Delete more_core.py
Browse files- more_core.py +0 -353
more_core.py
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import json
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import multiprocessing
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import os
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import random
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import string
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import time
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from typing import Dict, Any, List
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import tiktoken
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import uvicorn
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from apscheduler.schedulers.background import BackgroundScheduler
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from fastapi import FastAPI, Request, HTTPException
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from fastapi.responses import JSONResponse
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from starlette.responses import HTMLResponse
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# 禁用 SSL 警告
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import urllib3
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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import degpt as dg
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# debug for Log
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debug = False
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app = FastAPI(
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title="ones",
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description="High-performance API service",
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version="1.1.5|2025.1.12"
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)
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class APIServer:
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"""High-performance API server implementation"""
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def __init__(self, app: FastAPI):
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self.app = app
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self.encoding = tiktoken.get_encoding("cl100k_base")
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self._setup_routes()
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self._setup_scheduler()
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def _setup_scheduler(self):
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""" Schedule tasks to check and reload routes and models at regular intervals. """
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self.scheduler = BackgroundScheduler()
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# Scheduled Task 1: Check and reload routes every 30 seconds. Calls _reload_routes_if_needed method to check if routes need to be updated
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self.scheduler.add_job(self._reload_routes_if_needed, 'interval', seconds=30)
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# Scheduled Task 2: Reload models every 30 minutes (1800 seconds). This task will check and update the model data periodically
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self.scheduler.add_job(self._reload_check, 'interval', seconds=60 * 30)
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self.scheduler.start()
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def _setup_routes(self) -> None:
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"""Initialize API routes"""
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self.routes = """Initialize API routes"""
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# Static routes with names for filtering
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@self.app.get("/", name="root", include_in_schema=False)
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def root():
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return HTMLResponse(content="<h1>hello. It's home page.</h1>")
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@self.app.get("/web", name="web")
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def web():
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return HTMLResponse(content="<h1>hello. It's web page.</h1>")
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@self.app.get("/health", name="health")
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def health():
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return JSONResponse(content={"status": "working"})
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@self.app.get("/v1/models", name="models")
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def models():
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if debug:
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print("Fetching models...")
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models_str = dg.get_models()
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try:
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models_json = json.loads(models_str)
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return JSONResponse(content=models_json)
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except json.JSONDecodeError as e:
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raise HTTPException(status_code=500,
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detail=f"Invalid models data: {str(e)}")
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# Register dynamic chat completion routes
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routes = self._get_routes()
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if debug:
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print(f"Registering routes: {routes}")
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for path in routes:
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self._register_route(path)
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existing_routes = [route.path for route in self.app.routes if hasattr(route, 'path')]
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if debug:
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print(f"All routes now: {existing_routes}")
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def _get_routes(self) -> List[str]:
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"""Get configured API routes"""
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default_path = "/api/v1/chat/completions"
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replace_chat = os.getenv("REPLACE_CHAT", "")
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prefix_chat = os.getenv("PREFIX_CHAT", "")
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append_chat = os.getenv("APPEND_CHAT", "")
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if replace_chat:
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return [path.strip() for path in replace_chat.split(",") if path.strip()]
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routes = []
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if prefix_chat:
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routes.extend(f"{prefix.rstrip('/')}{default_path}"
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for prefix in prefix_chat.split(","))
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return routes
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if append_chat:
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append_paths = [path.strip() for path in append_chat.split(",") if path.strip()]
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routes = [default_path] + append_paths
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return routes
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return [default_path]
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def _register_route(self, path: str) -> None:
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"""Register a single API route"""
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global debug
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async def chat_endpoint(request: Request) -> Dict[str, Any]:
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try:
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if debug:
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print(f"Request chat_endpoint...")
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headers = dict(request.headers)
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data = await request.json()
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if debug:
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print(f"Request received...\r\n\tHeaders: {headers},\r\n\tData: {data}")
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return self._generate_response(headers, data)
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except Exception as e:
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if debug:
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print(f"Request processing error: {e}")
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raise HTTPException(status_code=500, detail="Internal server error") from e
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self.app.post(path)(chat_endpoint)
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def _calculate_tokens(self, text: str) -> int:
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"""Calculate token count for text"""
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return len(self.encoding.encode(text))
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def _generate_id(self, letters: int = 4, numbers: int = 6) -> str:
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"""Generate unique chat completion ID"""
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letters_str = ''.join(random.choices(string.ascii_lowercase, k=letters))
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numbers_str = ''.join(random.choices(string.digits, k=numbers))
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return f"chatcmpl-{letters_str}{numbers_str}"
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def is_chatgpt_format(self, data):
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"""Check if the data is in the expected ChatGPT format"""
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try:
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# If the data is a string, try to parse it as JSON
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if isinstance(data, str):
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try:
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data = json.loads(data)
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except json.JSONDecodeError:
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return False # If the string can't be parsed, it's not in the expected format
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# Now check if data is a dictionary and contains the necessary structure
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if isinstance(data, dict):
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# Ensure 'choices' is a list and the first item has a 'message' field
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if "choices" in data and isinstance(data["choices"], list) and len(data["choices"]) > 0:
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if "message" in data["choices"][0]:
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return True
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except Exception as e:
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print(f"Error checking ChatGPT format: {e}")
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return False
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def process_result(self, result, model):
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# 如果result是字符串,尝试将其转换为JSON
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if isinstance(result, str):
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try:
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result = json.loads(result) # 转换为JSON
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except json.JSONDecodeError:
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return result
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# 确保result是一个字典(JSON对象)
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if isinstance(result, dict):
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# 设置新的id和object值
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result['id'] = self._generate_id() # 根据需要设置新的ID值
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result['object'] = "chat.completion" # 根据需要设置新的object值
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# 添加model值
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result['model'] = model # 根据需要设置model值
