46 Commits

Author SHA1 Message Date
github-actions[bot]
5edc624fbf chore: bump version to 1.6.0 [skip ci] 2025-10-03 13:39:59 +00:00
Michele Dolfi
45f0f3c8f9 fix: update locked dependencies (#392)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-10-03 15:33:45 +02:00
Michele Dolfi
0595d31d5b feat: pin new version of jobkit with granite-docling and connectors (#391)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-10-03 14:24:51 +02:00
Michele Dolfi
f6b5f0e063 docs: fix docs for websocket breaking condition (#390)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-10-02 10:55:00 +02:00
Michele Dolfi
8b22a39141 fix(UI): allow both lowercase and uppercase extensions (#386)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-29 09:40:49 +02:00
erikmargaronis
d4eac053f9 fix: Correctly raise HTTPException for Gateway Timeout (#382)
Signed-off-by: Erik Margaronis <erik.margaronis@gmail.com>
2025-09-29 08:06:21 +02:00
Rui Dias Gomes
fa1c5f04f3 ci: improve caching steps (#371)
Signed-off-by: rmdg88 <rmdg88@gmail.com>
2025-09-23 18:15:12 +02:00
Viktor Kuropiatnyk
ba61af2359 fix: Pinning of higher version of dependencies to fix potential security issues (#363)
Signed-off-by: Viktor Kuropiatnyk <vku@zurich.ibm.com>
2025-09-18 08:57:41 +02:00
github-actions[bot]
6b6dd8a0d0 chore: bump version to 1.5.1 [skip ci] 2025-09-17 13:45:40 +00:00
Michele Dolfi
513ae0c119 fix: remove old dependencies, fixes in docling-parse and more minor dependencies upgrade (#362)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-17 15:36:23 +02:00
Rui Dias Gomes
bde040661f fix: updates rapidocr deps (#361)
Signed-off-by: rmdg88 <rmdg88@gmail.com>
2025-09-16 14:00:21 +02:00
github-actions[bot]
496f7ec26b chore: bump version to 1.5.0 [skip ci] 2025-09-09 08:46:36 +00:00
Michele Dolfi
9d6def0ec8 feat: add chunking endpoints (#353)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-09 08:38:54 +02:00
github-actions[bot]
a4fed2d965 chore: bump version to 1.4.1 [skip ci] 2025-09-08 10:28:12 +00:00
Michele Dolfi
b0360d723b fix: trigger fix after ci fixes (#355)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-08 12:23:07 +02:00
Michele Dolfi
4adc0dfa79 ci: fix use simple tag for testing (#354)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-08 11:29:55 +02:00
github-actions[bot]
40c7f1bcd3 chore: bump version to 1.4.0 [skip ci] 2025-09-05 17:57:08 +00:00
Michele Dolfi
d64a2a974a feat(docling): perfomance improvements in parsing, new layout model, fixes in html processing (#352)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-05 16:21:29 +02:00
Tiago Santana
0d4545a65a docs: add split processing example (#303)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-04 10:42:11 +02:00
Rui Dias Gomes
fe98338239 ci: fix runner disk space issue (#350)
Signed-off-by: Rui Dias Gomes <66125272+rmdg88@users.noreply.github.com>
2025-09-04 09:17:19 +02:00
Michele Dolfi
b844ce737e ci: remove mdlint (#348)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-09-03 15:42:55 +02:00
Antonio Pisano
27fdd7b85a docs: document DOCLING_NUM_THREADS environment variable (#341)
Signed-off-by: Antonio Pisano <antonio.pisano@wu.ac.at>
Co-authored-by: Antonio Pisano <antonio.pisano@wu.ac.at>
2025-09-03 11:00:28 +02:00
Rui Dias Gomes
1df62adf01 ci: workflow improvements (#310)
Signed-off-by: rmdg88 <rmdg88@gmail.com>
Signed-off-by: Rui Dias Gomes <66125272+rmdg88@users.noreply.github.com>
2025-09-03 10:06:30 +02:00
Michele Dolfi
e5449472b2 fix: upgrade to latest docling version with fixes (#335)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-25 10:55:43 +02:00
Michele Dolfi
81f0a8ddf8 docs: fix parameters typo (#333)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-22 14:59:12 +02:00
Michele Dolfi
a69cc867f5 docs: Describe how to use Docling MCP (#332)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-22 14:56:08 +02:00
github-actions[bot]
624f65d41b chore: bump version to 1.3.1 [skip ci] 2025-08-21 07:01:51 +00:00
Michele Dolfi
f02dbc0144 fix: configuration and performance fixes via upgrade of packages (#328)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-20 20:40:52 +02:00
Michele Dolfi
37fe02277b docs: fix parameter in api key docs (#323)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-15 11:00:05 +02:00
github-actions[bot]
783ada0580 chore: bump version to 1.3.0 [skip ci] 2025-08-14 14:26:57 +00:00
VIktor Kuropiantnyk
71edf41849 docs: example of docling-serve deployment in the RQ engine mode (#321)
Signed-off-by: Viktor Kuropiatnyk <vku@zurich.ibm.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 16:10:39 +02:00
Michele Dolfi
9a64410552 feat: Add configuration option for apikey security (#322)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 15:25:53 +02:00
Michele Dolfi
6e9aa8c759 docs: handling models in docling-serve (#319)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 09:12:04 +02:00
Michele Dolfi
885f319d3a feat: Add RQ engine (#315)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-14 08:48:31 +02:00
Tiago Santana
d584895e11 docs: add Gradio cache usage (#312)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-08-13 16:49:54 +02:00
github-actions[bot]
d26e6637d8 chore: bump version to 1.2.2 [skip ci] 2025-08-13 14:48:17 +00:00
VIktor Kuropiantnyk
7692eb2600 fix: update of transformers module to 4.55.1 (#316)
Signed-off-by: Viktor Kuropiatnyk <vku@zurich.ibm.com>
2025-08-13 16:07:52 +02:00
github-actions[bot]
3bd7828570 chore: bump version to 1.2.1 [skip ci] 2025-08-13 07:37:55 +00:00
Michele Dolfi
8b470cba8e fix: handling of vlm model options and update deps (#314)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-13 09:32:21 +02:00
Tiago Santana
8048f4589a fix: add missing response type in sync endpoints (#309)
Signed-off-by: Tiago Santana <54704492+SantanaTiago@users.noreply.github.com>
2025-08-08 12:32:19 +02:00
Thomas Vitale
b3058e91e0 docs: Update readme to use v1 (#306)
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
2025-08-08 09:02:29 +02:00
Thomas Vitale
63da9eedeb docs: Update deployment examples to use v1 API (#308)
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
2025-08-08 08:47:59 +02:00
Thomas Vitale
b15dc2529f docs: Fix typo in v1 migration instructions (#307)
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
2025-08-08 08:44:09 +02:00
github-actions[bot]
4c7207be00 chore: bump version to 1.2.0 [skip ci] 2025-08-07 09:20:10 +00:00
Michele Dolfi
db3fdb5bc1 feat: workers without shared models and convert params (#304)
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
2025-08-07 11:16:06 +02:00
Rui Dias Gomes
fd1b987e8d feat: add rocm image build support and fix cuda (#292)
Signed-off-by: rmdg88 <rmdg88@gmail.com>
Signed-off-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
Co-authored-by: Rui-Dias-Gomes <rui.dias.gomes@ibm.com>
2025-07-31 14:22:42 +02:00
55 changed files with 7044 additions and 3709 deletions

View File

@@ -3,32 +3,68 @@
set -e # trigger failure on error - do not remove!
set -x # display command on output
## debug
# TARGET_VERSION="1.2.x"
if [ -z "${TARGET_VERSION}" ]; then
>&2 echo "No TARGET_VERSION specified"
exit 1
fi
CHGLOG_FILE="${CHGLOG_FILE:-CHANGELOG.md}"
# update package version
# Update package version
uvx --from=toml-cli toml set --toml-path=pyproject.toml project.version "${TARGET_VERSION}"
uv lock --upgrade-package docling-serve
# collect release notes
# Extract all docling packages and versions from uv.lock
DOCVERSIONS=$(uvx --with toml python3 - <<'PY'
import toml
data = toml.load("uv.lock")
for pkg in data.get("package", []):
if pkg["name"].startswith("docling"):
print(f"{pkg['name']} {pkg['version']}")
PY
)
# Format docling versions list without trailing newline
DOCLING_VERSIONS="### Docling libraries included in this release:"
while IFS= read -r line; do
DOCLING_VERSIONS+="
- $line"
done <<< "$DOCVERSIONS"
# Collect release notes
REL_NOTES=$(mktemp)
uv run --no-sync semantic-release changelog --unreleased >> "${REL_NOTES}"
# update changelog
# Strip trailing blank lines from release notes and append docling versions
{
sed -e :a -e '/^\n*$/{$d;N;};/\n$/ba' "${REL_NOTES}"
printf "\n"
printf "%s" "${DOCLING_VERSIONS}"
printf "\n"
} > "${REL_NOTES}.tmp" && mv "${REL_NOTES}.tmp" "${REL_NOTES}"
# Update changelog
TMP_CHGLOG=$(mktemp)
TARGET_TAG_NAME="v${TARGET_VERSION}"
RELEASE_URL="$(gh repo view --json url -q ".url")/releases/tag/${TARGET_TAG_NAME}"
printf "## [${TARGET_TAG_NAME}](${RELEASE_URL}) - $(date -Idate)\n\n" >> "${TMP_CHGLOG}"
cat "${REL_NOTES}" >> "${TMP_CHGLOG}"
if [ -f "${CHGLOG_FILE}" ]; then
printf "\n" | cat - "${CHGLOG_FILE}" >> "${TMP_CHGLOG}"
fi
## debug
#RELEASE_URL="myrepo/releases/tag/${TARGET_TAG_NAME}"
# Strip leading blank lines from existing changelog to avoid multiple blank lines when appending
EXISTING_CL=$(sed -e :a -e '/^\n*$/{$d;N;};/\n$/ba' "${CHGLOG_FILE}")
{
printf "## [${TARGET_TAG_NAME}](${RELEASE_URL}) - $(date -Idate)\n\n"
cat "${REL_NOTES}"
printf "\n"
printf "%s\n" "${EXISTING_CL}"
} >> "${TMP_CHGLOG}"
mv "${TMP_CHGLOG}" "${CHGLOG_FILE}"
# push changes
# Push changes
git config --global user.name 'github-actions[bot]'
git config --global user.email 'github-actions[bot]@users.noreply.github.com'
git add pyproject.toml uv.lock "${CHGLOG_FILE}"
@@ -36,5 +72,5 @@ COMMIT_MSG="chore: bump version to ${TARGET_VERSION} [skip ci]"
git commit -m "${COMMIT_MSG}"
git push origin main
# create GitHub release (incl. Git tag)
# Create GitHub release (incl. Git tag)
gh release create "${TARGET_TAG_NAME}" -F "${REL_NOTES}"

View File

@@ -5,6 +5,8 @@ async
(?i)urls
uvicorn
[Ww]ebserver
RQ
(?i)url
keyfile
[Ww]ebsocket(s?)
[Kk]ubernetes
@@ -19,8 +21,10 @@ Kubeflow
(?i)PyTorch
(?i)CUDA
(?i)NVIDIA
(?i)ROCm
(?i)env
Gradio
Podman
bool
Ollama
inbody

View File

@@ -13,7 +13,7 @@ jobs:
actionlint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
- name: Download actionlint
id: get_actionlint
run: bash <(curl https://raw.githubusercontent.com/rhysd/actionlint/main/scripts/download-actionlint.bash)

View File

@@ -11,11 +11,11 @@ jobs:
outputs:
TARGET_TAG_V: ${{ steps.version_check.outputs.TRGT_VERSION }}
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
fetch-depth: 0 # for fetching tags, required for semantic-release
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v5
uses: astral-sh/setup-uv@v6
with:
enable-cache: true
- name: Install dependencies
@@ -40,12 +40,12 @@ jobs:
with:
app-id: ${{ vars.CI_APP_ID }}
private-key: ${{ secrets.CI_PRIVATE_KEY }}
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
token: ${{ steps.app-token.outputs.token }}
fetch-depth: 0 # for fetching tags, required for semantic-release
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v5
uses: astral-sh/setup-uv@v6
with:
enable-cache: true
- name: Install dependencies

View File

@@ -21,10 +21,10 @@ jobs:
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cpu --no-extra flash-attn
platforms: linux/amd64, linux/arm64
- name: docling-project/docling-serve-cu124
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu124
platforms: linux/amd64
# - name: docling-project/docling-serve-cu124
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu124
# platforms: linux/amd64
- name: docling-project/docling-serve-cu126
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu126
@@ -33,6 +33,10 @@ jobs:
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu128
platforms: linux/amd64
# - name: docling-project/docling-serve-rocm
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group rocm --no-extra flash-attn
# platforms: linux/amd64
permissions:
packages: write

View File

@@ -25,10 +25,10 @@ jobs:
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cpu --no-extra flash-attn
platforms: linux/amd64, linux/arm64
- name: docling-project/docling-serve-cu124
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu124
platforms: linux/amd64
# - name: docling-project/docling-serve-cu124
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu124
# platforms: linux/amd64
- name: docling-project/docling-serve-cu126
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu126
@@ -37,7 +37,10 @@ jobs:
build_args: |
UV_SYNC_EXTRA_ARGS=--no-group pypi --group cu128
platforms: linux/amd64
# - name: docling-project/docling-serve-rocm
# build_args: |
# UV_SYNC_EXTRA_ARGS=--no-group pypi --group rocm --no-extra flash-attn
# platforms: linux/amd64
permissions:
packages: write
contents: read

View File

@@ -10,9 +10,9 @@ jobs:
matrix:
python-version: ['3.12']
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v5
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true

View File

@@ -10,9 +10,9 @@ jobs:
matrix:
python-version: ['3.12']
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v5
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
@@ -28,7 +28,7 @@ jobs:
run: uv sync --frozen --all-extras --no-extra flash-attn
- name: Run styling check
run: pre-commit run --all-files
run: uv run pre-commit run --all-files
build-package:
uses: ./.github/workflows/job-build.yml
@@ -47,21 +47,22 @@ jobs:
name: python-package-distributions
path: dist/
- name: Install uv and set the python version
uses: astral-sh/setup-uv@v5
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
- name: Create virtual environment
run: uv venv
- name: Install package
run: uv pip install dist/*.whl
- name: Create the server
run: python -c 'from docling_serve.app import create_app; create_app()'
markdown-lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: markdownlint-cli2-action
uses: DavidAnson/markdownlint-cli2-action@v16
with:
globs: "**/*.md"
run: .venv/bin/python -c 'from docling_serve.app import create_app; create_app()'
# markdown-lint:
# runs-on: ubuntu-latest
# steps:
# - uses: actions/checkout@v5
# - name: markdownlint-cli2-action
# uses: DavidAnson/markdownlint-cli2-action@v16
# with:
# globs: "**/*.md"

