app.py

import gradio as gr
import csv
import re
import tempfile
import os
import requests

# 1. Load system prompt from a file
with open("system_instructions.txt", "r", encoding="utf-8") as f:
    ECO_PROMPT = f.read()

# DeepSeek API configuration
DEEPSEEK_API_KEY = os.environ.get("DEEPSEEK_API_KEY")
DEEPSEEK_API_URL = "https://api.deepseek.com/v1/chat/completions"  # Verify actual API endpoint

def score_qa(question, answer):
    """Query DeepSeek API to get a score for Q&A pair"""
    try:
        # Format the prompt using our template
        prompt = ECO_PROMPT.format(question=question, answer=answer)
        
        headers = {
            "Authorization": f"Bearer {DEEPSEEK_API_KEY}",
            "Content-Type": "application/json"
        }

        payload = {
            "model": "deepseek-chat",  # Verify correct model name
            "messages": [{
                "role": "user",
                "content": prompt
            }],
            "temperature": 0.1,  # More deterministic output for scoring
            "max_tokens": 5
        }

        response = requests.post(DEEPSEEK_API_URL, json=payload, headers=headers)
        response.raise_for_status()
        
        # Parse response (adjust based on actual API response structure)
        output = response.json()['choices'][0]['message']['content']
        
        # Extract score using same logic as before
        match = re.search(r"\d+", output)
        return int(match.group(0)) if match else 1

    except Exception as e:
        print(f"API Error: {str(e)}")
        return 1  # Fallback score on error

def judge_ecolinguistics_from_csv(csv_file):
    """Existing CSV processing function remains the same"""
    # [Keep the existing implementation exactly as you have it]
    # ... (same file processing logic)
    # ... (same CSV writing logic)
    # ... (same percentage calculation)

    return out_path, percentage_display

# [Keep the Gradio interface configuration exactly as is]
demo = gr.Interface(
    fn=judge_ecolinguistics_from_csv,
    inputs=gr.File(label="Upload CSV with question_number, question, answer"),
    outputs=[
        gr.File(label="Download scored CSV"),
        gr.HTML(label="Percentage Score")
    ],
    title="Ecolinguistics Q&A Scoring",
    description=(
        "Upload a CSV with columns [question_number, question, answer]. "
        "DeepSeek scores each answer from 0–5, then shows a final "
        "percentage score. A detailed CSV with individual scores is provided."
    )
)

if __name__ == "__main__":
    demo.launch()