import streamlit as st import google.generativeai as genai from reportlab.lib.pagesizes import letter from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle from reportlab.lib.units import inch from reportlab.platypus import ( SimpleDocTemplate, Paragraph, Spacer, PageBreak, Table, TableStyle, Image as RLImage, ) from reportlab.lib.enums import TA_CENTER, TA_JUSTIFY, TA_LEFT, TA_RIGHT from reportlab.lib import colors from io import BytesIO from datetime import datetime import os from dotenv import load_dotenv import re import warnings import logging import json from typing import Tuple, Dict, Any, List import requests from PIL import Image import io
warnings.filterwarnings("ignore") os.environ.setdefault("GRPC_VERBOSITY", "ERROR") os.environ.setdefault("GLOG_minloglevel", "2") logging.getLogger("google").setLevel(logging.ERROR)
load_dotenv()
MIN_UNIVERSITY_NAME_LENGTH = 3 MIN_STUDENT_NAME_LENGTH = 2 MIN_STUDENT_ID_LENGTH = 3 MIN_PROGRAM_NAME_LENGTH = 5 MIN_SUBJECT_NAME_LENGTH = 3 MIN_TOPIC_LENGTH = 20 MAX_QUESTIONS = 10 CACHE_TTL = 3600
st.set_page_config( page_title="Assignment Maker By Ethicallogix", page_icon="📚", layout="wide", initial_sidebar_state="expanded", )
st.markdown( """ <style> .stButton>button { border-radius: 10px; transition: all 0.3s ease; } .stButton>button:hover { transform: translateY(-2px); box-shadow: 0 4px 12px rgba(0,0,0,0.15); } .reportview-container .main .block-container{ padding-top:1rem; } .success-box { padding: 1rem; border-radius: 0.5rem; background-color: #d4edda; border: 1px solid #c3e6cb; color: #155724; margin: 1rem 0; } </style> """, unsafe_allow_html=True, )
def initialize_session_state(): defaults = { "assignment_generated": False, "assignment_content": None, "generation_time": None, "total_generated": 0, "generation_history": [], "is_generating": False, "student_info": None, "section_images": {} } for key, value in defaults.items(): if key not in st.session_state: st.session_state[key] = value
initialize_session_state()
st.title("📚 Ethicallogix Assignment Maker") st.markdown( "
Generate professional academic assignments with AI-powered content and images
", unsafe_allow_html=True, ) st.markdown("---")with st.sidebar: st.header("Powered By Ethicallogix") api_key = os.getenv("GOOGLE_API_KEY", "")
# Gamma API Configuration st.subheader("🎨 Image Generation") gamma_api_key = st.text_input( "Gamma API Key (Optional)", type="password", placeholder="Enter your Gamma API key", help="Get your API key from https://gamma.app/api" ) include_images = st.checkbox("Generate Images for Sections", value=False) image_style = st.selectbox( "Image Style", ["Academic", "Professional", "Modern", "Minimalist", "Detailed"], index=0 ) gemini_model = "gemini-2.0-flash-exp" st.subheader("⚙️ Advanced Options") num_questions = st.slider("Number of Questions", 1, MAX_QUESTIONS, 3) assignment_type = st.selectbox( "Assignment Type", [ "Assignment", "Research Paper", "Problem Solving", "Essay", "Case Study", "Technical Report", "Literature Review", "Project Proposal", ], ) word_count_preference = st.selectbox( "Answer Length", ["Concise (200-300 words)", "Standard (400-600 words)", "Detailed (800-1000 words)"], index=1, ) difficulty = st.selectbox( "Difficulty Level", ["Beginner", "Intermediate", "Advanced", "Expert"], index=1 ) include_references = st.checkbox("Include Academic References (APA)", value=True) include_examples = st.checkbox("Include Practical Examples", value=True) include_learning_objectives = st.checkbox("Include Learning Objectives", value=False) include_rubric = st.checkbox("Include Grading Rubric", value=False) st.markdown("---") st.subheader("ℹ️ About") st.markdown( """ **Features:** - 📝 Q→A academic assignments - 🎨 AI-generated section images - 🎯 Optional learning objectives & rubric - 📄 Professional PDF output - 🎨 Formatted cover page - 📊 Page numbering - 💾 Multiple export formats """ ) st.markdown("---") if st.button("🔄 Reset App", use_container_width=True): for k in list(st.session_state.keys()): del