View File

@@ -53,7 +53,7 @@ jobs:
df -h
- name: Check out the repo
uses: actions/checkout@v4
uses: actions/checkout@v5
- name: Log in to the GHCR container image registry
if: ${{ inputs.publish }}
@@ -88,19 +88,115 @@ jobs:
with:
images: ${{ env.GHCR_REGISTRY }}/${{ inputs.ghcr_image_name }}
# # Local test
# - name: Set metadata outputs for local testing ## comment out Free up space, Log in to cr, Cache Docker, Extract metadata, and quay blocks and run act
# id: ghcr_meta
# run: |
# echo "tags=ghcr.io/docling-project/docling-serve:pr-123" >> $GITHUB_OUTPUT
# echo "labels=org.opencontainers.image.source=https://github.com/docling-project/docling-serve" >> $GITHUB_OUTPUT
- name: Build and push image to ghcr.io
id: ghcr_push
uses: docker/build-push-action@v5
uses: docker/build-push-action@v6
with:
context: .
push: ${{ inputs.publish }}
push: ${{ inputs.publish }} # set 'false' for local test
tags: ${{ steps.ghcr_meta.outputs.tags }}
labels: ${{ steps.ghcr_meta.outputs.labels }}
platforms: ${{ inputs.platforms}}
platforms: ${{ inputs.platforms }}
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: ${{ inputs.build_args }}
pull: true
##
## This stage runs after the build, so it leverages all build cache
##
- name: Export built image for testing
id: ghcr_export_built_image
uses: docker/build-push-action@v6
with:
context: .
push: false
load: true
tags: ${{ env.GHCR_REGISTRY }}/${{ inputs.ghcr_image_name }}:${{ github.sha }}-test
labels: |
org.opencontainers.image.title=docling-serve
org.opencontainers.image.test=true
platforms: linux/amd64 # when 'load' is true, we can't use a list ${{ inputs.platforms }}
cache-from: type=gha
cache-to: type=gha,mode=max
file: Containerfile
build-args: ${{ inputs.build_args }}
- name: Test image
if: steps.ghcr_export_built_image.outcome == 'success'
run: |
set -e
IMAGE_TAG="${{ env.GHCR_REGISTRY }}/${{ inputs.ghcr_image_name }}:${{ github.sha }}-test"
echo "Testing local image: $IMAGE_TAG"
# Remove existing container if any
docker rm -f docling-serve-test-container 2>/dev/null || true
echo "Starting container..."
docker run -d -p 5001:5001 --name docling-serve-test-container "$IMAGE_TAG"
echo "Waiting 15s for container to boot..."
sleep 15
# Health check
echo "Checking service health..."
for i in {1..20}; do
HEALTH_RESPONSE=$(curl -s http://localhost:5001/health || true)
echo "Health check response [$i]: $HEALTH_RESPONSE"
if echo "$HEALTH_RESPONSE" | grep -q '"status":"ok"'; then
echo "Service is healthy!"
# Install pytest and dependencies
echo "Installing pytest and dependencies..."
pip install uv
uv venv --allow-existing
source .venv/bin/activate
uv sync --all-extras --no-extra flash-attn
# Run pytest tests
echo "Running tests..."
# Test import
python -c 'from docling_serve.app import create_app; create_app()'
# Run pytest and check result directly
if ! pytest -sv -k "test_convert_url" tests/test_1-url-async.py \
--disable-warnings; then
echo "Tests failed!"
docker logs docling-serve-test-container
docker rm -f docling-serve-test-container
exit 1
fi
echo "Tests passed successfully!"
break
else
echo "Waiting for service... [$i/20]"
sleep 3
fi
done
# Final health check if service didn't pass earlier
if ! echo "$HEALTH_RESPONSE" | grep -q '"status":"ok"'; then
echo "Service did not become healthy in time."
docker logs docling-serve-test-container
docker rm -f docling-serve-test-container
exit 1
fi
# Cleanup
echo "Cleaning up test container..."
docker rm -f docling-serve-test-container
echo "Cleaning up test image..."
docker rmi "$IMAGE_TAG"
- name: Generate artifact attestation
if: ${{ inputs.publish }}
@@ -120,7 +216,7 @@ jobs:
- name: Build and push image to quay.io
if: ${{ inputs.publish }}
# id: push-serve-cpu-quay
uses: docker/build-push-action@v5
uses: docker/build-push-action@v6
with:
context: .
push: ${{ inputs.publish }}
@@ -131,11 +227,8 @@ jobs:
cache-to: type=gha,mode=max
file: Containerfile
build-args: ${{ inputs.build_args }}
# - name: Inspect the image details
# run: |
# echo "${{ steps.ghcr_push.outputs.metadata }}"
pull: true
- name: Remove Local Docker Images
- name: Remove local Docker images
run: |
docker image prune -af

5
.gitignore vendored
View File

@@ -445,4 +445,7 @@ pip-selfcheck.json
.action-lint
.markdown-lint
cookies.txt
cookies.txt
# Examples
/examples/splitted_pdf/*

View File

@@ -7,12 +7,12 @@ repos:
- id: ruff-format
name: "Ruff formatter"
args: [--config=pyproject.toml]
files: '^(docling_serve|tests).*\.(py|ipynb)$'
files: '^(docling_serve|tests|examples).*\.(py|ipynb)$'
# Run the Ruff linter.
- id: ruff
name: "Ruff linter"
args: [--exit-non-zero-on-fix, --fix, --config=pyproject.toml]
files: '^(docling_serve|tests).*\.(py|ipynb)$'
files: '^(docling_serve|tests|examples).*\.(py|ipynb)$'
- repo: local
hooks:
- id: system
@@ -33,7 +33,7 @@ repos:
args: ["--config=.github/vale.ini"]
files: \.md$
- repo: https://github.com/astral-sh/uv-pre-commit
# uv version.
rev: 0.7.13
# uv version, https://github.com/astral-sh/uv-pre-commit/releases
rev: 0.8.19
hooks:
- id: uv-lock

View File

@@ -1,3 +1,153 @@
## [v1.6.0](https://github.com/docling-project/docling-serve/releases/tag/v1.6.0) - 2025-10-03
### Feature
* Pin new version of jobkit with granite-docling and connectors ([#391](https://github.com/docling-project/docling-serve/issues/391)) ([`0595d31`](https://github.com/docling-project/docling-serve/commit/0595d31d5b357553426215ca6771796a47e41324))
### Fix
* Update locked dependencies ([#392](https://github.com/docling-project/docling-serve/issues/392)) ([`45f0f3c`](https://github.com/docling-project/docling-serve/commit/45f0f3c8f95d418ac30e3744d27d02a63f9e4490))
* **UI:** Allow both lowercase and uppercase extensions ([#386](https://github.com/docling-project/docling-serve/issues/386)) ([`8b22a39`](https://github.com/docling-project/docling-serve/commit/8b22a391418d22c1a4d706f880341f28702057b5))
* Correctly raise HTTPException for Gateway Timeout ([#382](https://github.com/docling-project/docling-serve/issues/382)) ([`d4eac05`](https://github.com/docling-project/docling-serve/commit/d4eac053f9ce0a60f9070127335bdd56e193d7fa))
* Pinning of higher version of dependencies to fix potential security issues ([#363](https://github.com/docling-project/docling-serve/issues/363)) ([`ba61af2`](https://github.com/docling-project/docling-serve/commit/ba61af23591eff200481aa2e532cf7d0701f0ea4))
### Documentation
* Fix docs for websocket breaking condition ([#390](https://github.com/docling-project/docling-serve/issues/390)) ([`f6b5f0e`](https://github.com/docling-project/docling-serve/commit/f6b5f0e06354d2db7d03d274b114499e3407dccf))
### Docling libraries included in this release:
- docling 2.55.1
- docling-core 2.48.4
- docling-ibm-models 3.9.1
- docling-jobkit 1.6.0
- docling-mcp 1.3.2
- docling-parse 4.5.0
- docling-serve 1.6.0
## [v1.5.1](https://github.com/docling-project/docling-serve/releases/tag/v1.5.1) - 2025-09-17
### Fix
* Remove old dependencies, fixes in docling-parse and more minor dependencies upgrade ([#362](https://github.com/docling-project/docling-serve/issues/362)) ([`513ae0c`](https://github.com/docling-project/docling-serve/commit/513ae0c119b66d3b17cf9a5d371a0f7971f43be7))
* Updates rapidocr deps ([#361](https://github.com/docling-project/docling-serve/issues/361)) ([`bde0406`](https://github.com/docling-project/docling-serve/commit/bde040661fb65c67699326cd6281c0e6232e26f2))
### Docling libraries included in this release:
- docling 2.52.0
- docling-core 2.48.1
- docling-ibm-models 3.9.1
- docling-jobkit 1.5.0
- docling-mcp 1.2.0
- docling-parse 4.5.0
- docling-serve 1.5.1
## [v1.5.0](https://github.com/docling-project/docling-serve/releases/tag/v1.5.0) - 2025-09-09
### Feature
* Add chunking endpoints ([#353](https://github.com/docling-project/docling-serve/issues/353)) ([`9d6def0`](https://github.com/docling-project/docling-serve/commit/9d6def0ec8b1804ad31aa71defa17658d73d29a1))
### Docling libraries included in this release:
- docling 2.46.0
- docling 2.51.0
- docling-core 2.47.0
- docling-ibm-models 3.9.1
- docling-jobkit 1.5.0
- docling-mcp 1.2.0
- docling-parse 4.4.0
- docling-serve 1.5.0
## [v1.4.1](https://github.com/docling-project/docling-serve/releases/tag/v1.4.1) - 2025-09-08
### Fix
* Trigger fix after ci fixes ([#355](https://github.com/docling-project/docling-serve/issues/355)) ([`b0360d7`](https://github.com/docling-project/docling-serve/commit/b0360d723bff202dcf44a25a3173ec1995945fc2))
### Docling libraries included in this release:
- docling 2.46.0
- docling 2.51.0
- docling-core 2.47.0
- docling-ibm-models 3.9.1
- docling-jobkit 1.4.1
- docling-mcp 1.2.0
- docling-parse 4.4.0
- docling-serve 1.4.1
## [v1.4.0](https://github.com/docling-project/docling-serve/releases/tag/v1.4.0) - 2025-09-05
### Feature
* **docling:** Perfomance improvements in parsing, new layout model, fixes in html processing ([#352](https://github.com/docling-project/docling-serve/issues/352)) ([`d64a2a9`](https://github.com/docling-project/docling-serve/commit/d64a2a974a276c7ae3b105c448fd79f77a653d20))
### Fix
* Upgrade to latest docling version with fixes ([#335](https://github.com/docling-project/docling-serve/issues/335)) ([`e544947`](https://github.com/docling-project/docling-serve/commit/e5449472b2a3e71796f41c8a58c251d8229305c1))
### Documentation
* Add split processing example ([#303](https://github.com/docling-project/docling-serve/issues/303)) ([`0d4545a`](https://github.com/docling-project/docling-serve/commit/0d4545a65a5a941fc1fdefda57e39cfb1ea106ab))
* Document DOCLING_NUM_THREADS environment variable ([#341](https://github.com/docling-project/docling-serve/issues/341)) ([`27fdd7b`](https://github.com/docling-project/docling-serve/commit/27fdd7b85ab18b3eece428366f46dc5cf0995e38))
* Fix parameters typo ([#333](https://github.com/docling-project/docling-serve/issues/333)) ([`81f0a8d`](https://github.com/docling-project/docling-serve/commit/81f0a8ddf80a532042d550ae4568f891458b45e7))
* Describe how to use Docling MCP ([#332](https://github.com/docling-project/docling-serve/issues/332)) ([`a69cc86`](https://github.com/docling-project/docling-serve/commit/a69cc867f5a3fb76648803ca866d65cc3a75c6b8))
### Docling libraries included in this release:
- docling 2.46.0
- docling 2.51.0
- docling-core 2.47.0
- docling-ibm-models 3.9.1
- docling-jobkit 1.4.1
- docling-mcp 1.2.0
- docling-parse 4.4.0
- docling-serve 1.4.0
## [v1.3.1](https://github.com/docling-project/docling-serve/releases/tag/v1.3.1) - 2025-08-21
### Fix
* Configuration and performance fixes via upgrade of packages ([#328](https://github.com/docling-project/docling-serve/issues/328)) ([`f02dbc0`](https://github.com/docling-project/docling-serve/commit/f02dbc01449fe1caf3fb4a73c0a5f4adf8265faf))
### Documentation
* Fix parameter in api key docs ([#323](https://github.com/docling-project/docling-serve/issues/323)) ([`37fe022`](https://github.com/docling-project/docling-serve/commit/37fe02277b3e2358eced28e15b4360e7c82d3b43))
## [v1.3.0](https://github.com/docling-project/docling-serve/releases/tag/v1.3.0) - 2025-08-14
### Feature
* Add configuration option for apikey security ([#322](https://github.com/docling-project/docling-serve/issues/322)) ([`9a64410`](https://github.com/docling-project/docling-serve/commit/9a644105523d312431993ded8dd88e064550a5db))
* Add RQ engine ([#315](https://github.com/docling-project/docling-serve/issues/315)) ([`885f319`](https://github.com/docling-project/docling-serve/commit/885f319d3a3488a4090869560447437a4104f14e))
### Documentation
* Example of docling-serve deployment in the RQ engine mode ([#321](https://github.com/docling-project/docling-serve/issues/321)) ([`71edf41`](https://github.com/docling-project/docling-serve/commit/71edf4184960d8664ef9da20617e2d0f91793d36))
* Handling models in docling-serve ([#319](https://github.com/docling-project/docling-serve/issues/319)) ([`6e9aa8c`](https://github.com/docling-project/docling-serve/commit/6e9aa8c759220458281c7fe4c87443ac41023eee))
* Add Gradio cache usage ([#312](https://github.com/docling-project/docling-serve/issues/312)) ([`d584895`](https://github.com/docling-project/docling-serve/commit/d584895e1108d71a0f45deadcd3c669eb0a58133))
## [v1.2.2](https://github.com/docling-project/docling-serve/releases/tag/v1.2.2) - 2025-08-13
### Fix
* Update of transformers module to 4.55.1 ([#316](https://github.com/docling-project/docling-serve/issues/316)) ([`7692eb2`](https://github.com/docling-project/docling-serve/commit/7692eb26006fd4deaa021180c99e23a1b65de506))
## [v1.2.1](https://github.com/docling-project/docling-serve/releases/tag/v1.2.1) - 2025-08-13
### Fix
* Handling of vlm model options and update deps ([#314](https://github.com/docling-project/docling-serve/issues/314)) ([`8b470cb`](https://github.com/docling-project/docling-serve/commit/8b470cba8ef500c271eb84c8368c8a1a1a5a6d6a))
* Add missing response type in sync endpoints ([#309](https://github.com/docling-project/docling-serve/issues/309)) ([`8048f45`](https://github.com/docling-project/docling-serve/commit/8048f4589a91de2b2b391ab33a326efd1b29f25b))
### Documentation
* Update readme to use v1 ([#306](https://github.com/docling-project/docling-serve/issues/306)) ([`b3058e9`](https://github.com/docling-project/docling-serve/commit/b3058e91e0c56e27110eb50f22cbdd89640bf398))
* Update deployment examples to use v1 API ([#308](https://github.com/docling-project/docling-serve/issues/308)) ([`63da9ee`](https://github.com/docling-project/docling-serve/commit/63da9eedebae3ad31d04e65635e573194e413793))
* Fix typo in v1 migration instructions ([#307](https://github.com/docling-project/docling-serve/issues/307)) ([`b15dc25`](https://github.com/docling-project/docling-serve/commit/b15dc2529f78d68a475e5221c37408c3f77d8588))
## [v1.2.0](https://github.com/docling-project/docling-serve/releases/tag/v1.2.0) - 2025-08-07
### Feature
* Workers without shared models and convert params ([#304](https://github.com/docling-project/docling-serve/issues/304)) ([`db3fdb5`](https://github.com/docling-project/docling-serve/commit/db3fdb5bc1a0ae250afd420d737abc4071a7546c))
* Add rocm image build support and fix cuda ([#292](https://github.com/docling-project/docling-serve/issues/292)) ([`fd1b987`](https://github.com/docling-project/docling-serve/commit/fd1b987e8dc174f1a6013c003dde33e9acbae39a))
## [v1.1.0](https://github.com/docling-project/docling-serve/releases/tag/v1.1.0) - 2025-07-30
### Feature

View File

@@ -1,13 +1,17 @@
ARG BASE_IMAGE=quay.io/sclorg/python-312-c9s:c9s
FROM ${BASE_IMAGE}
ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.8.19
USER 0
ARG UV_SYNC_EXTRA_ARGS=""
FROM ${BASE_IMAGE} AS docling-base
###################################################################################################
# OS Layer #
###################################################################################################
USER 0
RUN --mount=type=bind,source=os-packages.txt,target=/tmp/os-packages.txt \
dnf -y install --best --nodocs --setopt=install_weak_deps=False dnf-plugins-core && \
dnf config-manager --best --nodocs --setopt=install_weak_deps=False --save && \
@@ -21,16 +25,19 @@ RUN /usr/bin/fix-permissions /opt/app-root/src/.cache
ENV TESSDATA_PREFIX=/usr/share/tesseract/tessdata/
FROM ${UV_IMAGE} AS uv_stage
###################################################################################################
# Docling layer #
###################################################################################################
FROM docling-base
USER 1001
WORKDIR /opt/app-root/src
ENV \
# On container environments, always set a thread budget to avoid undesired thread congestion.
OMP_NUM_THREADS=4 \
LANG=en_US.UTF-8 \
LC_ALL=en_US.UTF-8 \
@@ -40,9 +47,9 @@ ENV \
UV_PROJECT_ENVIRONMENT=/opt/app-root \
DOCLING_SERVE_ARTIFACTS_PATH=/opt/app-root/src/.cache/docling/models
ARG UV_SYNC_EXTRA_ARGS=""
ARG UV_SYNC_EXTRA_ARGS
RUN --mount=from=ghcr.io/astral-sh/uv:0.7.19,source=/uv,target=/bin/uv \
RUN --mount=from=uv_stage,source=/uv,target=/bin/uv \
--mount=type=cache,target=/opt/app-root/src/.cache/uv,uid=1001 \
--mount=type=bind,source=uv.lock,target=uv.lock \
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
@@ -61,7 +68,8 @@ RUN echo "Downloading models..." && \
chmod -R g=u ${DOCLING_SERVE_ARTIFACTS_PATH}
COPY --chown=1001:0 ./docling_serve ./docling_serve
RUN --mount=from=ghcr.io/astral-sh/uv:0.7.19,source=/uv,target=/bin/uv \
RUN --mount=from=uv_stage,source=/uv,target=/bin/uv \
--mount=type=cache,target=/opt/app-root/src/.cache/uv,uid=1001 \
--mount=type=bind,source=uv.lock,target=uv.lock \
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \

