app.py

from openai import OpenAI
import gradio as gr
import json
from bot_actions import functions_dictionary, save_record
import os
 
CSS ="""
.contain { display: flex; flex-direction: column; }
.gradio-container { height: 100vh !important; }
#chatbot { flex-grow: 1; overflow: auto;}
footer {visibility: hidden}
"""

openAIToken = os.environ['openAIToken']
assistantId = os.environ['assistantId']
initial_message = os.environ['initialMessage']

client = OpenAI(api_key=openAIToken)

def handle_requires_action(data):
  actions_results = []
  for tool in data.required_action.submit_tool_outputs.tool_calls:
    function_name = tool.function.name
    function_args = json.loads(tool.function.arguments)
    print(function_name)
    print(function_args)
    try:
      result = functions_dictionary[tool.function.name](**function_args)
      print("Function result:", result)
      actions_results.append({"tool_output" : {"tool_call_id": tool.id, "output": result["message"]}})
    except Exception as e:
      print(e)

    
  # Submit all tool_outputs at the same time
  return actions_results 


def create_thread_openai(sessionStorage):
  streaming_thread = client.beta.threads.create()
  sessionStorage["threadId"] = streaming_thread.id
  return sessionStorage

def add_message_to_openai(text, threadId):
  print("User message: ", text)
  return client.beta.threads.messages.create(
    thread_id=threadId,
    role="user",
    content=text
  )

def transform_suggestions_into_list(string_of_suggestions):
  local_message = None
  parts = string_of_suggestions.split('#s#')
  list_of_suggestions = json.loads(parts[0])
  list_of_suggestions = [ x for x in list_of_suggestions if x]
  if len(parts) > 1:
    local_message = parts[1]
  return list_of_suggestions, local_message

def create_suggestions_list(suggestions):
  update_show = [gr.update(visible=True, value=w) for w in suggestions]
  update_hide = [gr.update(visible=False, value="") for _ in range(6-len(suggestions))]
  return update_show + update_hide

def process_text_chunk(text, list_of_suggestions, string_of_suggestions, is_loading_suggestions):
  print(text, end="", flush=True)
  local_message = None
  if "[" in text:
    is_loading_suggestions = True

  if is_loading_suggestions != True:
    local_message = text
  else:
    string_of_suggestions = string_of_suggestions + text
    if "#s#" in string_of_suggestions:
      is_loading_suggestions = False
      list_of_suggestions, local_message = transform_suggestions_into_list(string_of_suggestions)
      string_of_suggestions = ""
    elif "]" in string_of_suggestions and "]#" not in string_of_suggestions and not string_of_suggestions.endswith("]"):
      is_loading_suggestions = False
      local_message = string_of_suggestions
      string_of_suggestions = ""
  return local_message, list_of_suggestions, string_of_suggestions, is_loading_suggestions

def handle_events(threadId, chat_history, storage):
  list_of_suggestions = []
  string_of_suggestions = ""
  is_loading_suggestions = False
  try:
    with client.beta.threads.runs.stream(
      thread_id=threadId,
      assistant_id=assistantId
    ) as stream:
      for event in stream:
        if event.event == "thread.message.delta" and event.data.delta.content:
          text = event.data.delta.content[0].text.value
          local_message, list_of_suggestions, string_of_suggestions, is_loading_suggestions = process_text_chunk(text, list_of_suggestions, string_of_suggestions, is_loading_suggestions)
          if local_message is not None:
            chat_history[-1][1] += local_message 
            yield [ chat_history,  storage]
        if event.event == 'thread.run.requires_action':
          result = handle_requires_action(event.data)
          tool_outputs = [x["tool_output"] for x in result]
          with client.beta.threads.runs.submit_tool_outputs_stream(
            thread_id=stream.current_run.thread_id,
            run_id=event.data.id,
            tool_outputs=tool_outputs,
          ) as action_stream:
            for text in action_stream.text_deltas:
              local_message, list_of_suggestions, string_of_suggestions, is_loading_suggestions = process_text_chunk(text, list_of_suggestions, string_of_suggestions, is_loading_suggestions)
              if local_message is not None:
                chat_history[-1][1] += local_message
                yield [chat_history, storage]
            action_stream.close()
      stream.until_done()
      print("")
      storage["list_of_suggestions"] = list_of_suggestions
      return [chat_history, storage]
  except Exception as e:
    print(e)
    chat_history[-1][1] = "Error occured during processing your message. Please try again"
    yield [chat_history, storage]

def initiate_chatting(chat_history, storage):
  threadId = storage["threadId"]
  chat_history = [[None, ""]]
  add_message_to_openai(initial_message, threadId)
  for response in handle_events(threadId, chat_history, storage):
    yield response 

def respond_on_user_msg(chat_history, storage):
  message = chat_history[-1][0]
  threadId = storage["threadId"]
  print("Responding for threadId: ", threadId)
  chat_history[-1][1] = ""
  add_message_to_openai(message, threadId)
  for response in handle_events(threadId, chat_history, storage):
    yield response

def create_application():
  with gr.Blocks(css=CSS, fill_height=True) as demo:
    storage = gr.State({})
    chatbot = gr.Chatbot(label="Vehicle inspection bot", line_breaks=False, show_label=False, show_share_button=False, elem_id="chatbot", height=300)
    btn_list = []
    with gr.Row():
      for i in range(6):
          btn = gr.Button(visible=False, size="sm")
          btn_list.append(btn)
    msg = gr.Textbox(label="Answer", interactive=False)

    def user(user_message, history):
        return "", history + [[user_message, None]]

    def update_suggestions(storage):
      list_of_suggestions = storage['list_of_suggestions'] or []
      btn_list = create_suggestions_list(list_of_suggestions)
      return btn_list
    
    def hide_suggestions(): 
      return [gr.update(visible=False, value="") for _ in range(6)]

    def disable_msg():
      message_box = gr.Textbox(value=None, interactive=False)
      return message_box
    
    def enable_msg():
      message_box = gr.Textbox(value=None, interactive=True)
      return message_box

    add_user_message_flow = [user, [msg,chatbot],  [msg,chatbot]]
    chat_response_flow = [respond_on_user_msg, [chatbot, storage], [chatbot, storage]]
    update_suggestions_flow = [update_suggestions, storage, btn_list]
    hide_suggestions_flow = [hide_suggestions, None, btn_list]
    disable_msg_flow = [disable_msg, None, msg] 
    enable_msg_flow = [enable_msg, None, msg]

    msg.submit(*add_user_message_flow
        ).then(*hide_suggestions_flow
        ).then(*disable_msg_flow
        ).then(*chat_response_flow
        ).then(*update_suggestions_flow
        ).then(*enable_msg_flow)
    for sug_btn in btn_list:
      add_suggestion_message_flow = [user, [sug_btn, chatbot], [msg, chatbot]]
      sug_btn.click(*add_suggestion_message_flow
              ).then(*hide_suggestions_flow
              ).then(*disable_msg_flow
              ).then(*chat_response_flow
              ).then(*update_suggestions_flow
              ).then(*enable_msg_flow)
    
    demo.load(create_thread_openai, inputs=storage, outputs=storage
        ).then(initiate_chatting, inputs=[chatbot, storage], outputs=[chatbot, storage]
        ).then(*update_suggestions_flow
        ).then(*enable_msg_flow)
  return demo

if __name__ == "__main__":
  demo = create_application()
  demo.launch()