Update app.py

app.py

@@ -350,39 +350,73 @@ def retrieve_bot_answer(query):
 
 # from your_module import load_model, set_custom_prompt, set_custom_prompt_condense, create_vector_database, retrieve_bot_answer
 
-def main():
-    st.title("Docuverse")
+# def main():
+#     st.title("Docuverse")
+
+#     # Upload files
+#     uploaded_files = st.file_uploader("Upload your documents", type=["pdf", "md", "txt", "csv", "py", "epub", "html", "ppt", "pptx", "doc", "docx", "odt", "ipynb"], accept_multiple_files=True)
+
+#     if uploaded_files:
+#         # Process uploaded files
+#         for uploaded_file in uploaded_files:
+#             st.write(f"Uploaded: {uploaded_file.name}")
+#             st.write(f"Uploaded: {type(uploaded_file)}")
+
+#         st.write("Chat with the Document:")
+#         query = st.text_input("Ask a question:")
+
+#         if st.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
+#                     st.write("Bot Response:")
+#                     st.write(response)
+#                 except Exception as e:
+#                     st.error(f"An error occurred: {str(e)}")
+#             else:
+#                 st.warning("Please enter a question.")
+
+# if __name__ == "__main__":
+#     main()
+
+import gradio as gr
 
+def main():
     # Upload files
-    uploaded_files = st.file_uploader("Upload your documents", type=["pdf", "md", "txt", "csv", "py", "epub", "html", "ppt", "pptx", "doc", "docx", "odt", "ipynb"], accept_multiple_files=True)
-
-    if uploaded_files:
-        # Process uploaded files
-        for uploaded_file in uploaded_files:
-            st.write(f"Uploaded: {uploaded_file.name}")
-            st.write(f"Uploaded: {type(uploaded_file)}")
-
-        st.write("Chat with the Document:")
-        query = st.text_input("Ask a question:")
-
-        if st.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
-                    st.write("Bot Response:")
-                    st.write(response)
-                except Exception as e:
-                    st.error(f"An error occurred: {str(e)}")
-            else:
-                st.warning("Please enter a question.")
+    file_uploader = gr.inputs.file_uploader(multiple=True, accept_multiple_files=True, types=["pdf", "md", "txt", "csv", "py", "epub", "html", "ppt", "pptx", "doc", "docx", "odt", "ipynb"])
+
+    # Process uploaded files
+    def process_files(files):
+        for file in files:
+            print(f"Uploaded: {file.name}")
+            print(f"Uploaded: {type(file)}")
+
+    query = gr.inputs.text(label="Ask a question:")
+
+    # Load model, set prompts, create vector database, and retrieve answer
+    def get_answer(query, files):
+        try:
+            llm = load_model()
+            prompt = set_custom_prompt()
+            CONDENSE_QUESTION_PROMPT = set_custom_prompt_condense()
+            loaded_documents = load_document(files)
+            db = create_vector_database(loaded_documents)
+            response = retrieve_bot_answer(query)
+
+            # Display bot response
+            return response
+        except Exception as e:
+            return f"An error occurred: {str(e)}"
+
+    gr.outputs.text(get_answer, query, file_uploader)
 
 if __name__ == "__main__":
-    main()
+    gr.Interface(main).launch()