View File

@@ -60,6 +60,13 @@ docling-serve-cu128-image: Containerfile ## Build docling-serve container image
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu128:$(TAG) ghcr.io/docling-project/docling-serve-cu128:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-cu128:$(TAG) quay.io/docling-project/docling-serve-cu128:$(BRANCH_TAG)
.PHONY: docling-serve-rocm-image
docling-serve-rocm-image: Containerfile ## Build docling-serve container image with ROCm support
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve with ROCm 6.3]"
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-group pypi --group rocm --no-extra flash-attn" -f Containerfile --platform linux/amd64 -t ghcr.io/docling-project/docling-serve-rocm:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-rocm:$(TAG) ghcr.io/docling-project/docling-serve-rocm:$(BRANCH_TAG)
$(CMD_PREFIX) docker tag ghcr.io/docling-project/docling-serve-rocm:$(TAG) quay.io/docling-project/docling-serve-rocm:$(BRANCH_TAG)
.PHONY: action-lint
action-lint: .action-lint ## Lint GitHub Action workflows
.action-lint: $(shell find .github -type f) | action-lint-file
@@ -107,3 +114,24 @@ run-docling-cu124: ## Run the docling-serve container with GPU support and assig
$(CMD_PREFIX) docker rm -f docling-serve-cu124 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN CUDA 12.4]"
$(CMD_PREFIX) docker run -it --name docling-serve-cu124 -p 5001:5001 ghcr.io/docling-project/docling-serve-cu124:main
.PHONY: run-docling-cu126
run-docling-cu126: ## Run the docling-serve container with GPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-cu126 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN CUDA 12.6]"
$(CMD_PREFIX) docker run -it --name docling-serve-cu126 -p 5001:5001 ghcr.io/docling-project/docling-serve-cu126:main
.PHONY: run-docling-cu128
run-docling-cu128: ## Run the docling-serve container with GPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-cu128 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN CUDA 12.8]"
$(CMD_PREFIX) docker run -it --name docling-serve-cu128 -p 5001:5001 ghcr.io/docling-project/docling-serve-cu128:main
.PHONY: run-docling-rocm
run-docling-rocm: ## Run the docling-serve container with GPU support and assign a container name
$(ECHO_PREFIX) printf " %-12s Removing existing container if it exists...\n" "[CLEANUP]"
$(CMD_PREFIX) docker rm -f docling-serve-rocm 2>/dev/null || true
$(ECHO_PREFIX) printf " %-12s Running docling-serve container with GPU support on port 5001...\n" "[RUN ROCm 6.3]"
$(CMD_PREFIX) docker run -it --name docling-serve-rocm -p 5001:5001 ghcr.io/docling-project/docling-serve-rocm:main

View File

@@ -36,7 +36,8 @@ The server is available at
- API <http://127.0.0.1:5001>
- API documentation <http://127.0.0.1:5001/docs>
- UI playground <http://127.0.0.1:5001/ui>
![swagger.png](img/swagger.png)
![API documentation](img/fastapi-ui.png)
Try it out with a simple conversion:
@@ -46,21 +47,36 @@ curl -X 'POST' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"http_sources": [{"url": "https://arxiv.org/pdf/2501.17887"}]
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
### Container images
### Container Images
Available container images:
The following container images are available for running **Docling Serve** with different hardware and PyTorch configurations:
| Name | Description | Arch | Size |
| -----|-------------|------|------|
| [`ghcr.io/docling-project/docling-serve`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve) <br /> [`quay.io/docling-project/docling-serve`](https://quay.io/repository/docling-project/docling-serve) | Simple image for Docling Serve, installing all packages from the official pypi.org index. | `linux/amd64`, `linux/arm64` | 3.6 GB (arm64) <br /> 8.7 GB (amd64) |
| [`ghcr.io/docling-project/docling-serve-cpu`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cpu) <br /> [`quay.io/docling-project/docling-serve-cpu`](https://quay.io/repository/docling-project/docling-serve-cpu) | Cpu-only image which installs `torch` from the pytorch cpu index. | `linux/amd64`, `linux/arm64` | 3.6 GB |
| [`ghcr.io/docling-project/docling-serve-cu124`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cu124) <br /> [`quay.io/docling-project/docling-serve-cu124`](https://quay.io/repository/docling-project/docling-serve-cu124) | Cuda 12.4 image which installs `torch` from the pytorch cu124 index. | `linux/amd64` | 8.7 GB |
| [`ghcr.io/docling-project/docling-serve-cu126`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cu126) <br /> [`quay.io/docling-project/docling-serve-cu126`](https://quay.io/repository/docling-project/docling-serve-cu126) | Cuda 12.6 image which installs `torch` from the pytorch cu126 index. | `linux/amd64` | 8.7 GB |
| [`ghcr.io/docling-project/docling-serve-cu128`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cu128) <br /> [`quay.io/docling-project/docling-serve-cu128`](https://quay.io/repository/docling-project/docling-serve-cu128) | Cuda 12.8 image which installs `torch` from the pytorch cu128 index. | `linux/amd64` | 8.7 GB |
#### 📦 Distributed Images
| Image | Description | Architectures | Size |
|-------|-------------|----------------|------|
| [`ghcr.io/docling-project/docling-serve`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve) <br> [`quay.io/docling-project/docling-serve`](https://quay.io/repository/docling-project/docling-serve) | Base image with all packages installed from the official PyPI index. | `linux/amd64`, `linux/arm64` | 4.4 GB (arm64) <br> 8.7 GB (amd64) |
| [`ghcr.io/docling-project/docling-serve-cpu`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cpu) <br> [`quay.io/docling-project/docling-serve-cpu`](https://quay.io/repository/docling-project/docling-serve-cpu) | CPU-only variant, using `torch` from the PyTorch CPU index. | `linux/amd64`, `linux/arm64` | 4.4 GB |
| [`ghcr.io/docling-project/docling-serve-cu126`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cu126) <br> [`quay.io/docling-project/docling-serve-cu126`](https://quay.io/repository/docling-project/docling-serve-cu126) | CUDA 12.6 build with `torch` from the cu126 index. | `linux/amd64` | 10.0 GB |
| [`ghcr.io/docling-project/docling-serve-cu128`](https://github.com/docling-project/docling-serve/pkgs/container/docling-serve-cu128) <br> [`quay.io/docling-project/docling-serve-cu128`](https://quay.io/repository/docling-project/docling-serve-cu128) | CUDA 12.8 build with `torch` from the cu128 index. | `linux/amd64` | 11.4 GB |
#### 🚫 Not Distributed
An image for AMD ROCm 6.3 (`docling-serve-rocm`) is supported but **not published** due to its large size.
To build it locally:
```bash
git clone --branch main git@github.com:docling-project/docling-serve.git
cd docling-serve/
make docling-serve-rocm-image
```
For deployment using Docker Compose, see [docs/deployment.md](docs/deployment.md).
Coming soon: `docling-serve-slim` images will reduce the size by skipping the model weights download.

View File

@@ -11,6 +11,7 @@ import uvicorn
from rich.console import Console
from docling_serve.settings import docling_serve_settings, uvicorn_settings
from docling_serve.storage import get_scratch
warnings.filterwarnings(action="ignore", category=UserWarning, module="pydantic|torch")
warnings.filterwarnings(action="ignore", category=FutureWarning, module="easyocr")
@@ -361,6 +362,37 @@ def run(
)
@app.command()
def rq_worker() -> Any:
"""
Run the [bold]Docling JobKit[/bold] RQ worker.
"""
from docling_jobkit.convert.manager import DoclingConverterManagerConfig
from docling_jobkit.orchestrators.rq.orchestrator import RQOrchestratorConfig
from docling_jobkit.orchestrators.rq.worker import run_worker
rq_config = RQOrchestratorConfig(
redis_url=docling_serve_settings.eng_rq_redis_url,
results_prefix=docling_serve_settings.eng_rq_results_prefix,
sub_channel=docling_serve_settings.eng_rq_sub_channel,
scratch_dir=get_scratch(),
)
cm_config = DoclingConverterManagerConfig(
artifacts_path=docling_serve_settings.artifacts_path,
options_cache_size=docling_serve_settings.options_cache_size,
enable_remote_services=docling_serve_settings.enable_remote_services,
allow_external_plugins=docling_serve_settings.allow_external_plugins,
max_num_pages=docling_serve_settings.max_num_pages,
max_file_size=docling_serve_settings.max_file_size,
)
run_worker(
rq_config=rq_config,
cm_config=cm_config,
)
def main() -> None:
app()

