import streamlit as st import pandas as pd from fpdf import FPDF import matplotlib.pyplot as plt import seaborn as sns import io from datetime import datetime import tempfile # To handle temporary files import os # To interact with the operating system class ComprehensivePDF(FPDF): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.user_name = "" def header(self): self.set_font('Arial', 'B', 12) self.cell(0, 10, 'Visio AI - Comprehensive Analysis Report', 0, 1, 'C') self.ln(5) def footer(self): self.set_y(-15) self.set_font('Arial', 'I', 8) self.cell(0, 10, f'Page {self.page_no()}', 0, 0, 'C') def add_title_page(self, user_name=""): self.user_name = user_name self.add_page() self.set_font('Arial', 'B', 24) self.cell(0, 20, 'Comprehensive Analysis Report', 0, 1, 'C') self.ln(20) self.set_font('Arial', '', 12) if self.user_name: self.cell(0, 10, f"Prepared for: {self.user_name}", 0, 1, 'C') self.cell(0, 10, f"Date Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", 0, 1, 'C') self.ln(20) try: self.image("images/favicon.png", x=85, y=100, w=40) except FileNotFoundError: self.set_font('Arial', 'I', 10) self.cell(0, 10, "[Logo Not Found]", 0, 1, 'C') self.set_y(-40) self.set_font('Arial', 'I', 10) self.cell(0, 10, "Generated by Visio AI", 0, 1, 'C') def add_section_title(self, title): self.add_page() self.set_font('Arial', 'B', 16) self.cell(0, 10, title, 0, 1, 'L') self.ln(5) def add_text_content(self, title, content): self.set_font('Arial', 'B', 12) self.cell(0, 10, title, 0, 1, 'L') self.set_font('Courier', '', 10) self.multi_cell(0, 5, content) self.ln(5) # --- NEW BULLETPROOF HELPER FUNCTION --- def add_image_from_object(self, image_object, width): """ Saves a matplotlib figure or PIL image to a temporary file and adds it to the PDF, then deletes the file. """ fp = None try: # Create a named temporary file with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as fp: # Save the image object to the temporary file image_object.save(fp, format="PNG") temp_path = fp.name # Add the image to the PDF from the temporary file path self.image(temp_path, w=width) finally: # Ensure the temporary file is deleted if fp and os.path.exists(fp.name): os.remove(fp.name) def render_report_page(): st.markdown("

📄 Comprehensive Report Generator

", unsafe_allow_html=True) st.markdown("

Generate a complete PDF report of your session's activities.

", unsafe_allow_html=True) user_name = st.text_input("Enter your name (optional, will be shown on the report cover)") if st.button("Generate Full Report 🚀"): if 'updated_df' not in st.session_state and 'viz_ai_img_result' not in st.session_state and 'word_cloud_result' not in st.session_state: st.warning("There is no activity to report. Please train a model or use the AI tools first.") return with st.spinner("Assembling your comprehensive report..."): pdf = ComprehensivePDF() pdf.add_title_page(user_name) # --- Section 1: Data Analysis & ML --- if 'updated_df' in st.session_state and st.session_state.updated_df is not None: df = st.session_state.updated_df pdf.add_section_title("1. Dataset & Machine Learning Analysis") buffer = io.StringIO() df.info(buf=buffer) pdf.add_text_content("Dataset Information", buffer.getvalue()) pdf.add_text_content("Numerical Summary", df.describe(include='number').to_string()) if not df.select_dtypes(include='object').empty: pdf.add_text_content("Categorical Summary", df.describe(include='object').to_string()) if 'trained_model' in st.session_state and st.session_state.trained_model is not None: metrics = st.session_state.model_metrics algo_name = st.session_state.selected_algo_name pdf.set_font('Arial', 'B', 12) pdf.cell(0, 10, f"Machine Learning Model: {algo_name}", 0, 1, 'L') metrics_str = "" for key, val in metrics.items(): if key != 'Confusion Matrix': metrics_str += f"{key}: {val:.4f}\n" if isinstance(val, float) else f"{key}: {val}\n" pdf.add_text_content("Performance Metrics", metrics_str) if 'Confusion Matrix' in metrics: fig_cm, ax_cm = plt.subplots() sns.heatmap(metrics['Confusion Matrix'], annot=True, fmt='d', cmap='Blues', ax=ax_cm) ax_cm.set_title('Confusion Matrix') pdf.set_font('Arial', 'B', 12) pdf.cell(0, 10, "Confusion Matrix", 0, 1, 'L') pdf.add_image_from_object(fig_cm, width=170) plt.close(fig_cm) # Close the figure to free memory # --- Section 2: Viz AI Image Analysis --- if 'viz_ai_img_result' in st.session_state and st.session_state.viz_ai_img_result is not None: img_result = st.session_state.viz_ai_img_result pdf.add_section_title("2. Viz AI Image Analysis") pdf.add_image_from_object(img_result['image'], width=150) pdf.ln(5) pdf.add_text_content("Model Used", img_result['model']) pdf.add_text_content("User Prompt", img_result['prompt']) pdf.add_text_content("AI Analysis", img_result['analysis']) # --- Section 3: Word Cloud --- if 'word_cloud_result' in st.session_state and st.session_state.word_cloud_result is not None: wc_result = st.session_state.word_cloud_result pdf.add_section_title("3. Word Cloud Analysis") pdf.add_text_content("Source File", wc_result['source']) pdf.add_text_content("Settings", wc_result['settings']) pdf.set_font('Arial', 'B', 12) pdf.cell(0, 10, "Generated Word Cloud", 0, 1, 'L') pdf.add_image_from_object(wc_result['figure'], width=170) plt.close(wc_result['figure']) # Close the figure to free memory # --- Generate Download --- pdf_output = pdf.output() st.success("Report Generated!") st.download_button( label="📥 Download Full Report", data=pdf_output, file_name=f"VisioAI_Comprehensive_Report_{datetime.now().strftime('%Y%m%d')}.pdf", mime="application/pdf" )