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120 lines
4.0 KiB
120 lines
4.0 KiB
import asyncio
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import traceback
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import json
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from fastapi import FastAPI, WebSocket, Header
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from uvicorn import Config, Server
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from interpreter import interpreter as base_interpreter
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from .async_interpreter import AsyncInterpreter
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from fastapi.middleware.cors import CORSMiddleware
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from typing import List, Dict, Any
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from openai import OpenAI
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from pydantic import BaseModel
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import argparse
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import os
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os.environ["STT_RUNNER"] = "server"
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os.environ["TTS_RUNNER"] = "server"
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# Parse command line arguments for port number
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parser = argparse.ArgumentParser(description="FastAPI server.")
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parser.add_argument("--port", type=int, default=8000, help="Port to run on.")
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args = parser.parse_args()
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base_interpreter.tts = "openai"
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base_interpreter.llm.model = "gpt-4-turbo"
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async def main():
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interpreter = AsyncInterpreter(base_interpreter)
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"], # Allow all methods (GET, POST, etc.)
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allow_headers=["*"], # Allow all headers
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)
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@app.post("/load_chat")
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async def load_chat(messages: List[Dict[str, Any]]):
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interpreter.interpreter.messages = messages
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interpreter.active_chat_messages = messages
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print("🪼🪼🪼🪼🪼🪼 Messages loaded: ", interpreter.active_chat_messages)
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return {"status": "success"}
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@app.websocket("/ws")
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async def websocket_endpoint(websocket: WebSocket):
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await websocket.accept()
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try:
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async def receive_input():
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while True:
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data = await websocket.receive()
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if isinstance(data, bytes):
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await interpreter.input(data)
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elif "bytes" in data:
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await interpreter.input(data["bytes"])
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print("SERVER FEEDING AUDIO")
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elif "text" in data:
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print("RECEIVED INPUT", data)
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await interpreter.input(data["text"])
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async def send_output():
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while True:
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output = await interpreter.output()
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if isinstance(output, bytes):
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await websocket.send_bytes(output)
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# we dont send out bytes rn, no TTS
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pass
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elif isinstance(output, dict):
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await websocket.send_text(json.dumps(output))
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await asyncio.gather(receive_input(), send_output())
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except Exception as e:
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print(f"WebSocket connection closed with exception: {e}")
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traceback.print_exc()
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finally:
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await websocket.close()
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config = Config(app, host="0.0.0.0", port=8000, lifespan="on")
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server = Server(config)
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await server.serve()
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class Rename(BaseModel):
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input: str
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@app.post("/rename-chat")
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async def rename_chat(body_content: Rename, x_api_key: str = Header(None)):
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print("RENAME CHAT REQUEST in PY 🌙🌙🌙🌙")
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input_value = body_content.input
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client = OpenAI(
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# defaults to os.environ.get("OPENAI_API_KEY")
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api_key=x_api_key,
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)
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try:
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response = client.chat.completions.create(
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model="gpt-3.5-turbo",
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messages=[
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{
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"role": "user",
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"content": f"Given the following chat snippet, create a unique and descriptive title in less than 8 words. Your answer must not be related to customer service.\n\n{input_value}",
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}
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],
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temperature=0.3,
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stream=False,
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)
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print(response)
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completion = response["choices"][0]["message"]["content"]
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return {"data": {"content": completion}}
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except Exception as e:
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print(f"Error: {e}")
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traceback.print_exc()
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return {"error": str(e)}
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if __name__ == "__main__":
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asyncio.run(main())
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