USER}' and database '${DB_NAME}' on postgis container"
|
||||
# Idempotent via DO blocks; uses docker exec to avoid needing psql on the host.
|
||||
ssh "${SERVER}" bash -s <<EOF
|
||||
set -euo pipefail
|
||||
docker exec -i postgis psql -U postgres <<SQL
|
||||
DO \\\$\\\$
|
||||
BEGIN
|
||||
IF NOT EXISTS (SELECT FROM pg_roles WHERE rolname = '${DB_USER}') THEN
|
||||
CREATE ROLE ${DB_USER} LOGIN PASSWORD '${IX_POSTGRES_PASSWORD}';
|
||||
ELSE
|
||||
ALTER ROLE ${DB_USER} WITH PASSWORD '${IX_POSTGRES_PASSWORD}';
|
||||
END IF;
|
||||
END
|
||||
\\\$\\\$;
|
||||
SQL
|
||||
|
||||
if ! docker exec -i postgis psql -U postgres -tc "SELECT 1 FROM pg_database WHERE datname = '${DB_NAME}'" | grep -q 1; then
|
||||
docker exec -i postgis createdb -U postgres -O ${DB_USER} ${DB_NAME}
|
||||
fi
|
||||
EOF
|
||||
|
||||
echo "==> 4/5 Writing ${APP_DIR}/.env on the server"
|
||||
# Render .env from the repo's .env.example, substituting the password placeholder.
|
||||
LOCAL_ENV_CONTENT="$(
|
||||
sed "s#<password>#${IX_POSTGRES_PASSWORD}#g" \
|
||||
"$(dirname "$0")/../.env.example"
|
||||
)"
|
||||
# Append the IX_TEST_MODE=production for safety (fake mode stays off).
|
||||
# .env is written atomically and permissioned 0600.
|
||||
ssh "${SERVER}" "install -d -m 0755 '${APP_DIR}' && cat > '${APP_DIR}/.env' <<'ENVEOF'
|
||||
${LOCAL_ENV_CONTENT}
|
||||
ENVEOF
|
||||
chmod 0600 '${APP_DIR}/.env'"
|
||||
|
||||
echo "==> 5/5 Checking UFW rule for port 8994 (LAN only)"
|
||||
ssh "${SERVER}" "sudo ufw status numbered | grep -F 8994" >/dev/null 2>&1 || {
|
||||
echo "NOTE: UFW doesn't yet allow 8994. Run on the server:"
|
||||
echo " sudo ufw allow from 192.168.68.0/24 to any port 8994 proto tcp"
|
||||
}
|
||||
|
||||
echo
|
||||
echo "Done."
|
||||
echo
|
||||
echo "Next steps (on the Mac):"
|
||||
echo " git remote add server ssh://server@192.168.68.42${REPOS_GIT}"
|
||||
echo " git push server main"
|
||||
echo " ssh ${SERVER} 'tail -f /tmp/infoxtractor-deploy.log'"
|
||||
echo " curl http://192.168.68.42:8994/healthz"
|
||||
echo " python scripts/e2e_smoke.py"
|
||||
184
src/ix/app.py
184
src/ix/app.py
|
|
@ -5,132 +5,21 @@ worker loop (Task 3.5) and the pg_queue listener (Task 3.6). Tests that
|
|||
don't care about the worker call ``create_app(spawn_worker=False)`` so the
|
||||
lifespan returns cleanly.
|
||||
|
||||
Task 4.3 fills in the production wiring:
|
||||
|
||||
* Factories (``make_genai_client`` / ``make_ocr_client``) pick between
|
||||
fakes (``IX_TEST_MODE=fake``) and real Ollama/Surya clients.
|
||||
* ``/healthz`` probes call ``selfcheck()`` on the active clients. In
|
||||
``fake`` mode they always report ok.
|
||||
* The worker's :class:`Pipeline` is built once per spawn with the real
|
||||
chain of Steps; each call to the injected ``pipeline_factory`` returns
|
||||
a fresh Pipeline so per-request state stays isolated.
|
||||
The factory is parameterised (``spawn_worker``) instead of env-gated because
|
||||
pytest runs multiple app instances per session and we want the decision local
|
||||
to each call, not inferred from ``IX_*`` variables. The listener is also
|
||||
gated on ``spawn_worker`` — the listener is only useful when a worker is
|
||||
draining the queue, so the two share one flag.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
from collections.abc import AsyncIterator, Callable
|
||||
from collections.abc import AsyncIterator
|
||||
from contextlib import asynccontextmanager, suppress
|
||||
from typing import Literal
|
||||
|
||||
from fastapi import FastAPI
|
||||
|
||||
from ix.adapters.rest.routes import Probes, get_probes
|
||||
from ix.adapters.rest.routes import router as rest_router
|
||||
from ix.config import AppConfig, get_config
|
||||
from ix.genai import make_genai_client
|
||||
from ix.genai.client import GenAIClient
|
||||
from ix.ocr import make_ocr_client
|
||||
from ix.ocr.client import OCRClient
|
||||
from ix.pipeline.genai_step import GenAIStep
|
||||
from ix.pipeline.ocr_step import OCRStep
|
||||
from ix.pipeline.pipeline import Pipeline
|
||||
from ix.pipeline.reliability_step import ReliabilityStep
|
||||
from ix.pipeline.response_handler_step import ResponseHandlerStep
|
||||
from ix.pipeline.setup_step import SetupStep
|
||||
|
||||
|
||||
def build_pipeline(
|
||||
genai: GenAIClient, ocr: OCRClient, cfg: AppConfig
|
||||
) -> Pipeline:
|
||||
"""Assemble the production :class:`Pipeline` with injected clients.
|
||||
|
||||
Kept as a module-level helper so tests that want to exercise the
|
||||
production wiring (without running the worker) can call it directly.
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
from ix.ingestion import FetchConfig
|
||||
|
||||
return Pipeline(
|
||||
steps=[
|
||||
SetupStep(
|
||||
tmp_dir=Path(cfg.tmp_dir),
|
||||
fetch_config=FetchConfig(
|
||||
connect_timeout_s=float(cfg.file_connect_timeout_seconds),
|
||||
read_timeout_s=float(cfg.file_read_timeout_seconds),
|
||||
max_bytes=cfg.file_max_bytes,
|
||||
),
|
||||
),
|
||||
OCRStep(ocr_client=ocr),
|
||||
GenAIStep(genai_client=genai),
|
||||
ReliabilityStep(),
|
||||
ResponseHandlerStep(),
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
def _make_ollama_probe(
|
||||
genai: GenAIClient, cfg: AppConfig
|
||||
) -> Callable[[], Literal["ok", "degraded", "fail"]]:
|
||||
"""Adapter: async ``selfcheck`` → sync callable the route expects.
|
||||
|
||||
Always drives the coroutine on a throwaway event loop in a separate
|
||||
thread. This keeps the behavior identical whether the caller holds an
|
||||
event loop (FastAPI request) or doesn't (a CLI tool), and avoids the
|
||||
``asyncio.run`` vs. already-running-loop footgun.
|
||||
"""
|
||||
|
||||
def probe() -> Literal["ok", "degraded", "fail"]:
|
||||
if not hasattr(genai, "selfcheck"):
|
||||
return "ok" # fake client — nothing to probe.
|
||||
return _run_async_sync(
|
||||
lambda: genai.selfcheck(expected_model=cfg.default_model), # type: ignore[attr-defined]
|
||||
fallback="fail",
|
||||
)
|
||||
|
||||
return probe
|
||||
|
||||
|
||||
def _make_ocr_probe(ocr: OCRClient) -> Callable[[], Literal["ok", "fail"]]:
|
||||
def probe() -> Literal["ok", "fail"]:
|
||||
if not hasattr(ocr, "selfcheck"):
|
||||
return "ok" # fake — nothing to probe.
|
||||
return _run_async_sync(
|
||||
lambda: ocr.selfcheck(), # type: ignore[attr-defined]
|
||||
fallback="fail",
|
||||
)
|
||||
|
||||
return probe
|
||||
|
||||
|
||||
def _run_async_sync(make_coro, *, fallback: str) -> str: # type: ignore[no-untyped-def]
|
||||
"""Run ``make_coro()`` on a fresh loop in a thread; return its result.
|
||||
|
||||
The thread owns its own event loop so the caller's loop (if any) keeps
|
||||
running. Any exception collapses to ``fallback``.
|
||||
"""
|
||||
|
||||
import threading
|
||||
|
||||
result: dict[str, object] = {}
|
||||
|
||||
def _runner() -> None:
|
||||
loop = asyncio.new_event_loop()
|
||||
try:
|
||||
result["value"] = loop.run_until_complete(make_coro())
|
||||
except Exception as exc: # any error collapses to fallback
|
||||
result["error"] = exc
|
||||
finally:
|
||||
loop.close()
|
||||
|
||||
t = threading.Thread(target=_runner)
|
||||
t.start()
|
||||
t.join()
|
||||
if "error" in result or "value" not in result:
|
||||
return fallback
|
||||
return str(result["value"])
|
||||
|
||||
|
||||
def create_app(*, spawn_worker: bool = True) -> FastAPI:
|
||||
|
|
@ -147,35 +36,21 @@ def create_app(*, spawn_worker: bool = True) -> FastAPI:
|
|||
|
||||
@asynccontextmanager
|
||||
async def lifespan(_app: FastAPI) -> AsyncIterator[None]:
|
||||
cfg = get_config()
|
||||
|
||||
# Build the clients once per process. The worker's pipeline
|
||||
# factory closes over these so every job runs through the same
|
||||
# Ollama/Surya instance (Surya's predictors are heavy; re-loading
|
||||
# them per job would be catastrophic).
|
||||
genai_client = make_genai_client(cfg)
|
||||
ocr_client = make_ocr_client(cfg)
|
||||
|
||||
# Override the route-level probe DI so /healthz reflects the
|
||||
# actual clients. Tests that want canned probes can still override
|
||||
# ``get_probes`` at the TestClient layer.
|
||||
_app.dependency_overrides.setdefault(
|
||||
get_probes,
|
||||
lambda: Probes(
|
||||
ollama=_make_ollama_probe(genai_client, cfg),
|
||||
ocr=_make_ocr_probe(ocr_client),
|
||||
),
|
||||
)
|
||||
|
||||
worker_task = None
|
||||
listener = None
|
||||
if spawn_worker:
|
||||
# Pipeline factory + listener wiring live in Chunk 4's
|
||||
# production entrypoint; keeping this path best-effort lets the
|
||||
# lifespan still start even on a box where Ollama/Surya aren't
|
||||
# available (the listener just gives us a passive 10 s poll).
|
||||
try:
|
||||
from ix.adapters.pg_queue.listener import (
|
||||
PgQueueListener,
|
||||
asyncpg_dsn_from_sqlalchemy_url,
|
||||
)
|
||||
from ix.config import get_config
|
||||
|
||||
cfg = get_config()
|
||||
listener = PgQueueListener(
|
||||
dsn=asyncpg_dsn_from_sqlalchemy_url(cfg.postgres_url)
|
||||
)
|
||||
|
|
@ -184,10 +59,10 @@ def create_app(*, spawn_worker: bool = True) -> FastAPI:
|
|||
listener = None
|
||||
|
||||
try:
|
||||
worker_task = await _spawn_production_worker(
|
||||
cfg, genai_client, ocr_client, listener
|
||||
)
|
||||
except Exception:
|
||||
from ix.worker.loop import spawn_worker_task
|
||||
|
||||
worker_task = await spawn_worker_task(_app)
|
||||
except ImportError:
|
||||
worker_task = None
|
||||
try:
|
||||
yield
|
||||
|
|
@ -203,30 +78,3 @@ def create_app(*, spawn_worker: bool = True) -> FastAPI:
|
|||
app = FastAPI(lifespan=lifespan, title="infoxtractor", version="0.1.0")
|
||||
app.include_router(rest_router)
|
||||
return app
|
||||
|
||||
|
||||
async def _spawn_production_worker(
|
||||
cfg: AppConfig,
|
||||
genai: GenAIClient,
|
||||
ocr: OCRClient,
|
||||
listener, # type: ignore[no-untyped-def]
|
||||
) -> asyncio.Task[None]:
|
||||
"""Spawn the background worker with a production pipeline factory."""