View File

@@ -18,6 +18,7 @@ from fastapi import (
UploadFile,
WebSocket,
WebSocketDisconnect,
status,
)
from fastapi.middleware.cors import CORSMiddleware
from fastapi.openapi.docs import (
@@ -34,12 +35,17 @@ from docling_jobkit.datamodel.callback import (
ProgressCallbackRequest,
ProgressCallbackResponse,
)
from docling_jobkit.datamodel.chunking import (
BaseChunkerOptions,
ChunkingExportOptions,
HierarchicalChunkerOptions,
HybridChunkerOptions,
)
from docling_jobkit.datamodel.http_inputs import FileSource, HttpSource
from docling_jobkit.datamodel.s3_coords import S3Coordinates
from docling_jobkit.datamodel.task import Task, TaskSource
from docling_jobkit.datamodel.task import Task, TaskSource, TaskType
from docling_jobkit.datamodel.task_targets import (
InBodyTarget,
TaskTarget,
ZipTarget,
)
from docling_jobkit.orchestrators.base_orchestrator import (
@@ -48,15 +54,20 @@ from docling_jobkit.orchestrators.base_orchestrator import (
TaskNotFoundError,
)
from docling_serve.auth import APIKeyAuth, AuthenticationResult
from docling_serve.datamodel.convert import ConvertDocumentsRequestOptions
from docling_serve.datamodel.requests import (
ConvertDocumentsRequest,
FileSourceRequest,
GenericChunkDocumentsRequest,
HttpSourceRequest,
S3SourceRequest,
TargetName,
TargetRequest,
make_request_model,
)
from docling_serve.datamodel.responses import (
ChunkDocumentResponse,
ClearResponse,
ConvertDocumentResponse,
HealthCheckResponse,
@@ -156,6 +167,7 @@ def create_app(): # noqa: C901
offline_docs_assets = True
_log.info("Found static assets.")
require_auth = APIKeyAuth(docling_serve_settings.api_key)
app = FastAPI(
title="Docling Serve",
docs_url=None if offline_docs_assets else "/swagger",
@@ -246,10 +258,11 @@ def create_app(): # noqa: C901
########################
async def _enque_source(
orchestrator: BaseOrchestrator, conversion_request: ConvertDocumentsRequest
orchestrator: BaseOrchestrator,
request: ConvertDocumentsRequest | GenericChunkDocumentsRequest,
) -> Task:
sources: list[TaskSource] = []
for s in conversion_request.sources:
for s in request.sources:
if isinstance(s, FileSourceRequest):
sources.append(FileSource.model_validate(s))
elif isinstance(s, HttpSourceRequest):
@@ -257,18 +270,41 @@ def create_app(): # noqa: C901
elif isinstance(s, S3SourceRequest):
sources.append(S3Coordinates.model_validate(s))
convert_options: ConvertDocumentsRequestOptions
chunking_options: BaseChunkerOptions | None = None
chunking_export_options = ChunkingExportOptions()
task_type: TaskType
if isinstance(request, ConvertDocumentsRequest):
task_type = TaskType.CONVERT
convert_options = request.options
elif isinstance(request, GenericChunkDocumentsRequest):
task_type = TaskType.CHUNK
convert_options = request.convert_options
chunking_options = request.chunking_options
chunking_export_options.include_converted_doc = (
request.include_converted_doc
)
else:
raise RuntimeError("Uknown request type.")
task = await orchestrator.enqueue(
task_type=task_type,
sources=sources,
options=conversion_request.options,
target=conversion_request.target,
convert_options=convert_options,
chunking_options=chunking_options,
chunking_export_options=chunking_export_options,
target=request.target,
)
return task
async def _enque_file(
orchestrator: BaseOrchestrator,
files: list[UploadFile],
options: ConvertDocumentsRequestOptions,
target: TaskTarget,
task_type: TaskType,
convert_options: ConvertDocumentsRequestOptions,
chunking_options: BaseChunkerOptions | None,
chunking_export_options: ChunkingExportOptions | None,
target: TargetRequest,
) -> Task:
_log.info(f"Received {len(files)} files for processing.")
@@ -281,7 +317,12 @@ def create_app(): # noqa: C901
file_sources.append(DocumentStream(name=name, stream=buf))
task = await orchestrator.enqueue(
sources=file_sources, options=options, target=target
task_type=task_type,
sources=file_sources,
convert_options=convert_options,
chunking_options=chunking_options,
chunking_export_options=chunking_export_options,
target=target,
)
return task
@@ -378,7 +419,7 @@ def create_app(): # noqa: C901
response = RedirectResponse(url=logo_url)
return response
@app.get("/health")
@app.get("/health", tags=["health"])
def health() -> HealthCheckResponse:
return HealthCheckResponse()
@@ -390,7 +431,8 @@ def create_app(): # noqa: C901
# Convert a document from URL(s)
@app.post(
"/v1/convert/source",
response_model=ConvertDocumentResponse,
tags=["convert"],
response_model=ConvertDocumentResponse | PresignedUrlConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
@@ -400,11 +442,12 @@ def create_app(): # noqa: C901
)
async def process_url(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
conversion_request: ConvertDocumentsRequest,
):
task = await _enque_source(
orchestrator=orchestrator, conversion_request=conversion_request
orchestrator=orchestrator, request=conversion_request
)
completed = await _wait_task_complete(
orchestrator=orchestrator, task_id=task.task_id
@@ -412,21 +455,30 @@ def create_app(): # noqa: C901
if not completed:
# TODO: abort task!
return HTTPException(
raise HTTPException(
status_code=504,
detail=f"Conversion is taking too long. The maximum wait time is configure as DOCLING_SERVE_MAX_SYNC_WAIT={docling_serve_settings.max_sync_wait}.",
)
task = await orchestrator.get_raw_task(task_id=task.task_id)
task_result = await orchestrator.task_result(task_id=task.task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task=task, orchestrator=orchestrator, background_tasks=background_tasks
task_id=task.task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
# Convert a document from file(s)
@app.post(
"/v1/convert/file",
response_model=ConvertDocumentResponse,
tags=["convert"],
response_model=ConvertDocumentResponse | PresignedUrlConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
@@ -435,6 +487,7 @@ def create_app(): # noqa: C901
)
async def process_file(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
files: list[UploadFile],
options: Annotated[
@@ -444,7 +497,13 @@ def create_app(): # noqa: C901
):
target = InBodyTarget() if target_type == TargetName.INBODY else ZipTarget()
task = await _enque_file(
orchestrator=orchestrator, files=files, options=options, target=target
task_type=TaskType.CONVERT,
orchestrator=orchestrator,
files=files,
convert_options=options,
chunking_options=None,
chunking_export_options=None,
target=target,
)
completed = await _wait_task_complete(
orchestrator=orchestrator, task_id=task.task_id
@@ -452,34 +511,45 @@ def create_app(): # noqa: C901
if not completed:
# TODO: abort task!
return HTTPException(
raise HTTPException(
status_code=504,
detail=f"Conversion is taking too long. The maximum wait time is configure as DOCLING_SERVE_MAX_SYNC_WAIT={docling_serve_settings.max_sync_wait}.",
)
task = await orchestrator.get_raw_task(task_id=task.task_id)
task_result = await orchestrator.task_result(task_id=task.task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task=task, orchestrator=orchestrator, background_tasks=background_tasks
task_id=task.task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
# Convert a document from URL(s) using the async api
@app.post(
"/v1/convert/source/async",
tags=["convert"],
response_model=TaskStatusResponse,
)
async def process_url_async(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
conversion_request: ConvertDocumentsRequest,
):
task = await _enque_source(
orchestrator=orchestrator, conversion_request=conversion_request
orchestrator=orchestrator, request=conversion_request
)
task_queue_position = await orchestrator.get_queue_position(
task_id=task.task_id
)
return TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
@@ -488,9 +558,11 @@ def create_app(): # noqa: C901
# Convert a document from file(s) using the async api
@app.post(
"/v1/convert/file/async",
tags=["convert"],
response_model=TaskStatusResponse,
)
async def process_file_async(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
background_tasks: BackgroundTasks,
files: list[UploadFile],
@@ -501,24 +573,253 @@ def create_app(): # noqa: C901
):
target = InBodyTarget() if target_type == TargetName.INBODY else ZipTarget()
task = await _enque_file(
orchestrator=orchestrator, files=files, options=options, target=target
task_type=TaskType.CONVERT,
orchestrator=orchestrator,
files=files,
convert_options=options,
chunking_options=None,
chunking_export_options=None,
target=target,
)
task_queue_position = await orchestrator.get_queue_position(
task_id=task.task_id
)
return TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
# Chunking endpoints
for display_name, path_name, opt_cls in (
("HybridChunker", "hybrid", HybridChunkerOptions),
("HierarchicalChunker", "hierarchical", HierarchicalChunkerOptions),
):
req_cls = make_request_model(opt_cls)
@app.post(
f"/v1/chunk/{path_name}/source/async",
name=f"Chunk sources with {display_name} as async task",
tags=["chunk"],
response_model=TaskStatusResponse,
)
async def chunk_source_async(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
request: req_cls,
):
task = await _enque_source(orchestrator=orchestrator, request=request)
task_queue_position = await orchestrator.get_queue_position(
task_id=task.task_id
)
return TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
@app.post(
f"/v1/chunk/{path_name}/file/async",
name=f"Chunk files with {display_name} as async task",
tags=["chunk"],
response_model=TaskStatusResponse,
)
async def chunk_file_async(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
files: list[UploadFile],
convert_options: Annotated[
ConvertDocumentsRequestOptions,
FormDepends(
ConvertDocumentsRequestOptions,
prefix="convert_",
excluded_fields=[
"to_formats",
],
),
],
chunking_options: Annotated[
opt_cls,
FormDepends(
HybridChunkerOptions,
prefix="chunking_",
excluded_fields=["chunker"],
),
],
include_converted_doc: Annotated[
bool,
Form(
description="If true, the output will include both the chunks and the converted document."
),
] = False,
target_type: Annotated[
TargetName,
Form(description="Specification for the type of output target."),
] = TargetName.INBODY,
):
target = InBodyTarget() if target_type == TargetName.INBODY else ZipTarget()
task = await _enque_file(
task_type=TaskType.CHUNK,
orchestrator=orchestrator,
files=files,
convert_options=convert_options,
chunking_options=chunking_options,
chunking_export_options=ChunkingExportOptions(
include_converted_doc=include_converted_doc
),
target=target,
)
task_queue_position = await orchestrator.get_queue_position(
task_id=task.task_id
)
return TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
)
@app.post(
f"/v1/chunk/{path_name}/source",
name=f"Chunk sources with {display_name}",
tags=["chunk"],
response_model=ChunkDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
# "description": "Return the JSON item or an image.",
}
},
)
async def chunk_source(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
request: req_cls,
):
task = await _enque_source(orchestrator=orchestrator, request=request)
completed = await _wait_task_complete(
orchestrator=orchestrator, task_id=task.task_id
)
if not completed:
# TODO: abort task!
raise HTTPException(
status_code=504,
detail=f"Conversion is taking too long. The maximum wait time is configure as DOCLING_SERVE_MAX_SYNC_WAIT={docling_serve_settings.max_sync_wait}.",
)
task_result = await orchestrator.task_result(task_id=task.task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task_id=task.task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
@app.post(
f"/v1/chunk/{path_name}/file",
name=f"Chunk files with {display_name}",
tags=["chunk"],
response_model=ChunkDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
}
},
)
async def chunk_file(
background_tasks: BackgroundTasks,
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
files: list[UploadFile],
convert_options: Annotated[
ConvertDocumentsRequestOptions,
FormDepends(
ConvertDocumentsRequestOptions,
prefix="convert_",
excluded_fields=[
"to_formats",
],
),
],
chunking_options: Annotated[
opt_cls,
FormDepends(
HybridChunkerOptions,
prefix="chunking_",
excluded_fields=["chunker"],
),
],
include_converted_doc: Annotated[
bool,
Form(
description="If true, the output will include both the chunks and the converted document."
),
] = False,
target_type: Annotated[
TargetName,
Form(description="Specification for the type of output target."),
] = TargetName.INBODY,
):
target = InBodyTarget() if target_type == TargetName.INBODY else ZipTarget()
task = await _enque_file(
task_type=TaskType.CHUNK,
orchestrator=orchestrator,
files=files,
convert_options=convert_options,
chunking_options=chunking_options,
chunking_export_options=ChunkingExportOptions(
include_converted_doc=include_converted_doc
),
target=target,
)
completed = await _wait_task_complete(
orchestrator=orchestrator, task_id=task.task_id
)
if not completed:
# TODO: abort task!
raise HTTPException(
status_code=504,
detail=f"Conversion is taking too long. The maximum wait time is configure as DOCLING_SERVE_MAX_SYNC_WAIT={docling_serve_settings.max_sync_wait}.",
)
task_result = await orchestrator.task_result(task_id=task.task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task_id=task.task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
# Task status poll
@app.get(
"/v1/status/poll/{task_id}",
tags=["tasks"],
response_model=TaskStatusResponse,
)
async def task_status_poll(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
task_id: str,
wait: Annotated[
@@ -533,6 +834,7 @@ def create_app(): # noqa: C901
raise HTTPException(status_code=404, detail="Task not found.")
return TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
@@ -546,7 +848,15 @@ def create_app(): # noqa: C901
websocket: WebSocket,
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
task_id: str,
api_key: Annotated[str, Query()] = "",
):
if docling_serve_settings.api_key:
if api_key != docling_serve_settings.api_key:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Api key is required as ?api_key=SECRET.",
)
assert isinstance(orchestrator.notifier, WebsocketNotifier)
await websocket.accept()
@@ -568,6 +878,7 @@ def create_app(): # noqa: C901
task_queue_position = await orchestrator.get_queue_position(task_id=task_id)
task_response = TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
@@ -583,6 +894,7 @@ def create_app(): # noqa: C901
)
task_response = TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,
@@ -605,7 +917,10 @@ def create_app(): # noqa: C901
# Task result
@app.get(
"/v1/result/{task_id}",
response_model=ConvertDocumentResponse | PresignedUrlConvertDocumentResponse,
tags=["tasks"],
response_model=ConvertDocumentResponse
| PresignedUrlConvertDocumentResponse
| ChunkDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
@@ -613,14 +928,23 @@ def create_app(): # noqa: C901
},
)
async def task_result(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
background_tasks: BackgroundTasks,
task_id: str,
):
try:
task = await orchestrator.get_raw_task(task_id=task_id)
task_result = await orchestrator.task_result(task_id=task_id)
if task_result is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
response = await prepare_response(
task=task, orchestrator=orchestrator, background_tasks=background_tasks
task_id=task_id,
task_result=task_result,
orchestrator=orchestrator,
background_tasks=background_tasks,
)
return response
except TaskNotFoundError:
@@ -629,9 +953,12 @@ def create_app(): # noqa: C901
# Update task progress
@app.post(
"/v1/callback/task/progress",
tags=["internal"],
include_in_schema=False,
response_model=ProgressCallbackResponse,
)
async def callback_task_progress(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
request: ProgressCallbackRequest,
):
@@ -650,9 +977,11 @@ def create_app(): # noqa: C901
# Offload models
@app.get(
"/v1/clear/converters",
tags=["clear"],
response_model=ClearResponse,
)
async def clear_converters(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
):
await orchestrator.clear_converters()
@@ -661,9 +990,11 @@ def create_app(): # noqa: C901
# Clean results
@app.get(
"/v1/clear/results",
tags=["clear"],
response_model=ClearResponse,
)
async def clear_results(
auth: Annotated[AuthenticationResult, Depends(require_auth)],
orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
older_then: float = 3600,
):

56
docling_serve/auth.py Normal file
View File

@@ -0,0 +1,56 @@
from typing import Any
from fastapi import HTTPException, Request, status
from fastapi.security import APIKeyHeader
from pydantic import BaseModel
class AuthenticationResult(BaseModel):
valid: bool
errors: list[str] = []
detail: Any | None = None
class APIKeyAuth(APIKeyHeader):
"""
FastAPI dependency which evaluates a status API Key.
"""
def __init__(
self,
api_key: str,
header_name: str = "X-Api-Key",
fail_on_unauthorized: bool = True,
) -> None:
self.api_key = api_key
self.header_name = header_name
super().__init__(name=self.header_name, auto_error=False)
async def _validate_api_key(self, header_api_key: str | None):
if header_api_key is None:
return AuthenticationResult(
valid=False, errors=[f"Missing header {self.header_name}."]
)
header_api_key = header_api_key.strip()
# Otherwise check the apikey
if header_api_key == self.api_key or self.api_key == "":
return AuthenticationResult(
valid=True,
detail=header_api_key,
)
else:
return AuthenticationResult(
valid=False,
errors=["The provided API Key is invalid."],
)
async def __call__(self, request: Request) -> AuthenticationResult: # type: ignore
header_api_key = await super().__call__(request=request)
result = await self._validate_api_key(header_api_key)
if self.api_key and not result.valid:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED, detail=result.detail
)
return result

View File

@@ -1,16 +1,20 @@
import enum
from typing import Annotated, Literal
from functools import cache
from typing import Annotated, Generic, Literal
from pydantic import BaseModel, Field, model_validator
from pydantic_core import PydanticCustomError
from typing_extensions import Self
from typing_extensions import Self, TypeVar
from docling_jobkit.datamodel.chunking import (
BaseChunkerOptions,
)
from docling_jobkit.datamodel.http_inputs import FileSource, HttpSource
from docling_jobkit.datamodel.s3_coords import S3Coordinates
from docling_jobkit.datamodel.task_targets import (
InBodyTarget,
PutTarget,
S3Target,
TaskTarget,
ZipTarget,
)
@@ -43,12 +47,17 @@ SourceRequestItem = Annotated[
FileSourceRequest | HttpSourceRequest | S3SourceRequest, Field(discriminator="kind")
]
TargetRequest = Annotated[
InBodyTarget | ZipTarget | S3Target | PutTarget,
Field(discriminator="kind"),
]
## Complete Source request
class ConvertDocumentsRequest(BaseModel):
options: ConvertDocumentsRequestOptions = ConvertDocumentsRequestOptions()
sources: list[SourceRequestItem]
target: TaskTarget = InBodyTarget()
target: TargetRequest = InBodyTarget()
@model_validator(mode="after")
def validate_s3_source_and_target(self) -> Self:
@@ -70,3 +79,52 @@ class ConvertDocumentsRequest(BaseModel):
"error target", 'target kind "s3" requires source kind "s3"'
)
return self
## Source chunking requests
class BaseChunkDocumentsRequest(BaseModel):
convert_options: Annotated[
ConvertDocumentsRequestOptions, Field(description="Conversion options.")
] = ConvertDocumentsRequestOptions()
sources: Annotated[
list[SourceRequestItem],
Field(description="List of input document sources to process."),
]
include_converted_doc: Annotated[
bool,
Field(
description="If true, the output will include both the chunks and the converted document."
),
] = False
target: Annotated[
TargetRequest, Field(description="Specification for the type of output target.")
] = InBodyTarget()
ChunkingOptT = TypeVar("ChunkingOptT", bound=BaseChunkerOptions)
class GenericChunkDocumentsRequest(BaseChunkDocumentsRequest, Generic[ChunkingOptT]):
chunking_options: ChunkingOptT
@cache
def make_request_model(
opt_type: type[ChunkingOptT],
) -> type[GenericChunkDocumentsRequest[ChunkingOptT]]:
"""
Dynamically create (and cache) a subclass of GenericChunkDocumentsRequest[opt_type]
with chunking_options having a default factory.
"""
return type(
f"{opt_type.__name__}DocumentsRequest",
(GenericChunkDocumentsRequest[opt_type],), # type: ignore[valid-type]
{
"__annotations__": {"chunking_options": opt_type},
"chunking_options": Field(
default_factory=opt_type, description="Options specific to the chunker."
),
},
)

View File

@@ -5,8 +5,12 @@ from pydantic import BaseModel
from docling.datamodel.document import ConversionStatus, ErrorItem
from docling.utils.profiling import ProfilingItem
from docling_core.types.doc import DoclingDocument
from docling_jobkit.datamodel.task_meta import TaskProcessingMeta
from docling_jobkit.datamodel.result import (
ChunkedDocumentResultItem,
ExportDocumentResponse,
ExportResult,
)
from docling_jobkit.datamodel.task_meta import TaskProcessingMeta, TaskType
# Status
@@ -18,17 +22,8 @@ class ClearResponse(BaseModel):
status: str = "ok"
class DocumentResponse(BaseModel):
filename: str
md_content: Optional[str] = None
json_content: Optional[DoclingDocument] = None
html_content: Optional[str] = None
text_content: Optional[str] = None
doctags_content: Optional[str] = None
class ConvertDocumentResponse(BaseModel):
document: DocumentResponse
document: ExportDocumentResponse
status: ConversionStatus
errors: list[ErrorItem] = []
processing_time: float
@@ -36,16 +31,25 @@ class ConvertDocumentResponse(BaseModel):
class PresignedUrlConvertDocumentResponse(BaseModel):
status: ConversionStatus
processing_time: float
num_converted: int
num_succeeded: int
num_failed: int
class ConvertDocumentErrorResponse(BaseModel):
status: ConversionStatus
class ChunkDocumentResponse(BaseModel):
chunks: list[ChunkedDocumentResultItem]
documents: list[ExportResult]
processing_time: float
class TaskStatusResponse(BaseModel):
task_id: str
task_type: TaskType
task_status: str
task_position: Optional[int] = None
task_meta: Optional[TaskProcessingMeta] = None

