app.py

# app.py
import streamlit as st
import pytesseract
from PIL import Image
import fitz  # PyMuPDF
import io
import requests
import re

# --- Config ---
API_KEY = "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"  
API_URL = "https://openrouter.ai/api/v1/chat/completions"
MODEL = "mistralai/mistral-7b-instruct"

# Set page config
st.set_page_config(
    page_title="🔬 AI Science Lab Assistant", 
    layout="centered",
    page_icon="🔬"
)

# Custom CSS for styling
st.markdown("""
    <style>
    .header {
        font-size: 36px;
        color: #2e86c1;
        text-align: center;
        padding: 20px;
    }
    .subheader {
        font-size: 24px;
        color: #28b463;
        border-bottom: 2px solid #f4d03f;
        padding-bottom: 10px;
        margin-top: 30px;
    }
    .stButton>button {
        background-color: #28b463 !important;
        color: white !important;
        border-radius: 8px;
        padding: 8px 20px;
        transition: all 0.3s;
    }
    .stButton>button:hover {
        background-color: #239b56 !important;
        transform: scale(1.05);
    }
    .score-card {
        background: linear-gradient(135deg, #e8f8f5, #d1f2eb);
        border-radius: 15px;
        padding: 20px;
        box-shadow: 0 4px 8px rgba(0,0,0,0.1);
        margin-bottom: 20px;
    }
    .highlight {
        background-color: #f9e79f;
        padding: 5px;
        border-radius: 5px;
        font-weight: bold;
    }
    .tip-box {
        background-color: #eafaf1;
        border-left: 5px solid #28b463;
        padding: 15px;
        margin: 15px 0;
        border-radius: 0 8px 8px 0;
    }
    </style>
    """, unsafe_allow_html=True)

# Header
st.markdown('<p class="header">🔬 AI Science Lab Assistant</p>', unsafe_allow_html=True)

# Introduction
st.markdown("""
<div style="text-align: center; margin-bottom: 30px;">
    <p style="font-size: 18px;">Transform your lab reports with AI-powered analysis! Get instant feedback on completeness, 
    receive improvement suggestions, and ask questions about your scientific work.</p>
</div>
""", unsafe_allow_html=True)

# Features in columns
col1, col2, col3 = st.columns(3)
with col1:
    st.markdown("""
        <div style="text-align: center;">
            <h4>🔍 Comprehensive Analysis</h4>
            <p>Checks for all essential lab report sections</p>
        </div>
    """, unsafe_allow_html=True)
    
with col2:
    st.markdown("""
        <div style="text-align: center;">
            <h4>💯 Smart Scoring</h4>
            <p>Grades your report on completeness and structure</p>
        </div>
    """, unsafe_allow_html=True)
    
with col3:
    st.markdown("""
        <div style="text-align: center;">
            <h4>📈 Improvement Tips</h4>
            <p>Personalized suggestions to enhance your report</p>
        </div>
    """, unsafe_allow_html=True)

# Divider
st.markdown("---")

# --- File Upload ---
st.markdown('<p class="subheader">📤 Upload Your Lab Report</p>', unsafe_allow_html=True)
uploaded_file = st.file_uploader("Upload image (JPG, PNG) or PDF", 
                                 type=["jpg", "jpeg", "png", "pdf"],
                                 label_visibility="collapsed")

lab_text = ""
if uploaded_file:
    file_bytes = uploaded_file.read()
    file_ext = uploaded_file.name.split(".")[-1].lower()

    if file_ext == "pdf":
        doc = fitz.open(stream=file_bytes, filetype="pdf")
        for page in doc:
            lab_text += page.get_text()
    else:
        image = Image.open(io.BytesIO(file_bytes))
        lab_text = pytesseract.image_to_string(image)

    # Allow text editing
    st.markdown('<p class="subheader">✍️ Extracted Text</p>', unsafe_allow_html=True)
    st.caption("Review and edit the extracted text if needed before analysis")
    lab_text = st.text_area("", lab_text, height=300, label_visibility="collapsed")

# --- AI Evaluation ---
if lab_text.strip():
    # -- AI Evaluation Prompt --
    full_prompt = f"""You are a science teacher evaluating a student's lab report. Please provide a comprehensive analysis:

    Lab Report:
    {lab_text}

    Evaluation Guidelines:
    1. **Section Check**: Identify which of these sections are present and which are missing:
        - Title
        - Objective
        - Hypothesis
        - Materials
        - Procedure
        - Observations
        - Results
        - Conclusion
        - References
    
    2. **Completeness Score**: 
        - Assign a numerical score from 1-10 based on completeness
        - Justify the score based on missing sections and content quality
    
    3. **Improvement Tips**:
        - For each missing section, explain why it's important
        - Provide specific suggestions for improvement (e.g., "Try writing a more detailed observation section by including quantitative data")
        - Highlight any sections that need more detail or clarity
    
    4. **Structure Response**:
        - Start with: "### Missing Sections:"
        - Then: "### Completeness Score: X/10"
        - Then: "### Improvement Tips:"
        - Finally: "### Detailed Feedback:"
    
