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| Author | SHA1 | Date | |
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| 4820888ff9 | |||
| bcb4714778 | |||
| 7fec4bc575 | |||
| 612fbe2055 |
16
.dockerignore
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16
.dockerignore
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@@ -0,0 +1,16 @@
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.git
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.github
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.gitea
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.venv
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__pycache__
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*.py[cod]
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.pytest_cache
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.ruff_cache
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.coverage
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htmlcov
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.env
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.env.*
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!.env.example
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tests
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.cursor
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*.plan.md
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@@ -13,6 +13,9 @@ PAPERLESS_DOCUMENT_TYPE_ID=3
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PAPERLESS_TASK_TIMEOUT_S=600
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PAPERLESS_TASK_POLL_INTERVAL_S=5.0
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# 0 = unlimited concurrent per-page uploads
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PAPERLESS_UPLOAD_CONCURRENCY=0
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RENDER_DPI=200
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OCR_MAX_TOKENS=1024
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OCR_TEMPERATURE=0.0
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38
.github/workflows/build-docker.yml
vendored
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38
.github/workflows/build-docker.yml
vendored
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@@ -0,0 +1,38 @@
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name: Build and Publish Docker Image
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on:
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push:
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branches:
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- main
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jobs:
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build-and-push:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Login to Docker Registry
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uses: docker/login-action@v3
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with:
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registry: ${{ secrets.DOCKER_REGISTRY }}
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username: ${{ secrets.DOCKER_USERNAME }}
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password: ${{ secrets.DOCKER_PASSWORD }}
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- name: Build and push
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uses: docker/build-push-action@v5
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with:
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context: .
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file: Dockerfile
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push: true
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tags: |
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${{ secrets.DOCKER_REGISTRY }}/${{ secrets.DOCKER_USERNAME }}/notebook-tools:${{ gitea.sha }}
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${{ secrets.DOCKER_REGISTRY }}/${{ secrets.DOCKER_USERNAME }}/notebook-tools:latest
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labels: |
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org.opencontainers.image.source=${{ gitea.server_url }}/${{ gitea.repository }}
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org.opencontainers.image.description=Notebook tools — Paperless + llama.cpp OCR API
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cache-from: type=gha
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cache-to: type=gha,mode=max
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19
Dockerfile
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19
Dockerfile
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@@ -0,0 +1,19 @@
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# syntax=docker/dockerfile:1
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# Production image: uv sync (frozen lockfile), run FastAPI with uvicorn.
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FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim
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WORKDIR /app
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ENV UV_COMPILE_BYTECODE=1 \
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UV_LINK_MODE=copy
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COPY pyproject.toml uv.lock README.md ./
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COPY src ./src
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RUN uv sync --frozen --no-dev
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ENV PATH="/app/.venv/bin:$PATH"
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EXPOSE 8080
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CMD ["uvicorn", "notebook_tools.api:app", "--host", "0.0.0.0", "--port", "8080"]
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50
README.md
50
README.md
@@ -5,7 +5,7 @@ FastAPI service that:
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- splits them into pages (JPEG)
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- OCRs each page via your llama.cpp OpenAI-compatible endpoint
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- converts each page back into a single-page PDF
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- uploads **one Paperless document per page**
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- uploads **one Paperless document per page** (all uploads run **in parallel**; OCR stays **one page at a time** for VRAM)
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- patches each uploaded document with:
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- `content` = OCR text
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- custom fields `notebook_id` (field id 1) and `notebook_page` (field id 2)
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@@ -33,6 +33,51 @@ Then open the docs at:
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If other machines still can’t connect, check your macOS firewall and any router/network rules.
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## Docker
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Build and run (pass env via file or `-e`; the app reads `.env` only if you mount it):
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```bash
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docker build -t notebook-tools:local .
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docker run --rm -p 8080:8080 --env-file .env notebook-tools:local
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```
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`LLAMA_BASE_URL` / `PAPERLESS_BASE_URL` must be reachable **from inside the container** (use `host.docker.internal` on Docker Desktop, or your LAN IP, not `127.0.0.1` for services on the host).
