Create app.py

app.py

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+from fastapi import FastAPI, HTTPException, Depends, status
+from fastapi.security import HTTPBearer, HTTPBearerToken
+from pydantic import BaseModel
+from transformers import pipeline
+import gradio as gr
+import os
+from dotenv import load_dotenv
+import uvicorn
+import threading
+
+load_dotenv()
+
+app = FastAPI(title="AI Prompt Enhancer", version="1.0.0")
+security = HTTPBearer()
+
+API_KEY = os.getenv("API_KEY")
+if not API_KEY:
+    raise ValueError("API_KEY not found in environment variables")
+
+pipe = pipeline("text-generation", model="unsloth/gemma-3-270m-it-GGUF")
+
+def load_system_prompt():
+    try:
+        with open("prompt.txt", "r", encoding="utf-8") as f:
+            return f.read().strip()
+    except FileNotFoundError:
+        return "You are an AI assistant that enhances prompts to make them more effective and detailed."
+
+SYSTEM_PROMPT = load_system_prompt()
+
+class EnhanceRequest(BaseModel):
+    prompt: str
+
+class EnhanceResponse(BaseModel):
+    enhanced_prompt: str
+
+def verify_api_key(token: HTTPBearerToken = Depends(security)):
+    if token.credentials != API_KEY:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="Invalid API key"
+        )
+    return token.credentials
+
+@app.post("/enhance", response_model=EnhanceResponse)
+async def enhance_prompt(request: EnhanceRequest, api_key: str = Depends(verify_api_key)):
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user", "content": request.prompt}
+    ]
+    
+    try:
+        result = pipe(messages, max_length=512, temperature=0.7)
+        enhanced_prompt = result[0]["generated_text"]
+        
+        if isinstance(enhanced_prompt, list):
+            user_message = next((msg["content"] for msg in enhanced_prompt if msg["role"] == "assistant"), enhanced_prompt[-1]["content"])
+        else:
+            user_message = enhanced_prompt.split("assistant")[-1].strip() if "assistant" in enhanced_prompt else enhanced_prompt
+        
+        return EnhanceResponse(enhanced_prompt=user_message)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Enhancement failed: {str(e)}")
+
+def enhance_gradio(prompt_text):
+    if not prompt_text.strip():
+        return "Please enter a prompt to enhance."
+    
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user", "content": prompt_text}
+    ]
+    
+    try:
+        result = pipe(messages, max_length=512, temperature=0.7)
+        enhanced_prompt = result[0]["generated_text"]
+        
+        if isinstance(enhanced_prompt, list):
+            user_message = next((msg["content"] for msg in enhanced_prompt if msg["role"] == "assistant"), enhanced_prompt[-1]["content"])
+        else:
+            user_message = enhanced_prompt.split("assistant")[-1].strip() if "assistant" in enhanced_prompt else enhanced_prompt
+        
+        return user_message
+    except Exception as e:
+        return f"Enhancement failed: {str(e)}"
+
+iface = gr.Interface(
+    fn=enhance_gradio,
+    inputs=gr.Textbox(
+        lines=5,
+        placeholder="Enter your prompt here to enhance it...",
+        label="Original Prompt"
+    ),
+    outputs=gr.Textbox(
+        lines=8,
+        label="Enhanced Prompt"
+    ),
+    title="AI Prompt Enhancer",
+    description="Transform your basic prompts into detailed, effective instructions.",
+    examples=[
+        ["Write a story about a robot"],
+        ["Explain machine learning"],
+        ["Create a marketing plan"]
+    ]
+)
+
+def run_gradio():
+    iface.launch(server_name="0.0.0.0", server_port=7860, share=False)
+
+if __name__ == "__main__":
+    gradio_thread = threading.Thread(target=run_gradio, daemon=True)
+    gradio_thread.start()
+    
+    uvicorn.run(app, host="0.0.0.0", port=8000)