Update app.py

app.py

@@ -11,7 +11,11 @@ from IPython import get_ipython
 # from termcolor import colored # doesn't actually work in Colab ¯\_(ツ)_/¯
 
 GPT_MODEL = "gpt-3.5-turbo-1106"
-openai.api_key  = os.environ['OPENAI_API_KEY']
+
+from google.colab import userdata
+openai.api_key = userdata.get('OPENAI_API_KEY')
+
+messages=[]
 
 def exec_python(cell):
     ipython = get_ipython()
@@ -23,7 +27,6 @@ def exec_python(cell):
         log += f"\n{result.error_in_exec}"
     prompt = """You are a genius math tutor, Python code expert, and a helpful assistant.
     answer = {ans}
-
     Please answer user questions very well with explanations and match it with the multiple choices question.
     """.format(ans = log)
     return log
@@ -98,7 +101,6 @@ def openai_api_calculate_cost(usage,model=GPT_MODEL):
 def chat_completion_request(messages, functions=None, function_call=None, model=GPT_MODEL):
     """
     This function sends a POST request to the OpenAI API to generate a chat completion.
-
     Parameters:
     - messages (list): A list of message objects. Each object should have a 'role' (either 'system', 'user', or 'assistant') and 'content'
       (the content of the message).
@@ -106,7 +108,6 @@ def chat_completion_request(messages, functions=None, function_call=None, model=
     - function_call (str or dict, optional): If it's a string, it can be either 'auto' (the model decides whether to call a function) or 'none'
       (the model will not call a function). If it's a dict, it should describe the function to call.
     - model (str): The ID of the model to use.
-
     Returns:
     - response (requests.Response): The response from the OpenAI API. If the request was successful, the response's JSON will contain the chat completion.
     """
@@ -189,7 +190,7 @@ def function_call_process(assistant_message):
 
     # print(result)
 
-def second_call(prompt):
+def second_call(prompt, result, function_name = "exec_python"):
   # Add a new message to the conversation with the function result
   messages.append({
       "role": "function",
@@ -216,7 +217,7 @@ def main_function(init_prompt, prompt, user_input):
     first_call_result, cost1 = first_call(init_prompt, user_input)
     function_call_process_result = function_call_process(first_call_result)
     second_prompt_build_result = second_prompt_build(prompt, function_call_process_result)
-    second_call_result, cost2 = second_call(second_prompt_build_result)
+    second_call_result, cost2 = second_call(second_prompt_build_result, function_call_process_result)
     return first_call_result, function_call_process_result, second_call_result, cost1, cost2
 
 def gradio_function():