# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
import functools
from typing import Any, Callable, Dict, Generic, Optional, TypeVar
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import AsyncHttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator_async import distributed_trace_async
from ... import models as _models
from ...operations._operations import build_analyze_conversations_request
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
[docs]class ConversationAnalysisClientOperationsMixin:
[docs] @distributed_trace_async
async def analyze_conversations(
self,
conversation_analysis_options: "_models.ConversationAnalysisOptions",
*,
project_name: str,
deployment_name: str,
**kwargs: Any
) -> "_models.AnalyzeConversationResult":
"""Analyzes the input conversation utterance.
:param conversation_analysis_options: Post body of the request.
:type conversation_analysis_options:
~azure.ai.language.conversations.models.ConversationAnalysisOptions
:keyword project_name: The name of the project to use.
:paramtype project_name: str
:keyword deployment_name: The name of the specific deployment of the project to use.
:paramtype deployment_name: str
:return: AnalyzeConversationResult
:rtype: ~azure.ai.language.conversations.models.AnalyzeConversationResult
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["_models.AnalyzeConversationResult"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
json = self._serialize.body(conversation_analysis_options, 'ConversationAnalysisOptions')
request = build_analyze_conversations_request(
content_type=content_type,
project_name=project_name,
deployment_name=deployment_name,
json=json,
template_url=self.analyze_conversations.metadata['url'],
)
path_format_arguments = {
"Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
raise HttpResponseError(response=response, model=error)
deserialized = self._deserialize('AnalyzeConversationResult', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
analyze_conversations.metadata = {'url': '/:analyze-conversations'} # type: ignore