st.session_state[k] st.rerun() def generate_image_gamma(prompt: str, api_key: str, style: str = "Academic") -> BytesIO: """ Generate an image using Gamma API """ try: # Gamma API endpoint (replace with actual endpoint) url = "https://api.gamma.app/v1/images/generate"
headers = { "Authorization": f"Bearer {api_key}", "Content-Type": "application/json" } # Enhance prompt with style enhanced_prompt = f"{style} style: {prompt}. Clean, professional, suitable for academic document." payload = { "prompt": enhanced_prompt, "width": 800, "height": 500, "format": "png" } response = requests.post(url, headers=headers, json=payload, timeout=30) if response.status_code == 200: return BytesIO(response.content) else: st.warning(f"Image generation failed: {response.status_code}") return None except Exception as e: st.warning(f"Error generating image: {str(e)}") return None def extract_sections(content: str) -> List[Dict[str, str]]: """ Extract main sections and their titles from the generated content """ sections = [] lines = content.splitlines() current_section = None
for line in lines: line = line.strip() # Match ## headings (main sections) if line.startswith("## "): section_title = line.replace("## ", "").replace("**", "").strip() # Skip references section if "REFERENCE" not in section_title.upper(): current_section = { "title": section_title, "content": "" } sections.append(current_section) elif current_section: current_section["content"] += line + " " return sections def generate_image_prompt(section_title: str, section_content: str, subject: str) -> str: """ Generate a descriptive prompt for image generation based on section """ # Truncate content to first 200 chars for context content_snippet = section_content[:200]
prompt = f"Create an educational illustration for {subject} about {section_title}. " prompt += f"Context: {content_snippet}... " prompt += "Make it visually clear, informative, and suitable for academic materials." return prompt st.subheader("📝 Assignment Details")
col1, col2 = st.columns(2) with col1: university_name = st.text_input( "University Name *", placeholder="University of Lahore", help=f"Minimum {MIN_UNIVERSITY_NAME_LENGTH} characters" ) student_name = st.text_input( "Student Name *", placeholder="Muhammad Haseeb", help=f"Minimum {MIN_STUDENT_NAME_LENGTH} characters" ) student_id = st.text_input( "Student ID *", placeholder="F2024332157", help=f"Minimum {MIN_STUDENT_ID_LENGTH} characters" ) program_name = st.text_input( "Program Name *", placeholder="BS Data Science", help=f"Minimum {MIN_PROGRAM_NAME_LENGTH} characters" ) with col2: st.text_input("", placeholder="", disabled=True, label_visibility="hidden") subject_name = st.text_input( "Subject Name *", placeholder="Machine Learning", help=f"Minimum {MIN_SUBJECT_NAME_LENGTH} characters" ) instructor_name = st.text_input( "Instructor Name", placeholder="Dr. Sarah Johnson" ) semester = st.text_input( "Semester/Term", placeholder="Fall 2024" )
st.markdown("### 📋 Assignment Topic / Prompt") assignment_topic = st.text_area( "Describe the topic or assignment brief *", height=140, placeholder="Example: Explain time complexity of sorting algorithms and implement merge sort in Python with detailed analysis and complexity comparison.", help=f"Minimum {MIN_TOPIC_LENGTH} characters" ) if assignment_topic: chars = len(assignment_topic) words = len(assignment_topic.split()) st.caption(f"📊 {chars} characters | {words} words")
