app.py

import streamlit as st
import time
import PyPDF2  # Import PyPDF2 for PDF text extraction
from openai import OpenAI
from docx import Document
from docx.shared import Pt
from docx.enum.text import WD_PARAGRAPH_ALIGNMENT
import os

# Set the page configuration
st.set_page_config(page_title="Report Generation AI")

# Title and caption
st.title("AI Report Generator")
st.caption("Generate Professional Reports from PDF Documents")

# Sidebar for API Key input
with st.sidebar:
    OPENAI_API_KEY = st.text_input("Enter your Access Key", type="password")

# Check for valid API key
if OPENAI_API_KEY:
    client = OpenAI(api_key=OPENAI_API_KEY)
else:
    st.error("Please enter your Access Key to continue.")
    st.stop()

ASSISTANT_ID = "asst_d68xqxiRtvYkmewBPugwZaGx"

# Initialize session state for chat history
if "messages" not in st.session_state:
    st.session_state["messages"] = []

# Clear chat button above chat input
if st.button("Clear Chat", use_container_width=True):
    st.session_state.messages = []
    st.rerun()

# Display chat history
for message in st.session_state.messages:
    role, content = message["role"], message["content"]
    st.chat_message(role).write(content)

# Process user input
uploaded_file = st.file_uploader("Upload PDF file", type=["pdf"])

if uploaded_file:
    # Read the PDF file using PyPDF2
    pdf_reader = PyPDF2.PdfReader(uploaded_file)
    full_text = ""
    
    # Extract text from each page
    for page_num in range(len(pdf_reader.pages)):
        page = pdf_reader.pages[page_num]
        full_text += page.extract_text()

    st.write("Text extracted from PDF:")
    st.text_area("Extracted Text", full_text, height=300)

    # Process user input for assistant
    prompt = f"Please analyze the following text from the PDF: {full_text[:1000]}"  # Limit to the first 1000 chars for clarity
    st.session_state.messages.append({"role": "user", "content": prompt})
    st.chat_message("user").write(prompt)

    try:
        # Create a new thread for conversation
        thread = client.beta.threads.create()
        thread_id = thread.id

        # Send user message to OpenAI API
        client.beta.threads.messages.create(
            thread_id=thread_id,
            role="user",
            content=prompt
        )

        # Run the assistant to generate a response
        run = client.beta.threads.runs.create(
            thread_id=thread_id,
            assistant_id=ASSISTANT_ID
        )

        # Wait for response
        while True:
            run_status = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run.id)
            if run_status.status == "completed":
                break
            time.sleep(1)

        # Retrieve assistant response
        messages = client.beta.threads.messages.list(thread_id=thread_id)
        assistant_message = messages.data[0].content[0].text.value

        # Display assistant's response
        st.chat_message("assistant").write(assistant_message)

        # Store in session state
        st.session_state.messages.append({"role": "assistant", "content": assistant_message})

        # Generate Word (DOCX) file for download
        doc = Document()

        # Add a title and style
        title = doc.add_heading('AI Assistant Report', 0)
        title.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER  # Center align the title
        run = title.add_run("AI Assistant Report")
        run.bold = True
        run.font.size = Pt(18)

        # Add Executive Summary
        doc.add_heading('Executive Summary', level=1)
        doc.add_paragraph("Based on the provided PDF content, the analysis has been carried out. "
                          "Key insights and analysis are provided below, along with a variance analysis "
                          "and considerations for future actions.")

        # Step 1: Text Analysis
        doc.add_heading('Step 1: Text Analysis', level=1)
        
        # Create a table for the extracted data
        table = doc.add_table(rows=1, cols=6)
        hdr_cells = table.rows[0].cells
        hdr_cells[0].text = 'Sales (2025)'
        hdr_cells[1].text = 'Sales (2024)'
        hdr_cells[2].text = 'Sales Variance (%)'
        hdr_cells[3].text = 'Gross Profit (2025)'
        hdr_cells[4].text = 'Gross Profit (2024)'
        hdr_cells[5].text = 'Gross Profit Variance (%)'

        # Add sample row data (the actual data should be dynamically inserted here from the PDF)
        row = table.add_row().cells
        row[0].text = "1,392"
        row[1].text = "1,400"
        row[2].text = "-0.5"
        row[3].text = "200"
        row[4].text = "207"
        row[5].text = "-3.0"

        # Step 2: Assistant's Analysis
        doc.add_heading('Step 2: Assistant Analysis', level=1)
        doc.add_paragraph(f"The AI Assistant's insights are:\n{assistant_message}")
        
        # Add tables for key insights like sales, gross profit, and variance analysis
        doc.add_heading('Key Insights and Trends', level=2)
        doc.add_paragraph("Here is a summary of the analysis based on the provided data:")

        # Add another table for detailed analysis if necessary
        detailed_table = doc.add_table(rows=1, cols=3)
        detailed_hdr = detailed_table.rows[0].cells
        detailed_hdr[0].text = 'Month'
        detailed_hdr[1].text = 'Sales (ZAR)'
        detailed_hdr[2].text = 'Gross Profit (ZAR)'

        # Add sample data for detailed insights
        month_data = [
            ("February 2025", "1,392,000", "200,000"),
            ("February 2024", "1,400,000", "207,000"),
            ("Budgeted February 2025", "1,498,000", "221,000")
        ]

        for month, sales, profit in month_data:
            row = detailed_table.add_row().cells
            row[0].text = month
            row[1].text = sales
            row[2].text = profit

        # Style Table Text (bold for headings, adjust font size)
        for cell in hdr_cells:
            cell.paragraphs[0].runs[0].bold = True
            cell.paragraphs[0].runs[0].font.size = Pt(10.5)
        
        # Adjust font size and add bold to data cells
        for row in table.rows:
            for cell in row.cells:
                cell.paragraphs[0].runs[0].font.size = Pt(10.5)

        # Saving the DOCX file
        word_filename = "AI_Report_Formatted.docx"
        doc.save(word_filename)

        # Provide download link
        with open(word_filename, "rb") as file:
            st.download_button(
                label="Download the Report",
                data=file.read(),
                file_name=word_filename,
                mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document"
            )

    except Exception as e:
        st.error(f"Error processing the chat: {str(e)}")