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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 base64
import httpx
from dotenv import load_dotenv
load_dotenv()
# Dummy imports for example
from models import AVAILABLE_MODELS, MODEL_ALIASES # Ensure these are defined properly
# Env variables
IMAGE_API_URL = os.environ["IMAGE_API_URL"]
SNAPZION_UPLOAD_URL = "https://upload.snapzion.com/api/public-upload"
SNAPZION_API_KEY = os.environ["SNAP"]
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
model: Optional[str] = "default"
@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):
model = request.model or "default"
if model in ["gpt-image-1", "dall-e-3", "dall-e-2", "nextlm-image-1"]:
headers = {
'Content-Type': 'application/json',
'User-Agent': 'Mozilla/5.0',
'Referer': 'https://www.chatwithmono.xyz/',
'sec-ch-ua-platform': '"Windows"',
'sec-ch-ua': '"Not)A;Brand";v="8", "Chromium";v="138", "Google Chrome";v="138"',
'sec-ch-ua-mobile': '?0',
}
payload = {
"prompt": request.prompt,
"model": model
}
resp = await client.post("https://www.chatwithmono.xyz/api/image", headers=headers, json=payload)
if resp.status_code != 200:
return JSONResponse(
status_code=502,
content={"error": f"{model} generation failed", "details": resp.text}
)
data = resp.json()
b64_image = data.get("image")
if not b64_image:
return JSONResponse(status_code=502, content={"error": "Missing base64 image in response"})
data_uri = f"data:image/png;base64,{b64_image}"
upload_headers = {"Authorization": SNAPZION_API_KEY}
upload_files = {
'file': ('image.png', base64.b64decode(b64_image), 'image/png')
}
upload_resp = await client.post(SNAPZION_UPLOAD_URL, headers=upload_headers, files=upload_files)
if upload_resp.status_code != 200:
return JSONResponse(
status_code=502,
content={"error": "Upload failed", "details": upload_resp.text}
)
upload_data = upload_resp.json()
results.append({
"url": upload_data.get("url"),
"b64_json": b64_image,
"data_uri": data_uri,
"model": model
})
else:
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"),
"model": "default"
})
return {
"created": int(time.time()),
"data": results
}
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