✨ add support for workflow polling

mindee/client.py

@@ -7,6 +7,7 @@
 from mindee.input import WorkflowOptions
 from mindee.input.local_response import LocalResponse
 from mindee.input.page_options import PageOptions
+from mindee.input.predict_options import AsyncPredictOptions, PredictOptions
 from mindee.input.sources.base_64_input import Base64Input
 from mindee.input.sources.bytes_input import BytesInput
 from mindee.input.sources.file_input import FileInput
@@ -123,14 +124,13 @@ def parse(
                     page_options.on_min_pages,
                     page_options.page_indexes,
                 )
+        options = PredictOptions(cropper, full_text, include_words)
         return self._make_request(
             product_class,
             input_source,
             endpoint,
-            include_words,
+            options,
             close_file,
-            cropper,
-            full_text,
         )
 
     def enqueue(
@@ -143,6 +143,8 @@ def enqueue(
         cropper: bool = False,
         endpoint: Optional[Endpoint] = None,
         full_text: bool = False,
+        workflow_id: Optional[str] = None,
+        rag: bool = False,
     ) -> AsyncPredictResponse:
         """
         Enqueues a document to an asynchronous endpoint.
@@ -169,6 +171,11 @@ def enqueue(
         :param endpoint: For custom endpoints, an endpoint has to be given.
 
         :param full_text: Whether to include the full OCR text response in compatible APIs.
+
+        :param workflow_id: Workflow ID.
+
+        :param rag: If set, will enable Retrieval-Augmented Generation.
+            Only works if a valid ``workflow_id`` is set.
         """
         if input_source is None:
             raise MindeeClientError("No input document provided.")
@@ -185,14 +192,15 @@ def enqueue(
                     page_options.on_min_pages,
                     page_options.page_indexes,
                 )
+        options = AsyncPredictOptions(
+            cropper, full_text, include_words, workflow_id, rag
+        )
         return self._predict_async(
             product_class,
             input_source,
+            options,
             endpoint,
-            include_words,
             close_file,
-            cropper,
-            full_text,
         )
 
     def load_prediction(
@@ -246,8 +254,9 @@ def execute_workflow(
         :param input_source: The document/source file to use.
             Has to be created beforehand.
         :param workflow_id: ID of the workflow.
-        :param page_options: If set, remove pages from the document as specified. This is done before sending the file\
- to the server. It is useful to avoid page limitations.
+        :param page_options: If set, remove pages from the document as specified.
+            This is done before sending the file to the server.
+            It is useful to avoid page limitations.
         :param options: Options for the workflow.
         :return:
         """
@@ -259,13 +268,11 @@ def execute_workflow(
                     page_options.page_indexes,
                 )
 
-        logger.debug("Sending document to workflow: %s", workflow_id)
-
         if not options:
             options = WorkflowOptions(
                 alias=None, priority=None, full_text=False, public_url=None, rag=False
             )
-
+        logger.debug("Sending document to workflow: %s", workflow_id)
         return self._send_to_workflow(GeneratedV1, input_source, workflow_id, options)
 
     def _validate_async_params(
@@ -285,7 +292,7 @@ def _validate_async_params(
         if max_retries < min_retries:
             raise MindeeClientError(f"Cannot set retries to less than {min_retries}.")
 
-    def enqueue_and_parse(
+    def enqueue_and_parse(  # pylint: disable=too-many-locals
         self,
         product_class: Type[Inference],
         input_source: Union[LocalInputSource, UrlInputSource],
@@ -298,40 +305,51 @@ def enqueue_and_parse(
         delay_sec: float = 1.5,
         max_retries: int = 80,
         full_text: bool = False,
+        workflow_id: Optional[str] = None,
+        rag: bool = False,
     ) -> AsyncPredictResponse:
         """
         Enqueues to an asynchronous endpoint and automatically polls for a response.
 
-        :param product_class: The document class to use. The response object will be instantiated based on this\
-parameter.
+        :param product_class: The document class to use.
+            The response object will be instantiated based on this parameter.
 
-        :param input_source: The document/source file to use. Has to be created beforehand.
+        :param input_source: The document/source file to use.
+            Has to be created beforehand.
 
-        :param include_words: Whether to include the full text for each page. This performs a full OCR operation on\
- the server and will increase response time.
+        :param include_words: Whether to include the full text for each page.
+            This performs a full OCR operation on the server and will increase response time.
 
