remove gitignore

.venv/lib/python3.10/site-packages/dashscope/audio/asr/transcription.py

@@ -0,0 +1,209 @@
+import asyncio
+import time
+from typing import List, Union
+
+import aiohttp
+
+from dashscope.api_entities.dashscope_response import (DashScopeAPIResponse,
+                                                       TranscriptionResponse)
+from dashscope.client.base_api import BaseAsyncApi
+from dashscope.common.constants import ApiProtocol, HTTPMethod
+from dashscope.common.logging import logger
+from dashscope.common.utils import _get_task_group_and_task
+
+
+class Transcription(BaseAsyncApi):
+    """API for File Transcription models.
+    """
+
+    MAX_QUERY_TRY_COUNT = 3
+
+    class Models:
+        paraformer_v1 = 'paraformer-v1'
+        paraformer_8k_v1 = 'paraformer-8k-v1'
+        paraformer_mtl_v1 = 'paraformer-mtl-v1'
+
+    @classmethod
+    def call(cls,
+             model: str,
+             file_urls: List[str],
+             phrase_id: str = None,
+             api_key: str = None,
+             **kwargs) -> TranscriptionResponse:
+        """Transcribe the given files synchronously.
+
+        Args:
+            model (str): The requested model_id.
+            file_urls (List[str]): List of stored URLs.
+            phrase_id (str, `optional`): The ID of phrase.
+
+            **kwargs:
+                channel_id (List[int], optional):
+                    The selected channel_id of audio file.
+                disfluency_removal_enabled(bool, `optional`):
+                    Filter mood words, turned off by default.
+                diarization_enabled (bool, `optional`):
+                    Speech auto diarization, turned off by default.
+                speaker_count (int, `optional`): The number of speakers.
+                timestamp_alignment_enabled (bool, `optional`):
+                    Timestamp-alignment calibration, turned off by default.
+                special_word_filter(str, `optional`): Sensitive word filter.
+                audio_event_detection_enabled(bool, `optional`):
+                    Audio event detection, turned off by default.
+
+        Returns:
+            TranscriptionResponse: The result of batch transcription.
+        """
+        kwargs.update(cls._fill_resource_id(phrase_id, **kwargs))
+        kwargs = cls._tidy_kwargs(**kwargs)
+        response = super().call(model, file_urls, api_key=api_key, **kwargs)
+        return TranscriptionResponse.from_api_response(response)
+
+    @classmethod
+    def async_call(cls,
+                   model: str,
+                   file_urls: List[str],
+                   phrase_id: str = None,
+                   api_key: str = None,
+                   **kwargs) -> TranscriptionResponse:
+        """Transcribe the given files asynchronously,
+        return the status of task submission for querying results subsequently.
+
+        Args:
+            model (str): The requested model, such as paraformer-16k-1
+            file_urls (List[str]): List of stored URLs.
+            phrase_id (str, `optional`): The ID of phrase.
+
+        **kwargs:
+            channel_id (List[int], optional):
+                The selected channel_id of audio file.
+            disfluency_removal_enabled(bool, `optional`):
+                Filter mood words, turned off by default.
+            diarization_enabled (bool, `optional`):
+                Speech auto diarization, turned off by default.
+            speaker_count (int, `optional`): The number of speakers.
+            timestamp_alignment_enabled (bool, `optional`):
+                Timestamp-alignment calibration, turned off by default.
+            special_word_filter(str, `optional`): Sensitive word filter.
+            audio_event_detection_enabled(bool, `optional`):
+                Audio event detection, turned off by default.
+
+        Returns:
+            TranscriptionResponse: The response including task_id.
+        """
+        kwargs.update(cls._fill_resource_id(phrase_id, **kwargs))
+        kwargs = cls._tidy_kwargs(**kwargs)
+        response = cls._launch_request(model,
+                                       file_urls,
+                                       api_key=api_key,
+                                       **kwargs)
+        return TranscriptionResponse.from_api_response(response)
+
+    @classmethod
+    def fetch(
+        cls,
+        task: Union[str, TranscriptionResponse],
+        api_key: str = None,
+    ) -> TranscriptionResponse:
+        """Fetch the status of task, including results of batch transcription when task_status is SUCCEEDED.  # noqa: E501
+
+        Args:
+            task (Union[str, TranscriptionResponse]): The task_id or
+                response including task_id returned from async_call().
+
+        Returns:
+            TranscriptionResponse: The status of task_id,
+        including results of batch transcription when task_status is SUCCEEDED.
+        """
+        try_count: int = 0
+        while True:
+            try:
+                response = super().fetch(task, api_key=api_key)
+            except (asyncio.TimeoutError, aiohttp.ClientConnectorError) as e:
+                logger.error(e)
+                try_count += 1
+                if try_count <= Transcription.MAX_QUERY_TRY_COUNT:
+                    time.sleep(2)
+                    continue
+
+            try_count = 0
+            break
+
+        return TranscriptionResponse.from_api_response(response)
+
+    @classmethod
+    def wait(
+        cls,
+        task: Union[str, TranscriptionResponse],
+        api_key: str = None,
+    ) -> TranscriptionResponse:
+        """Poll task until the final results of transcription is obtained.
+
+        Args:
+            task (Union[str, TranscriptionResponse]): The task_id or
+                response including task_id returned from async_call().
+
+        Returns:
+            TranscriptionResponse: The result of batch transcription.
+        """
+        response = super().wait(task, api_key=api_key)
+        return TranscriptionResponse.from_api_response(response)
+
+    @classmethod
+    def _launch_request(cls,
+                        model: str,
+                        files: List[str],
+                        api_key: str = None,
+                        **kwargs) -> DashScopeAPIResponse:
+        """Submit transcribe request.
+
+        Args:
+            model (str): The requested model, such as paraformer-16k-1
+            files (List[str]): List of stored URLs.
+
+        Returns:
+            DashScopeAPIResponse: The result of task submission.
+        """
+        task_name, function = _get_task_group_and_task(__name__)
+
+        try_count: int = 0
+        while True:
+            try:
+                response = super().async_call(model=model,
+                                              task_group='audio',
+                                              task=task_name,
+                                              function=function,
+                                              input={'file_urls': files},
+                                              api_protocol=ApiProtocol.HTTP,
+                                              http_method=HTTPMethod.POST,
+                                              api_key=api_key,
+                                              **kwargs)
+            except (asyncio.TimeoutError, aiohttp.ClientConnectorError) as e:
+                logger.error(e)
+                try_count += 1
+                if try_count <= Transcription.MAX_QUERY_TRY_COUNT:
+                    time.sleep(2)
+                    continue
+
+            break
+
+        return response
+
+    @classmethod
+    def _fill_resource_id(cls, phrase_id: str, **kwargs):
+        resources_list: list = []
+        if phrase_id is not None and len(phrase_id) > 0:
+            item = {'resource_id': phrase_id, 'resource_type': 'asr_phrase'}
+            resources_list.append(item)
+
+            if len(resources_list) > 0:
+                kwargs['resources'] = resources_list
+
+        return kwargs
+
+    @classmethod
+    def _tidy_kwargs(cls, **kwargs):
+        for k in kwargs.copy():
+            if kwargs[k] is None:
+                kwargs.pop(k, None)
+        return kwargs