LLM/docling-serve
1
0
Fork 0
mirror of https://github.com/docling-project/docling-serve.git synced 2025-11-29 00:23:36 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat: Add new docling-serve cli (#50)

Browse Source 
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
This commit is contained in:
Michele Dolfi
2025-02-19 20:54:13 +01:00
committed by GitHub
parent 663e03303a
commit ec33a61faa
13 changed files with 526 additions and 215 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
.github/workflows/ci-images-dryrun.yml vendored
View File

@@ -20,7 +20,7 @@ jobs:
with:
publish: false
build_args: |
CPU_ONLY=true
UV_SYNC_EXTRA_ARGS=--no-extra cu124
ghcr_image_name: ds4sd/docling-serve-cpu
quay_image_name: ""
@@ -37,7 +37,7 @@ jobs:
with:
publish: false
build_args: |
CPU_ONLY=false
UV_SYNC_EXTRA_ARGS=--no-extra cpu
platforms: linux/amd64
ghcr_image_name: ds4sd/docling-serve
quay_image_name: ""

4
.github/workflows/images.yml vendored
View File

@@ -34,7 +34,7 @@ jobs:
publish: true
environment: registry-creds
build_args: |
CPU_ONLY=true
UV_SYNC_EXTRA_ARGS=--no-extra cu124
ghcr_image_name: ds4sd/docling-serve-cpu
quay_image_name: ds4sd/docling-serve-cpu
@@ -53,7 +53,7 @@ jobs:
publish: true
environment: registry-creds
build_args: |
CPU_ONLY=false
UV_SYNC_EXTRA_ARGS=--no-extra cpu
platforms: linux/amd64
ghcr_image_name: ds4sd/docling-serve
quay_image_name: ds4sd/docling-serve

4
.github/workflows/job-image.yml vendored
View File

@@ -105,8 +105,6 @@ jobs:
cache-to: type=gha,mode=max
file: Containerfile
build-args: ${{ inputs.build_args }}
# |
# --build-arg CPU_ONLY=true
- name: Generate artifact attestation
if: ${{ inputs.publish }}
@@ -137,8 +135,6 @@ jobs:
cache-to: type=gha,mode=max
file: Containerfile
build-args: ${{ inputs.build_args }}
# |
# --build-arg CPU_ONLY=true
- name: Remove Local Docker Images
run: |

16
Containerfile
View File

@@ -2,8 +2,8 @@ ARG BASE_IMAGE=quay.io/sclorg/python-312-c9s:c9s
FROM ${BASE_IMAGE}
ARG CPU_ONLY=false
ARG MODELS_LIST="layout tableformer picture_classifier easyocr"
ARG UV_SYNC_EXTRA_ARGS=""
USER 0
@@ -41,17 +41,10 @@ ENV PYTHONIOENCODING=utf-8
ENV UV_COMPILE_BYTECODE=1 UV_LINK_MODE=copy
ENV UV_PROJECT_ENVIRONMENT=/opt/app-root
ENV WITH_UI=True
COPY --chown=1001:0 pyproject.toml uv.lock README.md ./
RUN --mount=type=cache,target=/opt/app-root/src/.cache/uv,uid=1001 \
if [ "$CPU_ONLY" = "true" ]; then \
NO_EXTRA=cu124; \
else \
NO_EXTRA=cpu; \
fi && \
uv sync --frozen --no-install-project --no-dev --all-extras --no-extra ${NO_EXTRA}
uv sync --frozen --no-install-project --no-dev --all-extras ${UV_SYNC_EXTRA_ARGS} # --no-extra ${NO_EXTRA}
RUN echo "Downloading models..." && \
docling-tools models download ${MODELS_LIST} && \
@@ -59,8 +52,9 @@ RUN echo "Downloading models..." && \
chmod -R g=u /opt/app-root/src/.cache
COPY --chown=1001:0 --chmod=664 ./docling_serve ./docling_serve
RUN --mount=type=cache,target=/opt/app-root/src/.cache/uv,uid=1001 \
uv sync --frozen --no-dev --all-extras ${UV_SYNC_EXTRA_ARGS} # --no-extra ${NO_EXTRA}
EXPOSE 5001
CMD ["python", "-m", "docling_serve"]
CMD ["docling-serve", "run"]

