chore: bump version to 0.11.0 [skip ci]

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

CHANGELOG.md

@@ -1,3 +1,22 @@
+## [v0.11.0](https://github.com/docling-project/docling-serve/releases/tag/v0.11.0) - 2025-05-23
+
+### Feature
+
+* Page break placeholder in markdown exports options ([#194](https://github.com/docling-project/docling-serve/issues/194)) ([`32b8a80`](https://github.com/docling-project/docling-serve/commit/32b8a809f348bf9fbde657f93589a56935d3749d))
+* Clear results registry ([#192](https://github.com/docling-project/docling-serve/issues/192)) ([`de002df`](https://github.com/docling-project/docling-serve/commit/de002dfcdc111c942a08b156c84b7fa22b3fbaf3))
+* Upgrade to Docling 2.33.0 ([#198](https://github.com/docling-project/docling-serve/issues/198)) ([`abe5aa0`](https://github.com/docling-project/docling-serve/commit/abe5aa03f54d44ecf5c6d76e3258028997a53e68))
+* Api to trigger offloading the models ([#188](https://github.com/docling-project/docling-serve/issues/188)) ([`00be428`](https://github.com/docling-project/docling-serve/commit/00be4284904d55b78c75c5475578ef11c2ade94c))
+* Figure annotations @ docling components 0.0.7 ([#181](https://github.com/docling-project/docling-serve/issues/181)) ([`3ff1b2f`](https://github.com/docling-project/docling-serve/commit/3ff1b2f9834aca37472a895a0e3da47560457d77))
+
+### Fix
+
+* Usage of hashlib for FIPS ([#171](https://github.com/docling-project/docling-serve/issues/171)) ([`8406fb9`](https://github.com/docling-project/docling-serve/commit/8406fb9b59d83247b8379974cabed497703dfc4d))
+
+### Documentation
+
+* Example and instructions on how to load model weights to persistent volume ([#197](https://github.com/docling-project/docling-serve/issues/197)) ([`3f090b7`](https://github.com/docling-project/docling-serve/commit/3f090b7d15eaf696611d89bbbba5b98569610828))
+* Async api usage and fixes ([#195](https://github.com/docling-project/docling-serve/issues/195)) ([`21c1791`](https://github.com/docling-project/docling-serve/commit/21c1791e427f5b1946ed46c68dfda03c957dca8f))
+
 ## [v0.10.1](https://github.com/docling-project/docling-serve/releases/tag/v0.10.1) - 2025-04-30
 
 ### Fix

README.md

@@ -70,7 +70,7 @@ An easy to use UI is available at the `/ui` endpoint.
 
 ## Documentation and advance usages
 
-Visit the [Docling Serve documentation](./docs/README.md) for learning how to [configure the webserver](./docs/configuration.md), use all the [runtime options](./docs/usage.md) of the API and [deployment examples](./docs/deployment.md).
+Visit the [Docling Serve documentation](./docs/README.md) for learning how to [configure the webserver](./docs/configuration.md), use all the [runtime options](./docs/usage.md) of the API and [deployment examples](./docs/deployment.md), pre-load model weights into a persistent volume [model weights on persistent volume](./docs/pre-loading-models.md)
 
 ## Get help and support
 

docling_serve/app.py

@@ -39,6 +39,7 @@ from docling_serve.datamodel.requests import (
     ConvertDocumentsRequest,
 )
 from docling_serve.datamodel.responses import (
+    ClearResponse,
     ConvertDocumentResponse,
     HealthCheckResponse,
     MessageKind,
@@ -46,6 +47,7 @@ from docling_serve.datamodel.responses import (
     WebsocketMessage,
 )
 from docling_serve.datamodel.task import Task, TaskSource
+from docling_serve.docling_conversion import _get_converter_from_hash
 from docling_serve.engines.async_orchestrator import (
     BaseAsyncOrchestrator,
     ProgressInvalid,
@@ -544,4 +546,27 @@ def create_app():  # noqa: C901
                 status_code=400, detail=f"Invalid progress payload: {err}"
             )
 
