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from fastapi import FastAPI
from fastapi.responses import StreamingResponse, JSONResponse
from pydantic import BaseModel
from typing import List, Optional
import time
import json
import os
import httpx
from dotenv import load_dotenv
load_dotenv()
from models import AVAILABLE_MODELS, MODEL_ALIASES
# Require IMAGE_API_URL strictly from environment
IMAGE_API_URL = os.environ["IMAGE_API_URL"]
app = FastAPI()
def unix_id():
return str(int(time.time() * 1000))
# ==== Models ====
@app.get("/v1/models")
async def list_models():
return {"object": "list", "data": AVAILABLE_MODELS}
# ==== Chat Completion ====
class Message(BaseModel):
role: str
content: str
class ChatRequest(BaseModel):
messages: List[Message]
model: str
stream: Optional[bool] = False
@app.post("/v1/chat/completions")
async def chat_completion(request: ChatRequest):
model_id = MODEL_ALIASES.get(request.model, request.model)
headers = {
'accept': 'text/event-stream',
'content-type': 'application/json',
'origin': 'https://www.chatwithmono.xyz',
'referer': 'https://www.chatwithmono.xyz/',
'user-agent': 'Mozilla/5.0',
}
payload = {
"messages": [{"role": msg.role, "content": msg.content} for msg in request.messages],
"model": model_id
}
if request.stream:
async def event_stream():
chat_id = f"chatcmpl-{unix_id()}"
created = int(time.time())
sent_done = False
async with httpx.AsyncClient(timeout=120) as client:
async with client.stream("POST", "https://www.chatwithmono.xyz/api/chat", headers=headers, json=payload) as response:
async for line in response.aiter_lines():
if line.startswith("0:"):
try:
content_piece = json.loads(line[2:])
chunk_data = {
"id": chat_id,
"object": "chat.completion.chunk",
"created": created,
"model": model_id,
"choices": [{
"delta": {"content": content_piece},
"index": 0,
"finish_reason": None
}]
}
yield f"data: {json.dumps(chunk_data)}\n\n"
except:
continue
elif line.startswith(("e:", "d:")) and not sent_done:
sent_done = True
done_chunk = {
"id": chat_id,
"object": "chat.completion.chunk",
"created": created,
"model": model_id,
"choices": [{
"delta": {},
"index": 0,
"finish_reason": "stop"
}]
}
yield f"data: {json.dumps(done_chunk)}\n\ndata: [DONE]\n\n"
return StreamingResponse(event_stream(), media_type="text/event-stream")
else:
assistant_response = ""
usage_info = {}
async with httpx.AsyncClient(timeout=120) as client:
async with client.stream("POST", "https://www.chatwithmono.xyz/api/chat", headers=headers, json=payload) as response:
async for chunk in response.aiter_lines():
if chunk.startswith("0:"):
try:
piece = json.loads(chunk[2:])
assistant_response += piece
except:
continue
elif chunk.startswith(("e:", "d:")):
try:
data = json.loads(chunk[2:])
usage_info = data.get("usage", {})
except:
continue
return JSONResponse(content={
"id": f"chatcmpl-{unix_id()}",
"object": "chat.completion",
"created": int(time.time()),
"model": model_id,
"choices": [{
"index": 0,
"message": {
"role": "assistant",
"content": assistant_response
},
"finish_reason": "stop"
}],
"usage": {
"prompt_tokens": usage_info.get("promptTokens", 0),
"completion_tokens": usage_info.get("completionTokens", 0),
"total_tokens": usage_info.get("promptTokens", 0) + usage_info.get("completionTokens", 0),
}
})
# ==== Image Generation ====
class ImageGenerationRequest(BaseModel):
prompt: str
aspect_ratio: Optional[str] = "1:1"
n: Optional[int] = 1
user: Optional[str] = None
@app.post("/v1/images/generations")
async def generate_images(request: ImageGenerationRequest):
results = []
async with httpx.AsyncClient(timeout=60) as client:
for _ in range(request.n):
params = {
"prompt": request.prompt,
"aspect_ratio": request.aspect_ratio,
"link": "typegpt.net"
}
resp = await client.get(IMAGE_API_URL, params=params)
if resp.status_code != 200:
return JSONResponse(
status_code=502,
content={"error": "Image generation failed", "details": resp.text}
)
data = resp.json()
results.append({
"url": data.get("image_link"),
"b64_json": data.get("base64_output"),
"retries": data.get("attempt")
})
return {
"created": int(time.time()),
"data": results
}
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