6
Makefile
View File

@@ -26,15 +26,15 @@ md-lint-file:
.PHONY: docling-serve-cpu-image
docling-serve-cpu-image: Containerfile ## Build docling-serve "cpu only" container image
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve CPU ONLY]"
$(CMD_PREFIX) docker build --build-arg CPU_ONLY=true -f Containerfile --platform linux/amd64 -t ghcr.io/ds4sd/docling-serve-cpu:$(TAG) .
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve CPU]"
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-extra cu124" -f Containerfile -t ghcr.io/ds4sd/docling-serve-cpu:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve-cpu:$(TAG) ghcr.io/ds4sd/docling-serve-cpu:main
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve-cpu:$(TAG) quay.io/ds4sd/docling-serve-cpu:main
.PHONY: docling-serve-gpu-image
docling-serve-gpu-image: Containerfile ## Build docling-serve container image with GPU support
$(ECHO_PREFIX) printf " %-12s Containerfile\n" "[docling-serve with GPU]"
$(CMD_PREFIX) docker build --build-arg CPU_ONLY=false -f Containerfile --platform linux/amd64 -t ghcr.io/ds4sd/docling-serve:$(TAG) .
$(CMD_PREFIX) docker build --load --build-arg "UV_SYNC_EXTRA_ARGS=--no-extra cpu" -f Containerfile --platform linux/amd64 -t ghcr.io/ds4sd/docling-serve:$(TAG) .
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve:$(TAG) ghcr.io/ds4sd/docling-serve:main
$(CMD_PREFIX) docker tag ghcr.io/ds4sd/docling-serve:$(TAG) quay.io/ds4sd/docling-serve:main

78
README.md
View File

@@ -327,25 +327,83 @@ See `[project.optional-dependencies]` section in `pyproject.toml` for full list
### Run the server
The [start_server.sh](./start_server.sh) executable is a convenient script for launching the local webserver.
The `docling-serve` executable is a convenient script for launching the webserver both in
development and production mode.
```sh
# Run the server
bash start_server.sh
# Run the server in development mode
# - reload is enabled by default
# - listening on the 127.0.0.1 address
# - ui is enabled by default
docling-serve dev
# Run the server with live reload
RELOAD=true bash start_server.sh
# Run the server in production mode
# - reload is disabled by default
# - listening on the 0.0.0.0 address
# - ui is disabled by default
docling-serve run
```
### Environment variables
### Options
The following variables are available:
The `docling-serve` executable allows is controlled with both command line
options and environment variables.
<details>
<summary>`docling-serve` help message</summary>
```sh
$ docling-serve dev --help
Usage: docling-serve dev [OPTIONS]
Run a Docling Serve app in development mode. 🧪
This is equivalent to docling-serve run but with reload
enabled and listening on the 127.0.0.1 address.
Options can be set also with the corresponding ENV variable, with the exception
of --enable-ui, --host and --reload.
╭─ Options ──────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --host TEXT The host to serve on. For local development in localhost │
│ use 127.0.0.1. To enable public access, e.g. in a │
│ container, use all the IP addresses available with │
│ 0.0.0.0. │
│ [default: 127.0.0.1] │
│ --port INTEGER The port to serve on. [default: 5001] │
│ --reload --no-reload Enable auto-reload of the server when (code) files │
│ change. This is resource intensive, use it only during │
│ development. │
│ [default: reload] │
│ --root-path TEXT The root path is used to tell your app that it is being │
│ served to the outside world with some path prefix set up │
│ in some termination proxy or similar. │
│ --proxy-headers --no-proxy-headers Enable/Disable X-Forwarded-Proto, X-Forwarded-For, │
│ X-Forwarded-Port to populate remote address info. │
│ [default: proxy-headers] │
│ --enable-ui --no-enable-ui Enable the development UI. [default: enable-ui] │
│ --help Show this message and exit. │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
```
</details>
#### Environment variables
The environment variables controlling the `uvicorn` execution can be specified with the `UVICORN_` prefix:
- `UVICORN_WORKERS`: Number of workers to use.
- `UVICORN_RELOAD`: If `True`, this will enable auto-reload when you modify files, useful for development.
The environment variables controlling specifics of the Docling Serve app can be specified with the
`DOCLING_SERVE_` prefix:
- `DOCLING_SERVE_ENABLE_UI`: If `True`, The Gradio UI will be available at `/ui`.
Others:
- `DOCLING_ARTIFACTS_PATH`: if set Docling will use only the local weights of models, for example `/opt/app-root/.cache/docling/cache`.
- `TESSDATA_PREFIX`: Tesseract data location, example `/usr/share/tesseract/tessdata/`.
- `UVICORN_WORKERS`: Number of workers to use.
- `RELOAD`: If `True`, this will enable auto-reload when you modify files, useful for development.
- `WITH_UI`: If `True`, The Gradio UI will be available at `/ui`.
## Get help and support

