import streamlit as st import os import pandas as pd import fitz # PyMuPDF from google import genai from google.genai import types from docx import Document from pptx import Presentation from reportlab.lib.pagesizes import A4 from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer from reportlab.lib.styles import getSampleStyleSheet from bs4 import BeautifulSoup import re import base64 # Set Gemini API Key client = genai.Client(api_key=os.environ.get("GEMINI_API_KEY")) # --------- File Extractors --------- def extract_text_from_docx(docx_file): document = Document(docx_file) return "\n".join([para.text for para in document.paragraphs]) def extract_text_from_csv(csv_file): df = pd.read_csv(csv_file) return df.to_string(index=False) def extract_text_from_xlsx(xlsx_file): df = pd.read_excel(xlsx_file) return df.to_string(index=False) def extract_text_from_pptx(pptx_file): prs = Presentation(pptx_file) text_runs = [] for slide in prs.slides: for shape in slide.shapes: if hasattr(shape, "text"): text_runs.append(shape.text) return "\n".join(text_runs) def extract_text_from_pdf(pdf_file): doc = fitz.open(stream=pdf_file.read(), filetype="pdf") text = "" for page in doc: text += page.get_text() return text def extract_text_from_html(html_file): soup = BeautifulSoup(html_file.read(), "html.parser") return soup.get_text() def extract_text_from_tex(tex_file): content = tex_file.read().decode("utf-8") content = re.sub(r'\\[a-zA-Z]+\{[^}]*\}', '', content) content = re.sub(r'\\[a-zA-Z]+', '', content) return content def process_image(image_file): image_bytes = image_file.read() encoded_image = base64.b64encode(image_bytes).decode("utf-8") return { "inline_data": { "mime_type": image_file.type, "data": encoded_image } } def export_conversation_to_pdf(conversation_history): pdf_path = "Conversation.pdf" doc = SimpleDocTemplate(pdf_path, pagesize=A4) styles = getSampleStyleSheet() elements = [] for i, (user_q, gemini_a) in enumerate(conversation_history): elements.append(Paragraph(f"Q{i+1}: {user_q}", styles["Normal"])) elements.append(Spacer(1, 8)) elements.append(Paragraph(f"A{i+1}: {gemini_a.replace(chr(10), '
')}", styles["Normal"])) elements.append(Spacer(1, 16)) doc.build(elements) return pdf_path # --------- Main App --------- def main(): st.set_page_config(page_title="Gemini 2.5 Pro Chat Q&A", layout="wide") st.title("📄 Chat with Your Documents leveraging Internet Using Gemini 2.5 Pro (Team 18))") if "conversation" not in st.session_state: st.session_state.conversation = [] if "documents_text" not in st.session_state: st.session_state.documents_text = [] if "chat_active" not in st.session_state: st.session_state.chat_active = True if "chat_history" not in st.session_state: st.session_state.chat_history = [] uploaded_files = st.file_uploader( "Upload files (.txt, .docx, .csv, .xlsx, .pptx, .pdf, .html, .htm, .tex, .jpg, .jpeg, .png):", type=["txt", "docx", "csv", "xlsx", "pptx", "pdf", "html", "htm", "tex", "jpg", "jpeg", "png"], accept_multiple_files=True ) if uploaded_files: all_text_content = "" for uploaded_file in uploaded_files: filetype = uploaded_file.name.split(".")[-1].lower() try: if filetype == "txt": all_text_content += uploaded_file.read().decode("utf-8") + "\n" elif filetype == "docx": all_text_content += extract_text_from_docx(uploaded_file) + "\n" elif filetype == "csv": all_text_content += extract_text_from_csv(uploaded_file) + "\n" elif filetype == "xlsx": all_text_content += extract_text_from_xlsx(uploaded_file) + "\n" elif filetype == "pptx": all_text_content += extract_text_from_pptx(uploaded_file) + "\n" elif filetype == "pdf": all_text_content += extract_text_from_pdf(uploaded_file) + "\n" elif filetype in ["html", "htm"]: all_text_content += extract_text_from_html(uploaded_file) + "\n" elif filetype == "tex": all_text_content += extract_text_from_tex(uploaded_file) + "\n" elif filetype in ["jpg", "jpeg", "png"]: image_data = process_image(uploaded_file) st.session_state.image_data = image_data all_text_content += "Image uploaded and processed.\n" st.image(uploaded_file, caption=uploaded_file.name, use_container_width=True) else: st.error(f"Unsupported file format: {uploaded_file.name}") except Exception as e: st.error(f"Failed to extract text from {uploaded_file.name}: {e}") st.session_state.documents_text = all_text_content if st.session_state.documents_text: st.markdown("### 💬 Conversation") for user_q, gemini_a in st.session_state.conversation: st.markdown(f"**You:** {user_q}") st.markdown(f"**Gemini:**\n\n{gemini_a}") if st.session_state.chat_active: with st.form(key="chat_form", clear_on_submit=True): user_input = st.text_input("Ask a question about the documents (type 'exit' to stop):") submit = st.form_submit_button("Send") if submit and user_input: if user_input.strip().lower() == "exit": st.session_state.chat_active = False st.success("Chat ended. Reload to start again.") else: with st.spinner("Gemini is thinking..."): content_blocks = [] if st.session_state.conversation: history_text = "\n\n".join( f"Q: {entry[0]}\nA: {entry[1]}" for entry in st.session_state.conversation ) content_blocks.append({"text": f"Previous conversation:\n{history_text}"}) if st.session_state.documents_text.strip(): content_blocks.append({"text": f"Context:\n{st.session_state.documents_text}"}) if "image_data" in st.session_state: content_blocks.append(st.session_state.image_data) content_blocks.append({"text": f"Question: {user_input}"}) # ✅ Gemini with Internet Search response = client.models.generate_content( model="gemini-2.0-flash", contents=content_blocks, config={"tools": [{"google_search": {}}]} ) st.session_state.conversation.append((user_input, response.text)) st.success("💡 Answer:") st.write(response.text) st.session_state.chat_history.append({ "question": user_input, "answer": response.text }) if st.session_state.conversation: pdf_path = export_conversation_to_pdf(st.session_state.conversation) with open(pdf_path, "rb") as f: st.download_button( label="📥 Export Conversation as PDF", data=f, file_name="Conversation.pdf", mime="application/pdf" ) if __name__ == "__main__": main()