View File

@@ -233,15 +233,21 @@ def change_ocr_lang(ocr_engine):
return "english,chinese"
def wait_task_finish(task_id: str, return_as_file: bool):
def wait_task_finish(auth: str, task_id: str, return_as_file: bool):
conversion_sucess = False
task_finished = False
task_status = ""
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = str(auth)
ssl_ctx = get_ssl_context()
while not task_finished:
try:
response = httpx.get(
f"{get_api_endpoint()}/v1/status/poll/{task_id}?wait=5",
headers=headers,
verify=ssl_ctx,
timeout=15,
)
@@ -265,6 +271,7 @@ def wait_task_finish(task_id: str, return_as_file: bool):
try:
response = httpx.get(
f"{get_api_endpoint()}/v1/result/{task_id}",
headers=headers,
timeout=15,
verify=ssl_ctx,
)
@@ -279,6 +286,7 @@ def wait_task_finish(task_id: str, return_as_file: bool):
def process_url(
auth,
input_sources,
to_formats,
image_export_mode,
@@ -326,11 +334,18 @@ def process_url(
):
logger.error("No input sources provided.")
raise gr.Error("No input sources provided.", print_exception=False)
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = str(auth)
print(f"{headers=}")
try:
ssl_ctx = get_ssl_context()
response = httpx.post(
f"{get_api_endpoint()}/v1/convert/source/async",
json=parameters,
headers=headers,
verify=ssl_ctx,
timeout=60,
)
@@ -354,6 +369,7 @@ def file_to_base64(file):
def process_file(
auth,
files,
to_formats,
image_export_mode,
@@ -402,11 +418,16 @@ def process_file(
"target": target,
}
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = str(auth)
try:
ssl_ctx = get_ssl_context()
response = httpx.post(
f"{get_api_endpoint()}/v1/convert/source/async",
json=parameters,
headers=headers,
verify=ssl_ctx,
timeout=60,
)
@@ -480,7 +501,7 @@ with gr.Blocks(
css=css,
theme=theme,
title="Docling Serve",
delete_cache=(3600, 3600), # Delete all files older than 1 hour every hour
delete_cache=(3600, 36000), # Delete all files older than 10 hour every hour
) as ui:
# Constants stored in states to be able to pass them as inputs to functions
processing_text = gr.State("Processing your document(s), please wait...")
@@ -549,14 +570,17 @@ with gr.Blocks(
with gr.Tab("Convert File"):
with gr.Row():
with gr.Column(scale=4):
raw_exts = itertools.chain.from_iterable(FormatToExtensions.values())
file_input = gr.File(
elem_id="file_input_zone",
label="Upload File",
file_types=[
f".{v}"
for v in itertools.chain.from_iterable(
FormatToExtensions.values()
)
f".{v.lower()}"
for v in raw_exts # lowercase
]
+ [
f".{v.upper()}"
for v in raw_exts # uppercase
],
file_count="multiple",
scale=4,
@@ -565,6 +589,15 @@ with gr.Blocks(
file_process_btn = gr.Button("Process File", scale=1)
file_reset_btn = gr.Button("Reset", scale=1)
# Auth
with gr.Row(visible=bool(docling_serve_settings.api_key)):
with gr.Column():
auth = gr.Textbox(
label="Authentication",
placeholder="API Key",
type="password",
)
# Options
with gr.Accordion("Options") as options:
with gr.Row():
@@ -590,6 +623,7 @@ with gr.Blocks(
label="Image Export Mode",
value="embedded",
)
with gr.Row():
with gr.Column(scale=1, min_width=200):
pipeline = gr.Radio(
@@ -724,6 +758,7 @@ with gr.Blocks(
).then(
process_url,
inputs=[
auth,
url_input,
to_formats,
image_export_mode,
@@ -750,7 +785,7 @@ with gr.Blocks(
outputs=[content_output, file_output],
).then(
wait_task_finish,
inputs=[task_id_rendered, return_as_file],
inputs=[auth, task_id_rendered, return_as_file],
outputs=[
output_markdown,
output_markdown_rendered,
@@ -811,6 +846,7 @@ with gr.Blocks(
).then(
process_file,
inputs=[
auth,
file_input,
to_formats,
image_export_mode,
@@ -837,7 +873,7 @@ with gr.Blocks(
outputs=[content_output, file_output],
).then(
wait_task_finish,
inputs=[task_id_rendered, return_as_file],
inputs=[auth, task_id_rendered, return_as_file],
outputs=[
output_markdown,
output_markdown_rendered,

View File

@@ -29,10 +29,15 @@ def is_pydantic_model(type_):
# Adapted from
# https://github.com/fastapi/fastapi/discussions/8971#discussioncomment-7892972
def FormDepends(cls: type[BaseModel]):
def FormDepends(
cls: type[BaseModel], prefix: str = "", excluded_fields: list[str] = []
):
new_parameters = []
for field_name, model_field in cls.model_fields.items():
if field_name in excluded_fields:
continue
annotation = model_field.annotation
description = model_field.description
default = (
@@ -63,7 +68,7 @@ def FormDepends(cls: type[BaseModel]):
new_parameters.append(
inspect.Parameter(
name=field_name,
name=f"{prefix}{field_name}",
kind=inspect.Parameter.POSITIONAL_ONLY,
default=default,
annotation=annotation,
@@ -71,19 +76,23 @@ def FormDepends(cls: type[BaseModel]):
)
async def as_form_func(**data):
newdata = {}
for field_name, model_field in cls.model_fields.items():
value = data.get(field_name)
if field_name in excluded_fields:
continue
value = data.get(f"{prefix}{field_name}")
newdata[field_name] = value
annotation = model_field.annotation
# Parse nested models from JSON string
if value is not None and is_pydantic_model(annotation):
try:
validator = TypeAdapter(annotation)
data[field_name] = validator.validate_json(value)
newdata[field_name] = validator.validate_json(value)
except Exception as e:
raise ValueError(f"Invalid JSON for field '{field_name}': {e}")
return cls(**data)
return cls(**newdata)
sig = inspect.signature(as_form_func)
sig = sig.replace(parameters=new_parameters)

View File

@@ -3,6 +3,7 @@ from functools import lru_cache
from docling_jobkit.orchestrators.base_orchestrator import BaseOrchestrator
from docling_serve.settings import AsyncEngine, docling_serve_settings
from docling_serve.storage import get_scratch
@lru_cache
@@ -19,6 +20,8 @@ def get_async_orchestrator() -> BaseOrchestrator:
local_config = LocalOrchestratorConfig(
num_workers=docling_serve_settings.eng_loc_num_workers,
shared_models=docling_serve_settings.eng_loc_share_models,
scratch_dir=get_scratch(),
)
cm_config = DoclingConverterManagerConfig(
@@ -32,6 +35,20 @@ def get_async_orchestrator() -> BaseOrchestrator:
cm = DoclingConverterManager(config=cm_config)
return LocalOrchestrator(config=local_config, converter_manager=cm)
elif docling_serve_settings.eng_kind == AsyncEngine.RQ:
from docling_jobkit.orchestrators.rq.orchestrator import (
RQOrchestrator,
RQOrchestratorConfig,
)
rq_config = RQOrchestratorConfig(
redis_url=docling_serve_settings.eng_rq_redis_url,
results_prefix=docling_serve_settings.eng_rq_results_prefix,
sub_channel=docling_serve_settings.eng_rq_sub_channel,
scratch_dir=get_scratch(),
)
return RQOrchestrator(config=rq_config)
elif docling_serve_settings.eng_kind == AsyncEngine.KFP:
from docling_jobkit.orchestrators.kfp.orchestrator import (
KfpOrchestrator,

View File

@@ -1,317 +1,78 @@
import asyncio
import logging
import os
import shutil
import time
from collections.abc import Iterable
from pathlib import Path
from typing import Union
import httpx
from fastapi import BackgroundTasks, HTTPException
from fastapi.responses import FileResponse
from fastapi import BackgroundTasks, Response
from docling.datamodel.base_models import OutputFormat
from docling.datamodel.document import ConversionResult, ConversionStatus
from docling_core.types.doc import ImageRefMode
from docling_jobkit.datamodel.convert import ConvertDocumentsOptions
from docling_jobkit.datamodel.task import Task
from docling_jobkit.datamodel.task_targets import InBodyTarget, PutTarget, TaskTarget
from docling_jobkit.datamodel.result import (
ChunkedDocumentResult,
DoclingTaskResult,
ExportResult,
RemoteTargetResult,
ZipArchiveResult,
)
from docling_jobkit.orchestrators.base_orchestrator import (
BaseOrchestrator,
)
from docling_serve.datamodel.responses import (
ChunkDocumentResponse,
ConvertDocumentResponse,
DocumentResponse,
PresignedUrlConvertDocumentResponse,
)
from docling_serve.settings import docling_serve_settings
from docling_serve.storage import get_scratch
_log = logging.getLogger(__name__)
def _export_document_as_content(
conv_res: ConversionResult,
export_json: bool,
export_html: bool,
export_md: bool,
export_txt: bool,
export_doctags: bool,
image_mode: ImageRefMode,
md_page_break_placeholder: str,
):
document = DocumentResponse(filename=conv_res.input.file.name)
if conv_res.status == ConversionStatus.SUCCESS:
new_doc = conv_res.document._make_copy_with_refmode(
Path(), image_mode, page_no=None
)
# Create the different formats
if export_json:
document.json_content = new_doc
if export_html:
document.html_content = new_doc.export_to_html(image_mode=image_mode)
if export_txt:
document.text_content = new_doc.export_to_markdown(
strict_text=True,
image_mode=image_mode,
)
if export_md:
document.md_content = new_doc.export_to_markdown(
image_mode=image_mode,
page_break_placeholder=md_page_break_placeholder or None,
)
if export_doctags:
document.doctags_content = new_doc.export_to_doctags()
elif conv_res.status == ConversionStatus.SKIPPED:
raise HTTPException(status_code=400, detail=conv_res.errors)
else:
raise HTTPException(status_code=500, detail=conv_res.errors)
return document
def _export_documents_as_files(
conv_results: Iterable[ConversionResult],
output_dir: Path,
export_json: bool,
export_html: bool,
export_md: bool,
export_txt: bool,
export_doctags: bool,
image_export_mode: ImageRefMode,
md_page_break_placeholder: str,
) -> ConversionStatus:
success_count = 0
failure_count = 0
# Default failure in case results is empty
conv_result = ConversionStatus.FAILURE
artifacts_dir = Path("artifacts/") # will be relative to the fname
for conv_res in conv_results:
conv_result = conv_res.status
if conv_res.status == ConversionStatus.SUCCESS:
success_count += 1
doc_filename = conv_res.input.file.stem
# Export JSON format:
if export_json:
fname = output_dir / f"{doc_filename}.json"
_log.info(f"writing JSON output to {fname}")
conv_res.document.save_as_json(
filename=fname,
image_mode=image_export_mode,
artifacts_dir=artifacts_dir,
)
# Export HTML format:
if export_html:
fname = output_dir / f"{doc_filename}.html"
_log.info(f"writing HTML output to {fname}")
conv_res.document.save_as_html(
filename=fname,
image_mode=image_export_mode,
artifacts_dir=artifacts_dir,
)
# Export Text format:
if export_txt:
fname = output_dir / f"{doc_filename}.txt"
_log.info(f"writing TXT output to {fname}")
conv_res.document.save_as_markdown(
filename=fname,
strict_text=True,
image_mode=ImageRefMode.PLACEHOLDER,
)
# Export Markdown format:
if export_md:
fname = output_dir / f"{doc_filename}.md"
_log.info(f"writing Markdown output to {fname}")
conv_res.document.save_as_markdown(
filename=fname,
artifacts_dir=artifacts_dir,
image_mode=image_export_mode,
page_break_placeholder=md_page_break_placeholder or None,
)
# Export Document Tags format:
if export_doctags:
fname = output_dir / f"{doc_filename}.doctags"
_log.info(f"writing Doc Tags output to {fname}")
conv_res.document.save_as_doctags(filename=fname)
else:
_log.warning(f"Document {conv_res.input.file} failed to convert.")
failure_count += 1
_log.info(
f"Processed {success_count + failure_count} docs, "
f"of which {failure_count} failed"
)
return conv_result
def process_results(
conversion_options: ConvertDocumentsOptions,
target: TaskTarget,
conv_results: Iterable[ConversionResult],
work_dir: Path,
) -> Union[ConvertDocumentResponse, FileResponse, PresignedUrlConvertDocumentResponse]:
# Let's start by processing the documents
try:
start_time = time.monotonic()
# Convert the iterator to a list to count the number of results and get timings
# As it's an iterator (lazy evaluation), it will also start the conversion
conv_results = list(conv_results)
processing_time = time.monotonic() - start_time
_log.info(
f"Processed {len(conv_results)} docs in {processing_time:.2f} seconds."
)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if len(conv_results) == 0:
raise HTTPException(
status_code=500, detail="No documents were generated by Docling."
)
# We have some results, let's prepare the response
response: Union[
FileResponse, ConvertDocumentResponse, PresignedUrlConvertDocumentResponse
]
# Booleans to know what to export
export_json = OutputFormat.JSON in conversion_options.to_formats
export_html = OutputFormat.HTML in conversion_options.to_formats
export_md = OutputFormat.MARKDOWN in conversion_options.to_formats
export_txt = OutputFormat.TEXT in conversion_options.to_formats
export_doctags = OutputFormat.DOCTAGS in conversion_options.to_formats
# Only 1 document was processed, and we are not returning it as a file
if len(conv_results) == 1 and isinstance(target, InBodyTarget):
conv_res = conv_results[0]
document = _export_document_as_content(
conv_res,
export_json=export_json,
export_html=export_html,
export_md=export_md,
export_txt=export_txt,
export_doctags=export_doctags,
image_mode=conversion_options.image_export_mode,
md_page_break_placeholder=conversion_options.md_page_break_placeholder,
)
response = ConvertDocumentResponse(
document=document,
status=conv_res.status,
processing_time=processing_time,
timings=conv_res.timings,
)
# Multiple documents were processed, or we are forced returning as a file
else:
# Temporary directory to store the outputs
output_dir = work_dir / "output"
output_dir.mkdir(parents=True, exist_ok=True)
# Worker pid to use in archive identification as we may have multiple workers
os.getpid()
# Export the documents
conv_result = _export_documents_as_files(
conv_results=conv_results,
output_dir=output_dir,
export_json=export_json,
export_html=export_html,
export_md=export_md,
export_txt=export_txt,
export_doctags=export_doctags,
image_export_mode=conversion_options.image_export_mode,
md_page_break_placeholder=conversion_options.md_page_break_placeholder,
)
files = os.listdir(output_dir)
if len(files) == 0:
raise HTTPException(status_code=500, detail="No documents were exported.")
file_path = work_dir / "converted_docs.zip"
shutil.make_archive(
base_name=str(file_path.with_suffix("")),
format="zip",
root_dir=output_dir,
)
# Other cleanups after the response is sent
# Output directory
# background_tasks.add_task(shutil.rmtree, work_dir, ignore_errors=True)
if isinstance(target, PutTarget):
try:
with open(file_path, "rb") as file_data:
r = httpx.put(str(target.url), files={"file": file_data})
r.raise_for_status()
response = PresignedUrlConvertDocumentResponse(
status=conv_result,
processing_time=processing_time,
)
except Exception as exc:
_log.error("An error occour while uploading zip to s3", exc_info=exc)
raise HTTPException(
status_code=500, detail="An error occour while uploading zip to s3."
)
else:
response = FileResponse(
file_path, filename=file_path.name, media_type="application/zip"
)
return response
async def prepare_response(
task: Task, orchestrator: BaseOrchestrator, background_tasks: BackgroundTasks
task_id: str,
task_result: DoclingTaskResult,
orchestrator: BaseOrchestrator,
background_tasks: BackgroundTasks,
):
if task.results is None:
raise HTTPException(
status_code=404,
detail="Task result not found. Please wait for a completion status.",
)
assert task.options is not None
work_dir = get_scratch() / task.task_id
response = process_results(
conversion_options=task.options,
target=task.target,
conv_results=task.results,
work_dir=work_dir,
response: (
Response
| ConvertDocumentResponse
| PresignedUrlConvertDocumentResponse
| ChunkDocumentResponse
)
if work_dir.exists():
task.scratch_dir = work_dir
if not isinstance(response, FileResponse):
_log.warning(
f"Task {task.task_id=} produced content in {work_dir=} but the response is not a file."
)
shutil.rmtree(work_dir, ignore_errors=True)
if isinstance(task_result.result, ExportResult):
response = ConvertDocumentResponse(
document=task_result.result.content,
status=task_result.result.status,
processing_time=task_result.processing_time,
timings=task_result.result.timings,
errors=task_result.result.errors,
)
elif isinstance(task_result.result, ZipArchiveResult):
response = Response(
content=task_result.result.content,
media_type="application/zip",
headers={
"Content-Disposition": 'attachment; filename="converted_docs.zip"'
},
)
elif isinstance(task_result.result, RemoteTargetResult):
response = PresignedUrlConvertDocumentResponse(
processing_time=task_result.processing_time,
num_converted=task_result.num_converted,
num_succeeded=task_result.num_succeeded,
num_failed=task_result.num_failed,
)
elif isinstance(task_result.result, ChunkedDocumentResult):
response = ChunkDocumentResponse(
chunks=task_result.result.chunks,
documents=task_result.result.documents,
processing_time=task_result.processing_time,
)
else:
raise ValueError("Unknown result type")
if docling_serve_settings.single_use_results:
if task.scratch_dir is not None:
background_tasks.add_task(
shutil.rmtree, task.scratch_dir, ignore_errors=True
)
async def _remove_task_impl():
await asyncio.sleep(docling_serve_settings.result_removal_delay)
await orchestrator.delete_task(task_id=task.task_id)
await orchestrator.delete_task(task_id=task_id)
async def _remove_task():
asyncio.create_task(_remove_task_impl()) # noqa: RUF006

