Update app.py

app.py

@@ -115,24 +115,24 @@ def load_model():
     )
     return llm
 
-def load_document(
-    # file_path: str,
-    uploaded_files: list,
-    mapping: dict = FILE_LOADER_MAPPING,
-    default_loader: BaseLoader = UnstructuredFileLoader,
-) -> Document:
-    loaded_documents = []
-    for uploaded_file in uploaded_files:
-        # Choose loader from mapping, load default if no match found
-        # ext = "." + uploaded_files.rsplit(".", 1)[-1]
-        ext = os.path.splitext(uploaded_file.name)[-1][1:].lower()
-        if ext in mapping:
-            loader_class, loader_args = mapping[ext]
-            loader = loader_class(uploaded_file, **loader_args)
-        else:
-            loader = default_loader(uploaded_file)
-        loaded_documents.extend(loader.load())
-    return loaded_documents
+# def load_document(
+#     # file_path: str,
+#     uploaded_files: list,
+#     mapping: dict = FILE_LOADER_MAPPING,
+#     default_loader: BaseLoader = UnstructuredFileLoader,
+# ) -> Document:
+#     loaded_documents = []
+#     for uploaded_file in uploaded_files:
+#         # Choose loader from mapping, load default if no match found
+#         # ext = "." + uploaded_files.rsplit(".", 1)[-1]
+#         ext = os.path.splitext(uploaded_file.name)[-1][1:].lower()
+#         if ext in mapping:
+#             loader_class, loader_args = mapping[ext]
+#             loader = loader_class(uploaded_file, **loader_args)
+#         else:
+#             loader = default_loader(uploaded_file)
+#         loaded_documents.extend(loader.load())
+#     return loaded_documents
 
 def create_vector_database(loaded_documents):
     # DB_DIR: str = os.path.join(ABS_PATH, "db")
@@ -351,78 +351,45 @@ 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")
-
-#     # 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()
-
-
-
-
-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.")
+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)}")
+            ext = os.path.splitext(uploaded_file.name)[-1][1:].lower()
+            if ext in FILE_LOADER_MAPPING:
+                loader_class, loader_args = FILE_LOADER_MAPPING[ext]
+                loader = loader_class(uploaded_file, **loader_args)
+            else:
+                loader = UnstructuredFileLoader(uploaded_file)
+            loaded_documents.extend(loader.load())
+
+        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()
+                    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__":
-    app.run()
+    main()