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#
# Copyright 2024 The InfiniFlow 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.
#
from openai.lib.azure import AzureOpenAI
from zhipuai import ZhipuAI
import io
from abc import ABC
from ollama import Client
from openai import OpenAI
import os
import json
from rag.utils import num_tokens_from_string
import base64
import re
class Base(ABC):
def __init__(self, key, model_name):
pass
def transcription(self, audio, **kwargs):
transcription = self.client.audio.transcriptions.create(
model=self.model_name,
file=audio,
response_format="text"
)
return transcription.text.strip(), num_tokens_from_string(transcription.text.strip())
def audio2base64(self,audio):
if isinstance(audio, bytes):
return base64.b64encode(audio).decode("utf-8")
if isinstance(audio, io.BytesIO):
return base64.b64encode(audio.getvalue()).decode("utf-8")
raise TypeError("The input audio file should be in binary format.")
class GPTSeq2txt(Base):
def __init__(self, key, model_name="whisper-1", base_url="https://api.openai.com/v1"):
if not base_url: base_url = "https://api.openai.com/v1"
self.client = OpenAI(api_key=key, base_url=base_url)
self.model_name = model_name
class QWenSeq2txt(Base):
def __init__(self, key, model_name="paraformer-realtime-8k-v1", **kwargs):
import dashscope
dashscope.api_key = key
self.model_name = model_name
def transcription(self, audio, format):
from http import HTTPStatus
from dashscope.audio.asr import Recognition
recognition = Recognition(model=self.model_name,
format=format,
sample_rate=16000,
callback=None)
result = recognition.call(audio)
ans = ""
if result.status_code == HTTPStatus.OK:
for sentence in result.get_sentence():
ans += sentence.text.decode('utf-8') + '\n'
return ans, num_tokens_from_string(ans)
return "**ERROR**: " + result.message, 0
class OllamaSeq2txt(Base):
def __init__(self, key, model_name, lang="Chinese", **kwargs):
self.client = Client(host=kwargs["base_url"])
self.model_name = model_name
self.lang = lang
class AzureSeq2txt(Base):
def __init__(self, key, model_name, lang="Chinese", **kwargs):
self.client = AzureOpenAI(api_key=key, azure_endpoint=kwargs["base_url"], api_version="2024-02-01")
self.model_name = model_name
self.lang = lang
class XinferenceSeq2txt(Base):
def __init__(self, key, model_name="", base_url=""):
self.client = OpenAI(api_key="xxx", base_url=base_url)
self.model_name = model_name
class TencentCloudSeq2txt(Base):
def __init__(
self, key, model_name="16k_zh", base_url="https://asr.tencentcloudapi.com"
):
from tencentcloud.common import credential
from tencentcloud.asr.v20190614 import asr_client
key = json.loads(key)
sid = key.get("tencent_cloud_sid", "")
sk = key.get("tencent_cloud_sk", "")
cred = credential.Credential(sid, sk)
self.client = asr_client.AsrClient(cred, "")
self.model_name = model_name
def transcription(self, audio, max_retries=60, retry_interval=5):
from tencentcloud.common.exception.tencent_cloud_sdk_exception import (
TencentCloudSDKException,
)
from tencentcloud.asr.v20190614 import models
import time
b64 = self.audio2base64(audio)
try:
# dispatch disk
req = models.CreateRecTaskRequest()
params = {
"EngineModelType": self.model_name,
"ChannelNum": 1,
"ResTextFormat": 0,
"SourceType": 1,
"Data": b64,
}
req.from_json_string(json.dumps(params))
resp = self.client.CreateRecTask(req)
# loop query
req = models.DescribeTaskStatusRequest()
params = {"TaskId": resp.Data.TaskId}
req.from_json_string(json.dumps(params))
retries = 0
while retries < max_retries:
resp = self.client.DescribeTaskStatus(req)
if resp.Data.StatusStr == "success":
text = re.sub(
r"\[\d+:\d+\.\d+,\d+:\d+\.\d+\]\s*", "", resp.Data.Result
).strip()
return text, num_tokens_from_string(text)
elif resp.Data.StatusStr == "failed":
return (
"**ERROR**: Failed to retrieve speech recognition results.",
0,
)
else:
time.sleep(retry_interval)
retries += 1
return "**ERROR**: Max retries exceeded. Task may still be processing.", 0
except TencentCloudSDKException as e:
return "**ERROR**: " + str(e), 0
except Exception as e:
return "**ERROR**: " + str(e), 0
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