-        :param close_file: Whether to ``close()`` the file after parsing it. Set to ``False`` if you need to access\
- the file after this operation.
+        :param close_file: Whether to ``close()`` the file after parsing it.
+            Set to ``False`` if you need to access the file after this operation.
 
-        :param page_options: If set, remove pages from the document as specified. This is done before sending the file\
- to the server. It is useful to avoid page limitations.
+        :param page_options: If set, remove pages from the document as specified.
+            This is done before sending the file to the server.
+            It is useful to avoid page limitations.
 
-        :param cropper: Whether to include cropper results for each page. This performs a cropping operation on the\
- server and will increase response time.
+        :param cropper: Whether to include cropper results for each page.
+            This performs a cropping operation on the server and will increase response time.
 
         :param endpoint: For custom endpoints, an endpoint has to be given.
 
-        :param initial_delay_sec: Delay between each polling attempts This should not be shorter than 1 second.
+        :param initial_delay_sec: Delay between each polling attempts.
+            This should not be shorter than 1 second.
 
-        :param delay_sec: Delay between each polling attempts This should not be shorter than 1 second.
+        :param delay_sec: Delay between each polling attempts.
+            This should not be shorter than 1 second.
 
         :param max_retries: Total amount of polling attempts.
 
         :param full_text: Whether to include the full OCR text response in compatible APIs.
+
+        :param workflow_id: Workflow ID.
+
+        :param rag: If set, will enable Retrieval-Augmented Generation.
+            Only works if a valid ``workflow_id`` is set.
         """
         self._validate_async_params(initial_delay_sec, delay_sec, max_retries)
         if not endpoint:
-            endpoint = self._initialize_ots_endpoint(product_class)
+            endpoint = self._initialize_ots_endpoint(product_class=product_class)
         queue_result = self.enqueue(
             product_class,
             input_source,
@@ -341,6 +359,8 @@ def enqueue_and_parse(
             cropper,
             endpoint,
             full_text,
+            workflow_id,
+            rag,
         )
         logger.debug(
             "Successfully enqueued document with job id: %s", queue_result.job.id
@@ -406,15 +426,16 @@ def _make_request(
         product_class: Type[Inference],
         input_source: Union[LocalInputSource, UrlInputSource],
         endpoint: Endpoint,
-        include_words: bool,
+        options: PredictOptions,
         close_file: bool,
-        cropper: bool,
-        full_text: bool,
     ) -> PredictResponse:
         response = endpoint.predict_req_post(
-            input_source, include_words, close_file, cropper, full_text
+            input_source,
+            options.include_words,
+            close_file,
+            options.cropper,
+            options.full_text,
         )
-
         dict_response = response.json()
 
         if not is_valid_sync_response(response):
@@ -423,28 +444,30 @@ def _make_request(
                 str(product_class.endpoint_name),
                 clean_response,
             )
-
         return PredictResponse(product_class, dict_response)
 
     def _predict_async(
         self,
         product_class: Type[Inference],
         input_source: Union[LocalInputSource, UrlInputSource],
+        options: AsyncPredictOptions,
         endpoint: Optional[Endpoint] = None,
-        include_words: bool = False,
         close_file: bool = True,
-        cropper: bool = False,
-        full_text: bool = False,
     ) -> AsyncPredictResponse:
         """Sends a document to the queue, and sends back an asynchronous predict response."""
         if input_source is None:
             raise MindeeClientError("No input document provided")
         if not endpoint:
             endpoint = self._initialize_ots_endpoint(product_class)
         response = endpoint.predict_async_req_post(
-            input_source, include_words, close_file, cropper, full_text
+            input_source=input_source,
+            include_words=options.include_words,
+            close_file=close_file,
+            cropper=options.cropper,
+            full_text=options.full_text,
+            workflow_id=options.workflow_id,
+            rag=options.rag,
         )
-
         dict_response = response.json()
 
         if not is_valid_async_response(response):

