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| # 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!") |