+    #### Clear requests
+
+    # Offload models
+    @app.get(
+        "/v1alpha/clear/converters",
+        response_model=ClearResponse,
+    )
+    async def clear_converters():
+        _get_converter_from_hash.cache_clear()
+        return ClearResponse()
+
+    # Clean results
+    @app.get(
+        "/v1alpha/clear/results",
+        response_model=ClearResponse,
+    )
+    async def clear_results(
+        orchestrator: Annotated[BaseAsyncOrchestrator, Depends(get_async_orchestrator)],
+        older_then: float = 3600,
+    ):
+        await orchestrator.clear_results(older_than=older_then)
+        return ClearResponse()
+
     return app

docling_serve/datamodel/convert.py

@@ -296,6 +296,14 @@ class ConvertDocumentsOptions(BaseModel):
         ),
     ] = 2.0
 
+    md_page_break_placeholder: Annotated[
+        str,
+        Field(
+            description="Add this placeholder betweek pages in the markdown output.",
+            examples=["<!-- page-break -->", ""],
+        ),
+    ] = ""
+
     do_code_enrichment: Annotated[
         bool,
         Field(

docling_serve/datamodel/responses.py

@@ -15,6 +15,10 @@ class HealthCheckResponse(BaseModel):
     status: str = "ok"
 
 
+class ClearResponse(BaseModel):
+    status: str = "ok"
+
+
 class DocumentResponse(BaseModel):
     filename: str
     md_content: Optional[str] = None

docling_serve/datamodel/task.py

@@ -1,8 +1,10 @@
+import datetime
+from functools import partial
 from pathlib import Path
 from typing import Optional, Union
 
 from fastapi.responses import FileResponse
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel, ConfigDict, Field
 
 from docling.datamodel.base_models import DocumentStream
 
@@ -25,6 +27,27 @@ class Task(BaseModel):
     result: Optional[Union[ConvertDocumentResponse, FileResponse]] = None
     scratch_dir: Optional[Path] = None
     processing_meta: Optional[TaskProcessingMeta] = None
+    created_at: datetime.datetime = Field(
+        default_factory=partial(datetime.datetime.now, datetime.timezone.utc)
+    )
+    started_at: Optional[datetime.datetime] = None
+    finished_at: Optional[datetime.datetime] = None
+    last_update_at: datetime.datetime = Field(
+        default_factory=partial(datetime.datetime.now, datetime.timezone.utc)
+    )
+
+    def set_status(self, status: TaskStatus):
+        now = datetime.datetime.now(datetime.timezone.utc)
+        if status == TaskStatus.STARTED and self.started_at is None:
+            self.started_at = now
+        if (
+            status in [TaskStatus.SUCCESS, TaskStatus.FAILURE]
+            and self.finished_at is None
+        ):
+            self.finished_at = now
+
+        self.last_update_at = now
+        self.task_status = status
 
     def is_completed(self) -> bool:
         if self.task_status in [TaskStatus.SUCCESS, TaskStatus.FAILURE]:

docling_serve/docling_conversion.py

@@ -58,7 +58,9 @@ def _hash_pdf_format_option(pdf_format_option: PdfFormatOption) -> bytes:
 
     # Serialize the dictionary to JSON with sorted keys to have consistent hashes
     serialized_data = json.dumps(data, sort_keys=True)
-    options_hash = hashlib.sha1(serialized_data.encode()).digest()
+    options_hash = hashlib.sha1(
+        serialized_data.encode(), usedforsecurity=False
+    ).digest()
     return options_hash
 