|
||||
|
||||
from ix.store.engine import get_session_factory
|
||||
from ix.worker.loop import Worker
|
||||
|
||||
def pipeline_factory() -> Pipeline:
|
||||
return build_pipeline(genai, ocr, cfg)
|
||||
|
||||
worker = Worker(
|
||||
session_factory=get_session_factory(),
|
||||
pipeline_factory=pipeline_factory,
|
||||
poll_interval_seconds=10.0,
|
||||
max_running_seconds=2 * cfg.pipeline_request_timeout_seconds,
|
||||
callback_timeout_seconds=cfg.callback_timeout_seconds,
|
||||
wait_for_work=listener.wait_for_work if listener is not None else None,
|
||||
)
|
||||
|
||||
stop = asyncio.Event()
|
||||
return asyncio.create_task(worker.run(stop))
|
||||
|
|
|
|||
|
|
@ -12,7 +12,6 @@ re-read after ``monkeypatch.setenv``. Production code never clears the cache.
|
|||
from __future__ import annotations
|
||||
|
||||
from functools import lru_cache
|
||||
from typing import Literal
|
||||
|
||||
from pydantic_settings import BaseSettings, SettingsConfigDict
|
||||
|
||||
|
|
@ -33,17 +32,14 @@ class AppConfig(BaseSettings):
|
|||
)
|
||||
|
||||
# --- Job store ---
|
||||
# Defaults assume the ix container runs with `network_mode: host` and
|
||||
# reaches the shared `postgis` and `ollama` containers on loopback;
|
||||
# spec §11 / docker-compose.yml ship that configuration.
|
||||
postgres_url: str = (
|
||||
"postgresql+asyncpg://infoxtractor:<password>"
|
||||
"@127.0.0.1:5431/infoxtractor"
|
||||
"@host.docker.internal:5431/infoxtractor"
|
||||
)
|
||||
|
||||
# --- LLM backend ---
|
||||
ollama_url: str = "http://127.0.0.1:11434"
|
||||
default_model: str = "qwen3:14b"
|
||||
ollama_url: str = "http://host.docker.internal:11434"
|
||||
default_model: str = "gpt-oss:20b"
|
||||
|
||||
# --- OCR ---
|
||||
ocr_engine: str = "surya"
|
||||
|
|
@ -66,13 +62,6 @@ class AppConfig(BaseSettings):
|
|||
# --- Observability ---
|
||||
log_level: str = "INFO"
|
||||
|
||||
# --- Test / wiring mode ---
|
||||
# ``fake``: factories return FakeGenAIClient / FakeOCRClient and
|
||||
# ``/healthz`` probes report ok. CI sets this so the Forgejo runner
|
||||
# doesn't need access to Ollama or GPU-backed Surya. ``None`` (default)
|
||||
# means production wiring: real OllamaClient + SuryaOCRClient.
|
||||
test_mode: Literal["fake"] | None = None
|
||||
|
||||
|
||||
@lru_cache(maxsize=1)
|
||||
def get_config() -> AppConfig:
|
||||
|
|
|
|||
|
|
@ -1,43 +1,18 @@
|
|||
"""GenAI subsystem: protocol + fake client + invocation-result dataclasses.
|
||||
|
||||
Real backends (Ollama, …) plug in behind :class:`GenAIClient`. The factory
|
||||
:func:`make_genai_client` picks between :class:`FakeGenAIClient` (for CI
|
||||
/ hermetic tests via ``IX_TEST_MODE=fake``) and :class:`OllamaClient`
|
||||
(production). Tests that want a real Ollama client anyway can call the
|
||||
constructor directly.
|
||||
Real backends (Ollama, etc.) plug in behind :class:`GenAIClient`. The MVP
|
||||
ships only :class:`FakeGenAIClient` from this package; the real Ollama
|
||||
client lands in Chunk 4.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from ix.config import AppConfig
|
||||
from ix.genai.client import GenAIClient, GenAIInvocationResult, GenAIUsage
|
||||
from ix.genai.fake import FakeGenAIClient
|
||||
from ix.genai.ollama_client import OllamaClient
|
||||
|
||||
|
||||
def make_genai_client(cfg: AppConfig) -> GenAIClient:
|
||||
"""Return the :class:`GenAIClient` configured for the current run.
|
||||
|
||||
When ``cfg.test_mode == "fake"`` the fake is returned; the pipeline
|
||||
callers are expected to override the injected client via DI if they
|
||||
want a non-default canned response. Otherwise a live
|
||||
:class:`OllamaClient` bound to ``cfg.ollama_url`` and the per-call
|
||||
timeout is returned.
|
||||
"""
|
||||
|
||||
if cfg.test_mode == "fake":
|
||||
return FakeGenAIClient(parsed=None)
|
||||
return OllamaClient(
|
||||
base_url=cfg.ollama_url,
|
||||
per_call_timeout_s=float(cfg.genai_call_timeout_seconds),
|
||||
)
|
||||
|
||||
|
||||
__all__ = [
|
||||
"FakeGenAIClient",
|
||||
"GenAIClient",
|
||||
"GenAIInvocationResult",
|
||||
"GenAIUsage",
|
||||
"OllamaClient",
|
||||
"make_genai_client",
|
||||
]
|
||||
|
|
|
|||
|
|
@ -1,340 +0,0 @@
|
|||
"""OllamaClient — real :class:`GenAIClient` implementation (spec §6 GenAIStep).
|
||||
|
||||
Wraps the Ollama ``/api/chat`` structured-output endpoint. Per spec:
|
||||
|
||||
* POST ``{base_url}/api/chat`` with ``format = <pydantic JSON schema>``,
|
||||
``stream = false``, and ``options`` carrying provider-neutral knobs
|
||||
(``temperature`` mapped, ``reasoning_effort`` dropped — Ollama ignores it).
|
||||
* Messages are passed through. Content-parts lists (``[{"type":"text",...}]``)
|
||||
are joined to a single string because MVP models (``gpt-oss:20b`` /
|
||||
``qwen2.5:32b``) don't accept native content-parts.
|
||||
* Per-call timeout is enforced via ``httpx``. A connection refusal, read
|
||||
timeout, or 5xx maps to ``IX_002_000``. A 2xx whose ``message.content`` is
|
||||
not valid JSON for the schema maps to ``IX_002_001``.
|
||||
|
||||
``selfcheck()`` targets ``/api/tags`` with a fixed 5 s timeout and is what
|
||||
``/healthz`` consumes.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any, Literal
|
||||
|
||||
import httpx
|
||||
from pydantic import BaseModel, ValidationError
|
||||
|
||||
from ix.errors import IXErrorCode, IXException
|
||||
from ix.genai.client import GenAIInvocationResult, GenAIUsage
|
||||
|
||||
_OLLAMA_TAGS_TIMEOUT_S: float = 5.0
|
||||
_BODY_SNIPPET_MAX_CHARS: int = 240
|
||||
|
||||
|
||||
class OllamaClient:
|
||||
"""Async Ollama backend satisfying :class:`~ix.genai.client.GenAIClient`.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
base_url:
|
||||
Root URL of the Ollama server (e.g. ``http://127.0.0.1:11434``).
|
||||
Trailing slashes are stripped.
|
||||
per_call_timeout_s:
|
||||
Hard per-call timeout for ``/api/chat``. Spec default: 1500 s.
|
||||
"""
|
||||
|
||||
def __init__(self, base_url: str, per_call_timeout_s: float) -> None:
|
||||
self._base_url = base_url.rstrip("/")
|
||||
self._per_call_timeout_s = per_call_timeout_s
|
||||
|
||||
async def invoke(
|
||||
self,
|
||||
request_kwargs: dict[str, Any],
|
||||
response_schema: type[BaseModel],
|
||||
) -> GenAIInvocationResult:
|
||||
"""Run one structured-output chat call; parse into ``response_schema``."""
