chore: bump version to 1.1.0 [skip ci]

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

.github/styles/config/vocabularies/Docling/accept.txt

@@ -0,0 +1,35 @@
+[Dd]ocling
+precommit
+asgi
+async
+(?i)urls
+uvicorn
+[Ww]ebserver
+keyfile
+[Ww]ebsocket(s?)
+[Kk]ubernetes
+UI
+(?i)vllm
+APIs
+[Ss]ubprocesses
+(?i)api
+Kubeflow
+(?i)Jobkit
+(?i)cpu
+(?i)PyTorch
+(?i)CUDA
+(?i)NVIDIA
+(?i)env
+Gradio
+bool
+Ollama
+inbody
+LGTMs
+Dolfi
+Lysak
+Nikos
+Nassar
+Panos
+Vagenas
+Staar
+Livathinos

.github/vale.ini

@@ -0,0 +1,11 @@
+StylesPath = styles
+MinAlertLevel = suggestion
+; Packages = write-good, proselint
+
+Vocab = Docling
+
+[*.md]
+BasedOnStyles = Vale
+
+[CHANGELOG.md]
+BasedOnStyles = 

.pre-commit-config.yaml

@@ -21,6 +21,17 @@ repos:
         pass_filenames: false
         language: system
         files: '\.py$'
+  - repo: https://github.com/errata-ai/vale
+    rev: v3.12.0  # Use latest stable version
+    hooks:
+      - id: vale
+        name: vale sync
+        pass_filenames: false
+        args: [sync, "--config=.github/vale.ini"]
+      - id: vale
+        name: Spell and Style Check with Vale
+        args: ["--config=.github/vale.ini"]
+        files: \.md$
   - repo: https://github.com/astral-sh/uv-pre-commit
     # uv version.
     rev: 0.7.13

CHANGELOG.md

@@ -1,3 +1,25 @@
+## [v1.1.0](https://github.com/docling-project/docling-serve/releases/tag/v1.1.0) - 2025-07-30
+
+### Feature
+
+* Add docling-mcp in the distribution ([#290](https://github.com/docling-project/docling-serve/issues/290)) ([`ecb1874`](https://github.com/docling-project/docling-serve/commit/ecb1874a507bef83d102e0e031e49fed34298637))
+* Add 3.0 openapi endpoint ([#287](https://github.com/docling-project/docling-serve/issues/287)) ([`ec594d8`](https://github.com/docling-project/docling-serve/commit/ec594d84fe36df23e7d010a2fcf769856c43600b))
+* Add new source and target ([#270](https://github.com/docling-project/docling-serve/issues/270)) ([`3771c1b`](https://github.com/docling-project/docling-serve/commit/3771c1b55403bd51966d07d8f760d5c4fbcc1760))
+
+### Fix
+
+* Referenced paths relative to zip root ([#289](https://github.com/docling-project/docling-serve/issues/289)) ([`1333f71`](https://github.com/docling-project/docling-serve/commit/1333f71c9c6495342b2169d574e921f828446f15))
+
+## [v1.0.1](https://github.com/docling-project/docling-serve/releases/tag/v1.0.1) - 2025-07-21
+
+### Fix
+
+* Docling update v2.42.0 ([#277](https://github.com/docling-project/docling-serve/issues/277)) ([`8706706`](https://github.com/docling-project/docling-serve/commit/8706706e8797b0a06ec4baa7cf87988311be68b6))
+
+### Documentation
+
+* Typo in README ([#276](https://github.com/docling-project/docling-serve/issues/276)) ([`766adb2`](https://github.com/docling-project/docling-serve/commit/766adb248113c7bd5144d14b3c82929a2ad29f8e))
+
 ## [v1.0.0](https://github.com/docling-project/docling-serve/releases/tag/v1.0.0) - 2025-07-14
 
