Update app.py

app.py

@@ -12,32 +12,36 @@ import os
 
 # Sidebar contents
 with st.sidebar:
-    st.title(':orange[BinDoc GmbH]')
+    st.title(':orange_book: BinDoc GmbH')
     st.markdown(
         "Experience the future of document interaction with the revolutionary"
     )
 
     st.markdown("**BinDocs Chat App**.")
 
-        
     st.markdown("Harnessing the power of a Large Language Model and AI technology,")
-       
-
 
     st.markdown("this innovative platform redefines PDF engagement,")
 
     st.markdown("enabling dynamic conversations that bridge the gap between")
     st.markdown("human and machine intelligence.")
 
-    
-    
     add_vertical_space(3)  # Add more vertical space between text blocks
     st.write('Made with ❤️ by Anne')
+    
+    # API key input (this will not display the entered text)
+    api_key = st.text_input('Enter your OpenAI API Key:', type='password')
+    
+    if api_key:
+        os.environ['OPENAI_API_KEY'] = api_key
+    else:
+        st.warning('API key is required to proceed.')
+
+
 
-# User input for the OpenAI API key
-openai_api_key = st.text_input("Enter your OpenAI API key:")
 
-def load_pdf(file_path, openai_api_key):
+
+def load_pdf(file_path):
     pdf_reader = PdfReader(file_path)
     text = ""
     for page in pdf_reader.pages:
@@ -56,18 +60,15 @@ def load_pdf(file_path, openai_api_key):
         with open(f"{store_name}.pkl", "rb") as f:
             VectorStore = pickle.load(f)
     else:
-        embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)  # Pass the API key here
+        embeddings = OpenAIEmbeddings()
         VectorStore = FAISS.from_texts(chunks, embedding=embeddings)
         with open(f"{store_name}.pkl", "wb") as f:
             pickle.dump(VectorStore, f)
 
     return VectorStore
 
-def load_chatbot(openai_api_key):
-    openai_config = {
-        "api_key": openai_api_key
-    }
-    return load_qa_chain(llm=OpenAI(config=openai_config), chain_type="stuff")
+def load_chatbot():
+    return load_qa_chain(llm=OpenAI(), chain_type="stuff")
 
 def main():
     st.title("BinDocs Chat App")
@@ -80,12 +81,6 @@ def main():
     if "current_input" not in st.session_state:
         st.session_state['current_input'] = ""
 
-    if "processing_input" not in st.session_state:
-        st.session_state['processing_input'] = ""
-
-    # Pass the openai_api_key parameter here
-    VectorStore = load_pdf(pdf, openai_api_key)
-
     display_chat_history(st.session_state['chat_history'])
 
     st.write("<!-- Start Spacer -->", unsafe_allow_html=True)
@@ -95,21 +90,18 @@ def main():
     if pdf is not None:
         query = st.text_input("Ask questions about your PDF file (in any preferred language):", value=st.session_state['current_input'])
 
-        if query != st.session_state['current_input']:
-            st.session_state['current_input'] = query
-
         if st.button("Ask"):
-            st.session_state['processing_input'] = st.session_state['current_input']
-            st.session_state['chat_history'].append(("User", st.session_state['processing_input'], "new"))
+            st.session_state['current_input'] = query
+            st.session_state['chat_history'].append(("User", query, "new"))
 
             loading_message = st.empty()
             loading_message.text('Bot is thinking...')
 
-            VectorStore = load_pdf(pdf, openai_api_key)  # Pass the API key here
-            chain = load_chatbot(openai_api_key)  # Pass the API key here
-            docs = VectorStore.similarity_search(query=st.session_state['processing_input'], k=3)
+            VectorStore = load_pdf(pdf)
+            chain = load_chatbot()
+            docs = VectorStore.similarity_search(query=query, k=3)
             with get_openai_callback() as cb:
-                response = chain.run(input_documents=docs, question=st.session_state['processing_input'])
+                response = chain.run(input_documents=docs, question=query)
 
             # Display the bot's response immediately using JavaScript
             st.write(f"<div id='response' style='background-color: #caf; padding: 10px; border-radius: 10px; margin: 10px;'>Bot: {response}</div>", unsafe_allow_html=True)
@@ -120,5 +112,10 @@ def main():
         # Mark all messages as old after displaying
         st.session_state['chat_history'] = [(sender, msg, "old") for sender, msg, _ in st.session_state['chat_history']]
 
+def display_chat_history(chat_history):
+    for chat in chat_history:
+        background_color = "#FFA07A" if chat[2] == "new" else "#acf" if chat[0] == "User" else "#caf"
+        st.markdown(f"<div style='background-color: {background_color}; padding: 10px; border-radius: 10px; margin: 10px;'>{chat[0]}: {chat[1]}</div>", unsafe_allow_html=True)
+
 if __name__ == "__main__":
-    main()
+    main()