|
||||
|
||||
body = self._translate_request(request_kwargs, response_schema)
|
||||
url = f"{self._base_url}/api/chat"
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=self._per_call_timeout_s) as http:
|
||||
resp = await http.post(url, json=body)
|
||||
except httpx.HTTPError as exc:
|
||||
raise IXException(
|
||||
IXErrorCode.IX_002_000,
|
||||
detail=f"ollama {exc.__class__.__name__}: {exc}",
|
||||
) from exc
|
||||
except (ConnectionError, TimeoutError) as exc: # pragma: no cover - httpx wraps these
|
||||
raise IXException(
|
||||
IXErrorCode.IX_002_000,
|
||||
detail=f"ollama {exc.__class__.__name__}: {exc}",
|
||||
) from exc
|
||||
|
||||
if resp.status_code >= 500:
|
||||
raise IXException(
|
||||
IXErrorCode.IX_002_000,
|
||||
detail=(
|
||||
f"ollama HTTP {resp.status_code}: "
|
||||
f"{resp.text[:_BODY_SNIPPET_MAX_CHARS]}"
|
||||
),
|
||||
)
|
||||
if resp.status_code >= 400:
|
||||
raise IXException(
|
||||
IXErrorCode.IX_002_000,
|
||||
detail=(
|
||||
f"ollama HTTP {resp.status_code}: "
|
||||
f"{resp.text[:_BODY_SNIPPET_MAX_CHARS]}"
|
||||
),
|
||||
)
|
||||
|
||||
try:
|
||||
payload = resp.json()
|
||||
except ValueError as exc:
|
||||
raise IXException(
|
||||
IXErrorCode.IX_002_000,
|
||||
detail=f"ollama non-JSON body: {resp.text[:_BODY_SNIPPET_MAX_CHARS]}",
|
||||
) from exc
|
||||
|
||||
content = (payload.get("message") or {}).get("content") or ""
|
||||
json_blob = _extract_json_blob(content)
|
||||
try:
|
||||
parsed = response_schema.model_validate_json(json_blob)
|
||||
except ValidationError as exc:
|
||||
raise IXException(
|
||||
IXErrorCode.IX_002_001,
|
||||
detail=(
|
||||
f"{response_schema.__name__}: {exc.__class__.__name__}: "
|
||||
f"body={content[:_BODY_SNIPPET_MAX_CHARS]}"
|
||||
),
|
||||
) from exc
|
||||
except ValueError as exc:
|
||||
# ``model_validate_json`` raises ValueError on invalid JSON (not
|
||||
# a ValidationError). Treat as structured-output failure.
|
||||
raise IXException(
|
||||
IXErrorCode.IX_002_001,
|
||||
detail=(
|
||||
f"{response_schema.__name__}: invalid JSON: "
|
||||
f"body={content[:_BODY_SNIPPET_MAX_CHARS]}"
|
||||
),
|
||||
) from exc
|
||||
|
||||
usage = GenAIUsage(
|
||||
prompt_tokens=int(payload.get("prompt_eval_count") or 0),
|
||||
completion_tokens=int(payload.get("eval_count") or 0),
|
||||
)
|
||||
model_name = str(payload.get("model") or request_kwargs.get("model") or "")
|
||||
return GenAIInvocationResult(parsed=parsed, usage=usage, model_name=model_name)
|
||||
|
||||
async def selfcheck(
|
||||
self, expected_model: str
|
||||
) -> Literal["ok", "degraded", "fail"]:
|
||||
"""Probe ``/api/tags`` for ``/healthz``.
|
||||
|
||||
``ok`` when the server answers 2xx and ``expected_model`` is listed;
|
||||
``degraded`` when reachable but the model is missing; ``fail``
|
||||
otherwise. Spec §5, §11.
|
||||
"""
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=_OLLAMA_TAGS_TIMEOUT_S) as http:
|
||||
resp = await http.get(f"{self._base_url}/api/tags")
|
||||
except (httpx.HTTPError, ConnectionError, TimeoutError):
|
||||
return "fail"
|
||||
|
||||
if resp.status_code != 200:
|
||||
return "fail"
|
||||
|
||||
try:
|
||||
payload = resp.json()
|
||||
except ValueError:
|
||||
return "fail"
|
||||
|
||||
models = payload.get("models") or []
|
||||
names = {str(entry.get("name", "")) for entry in models}
|
||||
if expected_model in names:
|
||||
return "ok"
|
||||
return "degraded"
|
||||
|
||||
def _translate_request(
|
||||
self,
|
||||
request_kwargs: dict[str, Any],
|
||||
response_schema: type[BaseModel],
|
||||
) -> dict[str, Any]:
|
||||
"""Map provider-neutral kwargs to Ollama's /api/chat body.
|
||||
|
||||
Schema strategy for Ollama 0.11.8: we pass ``format="json"`` (loose
|
||||
JSON mode) and bake the Pydantic schema into a system message
|
||||
ahead of the caller's own system prompt. Rationale:
|
||||
|
||||
* The full Pydantic schema as ``format=<schema>`` crashes llama.cpp's
|
||||
structured-output implementation (SIGSEGV) on every non-trivial
|
||||
shape — ``anyOf`` / ``$ref`` / ``pattern`` all trigger it.
|
||||
* ``format="json"`` alone guarantees valid JSON but not the shape;
|
||||
models routinely return ``{}`` when not told what fields to emit.
|
||||
* Injecting the schema into the prompt is the cheapest way to
|
||||
get both: the model sees the expected shape explicitly, Pydantic
|
||||
validates the response at parse time (IX_002_001 on mismatch).
|
||||
|
||||
Non-Ollama ``GenAIClient`` impls can ignore this behaviour and use
|
||||
native structured-output (``response_format`` on OpenAI, etc.).
|
||||
"""
|
||||
|
||||
messages = self._translate_messages(
|
||||
list(request_kwargs.get("messages") or [])
|
||||
)
|
||||
messages = _inject_schema_system_message(messages, response_schema)
|
||||
body: dict[str, Any] = {
|
||||
"model": request_kwargs.get("model"),
|
||||
"messages": messages,
|
||||
"stream": False,
|
||||
# NOTE: format is deliberately omitted. `format="json"` made
|
||||
# reasoning models (qwen3) abort after emitting `{}` because the
|
||||
# constrained sampler terminated before the chain-of-thought
|
||||
# finished; `format=<schema>` segfaulted Ollama 0.11.8. Letting
|
||||
# the model stream freely and then extracting the trailing JSON
|
||||
# blob works for both reasoning and non-reasoning models.
|
||||
}
|
||||
|
||||
options: dict[str, Any] = {}
|
||||
if "temperature" in request_kwargs:
|
||||
options["temperature"] = request_kwargs["temperature"]
|
||||
# reasoning_effort intentionally dropped — Ollama doesn't support it.
|
||||
if options:
|
||||
body["options"] = options
|
||||
return body
|
||||
|
||||
@staticmethod
|
||||
def _translate_messages(
|
||||
messages: list[dict[str, Any]],
|
||||
) -> list[dict[str, Any]]:
|
||||
"""Collapse content-parts lists into single strings for Ollama."""
|
||||
out: list[dict[str, Any]] = []
|
||||
for msg in messages:
|
||||
content = msg.get("content")
|
||||
if isinstance(content, list):
|
||||
text_parts = [
|
||||
str(part.get("text", ""))
|
||||
for part in content
|
||||
if isinstance(part, dict) and part.get("type") == "text"
|
||||
]
|
||||
new_content = "\n".join(text_parts)
|
||||
else:
|
||||
new_content = content
|
||||
out.append({**msg, "content": new_content})
|
||||
return out
|
||||
|
||||
|
||||
def _extract_json_blob(text: str) -> str:
|
||||
"""Return the outermost balanced JSON object in ``text``.
|
||||
|
||||
Reasoning models (qwen3, deepseek-r1) wrap their real answer in
|
||||
``<think>…</think>`` blocks. Other models sometimes prefix prose or
|
||||
fence the JSON in ```json``` code blocks. Finding the last balanced
|
||||
``{…}`` is the cheapest robust parse that works for all three shapes;
|
||||
a malformed response yields the full text and Pydantic catches it
|
||||
downstream as ``IX_002_001``.
|
||||
"""
|
||||
start = text.find("{")
|
||||
if start < 0:
|
||||
return text
|
||||
depth = 0
|
||||
in_string = False
|
||||
escaped = False
|
||||
for i in range(start, len(text)):
|
||||
ch = text[i]
|
||||
if in_string:
|
||||
if escaped:
|
||||
escaped = False
|
||||
elif ch == "\\":
|
||||
escaped = True
|
||||
elif ch == '"':
|
||||
in_string = False
|
||||
continue
|
||||
if ch == '"':
|
||||
in_string = True
|
||||
elif ch == "{":
|
||||
depth += 1
|
||||
elif ch == "}":
|
||||
depth -= 1
|
||||
if depth == 0:
|
||||
return text[start : i + 1]
|
||||
return text[start:]
|
||||
|
||||
|
||||
def _inject_schema_system_message(
|
||||
messages: list[dict[str, Any]],
|
||||
response_schema: type[BaseModel],
|
||||
) -> list[dict[str, Any]]:
|
||||
"""Prepend a system message that pins the expected JSON shape.
|
||||
|
||||
Ollama's ``format="json"`` mode guarantees valid JSON but not the
|
||||
field set or names. We emit the Pydantic schema as JSON and
|
||||
instruct the model to match it. If the caller already provides a
|
||||
system message, we prepend ours; otherwise ours becomes the first
|
||||
system turn.
|
||||
"""
|
||||
import json as _json
|
||||
|
||||
schema_json = _json.dumps(
|
||||
_sanitise_schema_for_ollama(response_schema.model_json_schema()),
|
||||
indent=2,
|
||||
)
|
||||
guidance = (
|
||||
"Respond ONLY with a single JSON object matching this JSON Schema "
|
||||
"exactly. No prose, no code fences, no explanations. All top-level "
|
||||
"properties listed in `required` MUST be present. Use null for "
|
||||
"fields you cannot confidently extract. The JSON Schema:\n"
|
||||
f"{schema_json}"
|
||||
)
|
||||
return [{"role": "system", "content": guidance}, *messages]
|
||||
|
||||
|
||||
def _sanitise_schema_for_ollama(schema: Any) -> Any:
|
||||
"""Strip null branches from ``anyOf`` unions.
|
||||
|
||||
Ollama 0.11.8's llama.cpp structured-output implementation segfaults on
|
||||
Pydantic v2's standard Optional pattern::
|
||||
|
||||
{"anyOf": [{"type": "string"}, {"type": "null"}]}
|
||||
|
||||
We collapse any ``anyOf`` that includes a ``{"type": "null"}`` entry to
|
||||
its non-null branch — single branch becomes that branch inline; multiple
|
||||
branches keep the union without null. This only narrows what the LLM is
|
||||
*told* it may emit; Pydantic still validates the real response and can
|
||||
accept ``None`` at parse time if the field is ``Optional``.
|
||||
|
||||
Walk is recursive and structure-preserving. Other ``anyOf`` shapes (e.g.
|
||||
polymorphic unions without null) are left alone.
|
||||
"""
|
||||
if isinstance(schema, dict):
|
||||
cleaned: dict[str, Any] = {}
|
||||
for key, value in schema.items():
|
||||
if key == "anyOf" and isinstance(value, list):
|
||||
non_null = [
|
||||
_sanitise_schema_for_ollama(branch)
|
||||
for branch in value
|
||||
if not (isinstance(branch, dict) and branch.get("type") == "null")
|
||||
]
|
||||
if len(non_null) == 1:
|
||||
# Inline the single remaining branch; merge its keys into the
|
||||
# parent so siblings like ``default``/``title`` are preserved.
|
||||
only = non_null[0]
|
||||
if isinstance(only, dict):
|
||||
for ok, ov in only.items():
|
||||
cleaned.setdefault(ok, ov)
|
||||
else:
|
||||
cleaned[key] = non_null
|
||||
elif len(non_null) == 0:
|
||||
# Pathological: nothing left. Fall back to a permissive type.
|
||||
cleaned["type"] = "string"
|
||||
else:
|
||||
cleaned[key] = non_null
|
||||
else:
|
||||
cleaned[key] = _sanitise_schema_for_ollama(value)
|
||||
return cleaned
|
||||
if isinstance(schema, list):
|
||||
return [_sanitise_schema_for_ollama(item) for item in schema]
|
||||
return schema
|
||||
|
||||
|
||||
__all__ = ["OllamaClient"]
|
||||
|
|
@ -1,34 +1,13 @@
|
|||
"""OCR subsystem: protocol + fake + real Surya client + factory.
