enable retrying request for extension if API call fails

pilot/helpers/AgentConvo.py

@@ -70,7 +70,7 @@ def send_message(self, prompt_path=None, prompt_data=None, function_calls: Funct
         else:
             # if we don't, get the response from LLM
             try:
-                response = create_gpt_chat_completion(self.messages, self.high_level_step, function_calls=function_calls)
+                response = create_gpt_chat_completion(self.messages, self.high_level_step, self.agent.project, function_calls=function_calls)
             except TokenLimitError as e:
                 save_development_step(self.agent.project, prompt_path, prompt_data, self.messages, '', str(e))
                 raise e

pilot/prompts/prompts.py

@@ -86,10 +86,10 @@ def get_additional_info_from_openai(project, messages):
     while not is_complete:
         # Obtain clarifications using the OpenAI API
         # { 'text': new_code }
-        response = create_gpt_chat_completion(messages, 'additional_info')
+        response = create_gpt_chat_completion(messages, 'additional_info', project)
 
         if response is not None:
-            if response['text'].strip() == END_RESPONSE:
+            if response['text'] and response['text'].strip() == END_RESPONSE:
                 # print(response['text'] + '\n')
                 return messages
 
@@ -132,7 +132,9 @@ def get_additional_info_from_user(project, messages, role):
                 break
             response = create_gpt_chat_completion(
                 generate_messages_from_custom_conversation(role, [get_prompt('utils/update.prompt'), message, answer], 'user'),
-                'additional_info')
+                'additional_info',
+                project
+            )
 
             message = response
 

pilot/utils/llm_connection.py

@@ -5,7 +5,7 @@
 import time
 import json
 import tiktoken
-import questionary
+from prompt_toolkit.styles import Style
 
 from jsonschema import validate, ValidationError
 from utils.style import red
@@ -15,6 +15,7 @@
 from helpers.exceptions.TokenLimitError import TokenLimitError
 from utils.utils import fix_json, get_prompt
 from utils.function_calling import add_function_calls_to_request, FunctionCallSet, FunctionType
+from utils.questionary import styled_text
 
 
 def get_tokens_in_messages(messages: List[str]) -> int:
@@ -58,7 +59,7 @@ def num_tokens_from_functions(functions):
     return num_tokens
 
 
-def create_gpt_chat_completion(messages: List[dict], req_type, min_tokens=MIN_TOKENS_FOR_GPT_RESPONSE,
+def create_gpt_chat_completion(messages: List[dict], req_type, project,
                                function_calls: FunctionCallSet = None):
     """
     Called from:
@@ -69,7 +70,7 @@ def create_gpt_chat_completion(messages: List[dict], req_type, min_tokens=MIN_TO
             "Please check this message and say what needs to be changed... {message}"
     :param messages: [{ "role": "system"|"assistant"|"user", "content": string }, ... ]
     :param req_type: 'project_description' etc. See common.STEPS
-    :param min_tokens: defaults to 600
+    :param project: project
     :param function_calls: (optional) {'definitions': [{ 'name': str }, ...]}
         see `IMPLEMENT_CHANGES` etc. in `pilot/const/function_calls.py`
     :return: {'text': new_code}
@@ -99,7 +100,7 @@ def create_gpt_chat_completion(messages: List[dict], req_type, min_tokens=MIN_TO
     add_function_calls_to_request(gpt_data, function_calls)
 
     try:
-        response = stream_gpt_completion(gpt_data, req_type)
+        response = stream_gpt_completion(gpt_data, req_type, project)
         return response
     except TokenLimitError as e:
         raise e
@@ -186,12 +187,15 @@ def wrapper(*args, **kwargs):
                 print(err_str)
                 logger.error(f'There was a problem with request to openai API: {err_str}')
 
-                user_message = questionary.text(
+                project = args[2]
+                user_message = styled_text(
+                    project,
                     "Do you want to try make the same request again? If yes, just press ENTER. Otherwise, type 'no'.",
-                    style=questionary.Style([
-                        ('question', 'fg:red'),
-                        ('answer', 'fg:orange')
-                    ])).ask()
+                    style=Style.from_dict({
+                        'question': '#FF0000 bold',
+                        'answer': '#FF910A bold'
+                    })
+                )
 
                 # TODO: take user's input into consideration - send to LLM?
                 # https://github.com/Pythagora-io/gpt-pilot/issues/122
@@ -202,11 +206,12 @@ def wrapper(*args, **kwargs):
 
 
 @retry_on_exception
-def stream_gpt_completion(data, req_type):
+def stream_gpt_completion(data, req_type, project):
     """
     Called from create_gpt_chat_completion()
     :param data:
     :param req_type: 'project_description' etc. See common.STEPS
+    :param project: NEEDED FOR WRAPPER FUNCTION retry_on_exception
     :return: {'text': str} or {'function_calls': {'name': str, arguments: '{...}'}}
     """
 

pilot/utils/questionary.py

@@ -23,7 +23,7 @@ def styled_select(*args, **kwargs):
     return questionary.select(*args, **kwargs).unsafe_ask()  # .ask() is included here
 
 
-def styled_text(project, question, ignore_user_input_count=False):
+def styled_text(project, question, ignore_user_input_count=False, style=None):
     if not ignore_user_input_count:
         project.user_inputs_count += 1
         user_input = get_saved_user_input(project, question)
@@ -36,7 +36,7 @@ def styled_text(project, question, ignore_user_input_count=False):
 
     if project.ipc_client_instance is None or project.ipc_client_instance.client is None:
         config = {
-            'style': custom_style,
+            'style': style if style is not None else custom_style,
         }
         question = remove_ansi_codes(question) # Colorama and questionary are not compatible and styling doesn't work
         response = questionary.text(question, **config).unsafe_ask()  # .ask() is included here