2
docling_serve/.env.example
View File

@@ -1,3 +1,3 @@
TESSDATA_PREFIX=/usr/share/tesseract/tessdata/
UVICORN_WORKERS=2
RELOAD=True
UVICORN_RELOAD=True

291
docling_serve/__main__.py
View File

@@ -1,20 +1,281 @@
import os
import importlib
import logging
import platform
import sys
import warnings
from typing import Annotated, Any, Union
from docling_serve.helper_functions import _str_to_bool
import typer
import uvicorn
from rich.console import Console
# Launch the FastAPI server
if __name__ == "__main__":
from uvicorn import run
from docling_serve.settings import docling_serve_settings, uvicorn_settings
port = int(os.getenv("PORT", "5001"))
workers = int(os.getenv("UVICORN_WORKERS", "1"))
reload = _str_to_bool(os.getenv("RELOAD", "False"))
warnings.filterwarnings(action="ignore", category=UserWarning, module="pydantic|torch")
warnings.filterwarnings(action="ignore", category=FutureWarning, module="easyocr")
run(
"docling_serve.app:app",
host="0.0.0.0",
port=port,
workers=workers,
timeout_keep_alive=600,
reload=reload,
err_console = Console(stderr=True)
console = Console()
app = typer.Typer(
no_args_is_help=True,
rich_markup_mode="rich",
)
logger = logging.getLogger(__name__)
def version_callback(value: bool) -> None:
if value:
docling_serve_version = importlib.metadata.version("docling_serve")
docling_version = importlib.metadata.version("docling")
docling_core_version = importlib.metadata.version("docling-core")
docling_ibm_models_version = importlib.metadata.version("docling-ibm-models")
docling_parse_version = importlib.metadata.version("docling-parse")
platform_str = platform.platform()
py_impl_version = sys.implementation.cache_tag
py_lang_version = platform.python_version()
console.print(f"Docling Serve version: {docling_serve_version}")
console.print(f"Docling version: {docling_version}")
console.print(f"Docling Core version: {docling_core_version}")
console.print(f"Docling IBM Models version: {docling_ibm_models_version}")
console.print(f"Docling Parse version: {docling_parse_version}")
console.print(f"Python: {py_impl_version} ({py_lang_version})")
console.print(f"Platform: {platform_str}")
raise typer.Exit()
@app.callback()
def callback(
version: Annotated[
Union[bool, None],
typer.Option(
"--version", help="Show the version and exit.", callback=version_callback
),
] = None,
verbose: Annotated[
int,
typer.Option(
"--verbose",
"-v",
count=True,
help="Set the verbosity level. -v for info logging, -vv for debug logging.",
),
] = 0,
) -> None:
if verbose == 0:
logging.basicConfig(level=logging.WARNING)
elif verbose == 1:
logging.basicConfig(level=logging.INFO)
elif verbose == 2:
logging.basicConfig(level=logging.DEBUG)
def _run(
*,
command: str,
) -> None:
server_type = "development" if command == "dev" else "production"
console.print(f"Starting {server_type} server 🚀")
url = f"http://{uvicorn_settings.host}:{uvicorn_settings.port}"
url_docs = f"{url}/docs"
url_ui = f"{url}/ui"
console.print("")
console.print(f"Server started at [link={url}]{url}[/]")
console.print(f"Documentation at [link={url_docs}]{url_docs}[/]")
if docling_serve_settings.enable_ui:
console.print(f"UI at [link={url_ui}]{url_ui}[/]")
if command == "dev":
console.print("")
console.print(
"Running in development mode, for production use: "
"[bold]docling-serve run[/]",
)
console.print("")
console.print("Logs:")
uvicorn.run(
app="docling_serve.app:create_app",
factory=True,
host=uvicorn_settings.host,
port=uvicorn_settings.port,
reload=uvicorn_settings.reload,
workers=uvicorn_settings.workers,
root_path=uvicorn_settings.root_path,
proxy_headers=uvicorn_settings.proxy_headers,
)
@app.command()
def dev(
*,
# uvicorn options
host: Annotated[
str,
typer.Option(
help=(
"The host to serve on. For local development in localhost "