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### Docker Compose
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Save as `compose.yaml` (any directory with your `.env`):
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```yaml
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services:
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notebook-tools:
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image: git.danhenry.dev/daniel/notebook-tools:latest
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ports:
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- "8080:8080"
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env_file:
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- .env
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# Lets the container reach services bound on the host (e.g. llama on :9292).
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# Linux: requires Docker 20.10+ / Compose v2; omit on Docker Desktop if already available.
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extra_hosts:
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- "host.docker.internal:host-gateway"
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```
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```bash
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docker compose pull && docker compose up
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```
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Log in to `git.danhenry.dev` first if the registry requires auth: `docker login git.danhenry.dev`.
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For llama running **on the host**, set in `.env`:
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```bash
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LLAMA_BASE_URL="http://host.docker.internal:9292"
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```
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`PAPERLESS_BASE_URL` can stay a normal `https://…` URL if the container has network access to it.
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CI: on push to `main`, [.github/workflows/build-docker.yml](.github/workflows/build-docker.yml) builds and pushes using the same secrets pattern as your other Gitea repos (`DOCKER_REGISTRY`, `DOCKER_USERNAME`, `DOCKER_PASSWORD`). For Docker Hub, set `DOCKER_REGISTRY` to `docker.io` (or leave per your runner docs).
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## Example `.env`
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```bash
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@@ -47,6 +92,9 @@ PAPERLESS_CUSTOM_FIELD_NOTEBOOK_ID=1
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PAPERLESS_CUSTOM_FIELD_NOTEBOOK_PAGE=2
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PAPERLESS_DOCUMENT_TYPE_ID=3
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# Optional: cap concurrent Paperless uploads (0 = unlimited)
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PAPERLESS_UPLOAD_CONCURRENCY=4
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# Rendering / OCR knobs
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RENDER_DPI=200
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OCR_MAX_TOKENS=1024
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@@ -6,19 +6,25 @@ Design goals:
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- Keep the pipeline readable and linear.
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- Return enough information (created ids) for the job API.
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- Avoid hidden side-effects (everything is passed in / returned).
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Upload strategy:
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- All per-page PDFs are uploaded to Paperless concurrently (each upload still polls until a doc id exists).
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- OCR (llama) runs one page at a time to respect VRAM.
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- Each page is PATCHed once that page's upload has finished and OCR for that page is done.
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"""
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from __future__ import annotations
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from collections.abc import Awaitable, Callable
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import asyncio
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import io
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import logging
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import re
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from collections.abc import Awaitable, Callable
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from notebook_tools import pdf_utils
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from notebook_tools.llama_client import LlamaClient
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from notebook_tools.paperless_client import PaperlessClient
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from notebook_tools.settings import Settings
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from notebook_tools import pdf_utils
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from PIL import Image
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logger = logging.getLogger("notebook_tools.pipeline")
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@@ -124,49 +130,66 @@ async def run_pipeline_for_paperless_document(
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if on_progress:
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await on_progress(0, total_pages)
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# One small PDF per page (used by upload tasks).
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page_pdfs = [pdf_utils.jpeg_to_pdf_bytes(jpeg_bytes=b) for b in jpegs]
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# 3) Start all Paperless uploads in parallel (each task waits for ingest + document id).
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conc = settings.paperless_upload_concurrency
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upload_sem: asyncio.Semaphore | None = (
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asyncio.Semaphore(conc) if conc and conc > 0 else None
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)
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logger.info(
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"job_id=%s starting_parallel_uploads pages=%s concurrency=%s",
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job_id,
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total_pages,
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conc if conc and conc > 0 else "unlimited",
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)
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async def _upload_one_page(idx_1based: int) -> int:
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filename = f"job_{job_id}_page_{idx_1based}.pdf"
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pdf_bytes = page_pdfs[idx_1based - 1]
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logger.info("job_id=%s page=%s/%s upload_task_starting", job_id, idx_1based, total_pages)
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if upload_sem is not None:
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async with upload_sem:
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return await paperless.upload_pdf(filename=filename, pdf_bytes=pdf_bytes)
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return await paperless.upload_pdf(filename=filename, pdf_bytes=pdf_bytes)
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upload_tasks: list[asyncio.Task[int]] = [
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asyncio.create_task(_upload_one_page(i)) for i in range(1, total_pages + 1)
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]
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created_ids: list[int] = []
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# 3) For each page: OCR -> convert to single-page PDF -> upload -> patch metadata.