 ### Feature

MAINTAINERS.md

@@ -1,11 +1,11 @@
 # MAINTAINERS
 
-- Christoph Auer - [@cau-git](https://github.com/cau-git)
-- Michele Dolfi - [@dolfim-ibm](https://github.com/dolfim-ibm)
-- Maxim Lysak - [@maxmnemonic](https://github.com/maxmnemonic)
-- Nikos Livathinos - [@nikos-livathinos](https://github.com/nikos-livathinos)
-- Ahmed Nassar - [@nassarofficial](https://github.com/nassarofficial)
-- Panos Vagenas - [@vagenas](https://github.com/vagenas)
-- Peter Staar - [@PeterStaar-IBM](https://github.com/PeterStaar-IBM)
+- Christoph Auer - [`@cau-git`](https://github.com/cau-git)
+- Michele Dolfi - [`@dolfim-ibm`](https://github.com/dolfim-ibm)
+- Maxim Lysak - [`@maxmnemonic`](https://github.com/maxmnemonic)
+- Nikos Livathinos - [`@nikos-livathinos`](https://github.com/nikos-livathinos)
+- Ahmed Nassar - [`@nassarofficial`](https://github.com/nassarofficial)
+- Panos Vagenas - [`@vagenas`](https://github.com/vagenas)
+- Peter Staar - [`@PeterStaar-IBM`](https://github.com/PeterStaar-IBM)
 
 Maintainers can be contacted at [deepsearch-core@zurich.ibm.com](mailto:deepsearch-core@zurich.ibm.com).

README.md

@@ -12,11 +12,11 @@ Running [Docling](https://github.com/docling-project/docling) as an API service.
 
 - Learning how to [configure the webserver](./docs/configuration.md)
 - Get to know all [runtime options](./docs/usage.md) of the API
-- Explore usefule [deployment examples](./docs/deployment.md)
+- Explore useful [deployment examples](./docs/deployment.md)
 - And more
 
- > [!NOTE] Migration to the `v1` API
-> Docling Serve now has a stable v1 API. Read more on the [migration to v1](./docs/v1_migration.md).
+> [!NOTE]
+> **Migration to the `v1` API.** Docling Serve now has a stable v1 API. Read more on the [migration to v1](./docs/v1_migration.md).
 
 ## Getting started
 
@@ -68,9 +68,9 @@ Coming soon: `docling-serve-slim` images will reduce the size by skipping the mo
 
 An easy to use UI is available at the `/ui` endpoint.
 
-![ui-input.png](img/ui-input.png)
+![Input controllers in the UI](img/ui-input.png)
 
-![ui-output.png](img/ui-output.png)
+![Output visualization in the UI](img/ui-output.png)
 
 ## Get help and support
 

docling_serve/app.py

@@ -1,4 +1,5 @@
 import asyncio
+import copy
 import importlib.metadata
 import logging
 import shutil
@@ -24,7 +25,7 @@ from fastapi.openapi.docs import (
     get_swagger_ui_html,
     get_swagger_ui_oauth2_redirect_html,
 )
-from fastapi.responses import RedirectResponse
+from fastapi.responses import JSONResponse, RedirectResponse
 from fastapi.staticfiles import StaticFiles
 from scalar_fastapi import get_scalar_api_reference
 
@@ -34,8 +35,13 @@ from docling_jobkit.datamodel.callback import (
     ProgressCallbackResponse,
 )
 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_targets import InBodyTarget, TaskTarget, ZipTarget
+from docling_jobkit.datamodel.task_targets import (
+    InBodyTarget,
+    TaskTarget,
+    ZipTarget,
+)
 from docling_jobkit.orchestrators.base_orchestrator import (
     BaseOrchestrator,
     ProgressInvalid,
@@ -47,6 +53,7 @@ from docling_serve.datamodel.requests import (
     ConvertDocumentsRequest,
     FileSourceRequest,
     HttpSourceRequest,
+    S3SourceRequest,
     TargetName,
 )
 from docling_serve.datamodel.responses import (
@@ -54,6 +61,7 @@ from docling_serve.datamodel.responses import (
     ConvertDocumentResponse,
     HealthCheckResponse,
     MessageKind,
+    PresignedUrlConvertDocumentResponse,
     TaskStatusResponse,
     WebsocketMessage,
 )
@@ -62,7 +70,7 @@ from docling_serve.orchestrator_factory import get_async_orchestrator
 from docling_serve.response_preparation import prepare_response
 from docling_serve.settings import docling_serve_settings
 from docling_serve.storage import get_scratch
-from docling_serve.websocker_notifier import WebsocketNotifier
+from docling_serve.websocket_notifier import WebsocketNotifier
 
