import streamlit as st
import requests
import json
import os
import re


HF_API_URL = "https://router.huggingface.co/novita/v3/openai/chat/completions"
HF_TOKEN = os.environ["HF_PROJECT_TOKEN"]

HEADERS = {
    "Authorization": f"Bearer {HF_TOKEN}",
}

# Correctly format the prompt string with {user_prompt} placeholder inside the string
PROMPT_TEMPLATE = """
You are a prompt evaluation assistant called 👮 PromptPolice. Evaluate the following user prompt in JSON format using the structure provided below.
Prompt:
{user_prompt}
Evaluate based on the following criteria:
- Clarity (1-5)
- Context (1-5)
- Specificity (1-5)
- Intent (1-5)
Also include a suggestion for improving the prompt.
Respond ONLY in this JSON format:
{{
  "prompt": "...",
  "evaluation": {{
    "Clarity": ..., 
    "Context": ..., 
    "Specificity": ..., 
    "Intent": ..., 
    "suggestion": "..."
  }}
}}
"""

def evaluate_prompt(user_prompt):
    # Format the input prompt by inserting the user_prompt dynamically
    formatted_prompt = PROMPT_TEMPLATE.format(user_prompt=user_prompt)

    payload = {
        "messages": [
            {
                "role": "user",
                "content": formatted_prompt
            }
        ],
        "model": "deepseek/deepseek-v3-0324"
    }

    try:
        # Send request to DeepSeek API
        response = requests.post(HF_API_URL, headers=HEADERS, json=payload)
        response.raise_for_status()

        result = response.json()

        # Extract JSON formatted evaluation
        if isinstance(result, dict) and "choices" in result:
            raw_text = result["choices"][0]["message"]["content"]
            try:
                # This regex finds the first complete JSON block
                json_match = re.search(r'\{[\s\S]*\}', raw_text)
                if json_match:
                    json_str = json_match.group()
                    return json.loads(json_str)
                else:
                    return {"error": "No valid JSON object found in model output."}
            except (ValueError, json.JSONDecodeError) as e:
                return {"error": f"Failed to parse model output: {str(e)}"}
        return result
    except requests.exceptions.RequestException as e:
        return {"error": f"API request failed: {str(e)}"}

# --- Streamlit UI ---
st.set_page_config(page_title="👮 PromptPolice", layout="centered")
st.title("👮 PromptPolice: Prompt Evaluator")

user_prompt = st.text_area("Paste your AI prompt here:", height=200)

if st.button("Evaluate Prompt") and user_prompt:
    with st.spinner("Evaluating your prompt with DeepSeek..."):
        evaluation_result = evaluate_prompt(user_prompt)

    st.subheader("Evaluation Result (JSON):")
    st.code(json.dumps(evaluation_result, indent=2), language='json')