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import openai
import whisper
from gtts import gTTS
model = whisper.load_model("small")
def transcribe(filepath):
audio = whisper.load_audio(filepath)
audio = whisper.pad_or_trim(audio)
mel = whisper.log_mel_spectrogram(audio).to(model.device)
_, probs = model.detect_language(mel)
global language
language = max(probs, key=probs.get)
options = whisper.DecodingOptions(fp16=False)
result = whisper.decode(model, mel, options)
return result.text
def answer_by_chat(
question,
role1,
content1,
role2,
content2,
role3,
content3,
role4,
content4,
role5,
content5,
api_key,
):
openai.api_key = api_key
messages = [
{"role": role, "content": content}
for role, content in [
[role1, content1],
[role2, content2],
[role3, content3],
[role4, content4],
[role5, content5],
]
if role != "" and content != ""
]
messages.append({"role": "user", "content": question})
response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages)
response_text = response["choices"][0]["message"]["content"]
response_audio = speech_synthesis(response_text)
return response_text, response_audio
def speech_synthesis(sentence):
tts = gTTS(sentence, lang=language)
tts.save("tmp.mp3")
return "tmp.mp3"
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