backend to interface with ai models

.gitignore

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+**/.venv/
+**/__pycache__/

speech-speech/backend/.env

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+OPENAI_API_KEY=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

speech-speech/backend/api.py

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+from openai import OpenAI
+from fastapi import FastAPI, File, Response, Request
+from fastapi.responses import JSONResponse
+from fastapi.encoders import jsonable_encoder
+from json import dumps
+from pydantic import BaseModel
+import filetype
+import whisper
+
+
+app = FastAPI()
+openAI_clinet = OpenAI()
+model = whisper.load_model("base")
+
+
+class ConversationMessege(BaseModel):
+    role: str
+    content: str
+
+
+class Conversation(BaseModel):
+    messages: list[ConversationMessege]
+
+
+@app.post("/get-text")
+def get_text(response: Response, audio: bytes = File()):
+    response.headers["Access-Control-Allow-Origin"] = "*"
+    with open("audio", "wb") as f:
+        f.write(audio)
+    print(len(audio))
+    # transcript = openAI_clinet.audio.transcriptions.create(
+    #    model="whisper-1",
+    #    file=audio,
+    #    response_format="text",
+    #    RequestBody
+    # )
+    result = model.transcribe("audio")
+    data = {"len": len(audio), "user-transcript": result["text"]}
+    return data
+
+
+@app.post("/conversation")
+async def get_next_response(request: Request, response: Response):
+    response.headers["Access-Control-Allow-Origin"] = "*"
+    messages = await request.json()
+    res = openAI_clinet.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=messages,
+    )
+    res_msg = res.choices[0].message.content
+    role = res.choices[0].message.role
+    print(res_msg)
+    return {"role": role, "content": res_msg}

speech-speech/backend/requirements.txt

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+openai
+fastapi
+uvicorn
+python-multipart