|
||||
"""OCR subsystem: protocol + fake client.
|
||||
|
||||
Real engines (Surya today, Azure DI / AWS Textract … deferred) plug in
|
||||
behind :class:`OCRClient`. The factory :func:`make_ocr_client` picks
|
||||
between :class:`FakeOCRClient` (when ``IX_TEST_MODE=fake``) and
|
||||
:class:`SuryaOCRClient` (production). Unknown engine names raise so a
|
||||
typo'd ``IX_OCR_ENGINE`` surfaces at startup, not later.
|
||||
Real engines (Surya, Azure DI, …) plug in behind :class:`OCRClient`. The
|
||||
MVP ships only :class:`FakeOCRClient` from this package; the real Surya
|
||||
client lands in Chunk 4.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from ix.config import AppConfig
|
||||
from ix.contracts.response import OCRDetails, OCRResult
|
||||
from ix.ocr.client import OCRClient
|
||||
from ix.ocr.fake import FakeOCRClient
|
||||
from ix.ocr.surya_client import SuryaOCRClient
|
||||
|
||||
|
||||
def make_ocr_client(cfg: AppConfig) -> OCRClient:
|
||||
"""Return the :class:`OCRClient` configured for the current run."""
|
||||
|
||||
if cfg.test_mode == "fake":
|
||||
return FakeOCRClient(canned=OCRResult(result=OCRDetails()))
|
||||
if cfg.ocr_engine == "surya":
|
||||
return SuryaOCRClient()
|
||||
raise ValueError(f"Unknown ocr_engine: {cfg.ocr_engine!r}")
|
||||
|
||||
|
||||
__all__ = [
|
||||
"FakeOCRClient",
|
||||
"OCRClient",
|
||||
"SuryaOCRClient",
|
||||
"make_ocr_client",
|
||||
]
|
||||
__all__ = ["FakeOCRClient", "OCRClient"]
|
||||
|
|
|
|||
|
|
@ -5,19 +5,11 @@ method satisfies the Protocol. :class:`~ix.pipeline.ocr_step.OCRStep`
|
|||
depends on the Protocol, not a concrete class, so swapping engines
|
||||
(``FakeOCRClient`` in tests, ``SuryaOCRClient`` in prod) stays a wiring
|
||||
change at the app factory.
|
||||
|
||||
Per-page source location (``files`` + ``page_metadata``) flows in as
|
||||
optional kwargs: fakes ignore them; the real
|
||||
:class:`~ix.ocr.surya_client.SuryaOCRClient` uses them to render each
|
||||
page's pixels back from disk. Keeping these optional lets unit tests stay
|
||||
pages-only while production wiring (Task 4.3) plumbs through the real
|
||||
filesystem handles.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Any, Protocol, runtime_checkable
|
||||
from typing import Protocol, runtime_checkable
|
||||
|
||||
from ix.contracts import OCRResult, Page
|
||||
|
||||
|
|
@ -32,18 +24,8 @@ class OCRClient(Protocol):
|
|||
per input page (in the same order).
|
||||
"""
|
||||
|
||||
async def ocr(
|
||||
self,
|
||||
pages: list[Page],
|
||||
*,
|
||||
files: list[tuple[Path, str]] | None = None,
|
||||
page_metadata: list[Any] | None = None,
|
||||
) -> OCRResult:
|
||||
"""Run OCR over the input pages; return the structured result.
|
||||
|
||||
``files`` and ``page_metadata`` are optional for hermetic tests;
|
||||
real engines that need to re-render from disk read them.
|
||||
"""
|
||||
async def ocr(self, pages: list[Page]) -> OCRResult:
|
||||
"""Run OCR over the input pages; return the structured result."""
|
||||
...
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -30,17 +30,8 @@ class FakeOCRClient:
|
|||
self._canned = canned
|
||||
self._raise_on_call = raise_on_call
|
||||
|
||||
async def ocr(
|
||||
self,
|
||||
pages: list[Page],
|
||||
**_kwargs: object,
|
||||
) -> OCRResult:
|
||||
"""Return the canned result or raise the configured error.
|
||||
|
||||
Accepts (and ignores) any keyword args the production Protocol may
|
||||
carry — keeps the fake swappable for :class:`SuryaOCRClient` at
|
||||
call sites that pass ``files`` / ``page_metadata``.
|
||||
"""
|
||||
async def ocr(self, pages: list[Page]) -> OCRResult:
|
||||
"""Return the canned result or raise the configured error."""
|
||||
if self._raise_on_call is not None:
|
||||
raise self._raise_on_call
|
||||
return self._canned
|
||||
|
|
|
|||
|
|
@ -1,235 +0,0 @@
|
|||
"""SuryaOCRClient — real :class:`OCRClient` backed by ``surya-ocr``.
|
||||
|
||||
Per spec §6.2: the MVP OCR engine. Runs Surya's detection + recognition
|
||||
predictors over per-page PIL images rendered from the downloaded sources
|
||||
(PDFs via PyMuPDF, images via Pillow).
|
||||
|
||||
Design choices:
|
||||
|
||||
* **Lazy model loading.** ``__init__`` is cheap; the heavy predictors are
|
||||
built on first :meth:`ocr` / :meth:`selfcheck` / explicit :meth:`warm_up`.
|
||||
This keeps FastAPI's lifespan predictable — ops can decide whether to
|
||||
pay the load cost up front or on first request.
|
||||
* **Device is Surya's default.** CUDA on the prod box, MPS on M-series Macs.
|
||||
We deliberately don't pin.
|
||||
* **No text-token reuse from PyMuPDF.** The cross-check against Paperless'
|
||||
Tesseract output (ReliabilityStep's ``text_agreement``) is only meaningful
|
||||
with a truly independent OCR pass, so we always render-and-recognize
|
||||
even for PDFs that carry embedded text.
|
||||
|
||||
The ``surya-ocr`` package pulls torch + heavy model deps, so it's kept
|
||||
behind the ``[ocr]`` extra. All Surya imports are deferred into
|
||||
:meth:`warm_up` so running the unit tests (which patch the predictors)
|
||||
doesn't require the package to be installed.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import contextlib
|
||||
from pathlib import Path
|
||||
from typing import TYPE_CHECKING, Any, Literal
|
||||
|
||||
from ix.contracts import Line, OCRDetails, OCRResult, Page
|
||||
from ix.segmentation import PageMetadata
|
||||
|
||||
if TYPE_CHECKING: # pragma: no cover
|
||||
from PIL import Image as PILImage
|
||||
|
||||
|
||||
class SuryaOCRClient:
|
||||
"""Surya-backed OCR engine.
|
||||
|
||||
Attributes are created lazily by :meth:`warm_up`. The unit tests inject
|
||||
mocks directly onto ``_recognition_predictor`` / ``_detection_predictor``
|
||||
to avoid the Surya import chain.
|
||||
"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self._recognition_predictor: Any = None
|
||||
self._detection_predictor: Any = None
|
||||
|
||||
def warm_up(self) -> None:
|
||||
"""Load the detection + recognition predictors. Idempotent.
|
||||
|
||||
Called automatically on the first :meth:`ocr` / :meth:`selfcheck`,
|
||||
or explicitly from the app lifespan to front-load the cost.
|
||||
"""
|
||||
if (
|
||||
self._recognition_predictor is not None
|
||||
and self._detection_predictor is not None
|
||||
):
|
||||
return
|
||||
|
||||
# Deferred imports: only reachable when the optional [ocr] extra is
|
||||
# installed. Keeping them inside the method so base-install unit
|
||||
# tests (which patch the predictors) don't need surya on sys.path.
|
||||
from surya.detection import DetectionPredictor # type: ignore[import-not-found]
|
||||
from surya.foundation import FoundationPredictor # type: ignore[import-not-found]
|
||||
from surya.recognition import RecognitionPredictor # type: ignore[import-not-found]
|
||||
|
||||
foundation = FoundationPredictor()
|
||||
self._recognition_predictor = RecognitionPredictor(foundation)
|
||||
self._detection_predictor = DetectionPredictor()
|
||||
|
||||
async def ocr(
|
||||
self,
|
||||
pages: list[Page],
|
||||
*,
|
||||
files: list[tuple[Path, str]] | None = None,
|
||||
page_metadata: list[Any] | None = None,
|
||||
) -> OCRResult:
|
||||
"""Render each input page, run Surya, translate back to contracts."""
|
||||
self.warm_up()
|
||||
|
||||
images = self._render_pages(pages, files, page_metadata)
|
||||
|
||||
# Surya is blocking — run it off the event loop.
|
||||
loop = asyncio.get_running_loop()
|
||||
surya_results = await loop.run_in_executor(
|
||||
None, self._run_recognition, images
|
||||
)
|
||||
|
||||
out_pages: list[Page] = []
|
||||
all_text_fragments: list[str] = []
|
||||
for input_page, surya_result in zip(pages, surya_results, strict=True):
|
||||
lines: list[Line] = []
|
||||
for tl in getattr(surya_result, "text_lines", []) or []:
|
||||
flat = self._flatten_polygon(getattr(tl, "polygon", None))
|
||||
text = getattr(tl, "text", None)
|
||||
lines.append(Line(text=text, bounding_box=flat))
|
||||
if text:
|
||||
all_text_fragments.append(text)
|
||||
out_pages.append(
|
||||
Page(
|
||||
page_no=input_page.page_no,
|
||||
width=input_page.width,
|
||||
height=input_page.height,
|
||||
angle=input_page.angle,
|
||||
unit=input_page.unit,
|
||||
lines=lines,
|
||||
)
|
||||
)
|
||||
|
||||
details = OCRDetails(
|
||||
text="\n".join(all_text_fragments) if all_text_fragments else None,
|
||||
pages=out_pages,
|
||||
)
|
||||
return OCRResult(result=details, meta_data={"engine": "surya"})
|
||||
|
||||
async def selfcheck(self) -> Literal["ok", "fail"]:
|
||||
"""Run the predictors on a 1x1 image to confirm the stack works."""
|
||||
try:
|
||||
self.warm_up()
|
||||
except Exception:
|
||||
return "fail"
|
||||
|
||||
try:
|
||||
from PIL import Image as PILImageRuntime
|
||||
|
||||
img = PILImageRuntime.new("RGB", (1, 1), color="white")
|
||||
loop = asyncio.get_running_loop()
|
||||
await loop.run_in_executor(None, self._run_recognition, [img])
|
||||
except Exception:
|
||||
return "fail"
|
||||
return "ok"
|
||||
|
||||
def _run_recognition(self, images: list[PILImage.Image]) -> list[Any]:
|
||||
"""Invoke the recognition predictor. Kept tiny for threadpool offload."""
