Create app.py

app.py

@@ -0,0 +1,75 @@
+import gradio as gr
+from functions import extract_text_from_pdf, format_content, split_into_snippets, build_prompts
+
+def process_inputs(pdf_file, model_choice, output_format, oauth_token: gr.OAuthToken | None = None):
+    """Process PDF and generate summary"""
+    if oauth_token is None:
+        return "### Please log in to use this service"
+    
+    if not pdf_file:
+        return "### Please upload a PDF file"
+    
+    try:
+        text = extract_text_from_pdf(pdf_file.name)
+        return f"### Processing successful with {model_choice}!"
+    except Exception as e:
+        return f"### Error: {str(e)}"
+
+# Define core interface components
+iface = gr.Interface(
+    fn=process_inputs,
+    inputs=[
+        gr.File(
+            label="Upload PDF",
+            file_types=[".pdf"]
+        ),
+        gr.Dropdown(
+            choices=[
+                "GPT-3.5",
+                "GPT-4",
+                "Claude-3",
+                "Mistral"
+            ],
+            label="Model",
+            value="GPT-3.5"
+        ),
+        gr.Radio(
+            choices=["TXT", "MD", "HTML"],
+            label="Format",
+            value="TXT"
+        )
+    ],
+    outputs=gr.Markdown(
+        label="Output",
+        value="### Upload your PDF to begin"
+    ),
+    flagging_mode="never",
+    css="""
+        .gradio-container {
+            max-width: 800px !important;
+            margin: 0 auto !important;
+        }
+        .container {
+            max-width: 800px !important;
+            margin: 0 auto !important;
+            padding: 2rem !important;
+        }
+    """
+)
+
+# Create main app
+with gr.Blocks(theme=gr.themes.Default()) as demo:
+    gr.Markdown("## 🚀 PDF to LLM Summarizer")
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("📄 Extract and summarize text from PDFs using state-of-the-art language models")
+        with gr.Column():
+            gr.LoginButton(min_width=200)
+    
+    iface.render()
+    
+    gr.Markdown("Made with Gradio")
+
+if __name__ == "__main__":
+    demo.launch()