def validate_inputs() -> List[str]: errors = [] if not university_name or len(university_name.strip()) < MIN_UNIVERSITY_NAME_LENGTH: errors.append(f"❌ University name must be at least {MIN_UNIVERSITY_NAME_LENGTH} characters.") if not student_name or len(student_name.strip()) < MIN_STUDENT_NAME_LENGTH: errors.append(f"❌ Student name must be at least {MIN_STUDENT_NAME_LENGTH} characters.") if not student_id or len(student_id.strip()) < MIN_STUDENT_ID_LENGTH: errors.append(f"❌ Student ID must be at least {MIN_STUDENT_ID_LENGTH} characters.") if not program_name or len(program_name.strip()) < MIN_PROGRAM_NAME_LENGTH: errors.append(f"❌ Program name must be at least {MIN_PROGRAM_NAME_LENGTH} characters.") if not subject_name or len(subject_name.strip()) < MIN_SUBJECT_NAME_LENGTH: errors.append(f"❌ Subject name must be at least {MIN_SUBJECT_NAME_LENGTH} characters.") if not assignment_topic or len(assignment_topic.strip()) < MIN_TOPIC_LENGTH: errors.append(f"❌ Assignment topic must be at least {MIN_TOPIC_LENGTH} characters.") if include_images and not gamma_api_key: errors.append(f"❌ Gamma API key required for image generation.") return errors
def build_prompt( topic: str, subject: str, num_qs: int, assign_type: str, diff_level: str, include_refs: bool, include_ex: bool, include_lo: bool, include_rub: bool, word_pref: str, ) -> Tuple[str, Dict[str, Any]]: word_count = "100-150" if "Concise" in word_pref: word_count = "100-150" elif "Detailed" in word_pref: word_count = "800-1000"
examples_instruction = "\n- Include practical examples and real-world applications." if include_ex else "" lo_block = "" if include_lo: lo_block = """ [List 3–5 clear, measurable learning objectives that students should achieve after completing this assignment.] """
rubric_block = "" if include_rub: rubric_block = """ [Provide 4–5 criteria with brief descriptors for Excellent, Good, Satisfactory, and Poor performance (concise table style).] """
references_instruction = "" if include_refs: references_instruction = """ """
prompt = f""" You are an expert university professor and academic writer. Create a professional {assign_type} assignment suitable for {diff_level}-level students.
CRITICAL FORMATTING RULES:
- Use ## for main section headings (e.g., ## INTRODUCTION)
- Use ### for subsection headings (e.g., ### Importance of Biofertilizers)
- Do NOT use any "Question" or "Answer" format.
- Maintain consistent academic formatting and spacing.
- Write in formal academic English throughout.
Topic: {topic} Subject: {subject}
INSTRUCTIONS:
- Structure the assignment with clear sections and subsections.
- Each subsection should explain key aspects of the topic in a coherent, analytical manner.
- Maintain academic flow — introduction, main discussion (divided into logical subtopics), and conclusion.
- Use discipline-appropriate terminology and theoretical insights{examples_instruction}.
- Provide depth, evidence-based reasoning, and critical reflection.
- Each major section should contain approximately {word_count} words.
[Write short paragraph of introduction on 2-3 lines:
- Provide background and significance of the topic
- Explain its relevance to the academic discipline
- Outline the key concepts or challenges explored
- State the overall purpose and learning outcomes of the assignment]
{lo_block} {rubric_block}
[Organize this section into several subheadings and this section is short paragraph on 2-3 lines, e.g.:
Each subsection should elaborate comprehensively with academic reasoning and examples.]
[Write 1 paragraphs synthesizing the key insights from all sections and reflecting on the broader academic and practical significance of the topic.] """
meta = { "word_count_range": word_count, "examples_instruction": examples_instruction, "num_questions": num_qs, } return prompt, meta def generate_assignment( api_key: str, topic: str, subject: str, num_qs: int, assign_type: str, diff_level: str, include_refs: bool, include_ex: bool, include_lo: bool, include_rub: bool, model_name: str, word_pref: str, ) -> Tuple[str, float]: try: genai.configure(api_key=api_key) model = genai.GenerativeModel(model_name)
