server2 / app.py
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import time
import orjson
import asyncio
from typing import List, AsyncGenerator
from fastapi import FastAPI, HTTPException
import os
from fastapi.responses import StreamingResponse, ORJSONResponse
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel, Field
import httpx
import uvicorn
# Use orjson for faster JSON serialization
app = FastAPI(
title="Qwen3 API",
description="Streaming API for Qwen3-0.6B model",
version="2.0.0",
default_response_class=ORJSONResponse
)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Async HTTP client with connection pooling
BASE_URL = "http://localhost:8080/v1"
http_client: httpx.AsyncClient = None
@app.on_event("startup")
async def startup():
global http_client
http_client = httpx.AsyncClient(
base_url=BASE_URL,
timeout=httpx.Timeout(300.0, connect=10.0),
limits=httpx.Limits(max_keepalive_connections=10, max_connections=20),
http2=True
)
@app.on_event("shutdown")
async def shutdown():
global http_client
if http_client:
await http_client.aclose()
# ===== Models =====
class Message(BaseModel):
role: str
content: str
class Config:
extra = "ignore"
class ChatRequest(BaseModel):
messages: List[Message]
temperature: float = Field(default=0.6, ge=0.0, le=2.0)
top_p: float = Field(default=0.95, ge=0.0, le=1.0)
max_tokens: int = Field(default=4096, ge=1, le=32768)
stream: bool = Field(default=True)
class Config:
extra = "ignore"
class SimpleChatRequest(BaseModel):
prompt: str
temperature: float = Field(default=0.6, ge=0.0, le=2.0)
top_p: float = Field(default=0.95, ge=0.0, le=1.0)
max_tokens: int = Field(default=4096, ge=1, le=32768)
stream: bool = Field(default=True)
class Config:
extra = "ignore"
# ===== Optimized Think Tag Parser =====
__slots_parser__ = ['answer', 'thought', 'in_think', 'start_time', 'total_think_time', 'buffer']
class ParserState:
__slots__ = ['answer', 'thought', 'in_think', 'start_time', 'total_think_time']
def __init__(self):
self.answer = []
self.thought = []
self.in_think = False
self.start_time = 0.0
self.total_think_time = 0.0
def get_answer(self) -> str:
return ''.join(self.answer)
def get_thought(self) -> str:
return ''.join(self.thought)
def parse_chunk(content: str, state: ParserState) -> float:
buffer = content
while buffer:
if not state.in_think:
idx = buffer.find('<think>')
if idx != -1:
if idx > 0:
state.answer.append(buffer[:idx])
state.in_think = True
state.start_time = time.perf_counter()
buffer = buffer[idx + 7:]
else:
for i in range(min(6, len(buffer)), 0, -1):
if '<think>'[:i] == buffer[-i:]:
state.answer.append(buffer[:-i])
return 0.0
state.answer.append(buffer)
return 0.0
else:
idx = buffer.find('</think>')
if idx != -1:
if idx > 0:
state.thought.append(buffer[:idx])
state.total_think_time += time.perf_counter() - state.start_time
state.in_think = False
buffer = buffer[idx + 8:]
else:
for i in range(min(7, len(buffer)), 0, -1):
if '</think>'[:i] == buffer[-i:]:
state.thought.append(buffer[:-i])
return time.perf_counter() - state.start_time
state.thought.append(buffer)
return time.perf_counter() - state.start_time
return time.perf_counter() - state.start_time if state.in_think else 0.0
# ===== Async Streaming Functions =====
async def stream_from_backend(messages: list, temperature: float, top_p: float, max_tokens: int) -> AsyncGenerator[str, None]:
payload = {
"model": "",
"messages": messages,
"temperature": temperature,
"top_p": top_p,
"max_tokens": max_tokens,
"stream": True
}
async with http_client.stream(
"POST",
"/chat/completions",
json=payload,
headers={"Accept": "text/event-stream"}
) as response:
async for line in response.aiter_lines():
if line.startswith("data: "):
data = line[6:]
if data == "[DONE]":
break
try:
chunk = orjson.loads(data)
if chunk.get("choices") and chunk["choices"][0].get("delta", {}).get("content"):
yield chunk["choices"][0]["delta"]["content"]
except orjson.JSONDecodeError:
continue
async def generate_stream_fast(request: ChatRequest) -> AsyncGenerator[bytes, None]:
messages = [{"role": m.role, "content": m.content} for m in request.messages]
state = ParserState()
chunk_id = f"chatcmpl-{int(time.time() * 1000)}"
created = int(time.time())
try:
async for content in stream_from_backend(
messages, request.temperature, request.top_p, request.max_tokens
):
elapsed = parse_chunk(content, state)
sse_chunk = {
"id": chunk_id,
"object": "chat.completion.chunk",
"created": created,
"model": "qwen3-0.6b",
"choices": [{
"index": 0,
"delta": {"content": content},
"finish_reason": None
}],
"thinking": {
"in_progress": state.in_think,
"elapsed": elapsed if state.in_think else state.total_think_time
}
}
yield b"data: " + orjson.dumps(sse_chunk) + b"\n\n"
final_chunk = {
"id": chunk_id,
"object": "chat.completion.chunk",
"created": created,
"model": "qwen3-0.6b",
"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
"thinking": {
"in_progress": False,
"total_think_time": state.total_think_time,
"thought_content": state.get_thought(),
"answer_content": state.get_answer()
}
}
