Update app.py

app.py

@@ -97,19 +97,39 @@ def get_conversation_chain(vectorstore):
     return conversation_chain
 
 # 사용자 입력을 처리하는 함수입니다.
+# def handle_userinput(user_question):
+#     # 대화 체인을 사용하여 사용자 질문에 대한 응답을 생성합니다.
+#     response = st.session_state.conversation({'question': user_question})
+#     # 대화 기록을 저장합니다.
+#     st.session_state.chat_history = response['chat_history']
+
+#     for i, message in enumerate(st.session_state.chat_history):
+#         if i % 2 == 0:
+#             st.write(user_template.replace(
+#                 "{{MSG}}", message.content), unsafe_allow_html=True)
+#         else:
+#             st.write(bot_template.replace(
+#                 "{{MSG}}", message.content), unsafe_allow_html=True)
+
+
 def handle_userinput(user_question):
-    # 대화 체인을 사용하여 사용자 질문에 대한 응답을 생성합니다.
-    response = st.session_state.conversation({'question': user_question})
-    # 대화 기록을 저장합니다.
-    st.session_state.chat_history = response['chat_history']
+    if not st.session_state.conversation:
+        st.error("Please upload and process your documents first.")
+        return
 
-    for i, message in enumerate(st.session_state.chat_history):
-        if i % 2 == 0:
-            st.write(user_template.replace(
-                "{{MSG}}", message.content), unsafe_allow_html=True)
-        else:
-            st.write(bot_template.replace(
-                "{{MSG}}", message.content), unsafe_allow_html=True)
+    try:
+        response = st.session_state.conversation({'question': user_question})
+        st.session_state.chat_history = response['chat_history']
+
+        for i, message in enumerate(st.session_state.chat_history):
+            if i % 2 == 0:
+                st.write(user_template.replace(
+                    "{{MSG}}", message.content), unsafe_allow_html=True)
+            else:
+                st.write(bot_template.replace(
+                    "{{MSG}}", message.content), unsafe_allow_html=True)
+    except Exception as e:
+        st.error(f"An error occurred: {e}")
 
 
 def main():
@@ -123,7 +143,7 @@ def main():
     if "chat_history" not in st.session_state:
         st.session_state.chat_history = None
 
-    st.header("Chat with multiple Files :")
+    st.header("Chat with multiple Files:")
     user_question = st.text_input("Ask a question about your documents:")
     if user_question:
         handle_userinput(user_question)
@@ -137,38 +157,95 @@ def main():
         docs = st.file_uploader(
             "Upload your PDFs here and click on 'Process'", accept_multiple_files=True)
         if st.button("Process"):
-            with st.spinner("Processing"):
-                # get pdf text
-                doc_list = []
-
-                for file in docs:
-                    print('file - type : ', file.type)
-                    if file.type == 'text/plain':
-                        # file is .txt
-                        doc_list.extend(get_text_file(file))
-                    elif file.type in ['application/octet-stream', 'application/pdf']:
-                        # file is .pdf
-                        doc_list.extend(get_pdf_text(file))
-                    elif file.type == 'text/csv':
-                        # file is .csv
-                        doc_list.extend(get_csv_file(file))
-                    elif file.type == 'application/json':
-                        # file is .json
-                        doc_list.extend(get_json_file(file))
-
-                # get the text chunks
-                text_chunks = get_text_chunks(doc_list)
-
-                # create vector store
-                vectorstore = get_vectorstore(text_chunks)
-
-                # create conversation chain
-                st.session_state.conversation = get_conversation_chain(
-                    vectorstore)
+            if not docs:
+                st.error("Please upload at least one document.")
+                return
+
+            with st.spinner("Processing..."):
+                try:
+                    doc_list = []
+
+                    for file in docs:
+                        if file.type == 'text/plain':
+                            doc_list.extend(get_text_file(file))
+                        elif file.type in ['application/octet-stream', 'application/pdf']:
+                            doc_list.extend(get_pdf_text(file))
+                        elif file.type == 'text/csv':
+                            doc_list.extend(get_csv_file(file))
+                        elif file.type == 'application/json':
+                            doc_list.extend(get_json_file(file))
+
+                    if not doc_list:
+                        st.error("No valid documents processed. Please check your files.")
+                        return
+
+                    text_chunks = get_text_chunks(doc_list)
+
+                    vectorstore = get_vectorstore(text_chunks)
+
+                    st.session_state.conversation = get_conversation_chain(vectorstore)
+
+                    st.success("Documents processed successfully!")
+                except Exception as e:
+                    st.error(f"An error occurred during processing: {e}")
 
 
 if __name__ == '__main__':
     main()
+# def main():
+#     load_dotenv()
+#     st.set_page_config(page_title="Chat with multiple Files",
+#                        page_icon=":books:")
+#     st.write(css, unsafe_allow_html=True)
+
+#     if "conversation" not in st.session_state:
+#         st.session_state.conversation = None
+#     if "chat_history" not in st.session_state:
+#         st.session_state.chat_history = None
+
+#     st.header("Chat with multiple Files :")
+#     user_question = st.text_input("Ask a question about your documents:")
+#     if user_question:
+#         handle_userinput(user_question)
+
+#     with st.sidebar:
+#         openai_key = st.text_input("Paste your OpenAI API key (sk-...)")
+#         if openai_key:
+#             os.environ["OPENAI_API_KEY"] = openai_key
+
+#         st.subheader("Your documents")
+#         docs = st.file_uploader(
+#             "Upload your PDFs here and click on 'Process'", accept_multiple_files=True)
+#         if st.button("Process"):
+#             with st.spinner("Processing"):
+#                 # get pdf text
+#                 doc_list = []
+
+#                 for file in docs:
+#                     print('file - type : ', file.type)
+#                     if file.type == 'text/plain':
+#                         # file is .txt
+#                         doc_list.extend(get_text_file(file))
+#                     elif file.type in ['application/octet-stream', 'application/pdf']:
+#                         # file is .pdf
+#                         doc_list.extend(get_pdf_text(file))
+#                     elif file.type == 'text/csv':
+#                         # file is .csv
+#                         doc_list.extend(get_csv_file(file))
+#                     elif file.type == 'application/json':
+#                         # file is .json
+#                         doc_list.extend(get_json_file(file))
+
+#                 # get the text chunks
+#                 text_chunks = get_text_chunks(doc_list)
+
+#                 # create vector store
+#                 vectorstore = get_vectorstore(text_chunks)
+
+#                 # create conversation chain
+#                 st.session_state.conversation = get_conversation_chain(
+#                     vectorstore)
+
 
 # import streamlit as st
 # # from dotenv import load_dotenv