View File

@@ -28,6 +28,7 @@ class UvicornSettings(BaseSettings):
class AsyncEngine(str, enum.Enum):
LOCAL = "local"
KFP = "kfp"
RQ = "rq"
class DoclingServeSettings(BaseSettings):
@@ -50,6 +51,8 @@ class DoclingServeSettings(BaseSettings):
enable_remote_services: bool = False
allow_external_plugins: bool = False
api_key: str = ""
max_document_timeout: float = 3_600 * 24 * 7 # 7 days
max_num_pages: int = sys.maxsize
max_file_size: int = sys.maxsize
@@ -63,6 +66,11 @@ class DoclingServeSettings(BaseSettings):
eng_kind: AsyncEngine = AsyncEngine.LOCAL
# Local engine
eng_loc_num_workers: int = 2
eng_loc_share_models: bool = False
# RQ engine
eng_rq_redis_url: str = ""
eng_rq_results_prefix: str = "docling:results"
eng_rq_sub_channel: str = "docling:updates"
# KFP engine
eng_kfp_endpoint: Optional[AnyUrl] = None
eng_kfp_token: Optional[str] = None
@@ -86,6 +94,10 @@ class DoclingServeSettings(BaseSettings):
"KFP is not yet working. To enable the development version, you must set DOCLING_SERVE_ENG_KFP_EXPERIMENTAL=true."
)
if self.eng_kind == AsyncEngine.RQ:
if not self.eng_rq_redis_url:
raise ValueError("RQ Redis url is required when using the RQ engine.")
return self

View File

@@ -34,6 +34,7 @@ class WebsocketNotifier(BaseNotifier):
task_queue_position = await self.orchestrator.get_queue_position(task_id)
msg = TaskStatusResponse(
task_id=task.task_id,
task_type=task.task_type,
task_status=task.task_status,
task_position=task_queue_position,
task_meta=task.processing_meta,

View File

@@ -3,7 +3,9 @@
This documentation pages explore the webserver configurations, runtime options, deployment examples as well as development best practices.
- [Configuration](./configuration.md)
- [Advance usage](./usage.md)
- [Handling models](./models.md)
- [Usage](./usage.md)
- [Deployment](./deployment.md)
- [MCP](./mcp.md)
- [Development](./development.md)
- [`v1` migration](./v1_migration.md)

View File

@@ -44,6 +44,7 @@ THe following table describes the options to configure the Docling Serve app.
| | `DOCLING_SERVE_SINGLE_USE_RESULTS` | `true` | If true, results can be accessed only once. If false, the results accumulate in the scratch directory. |
| | `DOCLING_SERVE_RESULT_REMOVAL_DELAY` | `300` | When `DOCLING_SERVE_SINGLE_USE_RESULTS` is active, this is the delay before results are removed from the task registry. |
| | `DOCLING_SERVE_MAX_DOCUMENT_TIMEOUT` | `604800` (7 days) | The maximum time for processing a document. |
| | `DOCLING_NUM_THREADS` | `4` | Number of concurrent threads for processing a document. |
| | `DOCLING_SERVE_MAX_NUM_PAGES` | | The maximum number of pages for a document to be processed. |
| | `DOCLING_SERVE_MAX_FILE_SIZE` | | The maximum file size for a document to be processed. |
| | `DOCLING_SERVE_MAX_SYNC_WAIT` | `120` | Max number of seconds a synchronous endpoint is waiting for the task completion. |
@@ -52,7 +53,8 @@ THe following table describes the options to configure the Docling Serve app.
| | `DOCLING_SERVE_CORS_ORIGINS` | `["*"]` | A list of origins that should be permitted to make cross-origin requests. |
| | `DOCLING_SERVE_CORS_METHODS` | `["*"]` | A list of HTTP methods that should be allowed for cross-origin requests. |
| | `DOCLING_SERVE_CORS_HEADERS` | `["*"]` | A list of HTTP request headers that should be supported for cross-origin requests. |
| | `DOCLING_SERVE_ENG_KIND` | `local` | The compute engine to use for the async tasks. Possible values are `local` and `kfp`. See below for more configurations of the engines. |
| | `DOCLING_SERVE_API_KEY` | | If specified, all the API requests must contain the header `X-Api-Key` with this value. |
| | `DOCLING_SERVE_ENG_KIND` | `local` | The compute engine to use for the async tasks. Possible values are `local`, `rq` and `kfp`. See below for more configurations of the engines. |
### Compute engine
@@ -66,6 +68,17 @@ The following table describes the options to configure the Docling Serve local e
| ENV | Default | Description |
|-----|---------|-------------|
| `DOCLING_SERVE_ENG_LOC_NUM_WORKERS` | 2 | Number of workers/threads processing the incoming tasks. |
| `DOCLING_SERVE_ENG_LOC_SHARE_MODELS` | False | If true, each process will share the same models among all thread workers. Otherwise, one instance of the models is allocated for each worker thread. |
#### RQ engine
The following table describes the options to configure the Docling Serve RQ engine.
| ENV | Default | Description |
|-----|---------|-------------|
| `DOCLING_SERVE_ENG_RQ_REDIS_URL` | (required) | The connection Redis url, e.g. `redis://localhost:6373/` |
| `DOCLING_SERVE_ENG_RQ_RESULTS_PREFIX` | `docling:results` | The prefix used for storing the results in Redis. |
| `DOCLING_SERVE_ENG_RQ_SUB_CHANNEL` | `docling:updates` | The channel key name used for storing communicating updates between the workers and the orchestrator. |
#### KFP engine
@@ -79,3 +92,10 @@ The following table describes the options to configure the Docling Serve KFP eng
| `DOCLING_SERVE_ENG_KFP_SELF_CALLBACK_ENDPOINT` | | If set, it enables internal callbacks providing status update of the KFP job. Usually something like `https://NAME.NAMESPACE.svc.cluster.local:5001/v1/callback/task/progress`. |
| `DOCLING_SERVE_ENG_KFP_SELF_CALLBACK_TOKEN_PATH` | | The token used for authenticating the progress callback. For cluster-internal workloads, use `/run/secrets/kubernetes.io/serviceaccount/token`. |
| `DOCLING_SERVE_ENG_KFP_SELF_CALLBACK_CA_CERT_PATH` | | The CA certificate for the progress callback. For cluster-inetrnal workloads, use `/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt`. |
#### Gradio UI
When using Gradio UI and using the option to output conversion as file, Gradio uses cache to prevent files to be overwritten ([more info here](https://www.gradio.app/guides/file-access#the-gradio-cache)), and we defined the cache clean frequency of one hour to clean files older than 10hours. For situations that files need to be available to download from UI older than 10 hours, there is two options:
- Increase the older age of files to clean [here](https://github.com/docling-project/docling-serve/blob/main/docling_serve/gradio_ui.py#L483) to suffice the age desired;
- Or set the clean up manually by defining the temporary dir of Gradio to use the same as `DOCLING_SERVE_SCRATCH_PATH` absolute path. This can be achieved by setting the environment variable `GRADIO_TEMP_DIR`, that can be done via command line `export GRADIO_TEMP_DIR="<same_path_as_scratch>"` or in `Dockerfile` using `ENV GRADIO_TEMP_DIR="<same_path_as_scratch>"`. After this, set the clean of cache to `None` [here](https://github.com/docling-project/docling-serve/blob/main/docling_serve/gradio_ui.py#L483). Now, the clean up of `DOCLING_SERVE_SCRATCH_PATH` will also clean the Gradio temporary dir. (If you use this option, please remember when reversing changes to remove the environment variable `GRADIO_TEMP_DIR`, otherwise may lead to files not be available to download).

View File

@@ -0,0 +1,21 @@
# AMD ROCm deployment
services:
docling-serve:
image: ghcr.io/docling-project/docling-serve-rocm:main
container_name: docling-serve
ports:
- "5001:5001"
environment:
DOCLING_SERVE_ENABLE_UI: "true"
ROCR_VISIBLE_DEVICES: "0" # https://rocm.docs.amd.com/en/latest/conceptual/gpu-isolation.html#rocr-visible-devices
## This section is for compatibility with older cards
# HSA_OVERRIDE_GFX_VERSION: "11.0.0"
# HSA_ENABLE_SDMA: "0"
devices:
- /dev/kfd:/dev/kfd
- /dev/dri:/dev/dri
group_add:
- 44 # video group GID from host
- 992 # render group GID from host
restart: always

View File

@@ -1,15 +0,0 @@
services:
docling:
image: ghcr.io/docling-project/docling-serve-cu124
container_name: docling-serve
ports:
- 5001:5001
environment:
- DOCLING_SERVE_ENABLE_UI=true
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all # nvidia-smi
capabilities: [gpu]

View File

@@ -0,0 +1,20 @@
# NVIDIA CUDA deployment
services:
docling-serve:
image: ghcr.io/docling-project/docling-serve-cu126:main
container_name: docling-serve
ports:
- "5001:5001"
environment:
DOCLING_SERVE_ENABLE_UI: "true"
NVIDIA_VISIBLE_DEVICES: "all" # https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/docker-specialized.html
# deploy: # This section is for compatibility with Swarm
# resources:
# reservations:
# devices:
# - driver: nvidia
# count: all
# capabilities: [gpu]
runtime: nvidia
restart: always

View File

@@ -0,0 +1,192 @@
# This example deployment configures Docling Serve with a Service and RQ workers
# Create following secret
# kubectl create secret generic docling-serve-rq-secrets --from-literal=REDIS_PASSWORD=myredispassword --from-literal=RQ_REDIS_URL=redis://:myredispassword@docling-serve-redis-service:6373/
---
apiVersion: v1
kind: Service
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
ports:
- name: http
port: 5001
targetPort: http
selector:
app: docling-serve
component: docling-serve-api
---
kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve
labels:
app: docling-serve
component: docling-serve-api
spec:
replicas: 1
selector:
matchLabels:
app: docling-serve
component: docling-serve-api
template:
metadata:
labels:
app: docling-serve
component: docling-serve-api
spec:
restartPolicy: Always
containers:
- name: api
resources:
limits:
cpu: 1
memory: 8Gi
requests:
cpu: 250m
memory: 1Gi
env:
- name: DOCLING_SERVE_ENABLE_UI
value: 'true'
- name: DOCLING_SERVE_ENG_KIND
value: 'rq'
- name: DOCLING_SERVE_ENG_RQ_REDIS_URL
valueFrom:
secretKeyRef:
name: docling-serve-rq-secrets
key: RQ_REDIS_URL
ports:
- name: http
containerPort: 5001
protocol: TCP
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve-cpu'
---
kind: Deployment
apiVersion: apps/v1
metadata:
name: docling-serve-rq-workers
labels:
app: docling-serve-rq-workers
component: docling-serve-rq-worker
spec:
replicas: 2
selector:
matchLabels:
app: docling-serve-rq-workers
component: docling-serve-rq-worker
template:
metadata:
labels:
app: docling-serve-rq-workers
component: docling-serve-rq-worker
spec:
restartPolicy: Always
containers:
- name: worker
resources:
limits:
cpu: 1
memory: 4Gi
requests:
cpu: 250m
memory: 1Gi
env:
- name: DOCLING_SERVE_ENG_KIND
value: 'rq'
- name: DOCLING_SERVE_ENG_RQ_REDIS_URL
valueFrom:
secretKeyRef:
name: docling-serve-rq-secrets
key: RQ_REDIS_URL
ports:
- name: http
containerPort: 5001
protocol: TCP
imagePullPolicy: Always
image: 'ghcr.io/docling-project/docling-serve-cpu'
command: ["docling-serve"]
args: ["rq-worker"]
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: docling-serve-redis
labels:
app: docling-serve-redis
spec:
replicas: 1
selector:
matchLabels:
app: docling-serve-redis
template:
metadata:
labels:
app: docling-serve-redis
spec:
restartPolicy: Always
terminationGracePeriodSeconds: 30
containers:
- name: redis
resources:
limits:
cpu: 1
memory: 1Gi
requests:
cpu: 250m
memory: 100Mi
image: redis:latest
command: ["redis-server"]
args:
- "--port"
- "6373"
- "--dir"
- "/mnt/redis/data"
- "--appendonly"
- "yes"
- "--requirepass"
- "$(REDIS_PASSWORD)"
ports:
- containerPort: 6373
env:
- name: REDIS_PASSWORD
valueFrom:
secretKeyRef:
name: docling-serve-rq-secrets
key: REDIS_PASSWORD
volumeMounts:
- name: redis-data
mountPath: /mnt/redis/data
securityContext:
fsGroup: 1004
runAsNonRoot: true
allowPrivilegeEscalation: false
capabilities:
drop:
- ALL
seccompProfile:
type: RuntimeDefault
volumes:
- name: redis-data
emptyDir:
medium: Memory
sizeLimit: 2Gi
---
apiVersion: v1
kind: Service
metadata:
name: docling-serve-redis-service
labels:
app: docling-serve-redis
spec:
type: NodePort
ports:
- name: redis-service
protocol: TCP
port: 6373
targetPort: 6373
selector:
app: docling-serve-redis

View File

@@ -4,16 +4,17 @@ This document provides deployment examples for running the application in differ
Choose the deployment option that best fits your setup.
- **[Local GPU](#local-gpu)**: For deploying the application locally on a machine with a NVIDIA GPU (using Docker Compose).
- **[Local GPU NVIDIA](#local-gpu-nvidia)**: For deploying the application locally on a machine with a supported NVIDIA GPU (using Docker Compose).
- **[Local GPU AMD](#local-gpu-amd)**: For deploying the application locally on a machine with a supported AMD GPU (using Docker Compose).
- **[OpenShift](#openshift)**: For deploying the application on an OpenShift cluster, designed for cloud-native environments.
---
## Local GPU
## Local GPU NVIDIA
### Docker compose
Manifest example: [compose-gpu.yaml](./deploy-examples/compose-gpu.yaml)
Manifest example: [compose-nvidia.yaml](./deploy-examples/compose-nvidia.yaml)
This deployment has the following features:
@@ -22,7 +23,7 @@ This deployment has the following features:
Install the app with:
```sh
docker compose -f docs/deploy-examples/compose-gpu.yaml up -d
docker compose -f docs/deploy-examples/compose-nvidia.yaml up -d
```
For using the API:
@@ -34,7 +35,7 @@ curl -X 'POST' \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"http_sources": [{"url": "https://arxiv.org/pdf/2501.17887"}]
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
@@ -56,7 +57,7 @@ Docs:
<details>
<summary><b>Steps</b></summary>
1. Check driver version and which GPU you want to use (0/1/2/3.. and update [compose-gpu.yaml](./deploy-examples/compose-gpu.yaml) file or use `count: all`)
1. Check driver version and which GPU you want to use 0/1/2/n (and update [compose-nvidia.yaml](./deploy-examples/compose-nvidia.yaml) file or use `count: all`)
```sh
nvidia-smi
@@ -117,7 +118,75 @@ Docs:
5. Run the container:
```sh
docker compose -f docs/deploy-examples/compose-gpu.yaml up -d
docker compose -f docs/deploy-examples/compose-nvidia.yaml up -d
```
</details>
## Local GPU AMD
### Docker compose
Manifest example: [compose-amd.yaml](./deploy-examples/compose-amd.yaml)
This deployment has the following features:
- AMD rocm enabled
Install the app with:
```sh
docker compose -f docs/deploy-examples/compose-amd.yaml up -d
```
For using the API:
```sh
# Make a test query
curl -X 'POST' \
"localhost:5001/v1/convert/source/async" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
<details>
<summary><b>Requirements</b></summary>
- debian/ubuntu/rhel/fedora/opensuse
- docker
- AMDGPU driver >=6.3
- AMD ROCm >=6.3
Docs:
- [AMD ROCm installation](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html)
</details>
<details>
<summary><b>Steps</b></summary>
1. Check driver version and which GPU you want to use 0/1/2/n (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
rocm-smi --showdriverversion
rocminfo | grep -i "ROCm version"
```
2. Find both video group GID and render group GID from host (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
getent group video
getent group render
```
3. Build the image locally (and update [compose-amd.yaml](./deploy-examples/compose-amd.yaml) file)
```sh
make docling-serve-rocm-image
```
</details>
@@ -152,10 +221,35 @@ curl -X 'POST' \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"http_sources": [{"url": "https://arxiv.org/pdf/2501.17887"}]
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
### Multiple workers with RQ
Manifest example: [`docling-serve-rq-workers.yaml`](./deploy-examples/docling-serve-rq-workers.yaml)
This deployment example has the following features:
- Deployment configuration
- Service configuration
- Redis deployment
- Multiple (2 by default) worker Pods
Install the app with:
- create k8s secret:
```sh
kubectl create secret generic docling-serve-rq-secrets --from-literal=REDIS_PASSWORD=myredispassword --from-literal=RQ_REDIS_URL=redis://:myredispassword@docling-serve-redis-service:6373/
```
- apply deployment manifest:
```sh
oc apply -f docs/deploy-examples/docling-serve-rq-workers.yaml
```
### Secure deployment with `oauth-proxy`
Manifest example: [docling-serve-oauth.yaml](./deploy-examples/docling-serve-oauth.yaml)
@@ -189,7 +283,7 @@ curl -X 'POST' \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"http_sources": [{"url": "https://arxiv.org/pdf/2501.17887"}]
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}'
```
@@ -222,7 +316,7 @@ task_id=$(curl -s -X 'POST' \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"http_sources": [{"url": "https://arxiv.org/pdf/2501.17887"}]
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
}' \
-c cookies.txt | grep -oP '"task_id":"\K[^"]+')
```