|
||||
return list(
|
||||
self._recognition_predictor(
|
||||
images, det_predictor=self._detection_predictor
|
||||
)
|
||||
)
|
||||
|
||||
def _render_pages(
|
||||
self,
|
||||
pages: list[Page],
|
||||
files: list[tuple[Path, str]] | None,
|
||||
page_metadata: list[Any] | None,
|
||||
) -> list[PILImage.Image]:
|
||||
"""Render each input :class:`Page` to a PIL image.
|
||||
|
||||
We walk pages + page_metadata in lockstep so we know which source
|
||||
file each page came from and (for PDFs) what page-index to render.
|
||||
Text-only pages (``file_index is None``) get a blank 1x1 placeholder
|
||||
so Surya returns an empty result and downstream code still gets one
|
||||
entry per input page.
|
||||
"""
|
||||
from PIL import Image as PILImageRuntime
|
||||
|
||||
metas: list[PageMetadata] = list(page_metadata or [])
|
||||
file_records: list[tuple[Path, str]] = list(files or [])
|
||||
|
||||
# Per-file lazy PDF openers so we don't re-open across pages.
|
||||
pdf_docs: dict[int, Any] = {}
|
||||
|
||||
# Per-file running page-within-file counter. For PDFs we emit one
|
||||
# entry per PDF page in order; ``pages`` was built the same way by
|
||||
# DocumentIngestor, so a parallel counter reconstructs the mapping.
|
||||
per_file_cursor: dict[int, int] = {}
|
||||
|
||||
rendered: list[PILImage.Image] = []
|
||||
try:
|
||||
for idx, _page in enumerate(pages):
|
||||
meta = metas[idx] if idx < len(metas) else PageMetadata()
|
||||
file_index = meta.file_index
|
||||
if file_index is None or file_index >= len(file_records):
|
||||
# Text-only page — placeholder image; Surya returns empty.
|
||||
rendered.append(
|
||||
PILImageRuntime.new("RGB", (1, 1), color="white")
|
||||
)
|
||||
continue
|
||||
|
||||
local_path, mime = file_records[file_index]
|
||||
if mime == "application/pdf":
|
||||
doc = pdf_docs.get(file_index)
|
||||
if doc is None:
|
||||
import fitz # PyMuPDF
|
||||
|
||||
doc = fitz.open(str(local_path))
|
||||
pdf_docs[file_index] = doc
|
||||
pdf_page_no = per_file_cursor.get(file_index, 0)
|
||||
per_file_cursor[file_index] = pdf_page_no + 1
|
||||
pdf_page = doc.load_page(pdf_page_no)
|
||||
pix = pdf_page.get_pixmap(dpi=200)
|
||||
img = PILImageRuntime.frombytes(
|
||||
"RGB", (pix.width, pix.height), pix.samples
|
||||
)
|
||||
rendered.append(img)
|
||||
elif mime in ("image/png", "image/jpeg", "image/tiff"):
|
||||
frame_no = per_file_cursor.get(file_index, 0)
|
||||
per_file_cursor[file_index] = frame_no + 1
|
||||
img = PILImageRuntime.open(local_path)
|
||||
# Handle multi-frame (TIFF) — seek to the right frame.
|
||||
with contextlib.suppress(EOFError):
|
||||
img.seek(frame_no)
|
||||
rendered.append(img.convert("RGB"))
|
||||
else: # pragma: no cover - ingestor already rejected
|
||||
rendered.append(
|
||||
PILImageRuntime.new("RGB", (1, 1), color="white")
|
||||
)
|
||||
finally:
|
||||
for doc in pdf_docs.values():
|
||||
with contextlib.suppress(Exception):
|
||||
doc.close()
|
||||
return rendered
|
||||
|
||||
@staticmethod
|
||||
def _flatten_polygon(polygon: Any) -> list[float]:
|
||||
"""Flatten ``[[x1,y1],[x2,y2],[x3,y3],[x4,y4]]`` → 8-float list.
|
||||
|
||||
Surya emits 4 quad corners. The spec wants 8 raw-pixel coords so
|
||||
downstream provenance normalisation can consume them directly.
|
||||
"""
|
||||
if not polygon:
|
||||
return []
|
||||
flat: list[float] = []
|
||||
for point in polygon:
|
||||
if isinstance(point, (list, tuple)) and len(point) >= 2:
|
||||
flat.append(float(point[0]))
|
||||
flat.append(float(point[1]))
|
||||
return flat
|
||||
|
||||
|
||||
__all__ = ["SuryaOCRClient"]
|
||||
|
|
@ -56,11 +56,7 @@ class OCRStep(Step):
|
|||
assert ctx is not None, "SetupStep must populate response_ix.context"
|
||||
|
||||
pages = list(getattr(ctx, "pages", []))
|
||||
files = list(getattr(ctx, "files", []) or [])
|
||||
page_metadata = list(getattr(ctx, "page_metadata", []) or [])
|
||||
ocr_result = await self._client.ocr(
|
||||
pages, files=files, page_metadata=page_metadata
|
||||
)
|
||||
ocr_result = await self._client.ocr(pages)
|
||||
|
||||
# Inject page tags around each OCR page's content so the LLM can
|
||||
# cross-reference the visual anchor without a separate prompt hack.
|
||||
|
|
|
|||
|
|
@ -26,7 +26,7 @@ class Request(BaseModel):
|
|||
model_config = ConfigDict(extra="forbid")
|
||||
|
||||
use_case_name: str = "Bank Statement Header"
|
||||
default_model: str = "qwen3:14b"
|
||||
default_model: str = "gpt-oss:20b"
|
||||
system_prompt: str = (
|
||||
"You extract header metadata from a single bank or credit-card statement. "
|
||||
"Return only facts that appear in the document; leave a field null if uncertain. "
|
||||
|
|
|
|||
|
|
@ -28,6 +28,8 @@ from collections.abc import Callable
|
|||
from datetime import UTC, datetime
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from fastapi import FastAPI
|
||||
|
||||
from ix.contracts.response import ResponseIX
|
||||
from ix.errors import IXErrorCode, IXException
|
||||
from ix.pipeline.pipeline import Pipeline
|
||||
|
|
@ -177,3 +179,17 @@ class Worker:
|
|||
await session.commit()
|
||||
|
||||
|
||||
async def spawn_worker_task(app: FastAPI): # type: ignore[no-untyped-def]
|
||||
"""Hook called from the FastAPI lifespan (Task 3.4).
|
||||
|
||||
This module-level async function is here so ``ix.app`` can import it
|
||||
lazily without the app factory depending on the worker at import time.
|
||||
Production wiring (Chunk 4) constructs a real Pipeline; for now we
|
||||
build a no-op pipeline so the import chain completes. Tests that need
|
||||
the worker wire their own Worker explicitly.
|
||||
"""
|
||||
|
||||
# NOTE: the real spawn is done by explicit test fixtures / a production
|
||||
# wiring layer in Chunk 4. We return None so the lifespan's cleanup
|
||||
# branch is a no-op; the app still runs REST fine without a worker.
|
||||
return None
|
||||
|
|
|
|||
|
|
@ -1,70 +0,0 @@
|
|||
"""Live tests for :class:`OllamaClient` — gated on ``IX_TEST_OLLAMA=1``.
|
||||
|
||||
Never runs in CI (Forgejo runner has no LAN access to Ollama). Run locally::
|
||||
|
||||
IX_TEST_OLLAMA=1 uv run pytest tests/live/test_ollama_client_live.py -v
|
||||
|
||||
Assumes the Ollama server at ``http://192.168.68.42:11434`` already has
|
||||
``qwen3:14b`` pulled.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
|
||||
import pytest
|
||||
|
||||
from ix.genai.ollama_client import OllamaClient
|
||||
from ix.use_cases.bank_statement_header import BankStatementHeader
|
||||
|
||||
pytestmark = [
|
||||
pytest.mark.live,
|
||||
pytest.mark.skipif(
|
||||
os.environ.get("IX_TEST_OLLAMA") != "1",
|
||||
reason="live: IX_TEST_OLLAMA=1 required",
|
||||
),
|
||||
]
|
||||
|
||||
_OLLAMA_URL = "http://192.168.68.42:11434"
|
||||
_MODEL = "qwen3:14b"
|
||||
|
||||
|
||||
async def test_structured_output_round_trip() -> None:
|
||||
"""Real Ollama returns a parsed BankStatementHeader instance."""
|
||||
client = OllamaClient(base_url=_OLLAMA_URL, per_call_timeout_s=300.0)
|
||||
result = await client.invoke(
|
||||
request_kwargs={
|
||||
"model": _MODEL,
|
||||
"messages": [
|
||||
{
|
||||
"role": "system",
|
||||
"content": (
|
||||
"You extract bank statement header fields. "
|
||||
"Return valid JSON matching the given schema. "
|
||||
"Do not invent values."
|
||||
),
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": (
|
||||
"Bank: Deutsche Kreditbank (DKB)\n"
|
||||
"Currency: EUR\n"
|
||||
"IBAN: DE89370400440532013000\n"
|
||||
"Period: 2025-01-01 to 2025-01-31"
|
||||
),
|
||||
},
|
||||
],
|
||||
},
|
||||
response_schema=BankStatementHeader,
|
||||
)
|
||||
assert isinstance(result.parsed, BankStatementHeader)
|
||||
assert isinstance(result.parsed.bank_name, str)
|
||||
assert result.parsed.bank_name # non-empty
|
||||
assert isinstance(result.parsed.currency, str)
|
||||
assert result.model_name # server echoes a model name
|
||||
|
||||
|
||||
async def test_selfcheck_ok_against_real_server() -> None:
|
||||
"""``selfcheck`` returns ``ok`` when the target model is pulled."""
|
||||
client = OllamaClient(base_url=_OLLAMA_URL, per_call_timeout_s=5.0)
|
||||
assert await client.selfcheck(expected_model=_MODEL) == "ok"
|
||||
|
|
@ -1,83 +0,0 @@
|
|||
"""Live test for :class:`SuryaOCRClient` — gated on ``IX_TEST_OLLAMA=1``.
|
||||
|
||||
Downloads real Surya models (hundreds of MB) on first run. Never runs in
|
||||
CI. Exercised locally with::
|
||||
|
||||
IX_TEST_OLLAMA=1 uv run pytest tests/live/test_surya_client_live.py -v
|
||||
|
||||
Note: requires the ``[ocr]`` extra — ``uv sync --extra ocr --extra dev``.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from ix.contracts import Page
|
||||
from ix.segmentation import PageMetadata
|
||||
|
||||
pytestmark = [
|
||||
pytest.mark.live,
|
||||
pytest.mark.skipif(
|
||||
os.environ.get("IX_TEST_OLLAMA") != "1",
|
||||
reason="live: IX_TEST_OLLAMA=1 required",
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
async def test_extracts_dkb_and_iban_from_synthetic_giro() -> None:
|
||||
"""Real Surya run against ``tests/fixtures/synthetic_giro.pdf``.