"use [blue]127.0.0.1[/blue]. To enable public access, "
"e.g. in a container, use all the IP addresses "
"available with [blue]0.0.0.0[/blue]."
)
),
] = "127.0.0.1",
port: Annotated[
int,
typer.Option(help="The port to serve on."),
] = uvicorn_settings.port,
reload: Annotated[
bool,
typer.Option(
help=(
"Enable auto-reload of the server when (code) files change. "
"This is [bold]resource intensive[/bold], "
"use it only during development."
)
),
] = True,
root_path: Annotated[
str,
typer.Option(
help=(
"The root path is used to tell your app that it is being served "
"to the outside world with some [bold]path prefix[/bold] "
"set up in some termination proxy or similar."
)
),
] = uvicorn_settings.root_path,
proxy_headers: Annotated[
bool,
typer.Option(
help=(
"Enable/Disable X-Forwarded-Proto, X-Forwarded-For, "
"X-Forwarded-Port to populate remote address info."
)
),
] = uvicorn_settings.proxy_headers,
# docling options
enable_ui: Annotated[bool, typer.Option(help="Enable the development UI.")] = True,
) -> Any:
"""
Run a [bold]Docling Serve[/bold] app in [yellow]development[/yellow] mode. 🧪
This is equivalent to [bold]docling-serve run[/bold] but with [bold]reload[/bold]
enabled and listening on the [blue]127.0.0.1[/blue] address.
Options can be set also with the corresponding ENV variable, with the exception
of --enable-ui, --host and --reload.
"""
uvicorn_settings.host = host
uvicorn_settings.port = port
uvicorn_settings.reload = reload
uvicorn_settings.root_path = root_path
uvicorn_settings.proxy_headers = proxy_headers
docling_serve_settings.enable_ui = enable_ui
_run(
command="dev",
)
@app.command()
def run(
*,
host: Annotated[
str,
typer.Option(
help=(
"The host to serve on. For local development in localhost "
"use [blue]127.0.0.1[/blue]. To enable public access, "
"e.g. in a container, use all the IP addresses "
"available with [blue]0.0.0.0[/blue]."
)
),
] = uvicorn_settings.host,
port: Annotated[
int,
typer.Option(help="The port to serve on."),
] = uvicorn_settings.port,
reload: Annotated[
bool,
typer.Option(
help=(
"Enable auto-reload of the server when (code) files change. "
"This is [bold]resource intensive[/bold], "
"use it only during development."
)
),
] = uvicorn_settings.reload,
workers: Annotated[
Union[int, None],
typer.Option(
help=(
"Use multiple worker processes. "
"Mutually exclusive with the --reload flag."
)
),
] = uvicorn_settings.workers,
root_path: Annotated[
str,
typer.Option(
help=(
"The root path is used to tell your app that it is being served "
"to the outside world with some [bold]path prefix[/bold] "
"set up in some termination proxy or similar."
)
),
] = uvicorn_settings.root_path,
proxy_headers: Annotated[
bool,
typer.Option(
help=(
"Enable/Disable X-Forwarded-Proto, X-Forwarded-For, "
"X-Forwarded-Port to populate remote address info."
)
),
] = uvicorn_settings.proxy_headers,
# docling options
enable_ui: Annotated[
bool, typer.Option(help="Enable the development UI.")
] = docling_serve_settings.enable_ui,
) -> Any:
"""
Run a [bold]Docling Serve[/bold] app in [green]production[/green] mode. 🚀
This is equivalent to [bold]docling-serve dev[/bold] but with [bold]reload[/bold]
disabled and listening on the [blue]0.0.0.0[/blue] address.
Options can be set also with the corresponding ENV variable, e.g. UVICORN_PORT
or DOCLING_SERVE_ENABLE_UI.
"""
uvicorn_settings.host = host
uvicorn_settings.port = port
uvicorn_settings.reload = reload
uvicorn_settings.workers = workers
uvicorn_settings.root_path = root_path
uvicorn_settings.proxy_headers = proxy_headers
docling_serve_settings.enable_ui = enable_ui
_run(
command="run",
)
def main() -> None:
app()
# Launch the CLI when calling python -m docling_serve
if __name__ == "__main__":
main()

