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from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
import torch
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
model_name = "SkillForge45/CyberFuture-A1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16)
device = "cuda" if torch.cuda.is_available() else "cpu"
model.to(device)
class ChatRequest(BaseModel):
prompt: str
max_length: int = 100
@app.post("/chat/")
async def chat(request: ChatRequest):
try:
inputs = tokenizer(request.prompt, return_tensors="pt").to(device)
outputs = model.generate(
**inputs,
max_length=request.max_length,
temperature=0.7,
do_sample=True
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return {"response": response}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000) |