|
||||
|
||||
Assert the flat text contains ``"DKB"`` and the IBAN without spaces.
|
||||
"""
|
||||
from ix.ocr.surya_client import SuryaOCRClient
|
||||
|
||||
fixture = Path(__file__).parent.parent / "fixtures" / "synthetic_giro.pdf"
|
||||
assert fixture.exists(), f"missing fixture: {fixture}"
|
||||
|
||||
# Build Pages the way DocumentIngestor would for this PDF: count pages
|
||||
# via PyMuPDF so we pass the right number of inputs.
|
||||
import fitz
|
||||
|
||||
doc = fitz.open(str(fixture))
|
||||
try:
|
||||
pages = [
|
||||
Page(
|
||||
page_no=i + 1,
|
||||
width=float(p.rect.width),
|
||||
height=float(p.rect.height),
|
||||
lines=[],
|
||||
)
|
||||
for i, p in enumerate(doc)
|
||||
]
|
||||
finally:
|
||||
doc.close()
|
||||
|
||||
client = SuryaOCRClient()
|
||||
result = await client.ocr(
|
||||
pages,
|
||||
files=[(fixture, "application/pdf")],
|
||||
page_metadata=[PageMetadata(file_index=0) for _ in pages],
|
||||
)
|
||||
|
||||
flat_text = result.result.text or ""
|
||||
# Join page-level line texts if flat text missing (shape-safety).
|
||||
if not flat_text:
|
||||
flat_text = "\n".join(
|
||||
line.text or ""
|
||||
for page in result.result.pages
|
||||
for line in page.lines
|
||||
)
|
||||
|
||||
assert "DKB" in flat_text
|
||||
assert "DE89370400440532013000" in flat_text.replace(" ", "")
|
||||
|
||||
|
||||
async def test_selfcheck_ok_against_real_predictors() -> None:
|
||||
"""``selfcheck()`` returns ``ok`` once Surya's predictors load."""
|
||||
from ix.ocr.surya_client import SuryaOCRClient
|
||||
|
||||
client = SuryaOCRClient()
|
||||
assert await client.selfcheck() == "ok"
|
||||
|
|
@ -1,104 +0,0 @@
|
|||
"""Tests for ``ix.app`` lifespan / probe wiring (Task 4.3).
|
||||
|
||||
The lifespan selects fake clients when ``IX_TEST_MODE=fake`` and exposes
|
||||
their probes via the route DI hook. These tests exercise the probe
|
||||
adapter in isolation — no DB, no real Ollama/Surya.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Literal
|
||||
|
||||
from ix.app import _make_ocr_probe, _make_ollama_probe, build_pipeline
|
||||
from ix.config import AppConfig
|
||||
from ix.genai.fake import FakeGenAIClient
|
||||
from ix.ocr.fake import FakeOCRClient
|
||||
from ix.pipeline.genai_step import GenAIStep
|
||||
from ix.pipeline.ocr_step import OCRStep
|
||||
from ix.pipeline.pipeline import Pipeline
|
||||
from ix.pipeline.reliability_step import ReliabilityStep
|
||||
from ix.pipeline.response_handler_step import ResponseHandlerStep
|
||||
from ix.pipeline.setup_step import SetupStep
|
||||
|
||||
|
||||
def _cfg(**overrides: object) -> AppConfig:
|
||||
return AppConfig(_env_file=None, **overrides) # type: ignore[call-arg]
|
||||
|
||||
|
||||
class _SelfcheckOllamaClient:
|
||||
async def invoke(self, *a: object, **kw: object) -> object:
|
||||
raise NotImplementedError
|
||||
|
||||
async def selfcheck(
|
||||
self, expected_model: str
|
||||
) -> Literal["ok", "degraded", "fail"]:
|
||||
self.called_with = expected_model
|
||||
return "ok"
|
||||
|
||||
|
||||
class _SelfcheckOCRClient:
|
||||
async def ocr(self, *a: object, **kw: object) -> object:
|
||||
raise NotImplementedError
|
||||
|
||||
async def selfcheck(self) -> Literal["ok", "fail"]:
|
||||
return "ok"
|
||||
|
||||
|
||||
class _BrokenSelfcheckOllama:
|
||||
async def invoke(self, *a: object, **kw: object) -> object:
|
||||
raise NotImplementedError
|
||||
|
||||
async def selfcheck(
|
||||
self, expected_model: str
|
||||
) -> Literal["ok", "degraded", "fail"]:
|
||||
raise RuntimeError("boom")
|
||||
|
||||
|
||||
class TestOllamaProbe:
|
||||
def test_fake_client_without_selfcheck_reports_ok(self) -> None:
|
||||
cfg = _cfg(test_mode="fake", default_model="gpt-oss:20b")
|
||||
probe = _make_ollama_probe(FakeGenAIClient(parsed=None), cfg)
|
||||
assert probe() == "ok"
|
||||
|
||||
def test_real_selfcheck_returns_its_verdict(self) -> None:
|
||||
cfg = _cfg(default_model="gpt-oss:20b")
|
||||
client = _SelfcheckOllamaClient()
|
||||
probe = _make_ollama_probe(client, cfg) # type: ignore[arg-type]
|
||||
assert probe() == "ok"
|
||||
assert client.called_with == "gpt-oss:20b"
|
||||
|
||||
def test_selfcheck_exception_falls_back_to_fail(self) -> None:
|
||||
cfg = _cfg(default_model="gpt-oss:20b")
|
||||
probe = _make_ollama_probe(_BrokenSelfcheckOllama(), cfg) # type: ignore[arg-type]
|
||||
assert probe() == "fail"
|
||||
|
||||
|
||||
class TestOCRProbe:
|
||||
def test_fake_client_without_selfcheck_reports_ok(self) -> None:
|
||||
from ix.contracts.response import OCRDetails, OCRResult
|
||||
|
||||
probe = _make_ocr_probe(FakeOCRClient(canned=OCRResult(result=OCRDetails())))
|
||||
assert probe() == "ok"
|
||||
|
||||
def test_real_selfcheck_returns_its_verdict(self) -> None:
|
||||
probe = _make_ocr_probe(_SelfcheckOCRClient()) # type: ignore[arg-type]
|
||||
assert probe() == "ok"
|
||||
|
||||
|
||||
class TestBuildPipeline:
|
||||
def test_assembles_all_five_steps_in_order(self) -> None:
|
||||
from ix.contracts.response import OCRDetails, OCRResult
|
||||
|
||||
genai = FakeGenAIClient(parsed=None)
|
||||
ocr = FakeOCRClient(canned=OCRResult(result=OCRDetails()))
|
||||
cfg = _cfg(test_mode="fake")
|
||||
pipeline = build_pipeline(genai, ocr, cfg)
|
||||
assert isinstance(pipeline, Pipeline)
|
||||
steps = pipeline._steps # type: ignore[attr-defined]
|
||||
assert [type(s) for s in steps] == [
|
||||
SetupStep,
|
||||
OCRStep,
|
||||
GenAIStep,
|
||||
ReliabilityStep,
|
||||
ResponseHandlerStep,
|
||||
]
|
||||
|
|
@ -51,10 +51,10 @@ def test_defaults_match_spec(monkeypatch: pytest.MonkeyPatch) -> None:
|
|||
|
||||
assert cfg.postgres_url == (
|
||||
"postgresql+asyncpg://infoxtractor:<password>"
|
||||
"@127.0.0.1:5431/infoxtractor"
|
||||
"@host.docker.internal:5431/infoxtractor"
|
||||
)
|
||||
assert cfg.ollama_url == "http://127.0.0.1:11434"
|
||||
assert cfg.default_model == "qwen3:14b"
|
||||
assert cfg.ollama_url == "http://host.docker.internal:11434"
|
||||
assert cfg.default_model == "gpt-oss:20b"
|
||||
assert cfg.ocr_engine == "surya"
|
||||
assert cfg.tmp_dir == "/tmp/ix"
|
||||
assert cfg.pipeline_worker_concurrency == 1
|
||||
|
|
|
|||
|
|
@ -1,60 +0,0 @@
|
|||
"""Tests for the GenAI + OCR factories (Task 4.3).
|
||||
|
||||
The factories pick between fake and real clients based on
|
||||
``IX_TEST_MODE``. CI runs with ``IX_TEST_MODE=fake``, production runs
|
||||
without — so the selection knob is the one lever between hermetic CI and
|
||||
real clients.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from ix.config import AppConfig
|
||||
from ix.genai import make_genai_client
|
||||
from ix.genai.fake import FakeGenAIClient
|
||||
from ix.genai.ollama_client import OllamaClient
|
||||
from ix.ocr import make_ocr_client
|
||||
from ix.ocr.fake import FakeOCRClient
|
||||
from ix.ocr.surya_client import SuryaOCRClient
|
||||
|
||||
|
||||
def _cfg(**overrides: object) -> AppConfig:
|
||||
"""Build an AppConfig without loading the repo's .env.example."""
|
||||
return AppConfig(_env_file=None, **overrides) # type: ignore[call-arg]
|
||||
|
||||
|
||||
class TestGenAIFactory:
|
||||
def test_fake_mode_returns_fake(self) -> None:
|
||||
cfg = _cfg(test_mode="fake")
|
||||
client = make_genai_client(cfg)
|
||||
assert isinstance(client, FakeGenAIClient)
|
||||
|
||||
def test_production_returns_ollama_with_configured_url(self) -> None:
|
||||
cfg = _cfg(
|
||||
test_mode=None,
|
||||
ollama_url="http://ollama.host:11434",
|
||||
genai_call_timeout_seconds=42,
|
||||
)
|
||||
client = make_genai_client(cfg)
|
||||
assert isinstance(client, OllamaClient)
|
||||
# Inspect the private attrs for binding correctness.
|
||||
assert client._base_url == "http://ollama.host:11434"
|
||||
assert client._per_call_timeout_s == 42
|
||||
|
||||
|
||||
class TestOCRFactory:
|
||||
def test_fake_mode_returns_fake(self) -> None:
|
||||
cfg = _cfg(test_mode="fake")
|
||||
client = make_ocr_client(cfg)
|
||||
assert isinstance(client, FakeOCRClient)
|
||||
|
||||
def test_production_surya_returns_surya(self) -> None:
|
||||
cfg = _cfg(test_mode=None, ocr_engine="surya")
|
||||
client = make_ocr_client(cfg)
|
||||
assert isinstance(client, SuryaOCRClient)
|
||||
|
||||
def test_unknown_engine_raises(self) -> None:
|
||||
cfg = _cfg(test_mode=None, ocr_engine="tesseract")
|
||||
import pytest
|
||||
|
||||
with pytest.raises(ValueError, match="ocr_engine"):
|
||||
make_ocr_client(cfg)
|
||||
|
|
@ -363,8 +363,8 @@ class TestModelSelection:
|
|||
req = _make_request(include_provenance=False)
|
||||
resp = _response_with_segment_index(lines=["hello"])
|
||||
await step.process(req, resp)
|
||||
# use-case default is qwen3:14b
|
||||
assert client.request_kwargs["model"] == "qwen3:14b" # type: ignore[index]
|
||||
# use-case default is gpt-oss:20b
|
||||
assert client.request_kwargs["model"] == "gpt-oss:20b" # type: ignore[index]
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
|
|
|
|||
|
|
@ -1,270 +0,0 @@
|
|||
"""Tests for :class:`OllamaClient` — hermetic, pytest-httpx-driven.
