full sync with remote repo

app.py

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+import os
+import base64
+import requests
+import streamlit as st
+from reportlab.pdfgen import canvas
+from reportlab.lib.pagesizes import letter
+from io import BytesIO
+from PyPDF2 import PdfReader
+from PIL import Image
+
+# OpenAI API Key
+api_key = os.getenv("OPENAI_API_KEY")  # Ensure this environment variable is set
+
+headers = {
+    "Content-Type": "application/json",
+    "Authorization": f"Bearer {api_key}"
+}
+
+def extract_text_and_images_from_pdf(pdf_file):
+    text_content = ""
+    images = []
+
+    # Convert UploadedFile to BytesIO for compatibility
+    pdf_stream = BytesIO(pdf_file.read())
+
+    # Extract text using PdfReader
+    pdf_reader = PdfReader(pdf_stream)
+    for page in pdf_reader.pages:
+        text_content += page.extract_text()
+
+    # Extract images (This part requires creating images using ReportLab for demonstration)
+    # In a real scenario, extracting images from PDF is more complex and usually done with specialized libraries.
+    # Add image extraction logic if needed
+
+    return text_content, images
+
+def main():
+    st.title("Multimodal PDF Processing using GPT-4 Turbo Model")
+
+    text = """Prof. Louie F. Cervantes, M. Eng. (Information Engineering)
+    CCS 229 - Intelligent Systems
+    Department of Computer Science
+    College of Information and Communications Technology
+    West Visayas State University
+    """
+    with st.expander("About"):
+        st.text(text)
+
+    st.write("Upload a PDF file for analysis.")
+
+    # File upload for PDF
+    uploaded_pdf = st.file_uploader("Upload a PDF", type=["pdf"])
+    if uploaded_pdf is not None:
+        text_content, images = extract_text_and_images_from_pdf(uploaded_pdf)
+
+        # Display extracted text
+        st.subheader("Extracted Text")
+        st.text(text_content)
+
+        # Display extracted images
+        if images:
+            st.subheader("Extracted Images")
+            for img in images:
+                st.image(img, caption="Extracted Image", use_container_width=True)
+
+        # Prepare the multimodal payload
+        payload = {
+            "model": "gpt-4-turbo",
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": text_content}
+                        # Images can be added here if extracted
+                    ]
+                }
+            ],
+            "max_tokens": 2048,
+        }
+
+        if st.button("Generate Response"):
+            with st.spinner("Processing..."):
+                response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
+
+                if response.status_code != 200:
+                    st.error(f"Error: {response.status_code} - {response.text}")
+                else:
+                    content = response.json()
+                    content_string = content['choices'][0]['message']['content']
+                    st.success("Response generated!")
+                    st.markdown(f"AI Response: {content_string}")
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+streamlit
+requests
+Pillow
+reportlab
+PyPDF2