Update app.py

app.py

@@ -390,40 +390,39 @@ def retrieve_bot_answer(query):
 
 
 
-@gr.app
-def main():
-    title("Docuverse")
-
-    # Upload files
-    uploaded_files = gr.file_uploader("Upload your documents", types=["pdf", "md", "txt", "csv", "py", "epub", "html", "ppt", "pptx", "doc", "docx", "odt", "ipynb"], multiple=True)
-
-    if uploaded_files:
-        # Process uploaded files
-        for uploaded_file in uploaded_files:
-            print(f"Uploaded: {uploaded_file.name}")
-            print(f"Uploaded: {type(uploaded_file)}")
-
-        print("Chat with the Document:")
-        query = gr.text_input("Ask a question:")
-
-        if gr.button("Get Answer"):
-            if query:
-                # Load model, set prompts, create vector database, and retrieve answer
-                try:
-                    llm = load_model()
-                    prompt = set_custom_prompt()
-                    CONDENSE_QUESTION_PROMPT = set_custom_prompt_condense()
-                    loaded_documents = load_document(uploaded_files)
-                    db = create_vector_database(loaded_documents)
-                    response = retrieve_bot_answer(query)
-
-                    # Display bot response
-                    print("Bot Response:")
-                    print(response)
-                except Exception as e:
-                    print(f"An error occurred: {str(e)}")
-            else:
-                print("Please enter a question.")
+
+app = GradiOApp(title="Docuverse")
+
+# Upload files
+uploaded_files = app.file_uploader("Upload your documents", types=["pdf", "md", "txt", "csv", "py", "epub", "html", "ppt", "pptx", "doc", "docx", "odt", "ipynb"], multiple=True)
+
+if uploaded_files:
+    # Process uploaded files
+    for uploaded_file in uploaded_files:
+        print(f"Uploaded: {uploaded_file.name}")
+        print(f"Uploaded: {type(uploaded_file)}")
+
+    print("Chat with the Document:")
+    query = app.text_input("Ask a question:")
+
+    if app.button("Get Answer"):
+        if query:
+            # Load model, set prompts, create vector database, and retrieve answer
+            try:
+                llm = load_model()
+                prompt = set_custom_prompt()
+                CONDENSE_QUESTION_PROMPT = set_custom_prompt_condense()
+                loaded_documents = load_document(uploaded_files)
+                db = create_vector_database(loaded_documents)
+                response = retrieve_bot_answer(query)
+
+                # Display bot response
+                print("Bot Response:")
+                print(response)
+            except Exception as e:
+                print(f"An error occurred: {str(e)}")
+        else:
+            print("Please enter a question.")
 
 if __name__ == "__main__":
-    main()
+    app.run()