|
||||
|
||||
Covers spec §6 GenAIStep Ollama call contract:
|
||||
|
||||
* POST body shape (model / messages / format / stream / options).
|
||||
* Response parsing → :class:`GenAIInvocationResult`.
|
||||
* Error mapping: connection / timeout / 5xx → ``IX_002_000``;
|
||||
schema-violating body → ``IX_002_001``.
|
||||
* ``selfcheck()``: tags-reachable + model-listed → ``ok``;
|
||||
reachable-but-missing → ``degraded``; unreachable → ``fail``.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import httpx
|
||||
import pytest
|
||||
from pydantic import BaseModel
|
||||
from pytest_httpx import HTTPXMock
|
||||
|
||||
from ix.errors import IXErrorCode, IXException
|
||||
from ix.genai.ollama_client import OllamaClient
|
||||
|
||||
|
||||
class _Schema(BaseModel):
|
||||
"""Trivial structured-output schema for the round-trip tests."""
|
||||
|
||||
bank_name: str
|
||||
account_number: str | None = None
|
||||
|
||||
|
||||
def _ollama_chat_ok_body(content_json: str) -> dict:
|
||||
"""Build a minimal Ollama /api/chat success body."""
|
||||
return {
|
||||
"model": "gpt-oss:20b",
|
||||
"message": {"role": "assistant", "content": content_json},
|
||||
"done": True,
|
||||
"eval_count": 42,
|
||||
"prompt_eval_count": 17,
|
||||
}
|
||||
|
||||
|
||||
class TestInvokeHappyPath:
|
||||
async def test_posts_to_chat_endpoint_with_format_and_no_stream(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_response(
|
||||
url="http://ollama.test:11434/api/chat",
|
||||
method="POST",
|
||||
json=_ollama_chat_ok_body('{"bank_name":"DKB","account_number":"DE89"}'),
|
||||
)
|
||||
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
result = await client.invoke(
|
||||
request_kwargs={
|
||||
"model": "gpt-oss:20b",
|
||||
"messages": [
|
||||
{"role": "system", "content": "You extract."},
|
||||
{"role": "user", "content": "Doc body"},
|
||||
],
|
||||
"temperature": 0.2,
|
||||
"reasoning_effort": "high", # dropped silently
|
||||
},
|
||||
response_schema=_Schema,
|
||||
)
|
||||
|
||||
assert result.parsed == _Schema(bank_name="DKB", account_number="DE89")
|
||||
assert result.model_name == "gpt-oss:20b"
|
||||
assert result.usage.prompt_tokens == 17
|
||||
assert result.usage.completion_tokens == 42
|
||||
|
||||
# Verify request shape.
|
||||
requests = httpx_mock.get_requests()
|
||||
assert len(requests) == 1
|
||||
body = requests[0].read().decode()
|
||||
import json
|
||||
|
||||
body_json = json.loads(body)
|
||||
assert body_json["model"] == "gpt-oss:20b"
|
||||
assert body_json["stream"] is False
|
||||
# No `format` is sent: Ollama 0.11.8 segfaults on full schemas and
|
||||
# aborts to `{}` with `format=json` on reasoning models. Schema is
|
||||
# injected into the system prompt instead; we extract the trailing
|
||||
# JSON blob from the response and validate via Pydantic.
|
||||
assert "format" not in body_json
|
||||
assert body_json["options"]["temperature"] == 0.2
|
||||
assert "reasoning_effort" not in body_json
|
||||
# A schema-guidance system message is prepended to the caller's
|
||||
# messages so Ollama (format=json loose mode) emits the right shape.
|
||||
msgs = body_json["messages"]
|
||||
assert msgs[0]["role"] == "system"
|
||||
assert "JSON Schema" in msgs[0]["content"]
|
||||
assert msgs[1:] == [
|
||||
{"role": "system", "content": "You extract."},
|
||||
{"role": "user", "content": "Doc body"},
|
||||
]
|
||||
|
||||
async def test_text_parts_content_list_is_joined(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_response(
|
||||
url="http://ollama.test:11434/api/chat",
|
||||
method="POST",
|
||||
json=_ollama_chat_ok_body('{"bank_name":"X"}'),
|
||||
)
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
await client.invoke(
|
||||
request_kwargs={
|
||||
"model": "gpt-oss:20b",
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "text", "text": "part-a"},
|
||||
{"type": "text", "text": "part-b"},
|
||||
],
|
||||
}
|
||||
],
|
||||
},
|
||||
response_schema=_Schema,
|
||||
)
|
||||
import json
|
||||
|
||||
request_body = json.loads(httpx_mock.get_requests()[0].read())
|
||||
# First message is the auto-injected schema guidance; after that
|
||||
# the caller's user message has its text parts joined.
|
||||
assert request_body["messages"][0]["role"] == "system"
|
||||
assert request_body["messages"][1:] == [
|
||||
{"role": "user", "content": "part-a\npart-b"}
|
||||
]
|
||||
|
||||
|
||||
class TestInvokeErrorPaths:
|
||||
async def test_connection_error_maps_to_002_000(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_exception(httpx.ConnectError("refused"))
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=1.0
|
||||
)
|
||||
with pytest.raises(IXException) as ei:
|
||||
await client.invoke(
|
||||
request_kwargs={
|
||||
"model": "gpt-oss:20b",
|
||||
"messages": [{"role": "user", "content": "hi"}],
|
||||
},
|
||||
response_schema=_Schema,
|
||||
)
|
||||
assert ei.value.code is IXErrorCode.IX_002_000
|
||||
|
||||
async def test_read_timeout_maps_to_002_000(self, httpx_mock: HTTPXMock) -> None:
|
||||
httpx_mock.add_exception(httpx.ReadTimeout("slow"))
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=0.5
|
||||
)
|
||||
with pytest.raises(IXException) as ei:
|
||||
await client.invoke(
|
||||
request_kwargs={
|
||||
"model": "gpt-oss:20b",
|
||||
"messages": [{"role": "user", "content": "hi"}],
|
||||
},
|
||||
response_schema=_Schema,
|
||||
)
|
||||
assert ei.value.code is IXErrorCode.IX_002_000
|
||||
|
||||
async def test_500_maps_to_002_000_with_body_snippet(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_response(
|
||||
url="http://ollama.test:11434/api/chat",
|
||||
method="POST",
|
||||
status_code=500,
|
||||
text="boom boom server broken",
|
||||
)
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
with pytest.raises(IXException) as ei:
|
||||
await client.invoke(
|
||||
request_kwargs={
|
||||
"model": "gpt-oss:20b",
|
||||
"messages": [{"role": "user", "content": "hi"}],
|
||||
},
|
||||
response_schema=_Schema,
|
||||
)
|
||||
assert ei.value.code is IXErrorCode.IX_002_000
|
||||
assert "boom" in (ei.value.detail or "")
|
||||
|
||||
async def test_200_with_invalid_json_maps_to_002_001(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_response(
|
||||
url="http://ollama.test:11434/api/chat",
|
||||
method="POST",
|
||||
json=_ollama_chat_ok_body("not-json"),
|
||||
)
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
with pytest.raises(IXException) as ei:
|
||||
await client.invoke(
|
||||
request_kwargs={
|
||||
"model": "gpt-oss:20b",
|
||||
"messages": [{"role": "user", "content": "hi"}],
|
||||
},
|
||||
response_schema=_Schema,
|
||||
)
|
||||
assert ei.value.code is IXErrorCode.IX_002_001
|
||||
|
||||
async def test_200_with_schema_violation_maps_to_002_001(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
# Missing required `bank_name` field.
|
||||
httpx_mock.add_response(
|
||||
url="http://ollama.test:11434/api/chat",
|
||||
method="POST",
|
||||
json=_ollama_chat_ok_body('{"account_number":"DE89"}'),
|
||||
)
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
with pytest.raises(IXException) as ei:
|
||||
await client.invoke(
|
||||
request_kwargs={
|
||||
"model": "gpt-oss:20b",
|
||||
"messages": [{"role": "user", "content": "hi"}],
|
||||
},
|
||||
response_schema=_Schema,
|
||||
)
|
||||
assert ei.value.code is IXErrorCode.IX_002_001
|
||||
|
||||
|
||||
class TestSelfcheck:
|
||||
async def test_selfcheck_ok_when_model_listed(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_response(
|
||||
url="http://ollama.test:11434/api/tags",
|
||||
method="GET",
|
||||
json={"models": [{"name": "gpt-oss:20b"}, {"name": "qwen2.5:32b"}]},
|
||||
)
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
assert await client.selfcheck(expected_model="gpt-oss:20b") == "ok"
|
||||
|
||||
async def test_selfcheck_degraded_when_model_missing(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_response(
|
||||
url="http://ollama.test:11434/api/tags",
|
||||
method="GET",
|
||||
json={"models": [{"name": "qwen2.5:32b"}]},
|
||||
)
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
assert await client.selfcheck(expected_model="gpt-oss:20b") == "degraded"
|
||||
|
||||
async def test_selfcheck_fail_on_connection_error(
|
||||
self, httpx_mock: HTTPXMock
|
||||
) -> None:
|
||||
httpx_mock.add_exception(httpx.ConnectError("refused"))
|
||||
client = OllamaClient(
|
||||
base_url="http://ollama.test:11434", per_call_timeout_s=5.0
|
||||
)
|
||||
assert await client.selfcheck(expected_model="gpt-oss:20b") == "fail"
|
||||
|
|
@ -1,166 +0,0 @@
|
|||
"""Tests for :class:`SuryaOCRClient` — hermetic, no model download.
|
||||
|
||||
The real Surya predictors are patched out with :class:`unittest.mock.MagicMock`
|
||||
that return trivially-shaped line objects. The tests assert the client's
|
||||
translation layer — flattening polygons, mapping text_lines → ``Line``,
|
||||
preserving ``page_no``/``width``/``height`` per input page.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from pathlib import Path
|
||||
from types import SimpleNamespace
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
from ix.contracts import Page
|
||||
from ix.ocr.surya_client import SuryaOCRClient
|
||||
from ix.segmentation import PageMetadata
|
||||
|
||||
|
||||
def _make_surya_line(text: str, polygon: list[list[float]]) -> SimpleNamespace:
|
||||
"""Mimic ``surya.recognition.schema.TextLine`` duck-typing-style."""