 
 # Set up custom logging as we'll be intermixes with FastAPI/Uvicorn's logging
@@ -246,6 +254,8 @@ def create_app():  # noqa: C901
                 sources.append(FileSource.model_validate(s))
             elif isinstance(s, HttpSourceRequest):
                 sources.append(HttpSource.model_validate(s))
+            elif isinstance(s, S3SourceRequest):
+                sources.append(S3Coordinates.model_validate(s))
 
         task = await orchestrator.enqueue(
             sources=sources,
@@ -286,10 +296,79 @@ def create_app():  # noqa: C901
             if elapsed_time > docling_serve_settings.max_sync_wait:
                 return False
 
+    ##########################################
+    # Downgrade openapi 3.1 to 3.0.x helpers #
+    ##########################################
+
+    def ensure_array_items(schema):
+        """Ensure that array items are defined."""
+        if "type" in schema and schema["type"] == "array":
+            if "items" not in schema or schema["items"] is None:
+                schema["items"] = {"type": "string"}
+            elif isinstance(schema["items"], dict):
+                if "type" not in schema["items"]:
+                    schema["items"]["type"] = "string"
+
+    def handle_discriminators(schema):
+        """Ensure that discriminator properties are included in required."""
+        if "discriminator" in schema and "propertyName" in schema["discriminator"]:
+            prop = schema["discriminator"]["propertyName"]
+            if "properties" in schema and prop in schema["properties"]:
+                if "required" not in schema:
+                    schema["required"] = []
+                if prop not in schema["required"]:
+                    schema["required"].append(prop)
+
+    def handle_properties(schema):
+        """Ensure that property 'kind' is included in required."""
+        if "properties" in schema and "kind" in schema["properties"]:
+            if "required" not in schema:
+                schema["required"] = []
+            if "kind" not in schema["required"]:
+                schema["required"].append("kind")
+
+    # Downgrade openapi 3.1 to 3.0.x
+    def downgrade_openapi31_to_30(spec):
+        def strip_unsupported(obj):
+            if isinstance(obj, dict):
+                obj = {
+                    k: strip_unsupported(v)
+                    for k, v in obj.items()
+                    if k not in ("const", "examples", "prefixItems")
+                }
+
+                handle_discriminators(obj)
+                ensure_array_items(obj)
+
+                # Check for oneOf and anyOf to handle nested schemas
+                for key in ["oneOf", "anyOf"]:
+                    if key in obj:
+                        for sub in obj[key]:
+                            handle_discriminators(sub)
+                            ensure_array_items(sub)
+
+                return obj
+            elif isinstance(obj, list):
+                return [strip_unsupported(i) for i in obj]
+            return obj
+
+        if "components" in spec and "schemas" in spec["components"]:
+            for schema_name, schema in spec["components"]["schemas"].items():
+                handle_properties(schema)
+
+        return strip_unsupported(copy.deepcopy(spec))
+
     #############################
     # API Endpoints definitions #
     #############################
 