 

docling_serve/engines/async_kfp/orchestrator.py

@@ -130,13 +130,13 @@ class AsyncKfpOrchestrator(BaseAsyncOrchestrator):
         # CANCELED = "CANCELED"
         # PAUSED = "PAUSED"
         if run_info.state == V2beta1RuntimeState.SUCCEEDED:
-            task.task_status = TaskStatus.SUCCESS
+            task.set_status(TaskStatus.SUCCESS)
         elif run_info.state == V2beta1RuntimeState.PENDING:
-            task.task_status = TaskStatus.PENDING
+            task.set_status(TaskStatus.PENDING)
         elif run_info.state == V2beta1RuntimeState.RUNNING:
-            task.task_status = TaskStatus.STARTED
+            task.set_status(TaskStatus.STARTED)
         else:
-            task.task_status = TaskStatus.FAILURE
+            task.set_status(TaskStatus.FAILURE)
 
     async def task_status(self, task_id: str, wait: float = 0.0) -> Task:
         await self._update_task_from_run(task_id=task_id, wait=wait)

docling_serve/engines/async_local/worker.py

@@ -36,7 +36,7 @@ class AsyncLocalWorker:
             task = self.orchestrator.tasks[task_id]
 
             try:
-                task.task_status = TaskStatus.STARTED
+                task.set_status(TaskStatus.STARTED)
                 _log.info(f"Worker {self.worker_id} processing task {task_id}")
 
                 # Notify clients about task updates
@@ -106,7 +106,7 @@ class AsyncLocalWorker:
                 task.sources = []
                 task.options = None
 
-                task.task_status = TaskStatus.SUCCESS
+                task.set_status(TaskStatus.SUCCESS)
                 _log.info(
                     f"Worker {self.worker_id} completed job {task_id} "
                     f"in {processing_time:.2f} seconds"
@@ -116,7 +116,7 @@ class AsyncLocalWorker:
                 _log.error(
                     f"Worker {self.worker_id} failed to process job {task_id}: {e}"
                 )
-                task.task_status = TaskStatus.FAILURE
+                task.set_status(TaskStatus.FAILURE)
 
             finally:
                 await self.orchestrator.notify_task_subscribers(task_id)

docling_serve/engines/async_orchestrator.py

@@ -1,3 +1,6 @@
+import asyncio
+import datetime
+import logging
 import shutil
 from typing import Union
 
@@ -20,6 +23,8 @@ from docling_serve.engines.base_orchestrator import (
 )
 from docling_serve.settings import docling_serve_settings
 
+_log = logging.getLogger(__name__)
+
 
 class ProgressInvalid(OrchestratorError):
     pass
@@ -46,13 +51,50 @@ class BaseAsyncOrchestrator(BaseOrchestrator):
     async def task_result(
         self, task_id: str, background_tasks: BackgroundTasks
     ) -> Union[ConvertDocumentResponse, FileResponse, None]:
-        task = await self.get_raw_task(task_id=task_id)
-        if task.is_completed() and task.scratch_dir is not None:
-            if docling_serve_settings.single_use_results:
-                background_tasks.add_task(
-                    shutil.rmtree, task.scratch_dir, ignore_errors=True
-                )
-        return task.result
+        try:
+            task = await self.get_raw_task(task_id=task_id)
+            if task.is_completed() and 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 self.delete_task(task_id=task.task_id)
+
+                async def _remove_task():
+                    asyncio.create_task(_remove_task_impl())  # noqa: RUF006
+
+                background_tasks.add_task(_remove_task)
+
+            return task.result
+        except TaskNotFoundError:
+            return None
+
+    async def delete_task(self, task_id: str):
+        _log.info(f"Deleting {task_id=}")
+        if task_id in self.task_subscribers:
+            for websocket in self.task_subscribers[task_id]:
+                await websocket.close()
+
+            del self.task_subscribers[task_id]
+
+        if task_id in self.tasks:
+            del self.tasks[task_id]
+
+    async def clear_results(self, older_than: float = 0.0):
+        cutoff_time = datetime.datetime.now(datetime.timezone.utc) - datetime.timedelta(
+            seconds=older_than
+        )
+
+        tasks_to_delete = [
+            task_id
+            for task_id, task in self.tasks.items()
+            if task.finished_at is not None and task.finished_at < cutoff_time
+        ]
+        for task_id in tasks_to_delete:
+            await self.delete_task(task_id=task_id)
 
     async def notify_task_subscribers(self, task_id: str):
         if task_id not in self.task_subscribers:

docling_serve/engines/base_orchestrator.py

@@ -42,6 +42,10 @@ class BaseOrchestrator(ABC):
     ) -> Union[ConvertDocumentResponse, FileResponse, None]:
         pass
 