yield b"data: " + orjson.dumps(final_chunk) + b"\n\n"
yield b"data: [DONE]\n\n"
except Exception as e:
yield b"data: " + orjson.dumps({"error": {"message": str(e)}}) + b"\n\n"
async def generate_complete_fast(request: ChatRequest) -> dict:
messages = [{"role": m.role, "content": m.content} for m in request.messages]
state = ParserState()
response_parts = []
try:
async for content in stream_from_backend(
messages, request.temperature, request.top_p, request.max_tokens
):
response_parts.append(content)
parse_chunk(content, state)
full_response = ''.join(response_parts)
return {
"id": f"chatcmpl-{int(time.time() * 1000)}",
"object": "chat.completion",
"created": int(time.time()),
"model": "qwen3-0.6b",
"choices": [{
"index": 0,
"message": {
"role": "assistant",
"content": full_response,
"thinking": {
"thought_content": state.get_thought(),
"answer_content": state.get_answer(),
"total_think_time": state.total_think_time
}
},
"finish_reason": "stop"
}]
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
# ===== Endpoints =====
@app.get("/")
async def root():
return {"status": "ok", "message": "Qwen3 API is running"}
@app.get("/health")
async def health():
try:
response = await http_client.get("/models")
return {"status": "healthy" if response.status_code == 200 else "unhealthy"}
except Exception as e:
return {"status": "unhealthy", "error": str(e)}
@app.get("/v1/models")
async def list_models():
return {
"object": "list",
"data": [{
"id": "qwen3-0.6b",
"object": "model",
"created": int(time.time()),
"owned_by": "local"
}]
}
@app.post("/v1/chat/completions")
async def chat_completions(request: ChatRequest):
if request.stream:
return StreamingResponse(
generate_stream_fast(request),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"Transfer-Encoding": "chunked"
}
)
return await generate_complete_fast(request)
@app.post("/chat")
async def simple_chat(request: SimpleChatRequest):
chat_request = ChatRequest(
messages=[Message(role="user", content=request.prompt)],
temperature=request.temperature,
top_p=request.top_p,
max_tokens=request.max_tokens,
stream=request.stream
)
if request.stream:
return StreamingResponse(
generate_stream_fast(chat_request),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no"
}
)
return await generate_complete_fast(chat_request)
async def raw_stream_fast(request: ChatRequest) -> AsyncGenerator[bytes, None]:
messages = [{"role": m.role, "content": m.content} for m in request.messages]
try:
async for content in stream_from_backend(
messages, request.temperature, request.top_p, request.max_tokens
):
yield content.encode()
except Exception as e:
yield f"\n\nError: {str(e)}".encode()
@app.post("/chat/raw")
async def raw_chat(request: SimpleChatRequest):
chat_request = ChatRequest(
messages=[Message(role="user", content=request.prompt)],
temperature=request.temperature,
top_p=request.top_p,
max_tokens=request.max_tokens,
stream=True
)
return StreamingResponse(
raw_stream_fast(chat_request),
media_type="text/plain",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no"
}
)
@app.post("/fast")
async def fast_chat(prompt: str = "", max_tokens: int = 512):
messages = [{"role": "user", "content": prompt}]
response_parts = []
async for content in stream_from_backend(messages, 0.6, 0.95, max_tokens):
response_parts.append(content)
return {"response": ''.join(response_parts)}
# ===== Mini-server load tracking & coordination endpoints =====
# How many concurrent requests this mini should handle
MAX_CONCURRENT_REQUESTS = int(os.environ.get("MAX_CONCURRENT_REQUESTS", "1"))
# In-memory tracking per process
current_requests = 0
# For identification / debugging
MINI_SERVER_ID = os.environ.get("MINI_SERVER_ID", "mini-1")
class MiniStatus(BaseModel):
server_id: str
max_concurrent: int
current_requests: int
status: str
@app.get("/status")
async def mini_status():
"""
Used by the main server to know if this mini is idle/busy.
"""
status = "busy" if current_requests >= MAX_CONCURRENT_REQUESTS else "idle"
return MiniStatus(
server_id=MINI_SERVER_ID,
max_concurrent=MAX_CONCURRENT_REQUESTS,
current_requests=current_requests,
status=status,
)
@app.post("/reserve")
async def reserve_slot():
"""
Called by the main server BEFORE it forwards a chat request.
If this mini is full, returns 429 so main server can try another mini.
"""
global current_requests
if current_requests >= MAX_CONCURRENT_REQUESTS:
raise HTTPException(status_code=429, detail="Mini server busy")
current_requests += 1
return {
"server_id": MINI_SERVER_ID,
"current_requests": current_requests,
"max_concurrent": MAX_CONCURRENT_REQUESTS,
}
@app.post("/release")
async def release_slot():
"""
Called by the main server after request is finished (stream closed/response sent).
"""
global current_requests
if current_requests > 0:
current_requests -= 1
return {
"server_id": MINI_SERVER_ID,
"current_requests": current_requests,
"max_concurrent": MAX_CONCURRENT_REQUESTS,
}
if __name__ == "__main__":
uvicorn.run(
app,
host="0.0.0.0",
port=7860,
loop="uvloop",
http="httptools",
access_log=False,
workers=1
)