+    @app.get("/openapi-3.0.json")
+    def openapi_30():
+        spec = app.openapi()
+        downgraded = downgrade_openapi31_to_30(spec)
+        downgraded["openapi"] = "3.0.3"
+        return JSONResponse(downgraded)
+
     # Favicon
     @app.get("/favicon.ico", include_in_schema=False)
     async def favicon():
@@ -443,7 +522,8 @@ def create_app():  # noqa: C901
         orchestrator: Annotated[BaseOrchestrator, Depends(get_async_orchestrator)],
         task_id: str,
         wait: Annotated[
-            float, Query(help="Number of seconds to wait for a completed status.")
+            float,
+            Query(description="Number of seconds to wait for a completed status."),
         ] = 0.0,
     ):
         try:
@@ -525,7 +605,7 @@ def create_app():  # noqa: C901
     # Task result
     @app.get(
         "/v1/result/{task_id}",
-        response_model=ConvertDocumentResponse,
+        response_model=ConvertDocumentResponse | PresignedUrlConvertDocumentResponse,
         responses={
             200: {
                 "content": {"application/zip": {}},

docling_serve/datamodel/requests.py

@@ -1,12 +1,21 @@
 import enum
 from typing import Annotated, Literal
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, model_validator
+from pydantic_core import PydanticCustomError
+from typing_extensions import Self
 
 from docling_jobkit.datamodel.http_inputs import FileSource, HttpSource
-from docling_jobkit.datamodel.task_targets import InBodyTarget, TaskTarget, ZipTarget
+from docling_jobkit.datamodel.s3_coords import S3Coordinates
+from docling_jobkit.datamodel.task_targets import (
+    InBodyTarget,
+    S3Target,
+    TaskTarget,
+    ZipTarget,
+)
 
 from docling_serve.datamodel.convert import ConvertDocumentsRequestOptions
+from docling_serve.settings import AsyncEngine, docling_serve_settings
 
 ## Sources
 
@@ -19,6 +28,10 @@ class HttpSourceRequest(HttpSource):
     kind: Literal["http"] = "http"
 
 
+class S3SourceRequest(S3Coordinates):
+    kind: Literal["s3"] = "s3"
+
+
 ## Multipart targets
 class TargetName(str, enum.Enum):
     INBODY = InBodyTarget().kind
@@ -27,7 +40,7 @@ class TargetName(str, enum.Enum):
 
 ## Aliases
 SourceRequestItem = Annotated[
-    FileSourceRequest | HttpSourceRequest, Field(discriminator="kind")
+    FileSourceRequest | HttpSourceRequest | S3SourceRequest, Field(discriminator="kind")
 ]
 
 
@@ -36,3 +49,24 @@ class ConvertDocumentsRequest(BaseModel):
     options: ConvertDocumentsRequestOptions = ConvertDocumentsRequestOptions()
     sources: list[SourceRequestItem]
     target: TaskTarget = InBodyTarget()
+
+    @model_validator(mode="after")
+    def validate_s3_source_and_target(self) -> Self:
+        for source in self.sources:
+            if isinstance(source, S3SourceRequest):
+                if docling_serve_settings.eng_kind != AsyncEngine.KFP:
+                    raise PydanticCustomError(
+                        "error source", 'source kind "s3" requires engine kind "KFP"'
+                    )
+                if self.target.kind != "s3":
+                    raise PydanticCustomError(
+                        "error source", 'source kind "s3" requires target kind "s3"'
+                    )
+        if isinstance(self.target, S3Target):
+            for source in self.sources:
+                if isinstance(source, S3SourceRequest):
+                    return self
+            raise PydanticCustomError(
+                "error target", 'target kind "s3" requires source kind "s3"'
+            )
+        return self

docling_serve/datamodel/responses.py

@@ -35,6 +35,11 @@ class ConvertDocumentResponse(BaseModel):
     timings: dict[str, ProfilingItem] = {}
 
 
+class PresignedUrlConvertDocumentResponse(BaseModel):
+    status: ConversionStatus
+    processing_time: float
+
+
 class ConvertDocumentErrorResponse(BaseModel):
     status: ConversionStatus
 

docling_serve/response_preparation.py

@@ -7,6 +7,7 @@ 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
 
@@ -15,12 +16,16 @@ 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, TaskTarget
+from docling_jobkit.datamodel.task_targets import InBodyTarget, PutTarget, TaskTarget
 from docling_jobkit.orchestrators.base_orchestrator import (
     BaseOrchestrator,
 )
 