22
docs/examples.md Normal file
View File

@@ -0,0 +1,22 @@
# Examples
## Split processing
The example of provided of split processing demonstrates how to split a PDF into chunks of pages and send them for conversion. At the end, it concatenates all split pages into a single conversion `JSON`.
At beginning of file there's variables to be used (and modified) such as:
| Variable | Description |
| ---------|-------------|
| `path_to_pdf`| Path to PDF file to be split |
| `pages_per_file`| The number of pages per chunk to split PDF |
| `base_url`| Base url of the `docling-serve` host |
| `out_dir`| The output folder of each conversion `JSON` of split PDF and the final concatenated `JSON` |
The example follows the following logic:
- Get the number of pages of the `PDF`
- Based on the number of chunks of pages, send each chunk to conversion using `page_range` parameter
- Wait all conversions to finish
- Get all conversion results
- Save each conversion `JSON` result into a `JSON` file
- Concatenate all `JSONs` into a single `JSON` using `docling` concatenate method
- Save concatenated `JSON` into a `JSON` file

39
docs/mcp.md Normal file
View File

@@ -0,0 +1,39 @@
# Docling MCP in Docling Serve
The `docling-serve` container image includes all MCP (Model Communication Protocol) features starting from version v1.1.0. To leverage these features, you simply need to use a different entrypoint—no custom image builds or additional installations are required. The image provides the `docling-mcp-server` executable, which enables MCP functionality out of the box as of version v1.1.0 ([changelog](https://github.com/docling-project/docling-serve/blob/624f65d41b734e8b39ff267bc8bf6e766c376d6d/CHANGELOG.md)).
Read more on [Docling MCP](https://github.com/docling-project/docling-mcp) in its dedicated repository.
## Launching the MCP Service
By default, the container runs `docling-serve run` and exposes port 5001. To start the MCP service, override the entrypoint and specify your desired port mapping. For example:
```sh
podman run -p 8000:8000 quay.io/docling-project/docling-serve -- docling-mcp-server --transport streamable-http --port 8000 --host 0.0.0.0
```
This command starts the MCP server on port 8000, accessible at `http://localhost:8000/mcp`. Adjust the port and host as needed. Key arguments for `docling-mcp-server` include `--transport streamable-http` (HTTP transport for client connections), `--port <PORT>`, and `--host <HOST>` (use `0.0.0.0` to accept connections from any interface).
## Configuring MCP Clients
Most MCP-compatible clients, such as LM Studio and Claude Desktop, allow you to specify custom MCP server endpoints. The standard configuration uses a JSON block to define available MCP servers. For example, to connect to the Docling MCP server running on port 8000:
```json
{
"mcpServers": {
"docling": {
"url": "http://localhost:8000/mcp"
}
}
}
```
Insert this configuration in your client's settings where MCP servers are defined. Update the URL if you use a different port.
### LM Studio and Claude Desktop
Both LM Studio and Claude Desktop support MCP endpoints via configuration files or UI settings. Paste the above JSON block into the appropriate configuration section. For Claude Desktop, add the MCP server in the "Custom Model" or "MCP Server" section. For LM Studio, refer to its documentation for the location of the MCP server configuration.
### Other MCP Clients
Other clients, such as Continue Coding Assistant, also support custom MCP endpoints. Use the same configuration pattern: provide the MCP server URL ending with `/mcp` and ensure the port matches your container setup. See the [Docling MCP docs](https://github.com/docling-project/docling-mcp/tree/main/docs/integrations) for more details.

175
docs/models.md Normal file
View File

@@ -0,0 +1,175 @@
# Handling Models in Docling Serve
When enabling steps in Docling Serve that require extra models (such as picture classification, picture description, table detection, code recognition, formula extraction, or vision-language modules), you must ensure those models are available in the runtime environment. The standard container image includes only the default models. Any additional models must be downloaded and made available before use. If required models are missing, Docling Serve will raise runtime errors rather than downloading them automatically. This default choice wants to guarantee the system is not calling external services.
## Model Storage Location
Docling Serve loads models from the directory specified by the `DOCLING_SERVE_ARTIFACTS_PATH` environment variable. This path must be consistent across model download and runtime. When running with multiple workers or reload enabled, you must use the environment variable rather than the CLI argument for configuration [[source]](./configuration.md).
## Approaches for Making Extra Models Available
There are several ways to ensure required models are present:
### 1. Disable Local Models (Trigger Auto-Download)
You can configure the container to download all models at startup by clearing the artifacts path:
```sh
podman run -d -p 5001:5001 --name docling-serve \
-e DOCLING_SERVE_ARTIFACTS_PATH="" \
-e DOCLING_SERVE_ENABLE_UI=true \
quay.io/docling-project/docling-serve
```
This approach is simple for local development but not recommended for production, as it increases startup time and depends on network availability.
### 2. Build a Custom Image with Pre-Downloaded Models
You can create a new image that includes the required models:
```Dockerfile
FROM quay.io/docling-project/docling-serve
RUN docling-tools models download smolvlm
```
This method is suitable for production, as it ensures all models are present in the image and avoids runtime downloads.
### 3. Update the Entrypoint to Download Models Before Startup
You can override the entrypoint to download models before starting the service:
```sh
podman run -p 5001:5001 -e DOCLING_SERVE_ENABLE_UI=true \
quay.io/docling-project/docling-serve \
-- sh -c 'exec docling-tools models download smolvlm && exec docling-serve run'
```
This is useful for environments where you want to keep the base image unchanged but still automate model preparation.
### 4. Mount a Volume with Pre-Downloaded Models
Download models locally and mount them into the container:
```sh
# Download the models locally
docling-tools models download --all -o models
# Start the container with the local models folder
podman run -p 5001:5001 \
-v $(pwd)/models:/opt/app-root/src/models \
-e DOCLING_SERVE_ARTIFACTS_PATH="/opt/app-root/src/models" \
-e DOCLING_SERVE_ENABLE_UI=true \
quay.io/docling-project/docling-serve
```
This approach is robust for both local and production deployments, especially when using persistent storage.
## Kubernetes/Cluster Deployments
For Kubernetes or OpenShift clusters, the recommended approach is to use a PersistentVolumeClaim (PVC) for model storage, a Kubernetes Job to download models, and mount the volume into the deployment. This ensures models persist across pod restarts and scale-out scenarios.
### Example: PersistentVolumeClaim
```yaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: docling-model-cache-pvc
spec:
accessModes:
- ReadWriteOnce
volumeMode: Filesystem
resources:
requests:
storage: 10Gi
```
If you don't want to use default storage class, set your custom storage class with following:
```yaml
spec:
...
storageClassName: <Storage Class Name>
```
Manifest example: [docling-model-cache-pvc.yaml](./deploy-examples/docling-model-cache-pvc.yaml)
### Example: Model Download Job
```yaml
apiVersion: batch/v1
kind: Job
metadata:
name: docling-model-cache-load
spec:
template:
spec:
containers:
- name: loader
image: ghcr.io/docling-project/docling-serve-cpu:main
command:
- docling-tools
- models
- download
- '--output-dir=/modelcache'
- 'layout'
- 'tableformer'
- 'code_formula'
- 'picture_classifier'
- 'smolvlm'
- 'granite_vision'
- 'easyocr'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc
restartPolicy: Never
```
The job will mount the previously created persistent volume and execute command similar to how we would load models locally:
`docling-tools models download --output-dir <MOUNT-PATH> [LIST_OF_MODELS]`
In manifest, we specify desired models individually, or we can use `--all` parameter to download all models.
Manifest example: [docling-model-cache-job.yaml](./deploy-examples/docling-model-cache-job.yaml)
### Example: Deployment with Mounted Volume
```yaml
spec:
template:
spec:
containers:
- name: api
env:
- name: DOCLING_SERVE_ARTIFACTS_PATH
value: '/modelcache'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc
```
The value of `DOCLING_SERVE_ARTIFACTS_PATH` must match the mount path where models are stored.
Now, when docling-serve is executing tasks, the underlying docling installation will load model weights from mounted volume.
Manifest example: [docling-model-cache-deployment.yaml](./deploy-examples/docling-model-cache-deployment.yaml)
## Local Docker Execution
For local Docker or Podman execution, you can use any of the approaches above. Mounting a local directory with pre-downloaded models is the most reliable for repeated runs and avoids network dependencies.
## Troubleshooting and Best Practices
- If a required model is missing from the artifacts path, Docling Serve will raise a runtime error.
- Always ensure the value of `DOCLING_SERVE_ARTIFACTS_PATH` matches the directory where models are stored and mounted.
- For production and cluster environments, prefer persistent storage and pre-loading models via a dedicated job.
For more details and YAML manifest examples, see the [deployment documentation](./deployment.md).

View File

@@ -1,103 +0,0 @@
# Pre-loading models for docling
This document provides examples for pre-loading docling models to a persistent volume and re-using it for docling-serve deployments.
1. We need to create a persistent volume that will store models weights:
```yaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: docling-model-cache-pvc
spec:
accessModes:
- ReadWriteOnce
volumeMode: Filesystem
resources:
requests:
storage: 10Gi
```
If you don't want to use default storage class, set your custom storage class with following:
```yaml
spec:
...
storageClassName: <Storage Class Name>
```
Manifest example: [docling-model-cache-pvc.yaml](./deploy-examples/docling-model-cache-pvc.yaml)
2. In order to load model weights, we can use docling-toolkit to download them, as this is a one time operation we can use kubernetes job for this:
```yaml
apiVersion: batch/v1
kind: Job
metadata:
name: docling-model-cache-load
spec:
selector: {}
template:
metadata:
name: docling-model-load
spec:
containers:
- name: loader
image: ghcr.io/docling-project/docling-serve-cpu:main
command:
- docling-tools
- models
- download
- '--output-dir=/modelcache'
- 'layout'
- 'tableformer'
- 'code_formula'
- 'picture_classifier'
- 'smolvlm'
- 'granite_vision'
- 'easyocr'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc
restartPolicy: Never
```
The job will mount previously created persistent volume and execute command similar to how we would load models locally:
`docling-tools models download --output-dir <MOUNT-PATH> [LIST_OF_MODELS]`
In manifest, we specify desired models individually, or we can use `--all` parameter to download all models.
Manifest example: [docling-model-cache-job.yaml](./deploy-examples/docling-model-cache-job.yaml)
3. Now we can mount volume in the docling-serve deployment and set env `DOCLING_SERVE_ARTIFACTS_PATH` to point to it.
Following additions to deployment should be made:
```yaml
spec:
template:
spec:
containers:
- name: api
env:
...
- name: DOCLING_SERVE_ARTIFACTS_PATH
value: '/modelcache'
volumeMounts:
- name: docling-model-cache
mountPath: /modelcache
...
volumes:
- name: docling-model-cache
persistentVolumeClaim:
claimName: docling-model-cache-pvc
```
Make sure that value of `DOCLING_SERVE_ARTIFACTS_PATH` is the same as where models were downloaded and where volume is mounted.
Now when docling-serve is executing tasks, the underlying docling installation will load model weights from mounted volume.
Manifest example: [docling-model-cache-deployment.yaml](./deploy-examples/docling-model-cache-deployment.yaml)

View File

@@ -30,6 +30,10 @@ On top of the source of file (see below), both endpoints support the same parame
- `include_images` (bool): If enabled, images will be extracted from the document. Defaults to false.
- `images_scale` (float): Scale factor for images. Defaults to 2.0.
### Authentication
When authentication is activated (see the parameter `DOCLING_SERVE_API_KEY` in [configuration.md](./configuration.md)), all the API requests **must** provide the header `X-Api-Key` with the correct secret key.
## Convert endpoints
### Source endpoint
@@ -429,7 +433,7 @@ with connect(uri) as websocket:
payload = json.loads(message)
if payload["message"] == "error":
break
if payload["message"] == "error" and payload["task"]["task_status"] in ("success", "failure"):
if payload["message"] == "update" and payload["task"]["task_status"] in ("success", "failure"):
break
except:
break

View File

@@ -37,7 +37,7 @@ New version:
"options": {}, // conversion options
"sources": [
// input document provided as base64-encoded string
{"kind": "kind", "base64_string": "abc123...", "filename": "file.pdf"},
{"kind": "file", "base64_string": "abc123...", "filename": "file.pdf"},
// input document provided as http urls
{"kind": "http", "url": "https://..."},
]

View File

@@ -0,0 +1,124 @@
import json
import time
from pathlib import Path
import httpx
from pydantic import BaseModel
from pypdf import PdfReader
from docling_core.types.doc.document import DoclingDocument
# Variables to use
path_to_pdf = Path("./tests/2206.01062v1.pdf")
pages_per_file = 4
base_url = "http://localhost:5001/v1"
out_dir = Path("examples/splitted_pdf/")
class ConvertedSplittedPdf(BaseModel):
task_id: str
conversion_finished: bool = False
result: dict | None = None
def get_task_result(task_id: str):
response = httpx.get(
f"{base_url}/result/{task_id}",
timeout=15,
)
return response.json()
def check_task_status(task_id: str):
response = httpx.get(f"{base_url}/status/poll/{task_id}", timeout=15)
task = response.json()
task_status = task["task_status"]
task_finished = False
if task_status == "success":
task_finished = True
if task_status in ("failure", "revoked"):
raise RuntimeError("A conversion failed")
time.sleep(5)
return task_finished
def post_file(file_path: Path, start_page: int, end_page: int):
payload = {
"to_formats": ["json"],
"image_export_mode": "placeholder",
"ocr": False,
"abort_on_error": False,
"page_range": [start_page, end_page],
}
files = {
"files": (file_path.name, file_path.open("rb"), "application/pdf"),
}
response = httpx.post(
f"{base_url}/convert/file/async",
files=files,
data=payload,
timeout=15,
)
task = response.json()
return task["task_id"]
def main():
filename = path_to_pdf
splitted_pdfs: list[ConvertedSplittedPdf] = []
with open(filename, "rb") as input_pdf_file:
pdf_reader = PdfReader(input_pdf_file)
total_pages = len(pdf_reader.pages)
for start_page in range(0, total_pages, pages_per_file):
task_id = post_file(
filename, start_page + 1, min(start_page + pages_per_file, total_pages)
)
splitted_pdfs.append(ConvertedSplittedPdf(task_id=task_id))
all_files_converted = False
while not all_files_converted:
found_conversion_running = False
for splitted_pdf in splitted_pdfs:
if not splitted_pdf.conversion_finished:
found_conversion_running = True
print("checking conversion status...")
splitted_pdf.conversion_finished = check_task_status(
splitted_pdf.task_id
)
if not found_conversion_running:
all_files_converted = True
for splitted_pdf in splitted_pdfs:
splitted_pdf.result = get_task_result(splitted_pdf.task_id)
files = []
for i, splitted_pdf in enumerate(splitted_pdfs):
json_content = json.dumps(
splitted_pdf.result.get("document").get("json_content"), indent=2
)
doc = DoclingDocument.model_validate_json(json_content)
filename = f"{out_dir}/splited_json_{i}.json"
doc.save_as_json(filename=filename)
files.append(filename)
docs = [DoclingDocument.load_from_json(filename=f) for f in files]
concate_doc = DoclingDocument.concatenate(docs=docs)
exp_json_file = Path(f"{out_dir}/concatenated.json")
concate_doc.save_as_json(exp_json_file)
print("Finished")
if __name__ == "__main__":
main()

BIN
img/fastapi-ui.png Normal file

Binary file not shown.

