61 lines
1.4 KiB
Python
61 lines
1.4 KiB
Python
from openai import OpenAI
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from fastapi import FastAPI, File, Response, Request
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from io import BytesIO
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app = FastAPI()
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openAI_clinet = OpenAI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["*"],
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allow_headers=["*"],
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)
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class ConversationMessege(BaseModel):
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role: str
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content: str
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class Conversation(BaseModel):
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messages: list[ConversationMessege]
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@app.post("/get-text")
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async def stt(audio: bytes = File()):
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with BytesIO(audio) as f:
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f.name = "audio.mp3"
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transcript = openAI_clinet.audio.transcriptions.create(
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model="whisper-1",
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file=f,
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response_format="text",
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)
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data = {"len": len(audio), "user-transcript": transcript}
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return data
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@app.post("/conversation")
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async def get_next_response(request: Request):
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messages = await request.json()
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res = openAI_clinet.chat.completions.create(
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model="gpt-3.5-turbo",
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messages=messages,
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)
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res_msg = res.choices[0].message.content
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role = res.choices[0].message.role
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print(messages)
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print(res_msg)
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return {"role": role, "content": res_msg}
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@app.get("/speak")
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def tts(text: str):
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res = openAI_clinet.audio.speech.create(
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model="tts-1", voice="nova", input=text, response_format="mp3"
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)
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return Response(content=res.content, media_type="audio/mp3")
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