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Runtime error
Update server.py
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server.py
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@@ -1,13 +1,14 @@
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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import subprocess
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import tempfile
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import os
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app = FastAPI()
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# Load DeepSeek-Coder-V2-Base Model
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model_name = "deepseek-ai/DeepSeek-Coder-V2-Base"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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@@ -16,9 +17,6 @@ model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float
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class CodeRequest(BaseModel):
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user_story: str
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class TestRequest(BaseModel):
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code: str
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@app.post("/generate-code")
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def generate_code(request: CodeRequest):
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"""Generates code based on user story"""
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@@ -30,37 +28,6 @@ def generate_code(request: CodeRequest):
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return {"generated_code": generated_code}
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@app.post("/test-code")
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def test_code(request: TestRequest):
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"""Runs automated testing on the generated code"""
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try:
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with tempfile.NamedTemporaryFile(delete=False, suffix=".py") as temp_file:
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temp_file.write(request.code.encode())
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temp_file.close()
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result = subprocess.run(["pytest", temp_file.name], capture_output=True, text=True)
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os.unlink(temp_file.name)
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if result.returncode == 0:
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return {"test_status": "All tests passed!"}
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else:
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return {"test_status": "Test failed!", "details": result.stderr}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/execute-code")
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def execute_code():
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"""Executes AI-generated code"""
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sample_code = "print('Hello from AI-generated code!')"
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try:
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result = subprocess.run(["python3", "-c", sample_code], capture_output=True, text=True)
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return {"status": "Execution successful!", "output": result.stdout}
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except Exception as e:
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return {"status": "Execution failed!", "error": str(e)}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=7860)
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import os
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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app = FastAPI()
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# Fix: Set a writable cache directory
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os.environ["TRANSFORMERS_CACHE"] = "/app/cache"
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# Load DeepSeek-Coder-V2-Base Model
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model_name = "deepseek-ai/DeepSeek-Coder-V2-Base"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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class CodeRequest(BaseModel):
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user_story: str
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@app.post("/generate-code")
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def generate_code(request: CodeRequest):
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"""Generates code based on user story"""
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return {"generated_code": generated_code}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=7860)
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