270
docling_serve/app.py
View File

@@ -1,5 +1,4 @@
import logging
import os
import tempfile
from contextlib import asynccontextmanager
from io import BytesIO
@@ -8,7 +7,6 @@ from typing import Annotated, Any, Dict, List, Optional, Union
from docling.datamodel.base_models import DocumentStream, InputFormat
from docling.document_converter import DocumentConverter
from dotenv import load_dotenv
from fastapi import BackgroundTasks, FastAPI, UploadFile
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import RedirectResponse
@@ -22,17 +20,9 @@ from docling_serve.docling_conversion import (
converters,
get_pdf_pipeline_opts,
)
from docling_serve.helper_functions import FormDepends, _str_to_bool
from docling_serve.helper_functions import FormDepends
from docling_serve.response_preparation import ConvertDocumentResponse, process_results
# Load local env vars if present
load_dotenv()
WITH_UI = _str_to_bool(os.getenv("WITH_UI", "False"))
if WITH_UI:
import gradio as gr
from docling_serve.gradio_ui import ui as gradio_ui
from docling_serve.settings import docling_serve_settings
# Set up custom logging as we'll be intermixes with FastAPI/Uvicorn's logging
@@ -70,7 +60,6 @@ _log = logging.getLogger(__name__)
# Context manager to initialize and clean up the lifespan of the FastAPI app
@asynccontextmanager
async def lifespan(app: FastAPI):
# settings = Settings()
# Converter with default options
pdf_format_option, options_hash = get_pdf_pipeline_opts(ConvertDocumentsOptions())
@@ -86,143 +75,156 @@ async def lifespan(app: FastAPI):
yield
converters.clear()
if WITH_UI:
gradio_ui.close()
# if WITH_UI:
# gradio_ui.close()
##################################
# App creation and configuration #
##################################
app = FastAPI(
title="Docling Serve",
lifespan=lifespan,
)
origins = ["*"]
methods = ["*"]
headers = ["*"]
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=methods,
allow_headers=headers,
)
# Mount the Gradio app
if WITH_UI:
tmp_output_dir = Path(tempfile.mkdtemp())
gradio_ui.gradio_output_dir = tmp_output_dir
app = gr.mount_gradio_app(
app,
gradio_ui,
path="/ui",
allowed_paths=["./logo.png", tmp_output_dir],
root_path="/ui",
def create_app():
app = FastAPI(
title="Docling Serve",
lifespan=lifespan,
)
origins = ["*"]
methods = ["*"]
headers = ["*"]
#############################
# API Endpoints definitions #
#############################
# Favicon
@app.get("/favicon.ico", include_in_schema=False)
async def favicon():
response = RedirectResponse(url="https://ds4sd.github.io/docling/assets/logo.png")
return response
# Status
class HealthCheckResponse(BaseModel):
status: str = "ok"
@app.get("/health")
def health() -> HealthCheckResponse:
return HealthCheckResponse()
# API readiness compatibility for OpenShift AI Workbench
@app.get("/api", include_in_schema=False)
def api_check() -> HealthCheckResponse:
return HealthCheckResponse()
# Convert a document from URL(s)
@app.post(
"/v1alpha/convert/source",
response_model=ConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
# "description": "Return the JSON item or an image.",
}
},
)
def process_url(
background_tasks: BackgroundTasks, conversion_request: ConvertDocumentsRequest
):
sources: List[Union[str, DocumentStream]] = []
headers: Optional[Dict[str, Any]] = None
if isinstance(conversion_request, ConvertDocumentFileSourcesRequest):
for file_source in conversion_request.file_sources:
sources.append(file_source.to_document_stream())
else:
for http_source in conversion_request.http_sources:
sources.append(http_source.url)
if headers is None and http_source.headers:
headers = http_source.headers
# Note: results are only an iterator->lazy evaluation
results = convert_documents(
sources=sources, options=conversion_request.options, headers=headers
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=methods,
allow_headers=headers,
)
# The real processing will happen here
response = process_results(
background_tasks=background_tasks,
