Delete software_engineer_agent.py

software_engineer_agent.py

@@ -1,42 +0,0 @@
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-from langchain_core.messages import AIMessage
-
-MODEL_REPO = "Rahul-8799/software_engineer_mellum"
-
-tokenizer = AutoTokenizer.from_pretrained(MODEL_REPO, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(
-    MODEL_REPO,
-    torch_dtype=torch.float16,
-    device_map="auto"
-)
-
-def run(state: dict) -> dict:
-    """Software Engineer generates clean, modern UI code using best practices"""
-    messages = state["messages"]
-    prompt = messages[-1].content
-    
-    # Enhance the prompt with UI implementation guidelines
-    enhanced_prompt = f"""
-    Generate modern, clean UI code following these guidelines:
-    1. Use Tailwind CSS for styling (recommended for consistent spacing and responsive design)
-    2. Implement proper semantic HTML structure
-    3. Use CSS Grid and Flexbox for layouts
-    4. Add proper ARIA labels for accessibility
-    5. Implement responsive breakpoints
-    6. Use CSS variables for consistent theming
-    7. Add proper error handling and loading states
-    8. Implement proper component structure
-    
-    Original requirements: {prompt}
-    """
-    
-    input_ids = tokenizer(enhanced_prompt, return_tensors="pt").input_ids.to(model.device)
-    output_ids = model.generate(input_ids, max_new_tokens=3000)
-    output = tokenizer.decode(output_ids[0], skip_special_tokens=True)
-
-    return {
-        "messages": [AIMessage(content=output)],
-        "chat_log": state["chat_log"] + [{"role": "Software Engineer", "content": output}],
-        "dev_output": output,
-    }