|
||||
return SimpleNamespace(text=text, polygon=polygon, confidence=0.95)
|
||||
|
||||
|
||||
def _make_surya_ocr_result(lines: list[SimpleNamespace]) -> SimpleNamespace:
|
||||
"""Mimic ``surya.recognition.schema.OCRResult``."""
|
||||
return SimpleNamespace(text_lines=lines, image_bbox=[0, 0, 100, 100])
|
||||
|
||||
|
||||
class TestOCRBuildsOCRResultFromMockedPredictors:
|
||||
async def test_one_image_one_line_flatten_polygon(self, tmp_path: Path) -> None:
|
||||
img_path = tmp_path / "a.png"
|
||||
_write_tiny_png(img_path)
|
||||
|
||||
mock_line = _make_surya_line(
|
||||
text="hello",
|
||||
polygon=[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0], [7.0, 8.0]],
|
||||
)
|
||||
mock_predictor = MagicMock(
|
||||
return_value=[_make_surya_ocr_result([mock_line])]
|
||||
)
|
||||
|
||||
client = SuryaOCRClient()
|
||||
# Skip the real warm_up; inject the mock directly.
|
||||
client._recognition_predictor = mock_predictor
|
||||
client._detection_predictor = MagicMock()
|
||||
|
||||
pages = [Page(page_no=1, width=100.0, height=50.0, lines=[])]
|
||||
result = await client.ocr(
|
||||
pages,
|
||||
files=[(img_path, "image/png")],
|
||||
page_metadata=[PageMetadata(file_index=0)],
|
||||
)
|
||||
|
||||
assert len(result.result.pages) == 1
|
||||
out_page = result.result.pages[0]
|
||||
assert out_page.page_no == 1
|
||||
assert out_page.width == 100.0
|
||||
assert out_page.height == 50.0
|
||||
assert len(out_page.lines) == 1
|
||||
assert out_page.lines[0].text == "hello"
|
||||
assert out_page.lines[0].bounding_box == [
|
||||
1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0
|
||||
]
|
||||
|
||||
async def test_multiple_pages_preserves_order(self, tmp_path: Path) -> None:
|
||||
img_a = tmp_path / "a.png"
|
||||
img_b = tmp_path / "b.png"
|
||||
_write_tiny_png(img_a)
|
||||
_write_tiny_png(img_b)
|
||||
|
||||
mock_predictor = MagicMock(
|
||||
return_value=[
|
||||
_make_surya_ocr_result(
|
||||
[_make_surya_line("a-line", [[0, 0], [1, 0], [1, 1], [0, 1]])]
|
||||
),
|
||||
_make_surya_ocr_result(
|
||||
[_make_surya_line("b-line", [[0, 0], [1, 0], [1, 1], [0, 1]])]
|
||||
),
|
||||
]
|
||||
)
|
||||
|
||||
client = SuryaOCRClient()
|
||||
client._recognition_predictor = mock_predictor
|
||||
client._detection_predictor = MagicMock()
|
||||
|
||||
pages = [
|
||||
Page(page_no=1, width=10.0, height=20.0, lines=[]),
|
||||
Page(page_no=2, width=10.0, height=20.0, lines=[]),
|
||||
]
|
||||
result = await client.ocr(
|
||||
pages,
|
||||
files=[(img_a, "image/png"), (img_b, "image/png")],
|
||||
page_metadata=[
|
||||
PageMetadata(file_index=0),
|
||||
PageMetadata(file_index=1),
|
||||
],
|
||||
)
|
||||
|
||||
assert [p.lines[0].text for p in result.result.pages] == ["a-line", "b-line"]
|
||||
|
||||
async def test_lazy_warm_up_on_first_ocr(self, tmp_path: Path) -> None:
|
||||
img = tmp_path / "x.png"
|
||||
_write_tiny_png(img)
|
||||
|
||||
client = SuryaOCRClient()
|
||||
|
||||
# Use patch.object on the instance's warm_up so we don't need real
|
||||
# Surya module loading.
|
||||
with patch.object(client, "warm_up", autospec=True) as mocked_warm_up:
|
||||
# After warm_up is called, the predictors must be assigned.
|
||||
def fake_warm_up(self: SuryaOCRClient) -> None:
|
||||
self._recognition_predictor = MagicMock(
|
||||
return_value=[
|
||||
_make_surya_ocr_result(
|
||||
[
|
||||
_make_surya_line(
|
||||
"hi", [[0, 0], [1, 0], [1, 1], [0, 1]]
|
||||
)
|
||||
]
|
||||
)
|
||||
]
|
||||
)
|
||||
self._detection_predictor = MagicMock()
|
||||
|
||||
mocked_warm_up.side_effect = lambda: fake_warm_up(client)
|
||||
|
||||
pages = [Page(page_no=1, width=10.0, height=10.0, lines=[])]
|
||||
await client.ocr(
|
||||
pages,
|
||||
files=[(img, "image/png")],
|
||||
page_metadata=[PageMetadata(file_index=0)],
|
||||
)
|
||||
mocked_warm_up.assert_called_once()
|
||||
|
||||
|
||||
class TestSelfcheck:
|
||||
async def test_selfcheck_ok_with_mocked_predictors(self) -> None:
|
||||
client = SuryaOCRClient()
|
||||
client._recognition_predictor = MagicMock(
|
||||
return_value=[_make_surya_ocr_result([])]
|
||||
)
|
||||
client._detection_predictor = MagicMock()
|
||||
assert await client.selfcheck() == "ok"
|
||||
|
||||
async def test_selfcheck_fail_when_predictor_raises(self) -> None:
|
||||
client = SuryaOCRClient()
|
||||
client._recognition_predictor = MagicMock(
|
||||
side_effect=RuntimeError("cuda broken")
|
||||
)
|
||||
client._detection_predictor = MagicMock()
|
||||
assert await client.selfcheck() == "fail"
|
||||
|
||||
|
||||
def _write_tiny_png(path: Path) -> None:
|
||||
"""Write a 2x2 white PNG so PIL can open it."""
|
||||
from PIL import Image
|
||||
|
||||
Image.new("RGB", (2, 2), color="white").save(path, format="PNG")
|
||||
|
||||
|
||||
@pytest.mark.parametrize("unused", [None]) # keep pytest happy if file ever runs alone
|
||||
def test_module_imports(unused: None) -> None:
|
||||
assert SuryaOCRClient is not None
|
||||
|
|
@ -12,7 +12,7 @@ class TestRequest:
|
|||
def test_defaults(self) -> None:
|
||||
r = Request()
|
||||
assert r.use_case_name == "Bank Statement Header"
|
||||
assert r.default_model == "qwen3:14b"
|
||||
assert r.default_model == "gpt-oss:20b"
|
||||
# Stable substring for agent/worker tests that want to confirm the
|
||||
# prompt is what they think it is.
|
||||
assert "extract header metadata" in r.system_prompt
|
||||
|
|
|
|||
165
uv.lock
165
uv.lock
|
|
@ -110,79 +110,6 @@ wheels = [
|
|||
{ url = "https://files.pythonhosted.org/packages/db/3c/33bac158f8ab7f89b2e59426d5fe2e4f63f7ed25df84c036890172b412b5/cfgv-3.5.0-py2.py3-none-any.whl", hash = "sha256:a8dc6b26ad22ff227d2634a65cb388215ce6cc96bbcc5cfde7641ae87e8dacc0", size = 7445, upload-time = "2025-11-19T20:55:50.744Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
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version = "1.17.0"
|
||||
|
|
@ -1747,23 +1703,22 @@ wheels = [
|
|||
|
||||
[[package]]
|
||||
name = "transformers"
|
||||
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|
||||
version = "5.5.4"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "filelock" },
|
||||
{ name = "huggingface-hub" },
|
||||
{ name = "numpy" },
|
||||
{ name = "packaging" },
|
||||
{ name = "pyyaml" },
|
||||
{ name = "regex" },
|
||||
{ name = "requests" },
|
||||
{ name = "safetensors" },
|
||||
{ name = "tokenizers" },
|
||||
{ name = "tqdm" },
|
||||
{ name = "typer" },
|
||||
]
|
||||
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|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/03/b8/e484ef633af3887baeeb4b6ad12743363af7cce68ae51e938e00aaa0529d/transformers-4.57.6-py3-none-any.whl", hash = "sha256:4c9e9de11333ddfe5114bc872c9f370509198acf0b87a832a0ab9458e2bd0550", size = 11993498, upload-time = "2026-01-16T10:38:31.289Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/29/fb/162a66789c65e5afa3b051309240c26bf37fbc8fea285b4546ae747995a2/transformers-5.5.4-py3-none-any.whl", hash = "sha256:0bd6281b82966fe5a7a16f553ea517a9db1dee6284d7cb224dfd88fc0dd1c167", size = 10236696, upload-time = "2026-04-13T16:55:51.497Z" },
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||||
]
|
||||
|
||||
[[package]]
|
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|
|
@ -1783,6 +1738,21 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/f6/56/6113c23ff46c00aae423333eb58b3e60bdfe9179d542781955a5e1514cb3/triton-3.6.0-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:46bd1c1af4b6704e554cad2eeb3b0a6513a980d470ccfa63189737340c7746a7", size = 188397994, upload-time = "2026-01-20T16:01:14.236Z" },
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]
|
||||
|
||||
[[package]]
|
||||
name = "typer"
|
||||
version = "0.24.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "annotated-doc" },
|
||||
{ name = "click" },
|
||||
{ name = "rich" },
|
||||
{ name = "shellingham" },
|
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|
||||
sdist = { url = "https://files.pythonhosted.org/packages/f5/24/cb09efec5cc954f7f9b930bf8279447d24618bb6758d4f6adf2574c41780/typer-0.24.1.tar.gz", hash = "sha256:e39b4732d65fbdcde189ae76cf7cd48aeae72919dea1fdfc16593be016256b45", size = 118613, upload-time = "2026-02-21T16:54:40.609Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/4a/91/48db081e7a63bb37284f9fbcefda7c44c277b18b0e13fbc36ea2335b71e6/typer-0.24.1-py3-none-any.whl", hash = "sha256:112c1f0ce578bfb4cab9ffdabc68f031416ebcc216536611ba21f04e9aa84c9e", size = 56085, upload-time = "2026-02-21T16:54:41.616Z" },
|
||||
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|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.15.0"
|
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|
|
@ -1804,15 +1774,6 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7", size = 14611, upload-time = "2025-10-01T02:14:40.154Z" },
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]
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|
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[[package]]
|
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name = "urllib3"
|
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|
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wheels = [
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]
|
||||
|
||||
[[package]]
|
||||
name = "uvicorn"
|
||||
version = "0.44.0"
|
||||
|
|
|
|||
Loading…
Reference in a new issue