prompt, meta = build_prompt( topic, subject, num_qs, assign_type, diff_level, include_refs, include_ex, include_lo, include_rub, word_pref, ) start = datetime.now() response = model.generate_content(prompt) end = datetime.now() gen_time = (end - start).total_seconds() return response.text, gen_time except Exception as e: msg = str(e) if "API_KEY_INVALID" in msg or "invalid" in msg.lower(): return ( "❌ **API Key Error**: Your API key is invalid.\n\n" "**Solution:** Get your key at: https://makersuite.google.com/app/apikey" ), 0.0 if "quota" in msg.lower() or "resource_exhausted" in msg.lower(): return ( "❌ **Quota Exceeded**: You've reached your API usage limits.\n\n" "**Solution:** Check your quota at: https://console.cloud.google.com/" ), 0.0 if "timeout" in msg.lower(): return ( "❌ **Timeout Error**: Request took too long.\n\n" "**Solution:** Try reducing word count or number of questions." ), 0.0 if "PERMISSION_DENIED" in msg: return ( "❌ **Permission Error**: API key doesn't have permission to use this model.\n\n" "**Solution:** Enable the Generative AI API in Google Cloud Console." ), 0.0 return f"❌ **Unexpected Error**: {msg}", 0.0 @st.cache_data(ttl=CACHE_TTL) def create_pdf_with_images(student_info_json: str, assignment_content: str, include_refs: bool, section_images_json: str) -> bytes: student_info = json.loads(student_info_json) section_images = json.loads(section_images_json) if section_images_json else {} buffer = create_pdf(student_info, assignment_content, include_refs, section_images) return buffer.getvalue()
def create_pdf(student_info: Dict[str, str], assignment_content: str, include_refs: bool, section_images: Dict[str, bytes] = None) -> BytesIO: buffer = BytesIO() doc = SimpleDocTemplate( buffer, pagesize=letter, topMargin=0.8 * inch, bottomMargin=0.8 * inch, leftMargin=0.9 * inch, rightMargin=0.9 * inch, )
styles = getSampleStyleSheet() # Enhanced styles title_style = ParagraphStyle( "Title", parent=styles["Heading1"], fontSize=26, alignment=TA_CENTER, textColor=colors.HexColor("#1a2384"), fontName="Helvetica-Bold", spaceAfter=10, ) subtitle_style = ParagraphStyle( "Subtitle", parent=styles["Normal"], fontSize=12, alignment=TA_CENTER, textColor=colors.HexColor("#000000"), spaceAfter=14, fontName="Helvetica-Bold", ) info_style = ParagraphStyle( "Info", parent=styles["Normal"], fontSize=10, alignment=TA_LEFT, textColor=colors.HexColor("#000000"), ) heading_style = ParagraphStyle( "Heading", parent=styles["Heading2"], fontSize=12, alignment=TA_LEFT, textColor=colors.HexColor("#0a0a0a"), fontName="Helvetica-Bold", spaceBefore=12, spaceAfter=6, ) main_heading_style = ParagraphStyle( "MainHeading", parent=styles["Heading1"], fontSize=14, alignment=TA_LEFT, textColor=colors.HexColor("#000000"), fontName="Helvetica-Bold", spaceBefore=16, spaceAfter=10, ) question_style = ParagraphStyle( "Question", parent=styles["Normal"], fontSize=11, alignment=TA_LEFT, fontName="Helvetica-Bold", textColor=colors.HexColor("#1565c0"), spaceBefore=10, spaceAfter=6, ) answer_style = ParagraphStyle( "Answer", parent=styles["Normal"], fontSize=11, alignment=TA_JUSTIFY, leading=16, spaceAfter=8, textColor=colors.HexColor("#2c3e50"), ) small_style = ParagraphStyle( "Small", parent=styles["Normal"], fontSize=9, alignment=TA_LEFT, textColor=colors.HexColor("#020202"), leading=12, ) story = [] # Enhanced cover page story.append(Spacer(1, 0.4 * inch)) story.append(Paragraph(student_info.get("university", "UNIVERSITY").upper(), title_style)) story.append(Spacer(1, 0.1 * inch)) story.append(Paragraph("ACADEMIC ASSIGNMENT", subtitle_style)) story.append(Paragraph(student_info.get("subject", ""), subtitle_style)) story.append(Spacer(1, 0.15 * inch)) # Student information table student_table = [ ["Student Name:", student_info.get("name", "")], ["Student ID:", student_info.get("id", "")], ["Program:", student_info.get("program", "")], ["Instructor:", student_info.get("instructor", "N/A")], ["Semester / Term:", student_info.get("semester", "N/A")], ["Submission Date:", datetime.now().strftime("%B %d, %Y")], ] tbl = Table(student_table, colWidths=[2.0 * inch, 4.8 * inch], hAlign="CENTER") tbl.setStyle( TableStyle( [ ("BACKGROUND", (0, 0), (0, -1), colors.HexColor("#e8f0fe")), ("TEXTCOLOR", (0, 0), (-1, -1), colors.HexColor("#2c3e50")), ("FONTNAME", (0, 0), (0, -1), "Helvetica-Bold"), ("FONTNAME", (1, 0), (1, -1), "Helvetica"), ("FONTSIZE", (0, 0), (-1, -1), 10), ("BOTTOMPADDING", (0, 0), (-1, -1), 