    Be concise but thorough in your analysis.
    """

    def query_ai(prompt):
        headers = {
            "Authorization": f"Bearer {API_KEY}",
            "Content-Type": "application/json"
        }
        payload = {
            "model": MODEL,
            "messages": [
                {"role": "system", "content": "You are a helpful science teacher providing detailed lab report feedback."},
                {"role": "user", "content": prompt}
            ]
        }
        try:
            response = requests.post(API_URL, headers=headers, json=payload, timeout=120)
            response.raise_for_status()
            return response.json()['choices'][0]['message']['content']
        except Exception as e:
            st.error(f"Error connecting to AI service: {str(e)}")
            return None

    if st.button("🧪 Analyze Report", use_container_width=True):
        with st.spinner("🔍 Analyzing report with AI. This may take 20-30 seconds..."):
            result = query_ai(full_prompt)
            
        if result:
            st.success("✅ Analysis Complete!")
            st.balloons()
            
            # Extract score using regex
            score_match = re.search(r"Completeness Score:\s*(\d+)/10", result)
            score = int(score_match.group(1)) if score_match else None
            
            # Display score in a card
            if score is not None:
                with st.container():
                    st.markdown('<div class="score-card">', unsafe_allow_html=True)
                    
                    # Create columns for score visualization
                    col1, col2 = st.columns([1, 3])
                    
                    with col1:
                        st.markdown(f"<h2 style='text-align: center; color: #28b463;'>{score}/10</h2>", 
                                   unsafe_allow_html=True)
                        st.markdown("<h4 style='text-align: center;'>Completeness Score</h4>", 
                                  unsafe_allow_html=True)
                    
                    with col2:
                        # Create a color gradient based on score
                        if score >= 8:
                            color = "#28b463"  # Green
                        elif score >= 5:
                            color = "#f39c12"  # Orange
                        else:
                            color = "#e74c3c"  # Red
                            
                        # Display progress bar with styling
                        st.progress(score/10, text=f"{score*10}% complete")
                        st.markdown(
                            f"<style>"
                            f".stProgress > div > div > div {{"
                            f"    background-color: {color} !important;"
                            f"    border-radius: 10px;"
                            f"}}"
                            f"</style>",
                            unsafe_allow_html=True
                        )
                    
                    st.markdown('</div>', unsafe_allow_html=True)
            
            # Display AI analysis with formatting
            st.markdown("## 📝 Analysis Results")
            
            # Split sections for better display
            sections = {
                "Missing Sections": None,
                "Improvement Tips": None,
                "Detailed Feedback": None
            }
            
            current_section = None
            for line in result.split('\n'):
                if "### Missing Sections:" in line:
                    current_section = "Missing Sections"
                    sections[current_section] = []
                elif "### Improvement Tips:" in line:
                    current_section = "Improvement Tips"
                    sections[current_section] = []
                elif "### Detailed Feedback:" in line:
                    current_section = "Detailed Feedback"
                    sections[current_section] = []
                elif current_section and line.strip():
                    sections[current_section].append(line)
            
            # Display each section
            if sections["Missing Sections"]:
                st.markdown("### 🔍 Missing Sections")
                missing_text = '\n'.join(sections["Missing Sections"])
                st.markdown(f'<div class="highlight">{missing_text}</div>', unsafe_allow_html=True)
            
            if sections["Improvement Tips"]:
                st.markdown("### 💡 Improvement Tips")
                tips_text = '\n'.join(sections["Improvement Tips"])
                st.markdown(f'<div class="tip-box">{tips_text}</div>', unsafe_allow_html=True)
            
            if sections["Detailed Feedback"]:
                st.markdown("### 📋 Detailed Feedback")
                st.write('\n'.join(sections["Detailed Feedback"]))
            
            # Show full AI response in expander
            with st.expander("View Full AI Analysis"):
                st.markdown(result)
            
    # --- Question Answering Section ---
    st.markdown("---")
    st.markdown('<p class="subheader">❓ Ask About Your Report</p>', unsafe_allow_html=True)
    
    col1, col2 = st.columns([3, 1])
    with col1:
        user_question = st.text_input("Ask a question about your lab report", 
                                     placeholder="e.g., How can I improve my hypothesis?")
    with col2:
        st.markdown("<div style='height: 28px;'></div>", unsafe_allow_html=True)
        ask_button = st.button("🔍 Ask Question", use_container_width=True)
    
    if (ask_button or user_question) and user_question.strip():
        with st.spinner("Thinking..."):
            followup_prompt = f"""Lab Report:
            {lab_text}
            
            Question: {user_question}
            
            Answer the question based on the lab report. If the question can't be answered from the report, 
            suggest what information the student should add to answer it.
            """
            followup_response = query_ai(followup_prompt)
        
        if followup_response:
            st.markdown("### 💬 AI Response")
            st.markdown(f'<div class="tip-box">{followup_response}</div>', unsafe_allow_html=True)
else:
    # Show sample report if no file uploaded
    st.markdown("---")
    st.markdown('<p class="subheader">📝 Sample Lab Report</p>', unsafe_allow_html=True)
    st.markdown("""
    **Title:** Effect of Temperature on Enzyme Activity  
    **Objective:** To investigate how temperature affects catalase enzyme activity  
    **Hypothesis:** Enzyme activity will increase with temperature up to 37°C, then decrease  
    **Materials:** Test tubes, hydrogen peroxide, liver extract, thermometer  
    **Procedure:**  
    1. Prepare test tubes at 5 different temperatures  
    2. Add equal amounts of hydrogen peroxide and liver extract  
    3. Measure oxygen production  
    **Observations:** More bubbles at 37°C compared to lower or higher temperatures  
    **Conclusion:** Enzyme activity peaks at body temperature  
    """)
    
    st.info("👆 Upload your own lab report to get a personalized analysis!")