-from docling_serve.datamodel.responses import ConvertDocumentResponse, DocumentResponse
+from docling_serve.datamodel.responses import (
+    ConvertDocumentResponse,
+    DocumentResponse,
+    PresignedUrlConvertDocumentResponse,
+)
 from docling_serve.settings import docling_serve_settings
 from docling_serve.storage import get_scratch
 
@@ -40,7 +45,9 @@ def _export_document_as_content(
     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)
+        new_doc = conv_res.document._make_copy_with_refmode(
+            Path(), image_mode, page_no=None
+        )
 
         # Create the different formats
         if export_json:
@@ -77,11 +84,17 @@ def _export_documents_as_files(
     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
@@ -91,7 +104,9 @@ def _export_documents_as_files(
                 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
+                    filename=fname,
+                    image_mode=image_export_mode,
+                    artifacts_dir=artifacts_dir,
                 )
 
             # Export HTML format:
@@ -99,7 +114,9 @@ def _export_documents_as_files(
                 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
+                    filename=fname,
+                    image_mode=image_export_mode,
+                    artifacts_dir=artifacts_dir,
                 )
 
             # Export Text format:
@@ -118,6 +135,7 @@ def _export_documents_as_files(
                 _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,
                 )
@@ -136,6 +154,7 @@ def _export_documents_as_files(
         f"Processed {success_count + failure_count} docs, "
         f"of which {failure_count} failed"
     )
+    return conv_result
 
 
 def process_results(
@@ -143,7 +162,7 @@ def process_results(
     target: TaskTarget,
     conv_results: Iterable[ConversionResult],
     work_dir: Path,
-) -> Union[ConvertDocumentResponse, FileResponse]:
+) -> Union[ConvertDocumentResponse, FileResponse, PresignedUrlConvertDocumentResponse]:
     # Let's start by processing the documents
     try:
         start_time = time.monotonic()
@@ -167,7 +186,9 @@ def process_results(
         )
 
     # We have some results, let's prepare the response
-    response: Union[FileResponse, ConvertDocumentResponse]
+    response: Union[
+        FileResponse, ConvertDocumentResponse, PresignedUrlConvertDocumentResponse
+    ]
 
     # Booleans to know what to export
     export_json = OutputFormat.JSON in conversion_options.to_formats
@@ -207,7 +228,7 @@ def process_results(
         os.getpid()
 
         # Export the documents
-        _export_documents_as_files(
+        conv_result = _export_documents_as_files(
             conv_results=conv_results,
             output_dir=output_dir,
             export_json=export_json,
@@ -234,9 +255,24 @@ def process_results(
         # Output directory
         # background_tasks.add_task(shutil.rmtree, work_dir, ignore_errors=True)
 
-        response = FileResponse(
-            file_path, filename=file_path.name, media_type="application/zip"
-        )
+        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
 

docs/configuration.md

@@ -7,7 +7,7 @@ server and the actual app-specific configurations.
 
  > [!WARNING]
 > When the server is running with `reload` or with multiple `workers`, uvicorn
-> will spawn multiple subprocessed. This invalidates all the values configured
+> will spawn multiple subprocesses. This invalidates all the values configured
 > via the CLI command line options. Please use environment variables in this
 > type of deployments.
 
@@ -36,7 +36,7 @@ THe following table describes the options to configure the Docling Serve app.
 | CLI option | ENV | Default | Description |
 | -----------|-----|---------|-------------|
 | `--artifacts-path` | `DOCLING_SERVE_ARTIFACTS_PATH` | unset | If set to a valid directory, the model weights will be loaded from this path |
-|  | `DOCLING_SERVE_STATIC_PATH` | unset | If set to a valid directory, the static assets for the docs and ui will be loaded from this path |
+|  | `DOCLING_SERVE_STATIC_PATH` | unset | If set to a valid directory, the static assets for the docs and UI will be loaded from this path |
 |  | `DOCLING_SERVE_SCRATCH_PATH` |  | If set, this directory will be used as scratch workspace, e.g. storing the results before they get requested. If unset, a temporary created is created for this purpose. |
 | `--enable-ui` | `DOCLING_SERVE_ENABLE_UI` | `false` | Enable the demonstrator UI. |
 |  | `DOCLING_SERVE_ENABLE_REMOTE_SERVICES` | `false` | Allow pipeline components making remote connections. For example, this is needed when using a vision-language model via APIs. |

docs/pre-loading-models.md

@@ -74,7 +74,7 @@ This document provides examples for pre-loading docling models to a persistent v
     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 deploymeny should be made:
+    Following additions to deployment should be made:
 