+    @abstractmethod
+    async def clear_results(self, older_than: float = 0.0):
+        pass
+
     @abstractmethod
     async def process_queue(self):
         pass

docling_serve/gradio_ui.py

@@ -29,7 +29,7 @@ logger = logging.getLogger(__name__)
 ############################
 
 logo_path = "https://raw.githubusercontent.com/docling-project/docling/refs/heads/main/docs/assets/logo.svg"
-js_components_url = "https://unpkg.com/@docling/docling-components@0.0.6"
+js_components_url = "https://unpkg.com/@docling/docling-components@0.0.7"
 if (
     docling_serve_settings.static_path is not None
     and docling_serve_settings.static_path.is_dir()
@@ -83,7 +83,7 @@ css = """
     height: 140px;
 }
 
-docling-img::part(pages) {
+docling-img {
     gap: 1rem;
 }
 
@@ -443,7 +443,7 @@ def response_to_output(response, return_as_file):
         )
         # Embed document JSON and trigger load at client via an image.
         json_rendered_content = f"""
-            <docling-img id="dclimg" pagenumbers tooltip="parsed"></docling-img>
+            <docling-img id="dclimg" pagenumbers><docling-tooltip></docling-tooltip></docling-img>
             <script id="dcljson" type="application/json" onload="document.getElementById('dclimg').src = JSON.parse(document.getElementById('dcljson').textContent);">{json_content}</script>
             <img src onerror="document.getElementById('dclimg').src = JSON.parse(document.getElementById('dcljson').textContent);" />
             """

docling_serve/response_preparation.py

@@ -27,6 +27,7 @@ def _export_document_as_content(
     export_txt: bool,
     export_doctags: bool,
     image_mode: ImageRefMode,
+    md_page_break_placeholder: str,
 ):
     document = DocumentResponse(filename=conv_res.input.file.name)
 
@@ -40,10 +41,14 @@ def _export_document_as_content(
             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
+                strict_text=True,
+                image_mode=image_mode,
             )
         if export_md:
-            document.md_content = new_doc.export_to_markdown(image_mode=image_mode)
+            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:
@@ -63,6 +68,7 @@ def _export_documents_as_files(
     export_txt: bool,
     export_doctags: bool,
     image_export_mode: ImageRefMode,
+    md_page_break_placeholder: str,
 ):
     success_count = 0
     failure_count = 0
@@ -103,7 +109,9 @@ def _export_documents_as_files(
                 fname = output_dir / f"{doc_filename}.md"
                 _log.info(f"writing Markdown output to {fname}")
                 conv_res.document.save_as_markdown(
-                    filename=fname, image_mode=image_export_mode
+                    filename=fname,
+                    image_mode=image_export_mode,
+                    page_break_placeholder=md_page_break_placeholder or None,
                 )
 
             # Export Document Tags format:
@@ -170,6 +178,7 @@ def process_results(
             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(
@@ -198,6 +207,7 @@ def process_results(
             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)

docling_serve/settings.py

@@ -40,6 +40,7 @@ class DoclingServeSettings(BaseSettings):
     static_path: Optional[Path] = None
     scratch_path: Optional[Path] = None
     single_use_results: bool = True
+    result_removal_delay: float = 300  # 5 minutes
     options_cache_size: int = 2
     enable_remote_services: bool = False
     allow_external_plugins: bool = False

docs/configuration.md

@@ -42,6 +42,7 @@ THe following table describes the options to configure the Docling Serve app.
 |  | `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. |
 |  | `DOCLING_SERVE_ALLOW_EXTERNAL_PLUGINS` | `false` | Allow the selection of third-party plugins. |
 |  | `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_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. |