8), ("TOPPADDING", (0, 0), (-1, -1), 8), ("GRID", (0, 0), (-1, -1), 0.5, colors.HexColor("#b8d4f1")), ("VALIGN", (0, 0), (-1, -1), "MIDDLE"), ] ) ) story.append(tbl) story.append(Spacer(1, 0.3 * inch)) story.append(Paragraph("_" * 80, small_style)) story.append(Spacer(1, 0.2 * inch)) story.append(PageBreak()) # Main content parsing and formatting content_lines = assignment_content.splitlines() in_references = False current_main_heading = None for raw_line in content_lines: line = raw_line.strip() if not line: continue clean_line = line.replace("**", "") if re.match(r"^##\s*REFERENCES", clean_line.upper()): in_references = True # Handle main headings (##) if line.startswith("## "): clean_line = line.replace("## ", "").replace("**", "") current_main_heading = clean_line story.append(Paragraph(clean_line.upper(), main_heading_style)) # Add image if available for this section if section_images and clean_line.upper() in section_images: try: img_data = section_images[clean_line.upper()] img = RLImage(img_data, width=5*inch, height=3*inch) story.append(Spacer(1, 0.1 * inch)) story.append(img) story.append(Spacer(1, 0.2 * inch)) except Exception as e: pass continue if line.startswith("### "): clean_line = line.replace("### ", "").replace("**", "") story.append(Paragraph(clean_line, heading_style)) continue if re.match(r"^Subheading:\s*", clean_line, re.IGNORECASE): subheading_text = re.sub(r"^Subheading:\s*", "", clean_line, flags=re.IGNORECASE).strip() story.append(Paragraph(subheading_text, heading_style)) continue if re.match(r"^\*\*Question:\*\*", line, re.IGNORECASE): clean_line = re.sub(r"^\*\*Question:\*\*", "Question:", line, flags=re.IGNORECASE) story.append(Paragraph(clean_line, question_style)) continue if re.match(r"^\*\*Answer:\*\*", line, re.IGNORECASE): clean_line = re.sub(r"^\*\*Answer:\*\*", "Answer:", line, flags=re.IGNORECASE) story.append(Paragraph(clean_line, question_style)) continue if re.match(r"^\*\*(INTRODUCTION|LEARNING OBJECTIVES|EVALUATION RUBRIC|REFERENCES|ASSIGNMENT BODY|CONCLUSION)[\*:]", clean_line.upper(), re.IGNORECASE): clean_text = clean_line.replace("**", "").replace(":", "").strip().upper() story.append(Paragraph(clean_text, main_heading_style)) continue if re.match(r"^(INTRODUCTION:|LEARNING OBJECTIVES:|EVALUATION RUBRIC:|REFERENCES:|ASSIGNMENT BODY:|CONCLUSION:)", clean_line, re.IGNORECASE): story.append(Paragraph(clean_line.upper(), main_heading_style)) continue if re.match(r"^Q\d+[\.\)]", clean_line): story.append(Paragraph(clean_line, question_style)) continue if re.match(r"^Answer\s*\d+:", clean_line, re.IGNORECASE): story.append(Paragraph(clean_line, question_style)) continue if in_references and re.match(r"^\d+\.\s", clean_line): story.append(Paragraph(clean_line, small_style)) continue story.append(Paragraph(clean_line, answer_style)) # Page numbering callback def add_page_number(canvas, doc): page_num = canvas.getPageNumber() text = f"Page {page_num}" canvas.setFont("Helvetica", 9) canvas.setFillColor(colors.HexColor("#6b7280")) canvas.drawRightString(7.5 * inch, 0.55 * inch, text) canvas.setStrokeColor(colors.HexColor("#d1d5db")) canvas.setLineWidth(0.5) canvas.line(0.9 * inch, 0.65 * inch, 7.6 * inch, 0.65 * inch) doc.build(story, onFirstPage=add_page_number, onLaterPages=add_page_number) buffer.seek(0) return buffer st.markdown("---") generate_col1, generate_col2, generate_col3 = st.columns([1, 2, 1]) with generate_col2: generate_button = st.button( "🚀 Generate Assignment", type="primary", use_container_width=True, disabled=st.session_state.is_generating )
