Update app.py

app.py

@@ -103,7 +103,7 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
 # completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=system_prompt + history[-context_length*2:] + [prompt_msg], temperature=temperature, max_tokens=max_tokens)
 
         completion = RetrievalQA.from_chain_type(llm=ChatOpenAI(temperature=temperature, max_tokens=max_tokens, model_name="gpt-3.5-turbo"), chain_type="stuff", retriever=vectordb.as_retriever() , return_source_documents=True)
-        result = completion({"query": system_prompt + history[-context_length*2:] + [prompt_msg] })
+        completion = completion({"query": system_prompt + history[-context_length*2:] + [prompt_msg] })
         # from https://blog.devgenius.io/chat-with-document-s-using-openai-chatgpt-api-and-text-embedding-6a0ce3dc8bc8
         
         history.append(prompt_msg)
@@ -158,7 +158,7 @@ with gr.Blocks(css=css) as demo:
                 input_message = gr.Textbox(show_label=False, placeholder="Enter your needs assessment question and press enter", visible=True).style(container=False)
                 btn_submit = gr.Button("Submit")
                 total_tokens_str = gr.Markdown(elem_id="total_tokens_str")
-                btn_clear_conversation = gr.Button("🔃 Start New Conversation")
+                btn_clear_conversation = gr.Button("Start New Conversation")
             with gr.Column():
                 prompt_template = gr.Dropdown(label="Choose a expert:", choices=list(prompt_templates.keys()))
                 prompt_template_preview = gr.Markdown(elem_id="prompt_template_preview")