docs/deploy-examples/docling-model-cache-deployment.yaml

@@ -0,0 +1,47 @@
+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: 500m
+              memory: 2Gi
+            requests:
+              cpu: 250m
+              memory: 1Gi
+          env:
+            - name: DOCLING_SERVE_ENABLE_UI
+              value: 'true'
+            - name: DOCLING_SERVE_ARTIFACTS_PATH
+              value: '/modelcache'
+          ports:
+            - name: http
+              containerPort: 5001
+              protocol: TCP
+          imagePullPolicy: Always
+          image: 'ghcr.io/docling-project/docling-serve-cpu'
+          volumeMounts:
+            - name: docling-model-cache
+              mountPath: /modelcache
+      volumes:
+        - name: docling-model-cache
+          persistentVolumeClaim:
+            claimName: docling-model-cache-pvc

docs/deploy-examples/docling-model-cache-job.yaml

@@ -0,0 +1,33 @@
+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

docs/deploy-examples/docling-model-cache-pvc.yaml

@@ -0,0 +1,11 @@
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: docling-model-cache-pvc
+spec:
+  accessModes:
+    - ReadWriteOnce
+  volumeMode: Filesystem
+  resources:
+    requests:
+      storage: 10Gi

docs/pre-loading-models.md

@@ -0,0 +1,103 @@
+# 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 deploymeny 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 mouted volume.
+
+    Manifest example: [docling-model-cache-deployment.yaml](./deploy-examples/docling-model-cache-deployment.yaml)

docs/usage.md

@@ -9,6 +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.
 - `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`.
@@ -18,6 +19,7 @@ On top of the source of file (see below), both endpoints support the same parame
 - `table_mode` (str): Table mode to use. Allowed values: `fast`, `accurate`. Defaults to `fast`.
 - `abort_on_error` (bool): If enabled, abort on error. Defaults to false.
 - `return_as_file` (boo): If enabled, return the output as a file. Defaults to false.
+- `md_page_break_placeholder` (str): Add this placeholder betweek pages in the markdown output.
 - `do_table_structure` (bool): If enabled, the table structure will be extracted. Defaults to true.
 - `do_code_enrichment` (bool): If enabled, perform OCR code enrichment. Defaults to false.
 - `do_formula_enrichment` (bool): If enabled, perform formula OCR, return LaTeX code. Defaults to false.
@@ -244,7 +246,7 @@ files = {
     'files': ('2206.01062v1.pdf', open(file_path, 'rb'), 'application/pdf'),
 }
 
-response = await async_client.post(url, files=files, data={"parameters": json.dumps(parameters)})
+response = await async_client.post(url, files=files, data=parameters)
 assert response.status_code == 200, "Response should be 200 OK"
 
 data = response.json()
@@ -348,4 +350,92 @@ The response can be a JSON Document or a File.
 
 ## Asynchronous API
 
-TBA
+Both `/v1alpha/convert/source` and `/v1alpha/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.
+
+Launch an asynchronous conversion with:
+
+- `POST /v1alpha/convert/source/async` when providing the input as sources.
+- `POST /v1alpha/convert/file/async` when providing the input as multipart-form files.
+
+The response format is a task detail:
+
+```jsonc
+{
+  "task_id": "<task_id>",  // the task_id which can be used for the next operations
+  "task_status": "pending|started|success|failure",  // the task status
+  "task_position": 1,  // the position in the queue
+  "task_meta": null,  // metadata e.g. how many documents are in the total job and how many have been converted
+}
+```
+
+### Polling status
+
+For checking the progress of the conversion task and wait for its completion, use the endpoint:
+
+- `GET /v1alpha/status/poll/{task_id}`
+
+<details>
+<summary>Example waiting loop:</summary>
+
+```python
+import time
+import httpx
+
+# ...
+# response from the async task submission
+task = response.json()
+
+while task["task_status"] not in ("success", "failure"):
+    response = httpx.get(f"{base_url}/status/poll/{task['task_id']}")
+    task = response.json()
+
+    time.sleep(5)
+```
+
+<details>
+
+### 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:
+
+- `/v1alpha/status/ws/{task_id}`
+
+Websocket messages are JSON object with the following structure:
+
+```jsonc
+{
+  "message": "connection|update|error",  // type of message being sent
+  "task": {},  // the same content of the task description
+  "error": "",  // description of the error
+}
+```
+
+<details>
+<summary>Example websocker usage:</summary>
+
+```python
+from websockets.sync.client import connect
+
+uri = f"ws://{base_url}/v1alpha/status/ws/{task['task_id']}"
+with connect(uri) as websocket:
+    for message in websocket:
+        try:
+            payload = json.loads(message)
+            if payload["message"] == "error":
+                break
+            if payload["message"] == "error" and payload["task"]["task_status"] in ("success", "failure"):
+                break
+        except:
+          break
+```
+
+</details>
+
+### Fetch results
+
+When the task is completed, the result can be fetched with the endpoint:
+
+- `GET /v1alpha/result/{task_id}`