if generate_button: if not api_key or len(api_key.strip()) < 10: st.error("❌ **API Key Required**: Please enter a valid Google Gemini API key in the sidebar.") st.info("💡 Get your free API key at: https://makersuite.google.com/app/apikey") else: errors = validate_inputs() if errors: st.error("**Please fix the following errors:**") for err in errors: st.markdown(err) else: st.session_state.is_generating = True progress = st.progress(0, text="Initializing...") try: progress.progress(10, text="Building prompt...") progress.progress(20, text=f"Connecting to {gemini_model}...") assignment_content, gen_time = generate_assignment( api_key=api_key, topic=assignment_topic, subject=subject_name, num_qs=num_questions, assign_type=assignment_type, diff_level=difficulty, include_refs=include_references, include_ex=include_examples, include_lo=include_learning_objectives, include_rub=include_rubric, model_name=gemini_model, word_pref=word_count_preference, ) progress.progress(60, text="Processing response...") if assignment_content.startswith("❌"): st.error(assignment_content) progress.empty() else: # Generate images if enabled section_images = {} if include_images and gamma_api_key: progress.progress(70, text="Generating section images...") sections = extract_sections(assignment_content) for idx, section in enumerate(sections[:5]): # Limit to 5 sections progress.progress(70 + (idx * 4), text=f"Generating image for: {section['title']}") image_prompt = generate_image_prompt( section['title'], section['content'], subject_name ) img_buffer = generate_image_gamma(image_prompt, gamma_api_key, image_style) if img_buffer: section_images[section['title'].upper()] = img_buffer st.session_state.section_images = section_images progress.progress(90, text="Finalizing...") # Save to session state st.session_state.assignment_content = assignment_content st.session_state.assignment_generated = True st.session_state.student_info = { "university": university_name, "name": student_name, "id": student_id, "program": program_name, "subject": subject_name, "instructor": instructor_name or "N/A", "semester": semester or "N/A", } st.session_state.total_generated += 1 st.session_state.generation_time = gen_time # Add to history st.session_state.generation_history.append({ "timestamp": datetime.now(), "subject": subject_name, "student": student_name, "gen_time": gen_time }) progress.progress(100, text="Complete! ✨") st.success(f"✅ **Assignment generated successfully!** (Generation time: {gen_time:.1f}s)") if include_images and section_images: st.info(f"🎨 Generated {len(section_images)} section images") # Word count word_count = len(assignment_content.split()) st.info(f"📊 **Content Statistics:** {word_count:,} words | {len(assignment_content):,} characters") # Preview with enhanced display with st.expander("📄 Preview Assignment Content", expanded=True): # Show images in preview if available if section_images: sections = extract_sections(assignment_content) for section in sections: if section['title'].upper() in section_images: st.markdown(f"### {section['title']}") img_buffer = section_images[section['title'].upper()] img_buffer.seek(0) st.image(img_buffer, caption=f"Illustration for {section['title']}", use_container_width=True) st.markdown(assignment_content) # Create PDF and download options st.markdown("### 💾 Download Options") col1, col2, col3 = st.columns(3) student_info_json = json.dumps(st.session_state.student_info) section_images_json = json.dumps({k: v.getvalue() if hasattr(v, 'getvalue') else v for k, v in section_images.items()}) if section_images else "" pdf_bytes = create_pdf_with_images( student_info_json, assignment_content, include_references, section_images_json ) base_filename = f"{student_name.replace(' ', '_')}_{subject_name.replace(' ', '_')}_{datetime.now().strftime('%Y%m%d')}" with col1: st.download_button( "📥 Download PDF", data=pdf_bytes, file_name=f"{base_filename}.pdf", mime="application/pdf", use_container_width=True, ) with col2: st.download_button( "📥 Download Markdown", data=assignment_content, file_name=f"{base_filename}.md", mime="text/markdown", use_container_width=True, ) with col3: st.download_button( "📥 Download Text", data=assignment_content, file_name=f"{base_filename}.txt", mime="text/plain", use_container_width=True, ) progress.empty() except Exception as e: st.error(f"❌ **Unexpected Error**: {str(e)}") st.info("💡 Try refreshing the page or checking your API key.") progress.empty() finally: st.session_state.is_generating = False if st.session_state.assignment_generated and st.session_state.assignment_content and not st.session_state.is_generating: st.markdown("---") st.info("💡 Previous assignment available below")