conversion_options=conversion_request.options,
conv_results=results,
# Mount the Gradio app
if docling_serve_settings.enable_ui:
try:
import gradio as gr
from docling_serve.gradio_ui import ui as gradio_ui
tmp_output_dir = Path(tempfile.mkdtemp())
gradio_ui.gradio_output_dir = tmp_output_dir
app = gr.mount_gradio_app(
app,
gradio_ui,
path="/ui",
allowed_paths=["./logo.png", tmp_output_dir],
root_path="/ui",
)
except ImportError:
_log.warning(
"Docling Serve enable_ui is activated, but gradio is not installed. "
"Install it with `pip install docling-serve[ui]` "
"or `pip install gradio`"
)
#############################
# API Endpoints definitions #
#############################
# Favicon
@app.get("/favicon.ico", include_in_schema=False)
async def favicon():
response = RedirectResponse(
url="https://ds4sd.github.io/docling/assets/logo.png"
)
return response
# Status
class HealthCheckResponse(BaseModel):
status: str = "ok"
@app.get("/health")
def health() -> HealthCheckResponse:
return HealthCheckResponse()
# API readiness compatibility for OpenShift AI Workbench
@app.get("/api", include_in_schema=False)
def api_check() -> HealthCheckResponse:
return HealthCheckResponse()
# Convert a document from URL(s)
@app.post(
"/v1alpha/convert/source",
response_model=ConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
# "description": "Return the JSON item or an image.",
}
},
)
def process_url(
background_tasks: BackgroundTasks, conversion_request: ConvertDocumentsRequest
):
sources: List[Union[str, DocumentStream]] = []
headers: Optional[Dict[str, Any]] = None
if isinstance(conversion_request, ConvertDocumentFileSourcesRequest):
for file_source in conversion_request.file_sources:
sources.append(file_source.to_document_stream())
else:
for http_source in conversion_request.http_sources:
sources.append(http_source.url)
if headers is None and http_source.headers:
headers = http_source.headers
return response
# Note: results are only an iterator->lazy evaluation
results = convert_documents(
sources=sources, options=conversion_request.options, headers=headers
)
# The real processing will happen here
response = process_results(
background_tasks=background_tasks,
conversion_options=conversion_request.options,
conv_results=results,
)
# Convert a document from file(s)
@app.post(
"/v1alpha/convert/file",
response_model=ConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
}
},
)
async def process_file(
background_tasks: BackgroundTasks,
files: List[UploadFile],
options: Annotated[ConvertDocumentsOptions, FormDepends(ConvertDocumentsOptions)],
):
return response
_log.info(f"Received {len(files)} files for processing.")
# Load the uploaded files to Docling DocumentStream
file_sources = []
for file in files:
buf = BytesIO(file.file.read())
name = file.filename if file.filename else "file.pdf"
file_sources.append(DocumentStream(name=name, stream=buf))
results = convert_documents(sources=file_sources, options=options)
response = process_results(
background_tasks=background_tasks,
conversion_options=options,
conv_results=results,
# Convert a document from file(s)
@app.post(
"/v1alpha/convert/file",
response_model=ConvertDocumentResponse,
responses={
200: {
"content": {"application/zip": {}},
}
},
)
async def process_file(
background_tasks: BackgroundTasks,
files: List[UploadFile],
options: Annotated[
ConvertDocumentsOptions, FormDepends(ConvertDocumentsOptions)
],
):
return response
_log.info(f"Received {len(files)} files for processing.")
# Load the uploaded files to Docling DocumentStream
file_sources = []
for file in files:
buf = BytesIO(file.file.read())
name = file.filename if file.filename else "file.pdf"
file_sources.append(DocumentStream(name=name, stream=buf))
results = convert_documents(sources=file_sources, options=options)
response = process_results(
background_tasks=background_tasks,
conversion_options=options,
conv_results=results,
)
return response
return app

