Update app.py

app.py

@@ -1,7 +1,6 @@
 import os
 import openai
 import sys
-import sympy
 
 import gradio as gr
 from IPython import get_ipython
@@ -10,14 +9,16 @@ import requests
 from tenacity import retry, wait_random_exponential, stop_after_attempt
 from IPython import get_ipython
 # from termcolor import colored # doesn't actually work in Colab ¯\_(ツ)_/¯
+import ast
 
 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')
 
 def exec_python(cell):
     # result = 0
-    # print(cell)
+    print(cell)
     # print(type(cell))
     # code = json.loads(cell)
     # print(code)
@@ -27,13 +28,19 @@ def exec_python(cell):
     code = inputcode
     # code_string = code["cell"]
     local_namespace = {}
-    exec(code, globals(), local_namespace)
+    try:
+        exec(code, globals(), local_namespace)
+    except Exception as e:
+        return "Please figure and solve it step by step with explanation by yourself. Remember, you must give the correct answer!"
     print(local_namespace)
-    theanswers = local_namespace.values()
-    local_ans = list(theanswers)[-1]
-    print(theanswers)
-    print(local_ans)
-    return local_ans
+    if not local_namespace:
+        return "Please figure and solve it step by step with explanation by yourself. Remember, you must give the correct answer!"
+    else:
+        theanswers = local_namespace.values()
+        print(theanswers)
+        local_ans = list(theanswers)[-1]
+        print(local_ans)
+        return local_ans
 
 # Now let's define the function specification:
 functions = [
@@ -45,7 +52,7 @@ functions = [
                 "properties": {
                     "cell": {
                         "type": "string",
-                        "description": "Valid Python cell to execute.",
+                        "description": "Valid Python code to execute.",
                     }
                 },
                 "required": ["cell"],
@@ -124,6 +131,7 @@ def chat_completion_request(messages, functions=None, function_call=None, model=
 
     # Set up the data for the API request
     json_data = {"model": model, "messages": messages}
+    # json_data = {"model": model, "messages": messages, "response_format":{"type": "json_object"}}
     # json_data = {"model": model, "messages": messages, "temperature": 0.2, "top_p": 0.1}
 
     # If functions were provided, add them to the data
@@ -157,7 +165,7 @@ def first_call(init_prompt, user_input):
 
   # Generate a response
   chat_response = chat_completion_request(
-      messages, functions=functions
+      messages, functions=functions, function_call='auto'
   )
 
 
@@ -173,6 +181,12 @@ def first_call(init_prompt, user_input):
   # Let's see what we got back before continuing
   return assistant_message, cost1, messages
 
+def is_valid_dict_string(s):
+    try:
+        ast.literal_eval(s)
+        return True
+    except (SyntaxError, ValueError):
+        return False
 
 def function_call_process(assistant_message):
   if assistant_message.get("function_call") != None:
@@ -182,11 +196,24 @@ def function_call_process(assistant_message):
 
     # Retrieve the arguments to send the function
     # function_args = json.loads(assistant_message["function_call"]["arguments"], strict=False)
-    arg_dict =  {'cell': assistant_message["function_call"]["arguments"]}
+
+    # if isinstance(assistant_message["function_call"]["arguments"], dict):
+    #   arg_dict = json.loads(r"{jsonload}".format(jsonload=assistant_message["function_call"]["arguments"]), strict=False)
+    # else:
+    #   arg_dict =  {'cell': assistant_message["function_call"]["arguments"]}
+    # arg_dict = assistant_message["function_call"]["arguments"]
     # print(function_args)
 
+    if is_valid_dict_string(assistant_message["function_call"]["arguments"])==True:
+      arg_dict = json.loads(r"{jsonload}".format(jsonload=assistant_message["function_call"]["arguments"]), strict=False)
+      arg_dict = arg_dict['cell']
+      print("arg_dict : " + arg_dict)
+    else:
+      arg_dict = assistant_message["function_call"]["arguments"]
+      print(arg_dict)
+
     # Look up the function and call it with the provided arguments
-    result = functions_dict[function_name](**arg_dict)
+    result = functions_dict[function_name](arg_dict)
     return result
 
     # print(result)