mindee/input/predict_options.py

@@ -0,0 +1,31 @@
+from typing import Optional
+
+
+class PredictOptions:
+    """Options to pass to a prediction."""
+
+    def __init__(
+        self,
+        cropper: bool = False,
+        full_text: bool = False,
+        include_words: bool = False,
+    ):
+        self.cropper = cropper
+        self.full_text = full_text
+        self.include_words = include_words
+
+
+class AsyncPredictOptions(PredictOptions):
+    """Options to pass to an asynchronous prediction."""
+
+    def __init__(
+        self,
+        cropper: bool = False,
+        full_text: bool = False,
+        include_words: bool = False,
+        workflow_id: Optional[str] = None,
+        rag: bool = False,
+    ):
+        super().__init__(cropper, full_text, include_words)
+        self.workflow_id = workflow_id
+        self.rag = rag

mindee/mindee_http/endpoint.py

@@ -1,5 +1,5 @@
 import json
-from typing import Union
+from typing import Optional, Union
 
 import requests
 from requests import Response
@@ -60,6 +60,8 @@ def predict_async_req_post(
         close_file: bool = True,
         cropper: bool = False,
         full_text: bool = False,
+        workflow_id: Optional[str] = None,
+        rag: bool = False,
     ) -> requests.Response:
         """
         Make an asynchronous request to POST a document for prediction.
@@ -69,10 +71,19 @@ def predict_async_req_post(
         :param close_file: Whether to `close()` the file after parsing it.
         :param cropper: Including Mindee cropping results.
         :param full_text: Whether to include the full OCR text response in compatible APIs.
+        :param workflow_id: Workflow ID.
+        :param rag: If set, will enable Retrieval-Augmented Generation.
         :return: requests response
         """
         return self._custom_request(
-            "predict_async", input_source, include_words, close_file, cropper, full_text
+            "predict_async",
+            input_source,
+            include_words,
+            close_file,
+            cropper,
+            full_text,
+            workflow_id,
+            rag,
         )
 
     def _custom_request(
@@ -83,6 +94,8 @@ def _custom_request(
         close_file: bool = True,
         cropper: bool = False,
         full_text: bool = False,
+        workflow_id: Optional[str] = None,
+        rag: bool = False,
     ):
         data = {}
         if include_words:
@@ -93,11 +106,18 @@ def _custom_request(
             params["full_text_ocr"] = "true"
         if cropper:
             params["cropper"] = "true"
+        if rag:
+            params["rag"] = "true"
+
+        if workflow_id:
+            url = f"{self.settings.base_url}/workflows/{workflow_id}/{route}"
+        else:
+            url = f"{self.settings.url_root}/{route}"
 
         if isinstance(input_source, UrlInputSource):
             data["document"] = input_source.url
             response = requests.post(
-                f"{self.settings.url_root}/{route}",
+                url=url,
                 headers=self.settings.base_headers,
                 data=data,
                 params=params,
@@ -106,7 +126,7 @@ def _custom_request(
         else:
             files = {"document": input_source.read_contents(close_file)}
             response = requests.post(
-                f"{self.settings.url_root}/{route}",
+                url=url,
                 files=files,
                 headers=self.settings.base_headers,
                 data=data,

mindee/parsing/common/__init__.py

@@ -15,7 +15,6 @@
 from mindee.parsing.common.page import Page
 from mindee.parsing.common.predict_response import PredictResponse
 from mindee.parsing.common.prediction import Prediction
-from mindee.parsing.common.string_dict import StringDict
 from mindee.parsing.common.summary_helper import (
     clean_out_string,
     format_for_display,

mindee/parsing/common/async_predict_response.py

@@ -15,7 +15,7 @@ class AsyncPredictResponse(Generic[TypeInference], ApiResponse):
 
     job: Job
     """Job object link to the prediction. As long as it isn't complete, the prediction doesn't exist."""
-    document: Optional[Document]
+    document: Optional[Document] = None
 
     def __init__(
         self, inference_type: Type[TypeInference], raw_response: StringDict

mindee/parsing/common/document.py

@@ -29,9 +29,9 @@ class Document(Generic[TypePrediction, TypePage]):
     """Result of the base inference"""
     id: str
     """Id of the document as sent back by the server"""
-    extras: Optional[Extras]
+    extras: Optional[Extras] = None
     """Potential Extras fields sent back along the prediction"""
-    ocr: Optional[Ocr]
+    ocr: Optional[Ocr] = None
     """Potential raw text results read by the OCR (limited feature)"""
     n_pages: int
     """Amount of pages in the document"""