# # 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. # import base64 import io import json import os import re from abc import ABC import requests from openai import OpenAI from openai.lib.azure import AzureOpenAI from rag.utils import num_tokens_from_string class Base(ABC): def __init__(self, key, model_name, **kwargs): """ Abstract base class constructor. Parameters are not stored; initialization is left to subclasses. """ pass def transcription(self, audio_path, **kwargs): audio_file = open(audio_path, "rb") transcription = self.client.audio.transcriptions.create(model=self.model_name, file=audio_file) 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): _FACTORY_NAME = "OpenAI" def __init__(self, key, model_name="whisper-1", base_url="https://api.openai.com/v1", **kwargs): 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): _FACTORY_NAME = "Tongyi-Qianwen" def __init__(self, key, model_name="qwen-audio-asr", **kwargs): import dashscope dashscope.api_key = key self.model_name = model_name def transcription(self, audio_path): if "paraformer" in self.model_name or "sensevoice" in self.model_name: return f"**ERROR**: model {self.model_name} is not suppported yet.", 0 from dashscope import MultiModalConversation audio_path = f"file://{audio_path}" messages = [ { "role": "user", "content": [{"audio": audio_path}], } ] response = None full_content = "" try: response = MultiModalConversation.call(model="qwen-audio-asr", messages=messages, result_format="message", stream=True) for response in response: try: full_content += response["output"]["choices"][0]["message"].content[0]["text"] except Exception: pass return full_content, num_tokens_from_string(full_content) except Exception as e: return "**ERROR**: " + str(e), 0 class AzureSeq2txt(Base): _FACTORY_NAME = "Azure-OpenAI" 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): _FACTORY_NAME = "Xinference" def __init__(self, key, model_name="whisper-small", **kwargs): self.base_url = kwargs.get("base_url", None) self.model_name = model_name self.key = key def transcription(self, audio, language="zh", prompt=None, response_format="json", temperature=0.7): if isinstance(audio, str): audio_file = open(audio, "rb") audio_data = audio_file.read() audio_file_name = audio.split("/")[-1] else: audio_data = audio audio_file_name = "audio.wav" payload = {"model": self.model_name, "language": language, "prompt": prompt, "response_format": response_format, "temperature": temperature} files = {"file": (audio_file_name, audio_data, "audio/wav")} try: response = requests.post(f"{self.base_url}/v1/audio/transcriptions", files=files, data=payload) response.raise_for_status() result = response.json() if "text" in result: transcription_text = result["text"].strip() return transcription_text, num_tokens_from_string(transcription_text) else: return "**ERROR**: Failed to retrieve transcription.", 0 except requests.exceptions.RequestException as e: return f"**ERROR**: {str(e)}", 0 class TencentCloudSeq2txt(Base): _FACTORY_NAME = "Tencent Cloud" def __init__(self, key, model_name="16k_zh", base_url="https://asr.tencentcloudapi.com"): from tencentcloud.asr.v20190614 import asr_client from tencentcloud.common import credential 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): import time from tencentcloud.asr.v20190614 import models from tencentcloud.common.exception.tencent_cloud_sdk_exception import ( TencentCloudSDKException, ) 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 class GPUStackSeq2txt(Base): _FACTORY_NAME = "GPUStack" def __init__(self, key, model_name, base_url): if not base_url: raise ValueError("url cannot be None") if base_url.split("/")[-1] != "v1": base_url = os.path.join(base_url, "v1") self.base_url = base_url self.model_name = model_name self.key = key class GiteeSeq2txt(Base): _FACTORY_NAME = "GiteeAI" def __init__(self, key, model_name="whisper-1", base_url="https://ai.gitee.com/v1/"): if not base_url: base_url = "https://ai.gitee.com/v1/" self.client = OpenAI(api_key=key, base_url=base_url) self.model_name = model_name class DeepInfraSeq2txt(Base): _FACTORY_NAME = "DeepInfra" def __init__(self, key, model_name, base_url="https://api.deepinfra.com/v1/openai", **kwargs): if not base_url: base_url = "https://api.deepinfra.com/v1/openai" self.client = OpenAI(api_key=key, base_url=base_url) self.model_name = model_name