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# 4) OCR sequentially (VRAM), then await upload for that page + PATCH.
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try:
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for idx, jpeg_bytes in enumerate(jpegs, start=1):
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logger.info("job_id=%s page=%s/%s starting", job_id, idx, total_pages)
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# 3a) Page-number OCR (bottom corners only).
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logger.info("job_id=%s page=%s/%s ocr_starting", job_id, idx, total_pages)
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# 4a) Page-number OCR (bottom corners only).
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page_number = -1
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for corner_jpeg in _crop_bottom_corner_jpegs(full_page_jpeg=jpeg_bytes):
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candidate_text = await llama.ocr_jpeg(jpeg_bytes=corner_jpeg, prompt=PAGE_NUMBER_PROMPT)
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parsed = _parse_page_number(candidate_text)
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if parsed is not None:
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# Only accept non-negative numbers, or -1. Anything else becomes unknown.
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if parsed == -1 or parsed >= 0:
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page_number = parsed
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if page_number != -1:
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break
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logger.info("job_id=%s page=%s detected_page_number=%s", job_id, idx, page_number)
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# 3b) Full-page OCR for actual searchable text content.
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# 4b) Full-page OCR for searchable content.
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logger.info("job_id=%s page=%s ocr_full_page", job_id, idx)
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ocr_text = await llama.ocr_jpeg(jpeg_bytes=jpeg_bytes, prompt=ocr_prompt_override)
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logger.info("job_id=%s page=%s ocr_chars=%s", job_id, idx, len(ocr_text))
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page_pdf = pdf_utils.jpeg_to_pdf_bytes(jpeg_bytes=jpeg_bytes)
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logger.info("job_id=%s page=%s pdf_bytes=%s", job_id, idx, len(page_pdf))
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# Upload the per-page PDF as a new Paperless document.
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logger.info("job_id=%s page=%s uploading_to_paperless", job_id, idx)
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new_id = await paperless.upload_pdf(filename=f"job_{job_id}_page_{idx}.pdf", pdf_bytes=page_pdf)
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logger.info("job_id=%s page=%s awaiting_upload_then_patch", job_id, idx)
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new_id = await upload_tasks[idx - 1]
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logger.info("job_id=%s page=%s uploaded_document_id=%s", job_id, idx, new_id)
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# Patch metadata:
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# - content: OCR text so it becomes searchable in Paperless
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# - custom_fields: notebook_id + notebook_page
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# - document_type: per-page document type (Paperless id)
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# - title
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custom_fields = [
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{"field": settings.paperless_custom_field_notebook_id, "value": notebook_id},
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{"field": settings.paperless_custom_field_notebook_page, "value": page_number},
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]
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# Per your request, title is always in this exact format.
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# (We keep `title_prefix` in the API for now, but it is no longer used.)
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title = f"Notebook {notebook_id} Page {page_number}"
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logger.info("job_id=%s page=%s patching_document_id=%s", job_id, idx, new_id)
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@@ -182,6 +205,11 @@ async def run_pipeline_for_paperless_document(
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created_ids.append(new_id)
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if on_progress:
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await on_progress(idx, total_pages)
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except BaseException:
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for t in upload_tasks:
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if not t.done():
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t.cancel()
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await asyncio.gather(*upload_tasks, return_exceptions=True)
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raise
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return {"created_document_ids": created_ids}
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@@ -46,6 +46,9 @@ class Settings(BaseSettings):
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paperless_task_timeout_s: int = Field(600, alias="PAPERLESS_TASK_TIMEOUT_S")
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paperless_task_poll_interval_s: float = Field(5.0, alias="PAPERLESS_TASK_POLL_INTERVAL_S")
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# Max concurrent per-page uploads to Paperless (0 = unlimited). Limits load on the server.
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paperless_upload_concurrency: int = Field(0, alias="PAPERLESS_UPLOAD_CONCURRENCY")
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# Logging
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log_level: str = Field("INFO", alias="LOG_LEVEL")
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Reference in New Issue
Block a user