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return result
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def _generate_response(self, headers: Dict[str, str], data: Dict[str, Any]) -> Dict[str, Any]:
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"""Generate API response"""
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global debug
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if debug:
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print("inside _generate_response")
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try:
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# check model
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model = data.get("model")
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# print(f"model: {model}")
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# just auto will check
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if "auto" == model:
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model = dg.get_auto_model()
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# else:
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# if not dg.is_model_available(model):
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# raise HTTPException(status_code=400, detail="Invalid Model")
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# ## kuan
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# model = dg.get_model_by_autoupdate(model)
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# must has token ? token check
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authorization = headers.get('Authorization')
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token = os.getenv("TOKEN", "")
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if token and token not in authorization:
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raise HTTPException(status_code=401, detail="无效的Token")
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# call ai
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msgs = data.get("messages")
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if not msgs:
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raise HTTPException(status_code=400, detail="消息不能为空")
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if debug:
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print(f"request model: {model}")
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if token:
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print(f"request token: {token}")
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print(f"request messages: {msgs}")
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result = dg.chat_completion_messages(
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messages=msgs,
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model=model
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)
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if debug:
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print(f"result: {result}---- {self.is_chatgpt_format(result)}")
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# If the request body data already matches ChatGPT format, return it directly
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if self.is_chatgpt_format(result):
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# If data already follows ChatGPT format, use it directly
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response_data = self.process_result(result, model)
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else:
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# Calculate the current timestamp
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current_timestamp = int(time.time() * 1000)
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# Otherwise, calculate the tokens and return a structured response
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prompt_tokens = self._calculate_tokens(str(data))
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completion_tokens = self._calculate_tokens(result)
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total_tokens = prompt_tokens + completion_tokens
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response_data = {
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"id": self._generate_id(),
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"object": "chat.completion",
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"created": current_timestamp,
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"model": data.get("model", "gpt-4o"),
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"usage": {
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"prompt_tokens": prompt_tokens,
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"completion_tokens": completion_tokens,
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"total_tokens": total_tokens
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},
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"choices": [{
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"message": {
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"role": "assistant",
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"content": result
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},
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"finish_reason": "stop",
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"index": 0
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}]
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}
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# Print the response for debugging (you may remove this in production)
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if debug:
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print(f"Response Data: {response_data}")
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return response_data
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except Exception as e:
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dg.record_call(model,False)
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if debug:
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print(f"Response generation error: {e}")
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raise HTTPException(status_code=500, detail=str(e)) from e
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def _get_workers_count(self) -> int:
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"""Calculate optimal worker count"""
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try:
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cpu_cores = multiprocessing.cpu_count()
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recommended_workers = (2 * cpu_cores) + 1
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return min(max(4, recommended_workers), 8)
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except Exception as e:
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if debug:
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print(f"Worker count calculation failed: {e}, using default 4")
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return 4
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def get_server_config(self, host: str = "0.0.0.0", port: int = 7860) -> uvicorn.Config:
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"""Get server configuration"""
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workers = self._get_workers_count()
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if debug:
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print(f"Configuring server with {workers} workers")
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return uvicorn.Config(
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app=self.app,
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host=host,
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port=port,
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workers=workers,
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loop="uvloop",
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limit_concurrency=1000,
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timeout_keep_alive=30,
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access_log=True,
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log_level="info",
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http="httptools"
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)
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def run(self, host: str = "0.0.0.0", port: int = 7860) -> None:
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"""Run the API server"""
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config = self.get_server_config(host, port)
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server = uvicorn.Server(config)
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server.run()
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def _reload_check(self) -> None:
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dg.reload_check()
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def _reload_routes_if_needed(self) -> None:
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"""Check if routes need to be reloaded based on environment variables"""
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# reload Debug
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global debug
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debug = os.getenv("DEBUG", "False").lower() in ["true", "1", "t"]
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# relaod routes
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new_routes = self._get_routes()
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current_routes = [route for route in self.app.routes if hasattr(route, 'path')]
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# Check if the current routes are different from the new routes
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if [route.path for route in current_routes] != new_routes:
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if debug:
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print("Routes changed, reloading...")
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self._reload_routes(new_routes)
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| 318 |
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# def _reload_routes(self, new_routes: List[str]) -> None:
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# """Reload the routes based on the updated configuration"""
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# # Clear existing routes
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# self.app.routes.clear()
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# # Register new routes
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# for path in new_routes:
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# self._register_route(path)
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| 327 |
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def _reload_routes(self, new_routes: List[str]) -> None:
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"""Reload only dynamic routes while preserving static ones"""
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# Define static route names
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static_routes = {"root", "web", "health", "models"}
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# Remove only dynamic routes
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self.app.routes[:] = [
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route for route in self.app.routes
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if not hasattr(route, 'name') or route.name in static_routes
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]
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| 338 |
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# Register new dynamic routes
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for path in new_routes:
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self._register_route(path)
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def create_server() -> APIServer:
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"""Factory function to create server instance"""
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return APIServer(app)
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| 349 |
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| 350 |
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if __name__ == "__main__":
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port = int(os.getenv("PORT", "7860"))
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server = create_server()
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server.run(port=port)
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