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import os
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
import subprocess
import tempfile
app = FastAPI()
# ✅ Fix: Set writable cache directory for Hugging Face models
os.environ["TRANSFORMERS_CACHE"] = "/app/cache"
os.environ["HF_HOME"] = "/app/cache"
# ✅ Ensure cache directory exists
os.makedirs("/app/cache", exist_ok=True)
# ✅ Load AI Model
model_name = "deepseek-ai/DeepSeek-Coder-V2-Base"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
class CodeRequest(BaseModel):
user_story: str
class TestRequest(BaseModel):
code: str
@app.post("/generate-code")
def generate_code(request: CodeRequest):
"""Generates AI-powered structured code based on user story"""
prompt = f"Generate structured code for: {request.user_story}"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
output = model.generate(**inputs, max_length=300)
generated_code = tokenizer.decode(output[0], skip_special_tokens=True)
return {"generated_code": generated_code}
@app.post("/test-code")
def test_code(request: TestRequest):
"""Runs automated testing on AI-generated code"""
try:
with tempfile.NamedTemporaryFile(delete=False, suffix=".py") as temp_file:
temp_file.write(request.code.encode())
temp_file.close()
result = subprocess.run(["pytest", temp_file.name], capture_output=True, text=True)
os.unlink(temp_file.name)
if result.returncode == 0:
return {"test_status": "All tests passed!"}
else:
return {"test_status": "Test failed!", "details": result.stderr}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/execute-code")
def execute_code():
"""Executes AI-generated code and returns output"""
sample_code = "print('Hello from AI-generated code!')"
try:
result = subprocess.run(["python3", "-c", sample_code], capture_output=True, text=True)
return {"status": "Execution successful!", "output": result.stdout}
except Exception as e:
return {"status": "Execution failed!", "error": str(e)}
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)
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