     ```yaml
     spec:
@@ -98,6 +98,6 @@ This document provides examples for pre-loading docling models to a persistent v
 
     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 mouted volume.
+    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)

docs/usage.md

@@ -9,7 +9,7 @@ On top of the source of file (see below), both endpoints support the same parame
 - `from_formats` (List[str]): Input format(s) to convert from. Allowed values: `docx`, `pptx`, `html`, `image`, `pdf`, `asciidoc`, `md`. Defaults to all formats.
 - `to_formats` (List[str]): Output format(s) to convert to. Allowed values: `md`, `json`, `html`, `text`, `doctags`. Defaults to `md`.
 - `pipeline` (str). The choice of which pipeline to use. Allowed values are `standard` and `vlm`. Defaults to `standard`.
-- `page_range` (tuple). If speficied, only convert a range of pages. The page number starts at 1.
+- `page_range` (tuple). If specified, only convert a range of pages. The page number starts at 1.
 - `do_ocr` (bool): If enabled, the bitmap content will be processed using OCR. Defaults to `True`.
 - `image_export_mode`: Image export mode for the document (only in case of JSON, Markdown or HTML). Allowed values: embedded, placeholder, referenced. Optional, defaults to `embedded`.
 - `force_ocr` (bool): If enabled, replace any existing text with OCR-generated text over the full content. Defaults to `False`.
@@ -25,8 +25,8 @@ On top of the source of file (see below), both endpoints support the same parame
 - `do_picture_classification` (bool): If enabled, classify pictures in documents. Defaults to false.
 - `do_picture_description` (bool): If enabled, describe pictures in documents. Defaults to false.
 - `picture_description_area_threshold` (float): Minimum percentage of the area for a picture to be processed with the models. Defaults to 0.05.
-- `picture_description_local` (dict): Options for running a local vision-language model in the picture description. The parameters refer to a model hosted on Hugging Face. This parameter is mutually exclusive with picture_description_api.
-- `picture_description_api` (dict): API details for using a vision-language model in the picture description. This parameter is mutually exclusive with picture_description_local.
+- `picture_description_local` (dict): Options for running a local vision-language model in the picture description. The parameters refer to a model hosted on Hugging Face. This parameter is mutually exclusive with `picture_description_api`.
+- `picture_description_api` (dict): API details for using a vision-language model in the picture description. This parameter is mutually exclusive with `picture_description_local`.
 - `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.
 
@@ -307,7 +307,7 @@ Example URLs are:
     }
     ```
 
-- `http://localhost:11434/v1/chat/completions` for the local ollama api, with example `picture_description_api`:
+- `http://localhost:11434/v1/chat/completions` for the local Ollama api, with example `picture_description_api`:
   - the `granite3.2-vision:2b` model
 
     ```json
@@ -355,7 +355,7 @@ The response can be a JSON Document or a File.
 
 Both `/v1/convert/source` and `/v1/convert/file` endpoints are available as asynchronous variants.
 The advantage of the asynchronous endpoints is the possible to interrupt the connection, check for the progress update and fetch the result.
-This approach is more resilient against network stabilities and allows the client application logic to easily interleave conversion with other tasks.
+This approach is more resilient against network instabilities and allows the client application logic to easily interleave conversion with other tasks.
 
