You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
152 lines
5.0 KiB
152 lines
5.0 KiB
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
import base64
|
|
import traceback
|
|
from typing import Union
|
|
|
|
import numpy as np
|
|
from fastapi import APIRouter
|
|
|
|
from paddlespeech.cli.log import logger
|
|
from paddlespeech.server.engine.engine_pool import get_engine_pool
|
|
from paddlespeech.server.engine.vector.python.vector_engine import PaddleVectorConnectionHandler
|
|
from paddlespeech.server.restful.request import VectorRequest
|
|
from paddlespeech.server.restful.request import VectorScoreRequest
|
|
from paddlespeech.server.restful.response import ErrorResponse
|
|
from paddlespeech.server.restful.response import VectorResponse
|
|
from paddlespeech.server.restful.response import VectorScoreResponse
|
|
from paddlespeech.server.utils.errors import ErrorCode
|
|
from paddlespeech.server.utils.errors import failed_response
|
|
from paddlespeech.server.utils.exception import ServerBaseException
|
|
router = APIRouter()
|
|
|
|
|
|
@router.get('/paddlespeech/vector/help')
|
|
def help():
|
|
"""help
|
|
|
|
Returns:
|
|
json: The /paddlespeech/vector api response content
|
|
"""
|
|
response = {
|
|
"success": "True",
|
|
"code": 200,
|
|
"message": {
|
|
"global": "success"
|
|
},
|
|
"vector": [2.3, 3.5, 5.5, 6.2, 2.8, 1.2, 0.3, 3.6]
|
|
}
|
|
return response
|
|
|
|
|
|
@router.post(
|
|
"/paddlespeech/vector", response_model=Union[VectorResponse, ErrorResponse])
|
|
def vector(request_body: VectorRequest):
|
|
"""vector api
|
|
|
|
Args:
|
|
request_body (VectorRequest): the vector request body
|
|
|
|
Returns:
|
|
json: the vector response body
|
|
"""
|
|
try:
|
|
# 1. get the audio data
|
|
# the audio must be base64 format
|
|
audio_data = base64.b64decode(request_body.audio)
|
|
|
|
# 2. get single engine from engine pool
|
|
# and we use the vector_engine to create an connection handler to process the request
|
|
engine_pool = get_engine_pool()
|
|
vector_engine = engine_pool['vector']
|
|
connection_handler = PaddleVectorConnectionHandler(vector_engine)
|
|
|
|
# 3. we use the connection handler to process the audio
|
|
audio_vec = connection_handler.run(audio_data, request_body.task)
|
|
|
|
# 4. we need the result of the vector instance be numpy.ndarray
|
|
if not isinstance(audio_vec, np.ndarray):
|
|
logger.error(
|
|
f"the vector type is not numpy.array, that is: {type(audio_vec)}"
|
|
)
|
|
error_reponse = ErrorResponse()
|
|
error_reponse.message.description = f"the vector type is not numpy.array, that is: {type(audio_vec)}"
|
|
return error_reponse
|
|
|
|
response = {
|
|
"success": True,
|
|
"code": 200,
|
|
"message": {
|
|
"description": "success"
|
|
},
|
|
"result": {
|
|
"vec": audio_vec.tolist()
|
|
}
|
|
}
|
|
|
|
except ServerBaseException as e:
|
|
response = failed_response(e.error_code, e.msg)
|
|
except BaseException:
|
|
response = failed_response(ErrorCode.SERVER_UNKOWN_ERR)
|
|
traceback.print_exc()
|
|
|
|
return response
|
|
|
|
|
|
@router.post(
|
|
"/paddlespeech/vector/score",
|
|
response_model=Union[VectorScoreResponse, ErrorResponse])
|
|
def score(request_body: VectorScoreRequest):
|
|
"""vector api
|
|
|
|
Args:
|
|
request_body (VectorScoreRequest): the punctuation request body
|
|
|
|
Returns:
|
|
json: the punctuation response body
|
|
"""
|
|
try:
|
|
# 1. get the audio data
|
|
# the audio must be base64 format
|
|
enroll_data = base64.b64decode(request_body.enroll_audio)
|
|
test_data = base64.b64decode(request_body.test_audio)
|
|
|
|
# 2. get single engine from engine pool
|
|
# and we use the vector_engine to create an connection handler to process the request
|
|
engine_pool = get_engine_pool()
|
|
vector_engine = engine_pool['vector']
|
|
connection_handler = PaddleVectorConnectionHandler(vector_engine)
|
|
|
|
# 3. we use the connection handler to process the audio
|
|
score = connection_handler.get_enroll_test_score(enroll_data, test_data)
|
|
|
|
response = {
|
|
"success": True,
|
|
"code": 200,
|
|
"message": {
|
|
"description": "success"
|
|
},
|
|
"result": {
|
|
"score": score
|
|
}
|
|
}
|
|
|
|
except ServerBaseException as e:
|
|
response = failed_response(e.error_code, e.msg)
|
|
except BaseException:
|
|
response = failed_response(ErrorCode.SERVER_UNKOWN_ERR)
|
|
traceback.print_exc()
|
|
|
|
return response
|