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "docling-serve"
-version = "0.10.1"  # DO NOT EDIT, updated automatically
+version = "0.11.0"  # DO NOT EDIT, updated automatically
 description = "Running Docling as a service"
 license = {text = "MIT"}
 authors = [

tests/test_1-file-async.py

@@ -51,10 +51,12 @@ async def test_convert_url(async_client):
         time.sleep(2)
 
     assert task["task_status"] == "success"
+    print(f"Task completed with status {task['task_status']=}")
 
     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 "md_content" in result["document"]
     assert result["document"]["md_content"] is not None

tests/test_results_clear.py

@@ -0,0 +1,127 @@
+import asyncio
+import base64
+import json
+from pathlib import Path
+
+import pytest
+import pytest_asyncio
+from asgi_lifespan import LifespanManager
+from httpx import ASGITransport, AsyncClient
+
+from docling_serve.app import create_app
+from docling_serve.settings import docling_serve_settings
+
+
+@pytest.fixture(scope="session")
+def event_loop():
+    return asyncio.get_event_loop()
+
+
+@pytest_asyncio.fixture(scope="session")
+async def app():
+    app = create_app()
+
+    async with LifespanManager(app) as manager:
+        print("Launching lifespan of app.")
+        yield manager.app
+
+
+@pytest_asyncio.fixture(scope="session")
+async def client(app):
+    async with AsyncClient(
+        transport=ASGITransport(app=app), base_url="http://app.io"
+    ) as client:
+        print("Client is ready")
+        yield client
+
+
+async def convert_file(client: AsyncClient):
+    doc_filename = Path("tests/2408.09869v5.pdf")
+    encoded_doc = base64.b64encode(doc_filename.read_bytes()).decode()
+
+    payload = {
+        "options": {
+            "to_formats": ["json"],
+        },
+        "file_sources": [{"base64_string": encoded_doc, "filename": doc_filename.name}],
+    }
+
+    response = await client.post("/v1alpha/convert/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 client.get(f"/v1alpha/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']=}")
+
+        await asyncio.sleep(2)
+
+    assert task["task_status"] == "success"
+
+    return task
+
+
+@pytest.mark.asyncio
+async def test_clear_results(client: AsyncClient):
+    """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)
+
+    # Get result once
+    result_response = await client.get(f"/v1alpha/result/{task['task_id']}")
+    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"/v1alpha/result/{task['task_id']}")
+    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("/v1alpha/clear/results?older_then=0")
+    assert clear_response.status_code == 200, "Response should be 200 OK"
+    print("Clear ok.")
+
+    # Get deleted result
+    result_response = await client.get(f"/v1alpha/result/{task['task_id']}")
+    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):
+    """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)
+
+    # Get result once
+    result_response = await client.get(f"/v1alpha/result/{task['task_id']}")
+    assert result_response.status_code == 200, "Response should be 200 OK"
+    print("Result ok.")
+    result = result_response.json()
+    assert result["document"]["json_content"]["schema_name"] == "DoclingDocument"
+
+    print("Sleeping to wait the automatic task deletion.")
+    await asyncio.sleep(10)
+
+    # Get deleted result
+    result_response = await client.get(f"/v1alpha/result/{task['task_id']}")
+    assert result_response.status_code == 404, "Response should be removed"