 Launch an asynchronous conversion with:
 
@@ -402,7 +402,7 @@ while task["task_status"] not in ("success", "failure"):
 ### Subscribe with websockets
 
 Using websocket you can get the client application being notified about updates of the conversion task.
-To start the websocker connection, use the endpoint:
+To start the websocket connection, use the endpoint:
 
 - `/v1/status/ws/{task_id}`
 
@@ -417,7 +417,7 @@ Websocket messages are JSON object with the following structure:
 ```
 
 <details>
-<summary>Example websocker usage:</summary>
+<summary>Example websocket usage:</summary>
 
 ```python
 from websockets.sync.client import connect

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "docling-serve"
-version = "1.0.0"  # DO NOT EDIT, updated automatically
+version = "1.1.0"  # DO NOT EDIT, updated automatically
 description = "Running Docling as a service"
 license = {text = "MIT"}
 authors = [
@@ -35,8 +35,8 @@ classifiers = [
 requires-python = ">=3.10"
 dependencies = [
     "docling~=2.38",
-    "docling-core>=2.32.0",
-    "docling-jobkit[kfp,vlm]~=1.1",
+    "docling-core>=2.44.1",
+    "docling-jobkit[kfp,vlm]~=1.2",
     "fastapi[standard]~=0.115",
     "httpx~=0.28",
     "pydantic~=2.10",
@@ -46,6 +46,7 @@ dependencies = [
     "uvicorn[standard]>=0.29.0,<1.0.0",
     "websockets~=14.0",
     "scalar-fastapi>=1.0.3",
+    "docling-mcp>=1.0.0",
 ]
 
 [project.optional-dependencies]
@@ -128,7 +129,7 @@ torchvision = [
   { index = "pytorch-cu126", group = "cu126" },
   { index = "pytorch-cu128", group = "cu128" },
 ]
-# docling-jobkit = { git = "https://github.com/docling-project/docling-jobkit/", rev = "refactor" }
+# docling-jobkit = { git = "https://github.com/docling-project/docling-jobkit/", rev = "main" }
 # docling-jobkit = { path = "../docling-jobkit", editable = true }
 
 [[tool.uv.index]]

tests/test_fastapi_endpoints.py

@@ -1,6 +1,8 @@
 import asyncio
+import io
 import json
 import os
+import zipfile
 
 import pytest
 import pytest_asyncio
@@ -8,6 +10,8 @@ from asgi_lifespan import LifespanManager
 from httpx import ASGITransport, AsyncClient
 from pytest_check import check
 
+from docling_core.types.doc import DoclingDocument, PictureItem
+
 from docling_serve.app import create_app
 
 
@@ -153,3 +157,37 @@ async def test_convert_file(client: AsyncClient):
             data["document"]["doctags_content"],
             msg=f"DocTags document should contain '<doctag><page_header>'. Received: {safe_slice(data['document']['doctags_content'])}",
         )
+
+
+@pytest.mark.asyncio
+async def test_referenced_artifacts(client: AsyncClient):
+    """Test that paths in the zip file are relative to the zip file root."""
+
+    endpoint = "/v1/convert/file"
+    options = {
+        "to_formats": ["json"],
+        "image_export_mode": "referenced",
+        "target_type": "zip",
+        "ocr": False,
+    }
+
+    current_dir = os.path.dirname(__file__)
+    file_path = os.path.join(current_dir, "2206.01062v1.pdf")
+
+    files = {
+        "files": ("2206.01062v1.pdf", open(file_path, "rb"), "application/pdf"),
+    }
+
+    response = await client.post(endpoint, files=files, data=options)
+    assert response.status_code == 200, "Response should be 200 OK"
+
+    with zipfile.ZipFile(io.BytesIO(response.content)) as zip_file:
+        namelist = zip_file.namelist()
+        for file in namelist:
+            if file.endswith(".json"):
+                doc = DoclingDocument.model_validate(json.loads(zip_file.read(file)))
+                for item, _level in doc.iterate_items():
+                    if isinstance(item, PictureItem):
+                        assert item.image is not None
+                        print(f"{item.image.uri}=")
+                        assert str(item.image.uri) in namelist