passed the test on colab

app.py

@@ -11,61 +11,64 @@ from langchain.memory import ConversationBufferMemory
 from langchain.chains import RetrievalQA, LLMChain
 from langchain.prompts import PromptTemplate
 
-OPENAI_API_KEY = ''
 
 embedding_file = "all_faiss_store_openai.pkl"
 with open(embedding_file, 'rb') as f:
   VectorStore = pickle.load(f)
 
+
 """ initialize all the tools """
 
 template = """
 You are a knowledgeable assistant of Chartis' report and you are cautious about the answer you are giving. You will refuse to answer any questions that may generate an answer that violates the Open AI policy, or is not related to the given documents.
 Given the user input question: {question}
-
 • If the question can be inferred from the provided context, use the context to formulate your answer.
 • If the question cannot be answered based on the context, simply state that you don't know. Do not provide inaccurate or made-up information.
-
 Your answers should be:
 • Direct and succinct.
 • Accurate and directly addressing the user's questions.
 {context}
-
 Helpful Answer:"""
 
 
 QA_CHAIN_PROMPT = PromptTemplate(input_variables=["context", "question"], template=template,)
 
-chat_model = ChatOpenAI(temperature=0, model_name='gpt-3.5-turbo')
-
-# customized memory
-memory = ConversationBufferMemory(
-      return_messages=True,
-      output_key='result'
-)
-
-answer_chain = RetrievalQA.from_chain_type(
-      chat_model,
-      retriever=VectorStore.as_retriever(),
-      memory = memory,
-      chain_type_kwargs={"prompt": QA_CHAIN_PROMPT},
-      return_source_documents=True
-)
-
-
+OPENAI_API_KEY = ''
 
 def slow_echo(usr_message, chat_history):
+    global OPENAI_API_KEY
+    
+    # Check if the API key is set
+    if not OPENAI_API_KEY:
+        error_message = "OpenAI API key not set. Please provide the key first."
+        print(error_message)
+        return error_message, chat_history
+    
     try:
-        # Attempt to get a response from the OpenAI model
-        bot_result = answer_chain({"query": usr_message})
-        bot_response = bot_result['result']
-        source_page = bot_result['source_documents'][0].metadata['page']+1
+      chat_model = ChatOpenAI(temperature=0, model_name='gpt-3.5-turbo', openai_api_key=OPENAI_API_KEY)
+
+      # customized memory
+      memory = ConversationBufferMemory(
+            return_messages=True,
+            output_key='result'
+      )
 
-        bot_response = bot_response +'source page:'+ str(source_page)
+      answer_chain = RetrievalQA.from_chain_type(
+            chat_model,
+            retriever=VectorStore.as_retriever(),
+            memory = memory,
+            chain_type_kwargs={"prompt": QA_CHAIN_PROMPT},
+            return_source_documents=True
+      )
 
-        time.sleep(1)
+      # Get a response from the OpenAI model
+      bot_result = answer_chain({"query": usr_message})
+      bot_response = bot_result['result']
 
-        yield bot_response
+      chat_history.append((usr_message, bot_response))
+      time.sleep(1)
+
+      yield "", chat_history
 
     except openai.error.OpenAIError as e:
         # Handle OpenAI-specific errors
@@ -77,35 +80,33 @@ def slow_echo(usr_message, chat_history):
         error_message = f"Unexpected error: {e}"
         print(error_message)
 
+def get_opeanai_key(openai_key):
+    global OPENAI_API_KEY
+    OPENAI_API_KEY=openai_key
+
+    return {chatbot_col: gr.Column(visible=True)}
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    """
+    # Chartis Chatbot Demo
+    Please provide your own GPT key below first!
+    """)
 
-def get_key(api_key):
-    if api_key!='':
-        return "Key accepted! Displaying chatbot..."
-    else:
-        return "Invalid key. Please try again."
+    openai_gpt_key = gr.Textbox(label="OpenAI Key", value="", type="password", placeholder="sk-")
+    btn = gr.Button(value="Submit")
 
-key_interface = gr.Interface(
-    fn=get_key, 
-    inputs=gr.Textbox(label="Enter your OpenAI key:"), 
-    outputs="text",
-    live=True  # This will call the function every time the input changes.
-)
+    with gr.Column(visible=False) as chatbot_col:
+      chatbot = gr.Chatbot()
+      msg = gr.Textbox(label='Type in your questions about Chartis here and press Enter!',
+                        placeholder='Type in your questions.', scale=7)
+      clear = gr.ClearButton([msg, chatbot])
 
+      msg.submit(slow_echo, [msg, chatbot], [msg, chatbot])
 
-demo = gr.ChatInterface(
-    slow_echo,
-    chatbot=gr.Chatbot(height=500),
-    textbox=gr.Textbox(label='Type in your questions about Chartis report here and press Enter!',
-                       placeholder='Type in your questions.', container=False, scale=7),
-    title="Chartis Chatbot Demo",
-    retry_btn=None,
-    undo_btn=None,
-    clear_btn="Clear"
-).queue()
+    btn.click(get_opeanai_key, inputs=[openai_gpt_key], outputs=[chatbot_col])
 
 
-if __name__ == "__main__":
-    returned_data = key_interface.launch(return_data=True)
-    OPENAI_API_KEY = returned_data[0]['data']['textbox']
 
-    demo.launch(debug=True)
+demo.queue().launch(debug=True)