26
docling_serve/settings.py
View File

@@ -1,6 +1,28 @@
from typing import Union
from pydantic_settings import BaseSettings, SettingsConfigDict
class Settings(BaseSettings):
class UvicornSettings(BaseSettings):
model_config = SettingsConfigDict(
env_prefix="UVICORN_", env_file=".env", extra="allow"
)
model_config = SettingsConfigDict(env_prefix="DOCLING_")
host: str = "0.0.0.0"
port: int = 5001
reload: bool = False
root_path: str = ""
proxy_headers: bool = True
workers: Union[int, None] = None
class DoclingServeSettings(BaseSettings):
model_config = SettingsConfigDict(
env_prefix="DOCLING_SERVE_", env_file=".env", extra="allow"
)
enable_ui: bool = False
uvicorn_settings = UvicornSettings()
docling_serve_settings = DoclingServeSettings()

6
pyproject.toml
View File

@@ -36,6 +36,7 @@ dependencies = [
"pydantic~=2.10",
"pydantic-settings~=2.4",
"python-multipart>=0.0.14,<0.1.0",
"typer~=0.12",
"uvicorn[standard]>=0.29.0,<1.0.0",
]
@@ -74,6 +75,7 @@ dev = [
]
[tool.uv]
package = true
conflicts = [
[
{ extra = "cpu" },
@@ -104,6 +106,9 @@ explicit = true
[tool.setuptools.packages.find]
include = ["docling_serve"]
[project.scripts]
docling-serve = "docling_serve.__main__:main"
[project.urls]
Homepage = "https://github.com/DS4SD/docling-serve"
# Documentation = "https://ds4sd.github.io/docling"
@@ -118,6 +123,7 @@ include = '\.pyi?$'
[tool.isort]
profile = "black"
known_third_party = ["docling", "docling_core"]
line_length = 88
py_version=311

30
start_server.sh
View File

@@ -1,30 +0,0 @@
#!/bin/bash
set -Eeuo pipefail
# Network settings
export PORT="${PORT:-5001}"
export HOST="${HOST:-"0.0.0.0"}"
# Performance settings
UVICORN_WORKERS="${UVICORN_WORKERS:-1}"
# Development settings
export WITH_UI="${WITH_UI:-"true"}"
export RELOAD=${RELOAD:-"false"}
# --------------------------------------
# Process env settings
EXTRA_ARGS=""
if [ "$RELOAD" == "true" ]; then
EXTRA_ARGS="$EXTRA_ARGS --reload"
fi
# Launch
exec uv run uvicorn \
docling_serve.app:app \
--host=${HOST} \
--port=${PORT} \
--timeout-keep-alive=600 \
${EXTRA_ARGS} \
--workers=${UVICORN_WORKERS}

4
uv.lock generated
View File

@@ -583,7 +583,7 @@ wheels = [
[[package]]
name = "docling-serve"
version = "0.2.0"
source = { virtual = "." }
source = { editable = "." }
dependencies = [
{ name = "docling" },
{ name = "fastapi", extra = ["standard"] },
@@ -591,6 +591,7 @@ dependencies = [
{ name = "pydantic" },
{ name = "pydantic-settings" },
{ name = "python-multipart" },
{ name = "typer" },
{ name = "uvicorn", extra = ["standard"] },
]
@@ -646,6 +647,7 @@ requires-dist = [
{ name = "torch", marker = "extra == 'cu124'", specifier = ">=2.6.0", index = "https://download.pytorch.org/whl/cu124", conflict = { package = "docling-serve", extra = "cu124" } },
{ name = "torchvision", marker = "extra == 'cpu'", specifier = ">=0.21.0", index = "https://download.pytorch.org/whl/cpu", conflict = { package = "docling-serve", extra = "cpu" } },
{ name = "torchvision", marker = "extra == 'cu124'", specifier = ">=0.21.0", index = "https://download.pytorch.org/whl/cu124", conflict = { package = "docling-serve", extra = "cu124" } },
{ name = "typer", specifier = "~=0.12" },
{ name = "uvicorn", extras = ["standard"], specifier = ">=0.29.0,<1.0.0" },
]
provides-extras = ["ui", "tesserocr", "rapidocr", "cpu", "cu124"]