with st.expander("📖 View Previous Assignment", expanded=False): word_count = len(st.session_state.assignment_content.split()) st.caption(f"📊 {word_count:,} words | Generated: {st.session_state.generation_history[-1]['timestamp'].strftime('%Y-%m-%d %H:%M')}") # Show images if available if st.session_state.section_images: sections = extract_sections(st.session_state.assignment_content) for section in sections: if section['title'].upper() in st.session_state.section_images: st.markdown(f"### {section['title']}") img_buffer = st.session_state.section_images[section['title'].upper()] if isinstance(img_buffer, BytesIO): img_buffer.seek(0) st.image(img_buffer, caption=f"Illustration for {section['title']}", use_container_width=True) st.markdown(st.session_state.assignment_content) if st.session_state.student_info: st.markdown("### 💾 Download Previous Assignment") col1, col2, col3 = st.columns(3) student_info_json = json.dumps(st.session_state.student_info) section_images_json = json.dumps({k: v.getvalue() if hasattr(v, 'getvalue') else v for k, v in st.session_state.section_images.items()}) if st.session_state.section_images else "" pdf_bytes = create_pdf_with_images( student_info_json, st.session_state.assignment_content, include_references, section_images_json ) prev_base_filename = f"{st.session_state.student_info['name'].replace(' ', '_')}_{st.session_state.student_info['subject'].replace(' ', '_')}_{datetime.now().strftime('%Y%m%d')}" with col1: st.download_button( "📥 PDF", data=pdf_bytes, file_name=f"{prev_base_filename}.pdf", mime="application/pdf", use_container_width=True, ) with col2: st.download_button( "📥 Markdown", data=st.session_state.assignment_content, file_name=f"{prev_base_filename}.md", mime="text/markdown", use_container_width=True, ) with col3: st.download_button( "📥 Text", data=st.session_state.assignment_content, file_name=f"{prev_base_filename}.txt", mime="text/plain", use_container_width=True, ) if not st.session_state.assignment_generated: st.markdown("---") st.markdown("### 💡 Tips for Best Results")
tips_col1, tips_col2 = st.columns(2) with tips_col1: st.markdown(""" **Topic Guidelines:** - Be specific and clear about requirements - Include context and scope - Mention any specific concepts to cover - Specify format preferences (if any) **Image Generation:** - Enable images for visual learning enhancement - Choose appropriate style for your subject - Images are generated for main sections only """) with tips_col2: st.markdown(""" **Quality Tips:** - Choose appropriate difficulty level - Enable examples for better understanding - Include references for academic credibility - Adjust word count based on depth needed **API Keys:** - Gemini API: Required for text generation - Gamma API: Optional for image generation - Keep your API keys secure """) st.markdown("---") st.markdown( """
Developed by Muhammad Haseeb
Version 2.1 | Enhanced Edition with Image Generation
with st.sidebar: st.markdown("---") st.markdown("### 🆘 Developer Details") st.markdown(""" This Application Developed by Muhammad Haseeb Raza
**Image Generation:** - Powered by Gamma API - Generates relevant illustrations for each section - Enhances visual learning experience - Optional feature - can be disabled **Common Issues:** - Ensure both API keys are valid - Image generation may take longer - Images are limited to 5 sections max **Best Practices:** - Save assignments immediately after generation - Keep topics focused and specific - Review and edit generated content - Cite sources appropriately - Use images to enhance understanding """) st.markdown("---") st.markdown( """ <div style='text-align:center; font-size:0.8em; color:#9ca3af'> © 2025 Ethicallogix<br> All Rights Reserved </div> """, unsafe_allow_html=True, )