After

Width:  |  Height:  |  Size: 226 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 24 KiB

View File

@@ -1,6 +1,6 @@
[project]
name = "docling-serve"
version = "1.1.0" # DO NOT EDIT, updated automatically
version = "1.6.0" # DO NOT EDIT, updated automatically
description = "Running Docling as a service"
license = {text = "MIT"}
authors = [
@@ -8,7 +8,6 @@ authors = [
{name="Guillaume Moutier", email="gmoutier@redhat.com"},
{name="Anil Vishnoi", email="avishnoi@redhat.com"},
{name="Panos Vagenas", email="pva@zurich.ibm.com"},
{name="Panos Vagenas", email="pva@zurich.ibm.com"},
{name="Christoph Auer", email="cau@zurich.ibm.com"},
{name="Peter Staar", email="taa@zurich.ibm.com"},
]
@@ -35,8 +34,8 @@ classifiers = [
requires-python = ">=3.10"
dependencies = [
"docling~=2.38",
"docling-core>=2.44.1",
"docling-jobkit[kfp,vlm]~=1.2",
"docling-core>=2.45.0",
"docling-jobkit[kfp,rq,vlm]>=1.6.0,<2.0.0",
"fastapi[standard]~=0.115",
"httpx~=0.28",
"pydantic~=2.10",
@@ -51,18 +50,18 @@ dependencies = [
[project.optional-dependencies]
ui = [
"gradio~=5.9",
"pydantic<2.11.0", # fix compatibility between gradio and new pydantic 2.11
"gradio>=5.23.2,<6.0.0",
]
tesserocr = [
"tesserocr~=2.7"
]
rapidocr = [
"rapidocr-onnxruntime~=1.4; python_version<'3.13'",
"onnxruntime~=1.7",
"rapidocr (>=3.3,<4.0.0) ; python_version < '3.14'",
"onnxruntime (>=1.7.0,<2.0.0)",
"modelscope>=1.29.0",
]
flash-attn = [
"flash-attn~=2.7.0; sys_platform == 'linux' and platform_machine == 'x86_64'"
"flash-attn~=2.8.2; sys_platform == 'linux' and platform_machine == 'x86_64'"
]
[dependency-groups]
@@ -70,31 +69,43 @@ dev = [
"asgi-lifespan~=2.0",
"mypy~=1.11",
"pre-commit-uv~=4.1",
"pypdf>=6.0.0",
"pytest~=8.3",
"pytest-asyncio~=0.24",
"pytest-check~=2.4",
"python-semantic-release~=7.32",
"ruff>=0.9.6",
]
pypi = [
"torch>=2.6.0",
"torchvision>=0.21.0",
"torch>=2.7.1",
"torchvision>=0.22.1",
]
cpu = [
"torch>=2.6.0",
"torchvision>=0.21.0",
]
cu124 = [
"torch>=2.6.0",
"torchvision>=0.21.0",
"torch>=2.7.1",
"torchvision>=0.22.1",
]
# cu124 = [
# "torch>=2.6.0",
# "torchvision>=0.21.0",
# ]
cu126 = [
"torch>=2.6.0",
"torchvision>=0.21.0",
"torch>=2.7.1",
"torchvision>=0.22.1",
]
cu128 = [
"torch>=2.7.0",
"torchvision>=0.22.0",
"torch>=2.7.1",
"torchvision>=0.22.1",
]
rocm = [
"torch>=2.7.1",
"torchvision>=0.22.1",
"pytorch-triton-rocm>=3.3.1 ; sys_platform == 'linux' and platform_machine == 'x86_64'",
]
[tool.uv]
@@ -104,31 +115,41 @@ conflicts = [
[
{ group = "pypi" },
{ group = "cpu" },
{ group = "cu124" },
# { group = "cu124" },
{ group = "cu126" },
{ group = "cu128" },
{ group = "rocm" },
],
]
environments = ["sys_platform != 'darwin' or platform_machine != 'x86_64'"]
override-dependencies = [
"urllib3~=2.0"
"urllib3~=2.0",
"xgrammar>=0.1.24"
]
[tool.uv.sources]
torch = [
{ index = "pytorch-pypi", group = "pypi" },
{ index = "pytorch-cpu", group = "cpu" },
{ index = "pytorch-cu124", group = "cu124" },
{ index = "pytorch-cu126", group = "cu126" },
{ index = "pytorch-cu128", group = "cu128" },
# { index = "pytorch-cu124", group = "cu124", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu126", group = "cu126", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu128", group = "cu128", marker = "sys_platform == 'linux'" },
{ index = "pytorch-rocm", group = "rocm", marker = "sys_platform == 'linux'" },
]
torchvision = [
{ index = "pytorch-pypi", group = "pypi" },
{ index = "pytorch-cpu", group = "cpu" },
{ index = "pytorch-cu124", group = "cu124" },
{ index = "pytorch-cu126", group = "cu126" },
{ index = "pytorch-cu128", group = "cu128" },
# { index = "pytorch-cu124", group = "cu124", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu126", group = "cu126", marker = "sys_platform == 'linux'" },
{ index = "pytorch-cu128", group = "cu128", marker = "sys_platform == 'linux'" },
{ index = "pytorch-rocm", group = "rocm", marker = "sys_platform == 'linux'" },
]
pytorch-triton-rocm = [
{ index = "pytorch-rocm", marker = "sys_platform == 'linux'" },
]
# docling-jobkit = { git = "https://github.com/docling-project/docling-jobkit/", rev = "main" }
# docling-jobkit = { path = "../docling-jobkit", editable = true }
@@ -142,10 +163,10 @@ name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true
[[tool.uv.index]]
name = "pytorch-cu124"
url = "https://download.pytorch.org/whl/cu124"
explicit = true
# [[tool.uv.index]]
# name = "pytorch-cu124"
# url = "https://download.pytorch.org/whl/cu124"
# explicit = true
[[tool.uv.index]]
name = "pytorch-cu126"
@@ -157,6 +178,11 @@ name = "pytorch-cu128"
url = "https://download.pytorch.org/whl/cu128"
explicit = true
[[tool.uv.index]]
name = "pytorch-rocm"
url = "https://download.pytorch.org/whl/rocm6.3"
explicit = true
[tool.setuptools.packages.find]
include = ["docling_serve*"]
namespaces = true
@@ -254,6 +280,7 @@ module = [
"kfp.*",
"kfp_server_api.*",
"mlx_vlm.*",
"mlx.*",
"scalar_fastapi.*",
]
ignore_missing_imports = true

View File

@@ -6,10 +6,15 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client

View File

@@ -6,10 +6,15 @@ import httpx
import pytest
import pytest_asyncio
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client

View File

@@ -5,10 +5,15 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client

View File

@@ -6,16 +6,24 @@ import pytest
import pytest_asyncio
from websockets.sync.client import connect
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@pytest.mark.asyncio
async def test_convert_url(async_client: httpx.AsyncClient):
"""Test convert URL to all outputs"""
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
doc_filename = Path("tests/2408.09869v5.pdf")
encoded_doc = base64.b64encode(doc_filename.read_bytes()).decode()
@@ -57,7 +65,7 @@ async def test_convert_url(async_client: httpx.AsyncClient):
task = response.json()
uri = f"ws://localhost:5001/v1/status/ws/{task['task_id']}"
uri = f"ws://localhost:5001/v1/status/ws/{task['task_id']}?api_key={docling_serve_settings.api_key}"
with connect(uri) as websocket:
for message in websocket:
print(message)

View File

@@ -6,10 +6,15 @@ import httpx
import pytest
import pytest_asyncio
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client
@@ -57,3 +62,60 @@ async def test_convert_url(async_client):
time.sleep(2)
assert task["task_status"] == "success"
@pytest.mark.asyncio
@pytest.mark.parametrize("include_converted_doc", [False, True])
async def test_chunk_url(async_client, include_converted_doc: bool):
"""Test chunk URL"""
example_docs = [
"https://arxiv.org/pdf/2311.18481",
]
base_url = "http://localhost:5001/v1"
payload = {
"sources": [{"kind": "http", "url": random.choice(example_docs)}],
"include_converted_doc": include_converted_doc,
}
response = await async_client.post(
f"{base_url}/chunk/hybrid/source/async", json=payload
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(json.dumps(task, indent=2))
while task["task_status"] not in ("success", "failure"):
response = await async_client.get(f"{base_url}/status/poll/{task['task_id']}")
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(f"{task['task_status']=}")
print(f"{task['task_position']=}")
time.sleep(2)
assert task["task_status"] == "success"
result_resp = await async_client.get(f"{base_url}/result/{task['task_id']}")
assert result_resp.status_code == 200, "Response should be 200 OK"
result = result_resp.json()
print("Got result.")
assert "chunks" in result
assert len(result["chunks"]) > 0
assert "documents" in result
assert len(result["documents"]) > 0
assert result["documents"][0]["status"] == "success"
if include_converted_doc:
assert result["documents"][0]["content"]["json_content"] is not None
assert (
result["documents"][0]["content"]["json_content"]["schema_name"]
== "DoclingDocument"
)
else:
assert result["documents"][0]["content"]["json_content"] is None

View File

@@ -5,10 +5,15 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client

View File

@@ -3,10 +3,15 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client

View File

@@ -6,10 +6,15 @@ import pytest
import pytest_asyncio
from pytest_check import check
from docling_serve.settings import docling_serve_settings
@pytest_asyncio.fixture
async def async_client():
async with httpx.AsyncClient(timeout=60.0) as client:
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
async with httpx.AsyncClient(timeout=60.0, headers=headers) as client:
yield client

View File

@@ -13,6 +13,7 @@ from pytest_check import check
from docling_core.types.doc import DoclingDocument, PictureItem
from docling_serve.app import create_app
from docling_serve.settings import docling_serve_settings
@pytest.fixture(scope="session")
@@ -20,6 +21,14 @@ def event_loop():
return asyncio.get_event_loop()
@pytest.fixture(scope="session")
def auth_headers():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
return headers
@pytest_asyncio.fixture(scope="session")
async def app():
app = create_app()
@@ -46,7 +55,7 @@ async def test_health(client: AsyncClient):
@pytest.mark.asyncio
async def test_convert_file(client: AsyncClient):
async def test_convert_file(client: AsyncClient, auth_headers: dict):
"""Test convert single file to all outputs"""
endpoint = "/v1/convert/file"
@@ -79,7 +88,9 @@ async def test_convert_file(client: AsyncClient):
"files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
}
response = await client.post(endpoint, files=files, data=options)
response = await client.post(
endpoint, files=files, data=options, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
data = response.json()
@@ -160,7 +171,7 @@ async def test_convert_file(client: AsyncClient):
@pytest.mark.asyncio
async def test_referenced_artifacts(client: AsyncClient):
async def test_referenced_artifacts(client: AsyncClient, auth_headers: dict):
"""Test that paths in the zip file are relative to the zip file root."""
endpoint = "/v1/convert/file"
@@ -178,7 +189,9 @@ async def test_referenced_artifacts(client: AsyncClient):
"files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
}
response = await client.post(endpoint, files=files, data=options)
response = await client.post(
endpoint, files=files, data=options, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
with zipfile.ZipFile(io.BytesIO(response.content)) as zip_file:

View File

@@ -11,6 +11,7 @@ from docling_core.types import DoclingDocument
from docling_core.types.doc.document import PictureDescriptionData
from docling_serve.app import create_app
from docling_serve.settings import docling_serve_settings
@pytest.fixture(scope="session")
@@ -18,6 +19,14 @@ def event_loop():
return asyncio.get_event_loop()
@pytest.fixture(scope="session")
def auth_headers():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
return headers
@pytest_asyncio.fixture(scope="session")
async def app():
app = create_app()
@@ -37,7 +46,7 @@ async def client(app):
@pytest.mark.asyncio
async def test_convert_file(client: AsyncClient):
async def test_convert_file(client: AsyncClient, auth_headers: dict):
"""Test convert single file to all outputs"""
endpoint = "/v1/convert/file"
@@ -63,7 +72,9 @@ async def test_convert_file(client: AsyncClient):
"files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
}
response = await client.post(endpoint, files=files, data=options)
response = await client.post(
endpoint, files=files, data=options, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
data = response.json()

View File

@@ -17,6 +17,14 @@ def event_loop():
return asyncio.get_event_loop()
@pytest.fixture(scope="session")
def auth_headers():
headers = {}
if docling_serve_settings.api_key:
headers["X-Api-Key"] = docling_serve_settings.api_key
return headers
@pytest_asyncio.fixture(scope="session")
async def app():
app = create_app()
@@ -35,7 +43,7 @@ async def client(app):
yield client
async def convert_file(client: AsyncClient):
async def convert_file(client: AsyncClient, auth_headers: dict):
doc_filename = Path("tests/2408.09869v5.pdf")
encoded_doc = base64.b64encode(doc_filename.read_bytes()).decode()
@@ -52,7 +60,9 @@ async def convert_file(client: AsyncClient):
],
}
response = await client.post("/v1/convert/source/async", json=payload)
response = await client.post(
"/v1/convert/source/async", json=payload, headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
@@ -60,7 +70,9 @@ async def convert_file(client: AsyncClient):
print(json.dumps(task, indent=2))
while task["task_status"] not in ("success", "failure"):
response = await client.get(f"/v1/status/poll/{task['task_id']}")
response = await client.get(
f"/v1/status/poll/{task['task_id']}", headers=auth_headers
)
assert response.status_code == 200, "Response should be 200 OK"
task = response.json()
print(f"{task['task_status']=}")
@@ -74,52 +86,62 @@ async def convert_file(client: AsyncClient):
@pytest.mark.asyncio
async def test_clear_results(client: AsyncClient):
async def test_clear_results(client: AsyncClient, auth_headers: dict):
"""Test removal of task."""
# Set long delay deletion
docling_serve_settings.result_removal_delay = 100
# Convert and wait for completion
task = await convert_file(client)
task = await convert_file(client, auth_headers=auth_headers)
# Get result once
result_response = await client.get(f"/v1/result/{task['task_id']}")
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 200, "Response should be 200 OK"
print("Result 1 ok.")
result = result_response.json()
assert result["document"]["json_content"]["schema_name"] == "DoclingDocument"
# Get result twice
result_response = await client.get(f"/v1/result/{task['task_id']}")
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 200, "Response should be 200 OK"
print("Result 2 ok.")
result = result_response.json()
assert result["document"]["json_content"]["schema_name"] == "DoclingDocument"
# Clear
clear_response = await client.get("/v1/clear/results?older_then=0")
clear_response = await client.get(
"/v1/clear/results?older_then=0", headers=auth_headers
)
assert clear_response.status_code == 200, "Response should be 200 OK"
print("Clear ok.")
# Get deleted result
result_response = await client.get(f"/v1/result/{task['task_id']}")
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 404, "Response should be removed"
print("Result was no longer found.")
@pytest.mark.asyncio
async def test_delay_remove(client: AsyncClient):
async def test_delay_remove(client: AsyncClient, auth_headers: dict):
"""Test automatic removal of task with delay."""
# Set short delay deletion
docling_serve_settings.result_removal_delay = 5
# Convert and wait for completion
task = await convert_file(client)
task = await convert_file(client, auth_headers=auth_headers)
# Get result once
result_response = await client.get(f"/v1/result/{task['task_id']}")
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 200, "Response should be 200 OK"
print("Result ok.")
result = result_response.json()
@@ -129,5 +151,7 @@ async def test_delay_remove(client: AsyncClient):
await asyncio.sleep(10)
# Get deleted result
result_response = await client.get(f"/v1/result/{task['task_id']}")
result_response = await client.get(
f"/v1/result/{task['task_id']}", headers=auth_headers
)
assert result_response.status_code == 404, "Response should be removed"

8102
uv.lock generated

File diff suppressed because one or more lines are too long