improved logging

pilot/helpers/AgentConvo.py

@@ -29,7 +29,10 @@ class AgentConvo:
         self.high_level_step = self.agent.project.current_step
 
         # add system message
-        self.messages.append(get_sys_message(self.agent.role))
+        system_message = get_sys_message(self.agent.role)
+        logger.info('\n>>>>>>>>>> System Prompt >>>>>>>>>>\n%s\n>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>',
+                    system_message['content'])
+        self.messages.append(system_message)
 
     def send_message(self, prompt_path=None, prompt_data=None, function_calls: FunctionCallSet = None):
         """
@@ -103,6 +106,7 @@ class AgentConvo:
 
         # TODO we need to specify the response when there is a function called
         # TODO maybe we can have a specific function that creates the GPT response from the function call
+        logger.info('\n>>>>>>>>>> Assistant Prompt >>>>>>>>>>\n%s\n>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>', message_content)
         self.messages.append({"role": "assistant", "content": message_content})
         self.log_message(message_content)
 
@@ -133,6 +137,7 @@ class AgentConvo:
             if user_message == "":
                 accepted_messages.append(response)
 
+            logger.info('\n>>>>>>>>>> User Message >>>>>>>>>>\n%s\n>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>', user_message)
             self.messages.append({"role": "user", "content": user_message})
             response = self.send_message(None, None, function_calls)
 
@@ -202,4 +207,5 @@ class AgentConvo:
     def construct_and_add_message_from_prompt(self, prompt_path, prompt_data):
         if prompt_path is not None and prompt_data is not None:
             prompt = get_prompt(prompt_path, prompt_data)
+            logger.info('\n>>>>>>>>>> User Prompt >>>>>>>>>>\n%s\n>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>', prompt)
             self.messages.append({"role": "user", "content": prompt})

pilot/helpers/Project.py

@@ -338,8 +338,7 @@ class Project:
         if description is not None:
             question += '\n' + '-' * 100 + '\n' + white_bold(description) + '\n' + '-' * 100 + '\n'
 
-        if convo is not None:
-            reset_branch_id = convo.save_branch()
+        reset_branch_id = None if convo is None else convo.save_branch()
 
         while answer != 'continue':
             answer = ask_user(self, question,

pilot/helpers/cli.py

@@ -124,9 +124,13 @@ def execute_command(project, command, timeout=None, process_name: str = None, fo
         exit_code (int): The exit code of the process.
     """
     if timeout is not None:
-        if timeout < 1000:
-            timeout *= 1000
-        timeout = min(max(timeout, MIN_COMMAND_RUN_TIME), MAX_COMMAND_RUN_TIME)
+        if timeout == 0:
+            timeout = None
+        else:
+            if timeout < 1000:
+                timeout *= 1000
+
+            timeout = min(max(timeout, MIN_COMMAND_RUN_TIME), MAX_COMMAND_RUN_TIME)
 
     if not force:
         print(yellow_bold(f'\n--------- EXECUTE COMMAND ----------'))
@@ -229,6 +233,7 @@ def execute_command(project, command, timeout=None, process_name: str = None, fo
                 logger.error('CLI ERROR: ' + stderr_line)
                 
             if process_name is not None:
+                logger.info(f'Process {process_name} running as pid: {process.pid}')
                 break
 
     except (KeyboardInterrupt, TimeoutError) as e:
@@ -317,7 +322,10 @@ def execute_command_and_check_cli_response(command, timeout, convo):
     cli_response, llm_response, exit_code = execute_command(convo.agent.project, command, timeout=timeout)
     if llm_response is None:
         llm_response = convo.send_message('dev_ops/ran_command.prompt',
-            { 'cli_response': cli_response, 'command': command })
+            {
+                'cli_response': cli_response,
+                'command': command
+            })
     return cli_response, llm_response
 
 

pilot/prompts/prompts.py

@@ -193,12 +193,16 @@ def generate_messages_from_custom_conversation(role, messages, start_role='user'
       ... ]
     """
     # messages is list of strings
-    result = [get_sys_message(role)]
+    system_message = get_sys_message(role)
+    result = [system_message]
+    logger.info(f'\n>>>>>>>>>> {role} Prompt >>>>>>>>>>\n%s\n>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>', system_message['content'])
 
     for i, message in enumerate(messages):
         if i % 2 == 0:
             result.append({"role": start_role, "content": message})
+            logger.info(f'\n>>>>>>>>>> {start_role} Prompt >>>>>>>>>>\n%s\n>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>', message)
         else:
             result.append({"role": "assistant" if start_role == "user" else "user", "content": message})
+            logger.info('\n>>>>>>>>>> Assistant Prompt >>>>>>>>>>\n%s\n>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>', message)
 
     return result

pilot/utils/llm_connection.py

@@ -11,7 +11,7 @@ from jsonschema import validate, ValidationError
 from utils.style import red
 from typing import List
 from const.llm import MIN_TOKENS_FOR_GPT_RESPONSE, MAX_GPT_MODEL_TOKENS
-from logger.logger import logger
+from logger.logger import logger, logging
 from helpers.exceptions import TokenLimitError, ApiKeyNotDefinedError
 from utils.utils import fix_json, get_prompt
 from utils.function_calling import add_function_calls_to_request, FunctionCallSet, FunctionType
@@ -156,7 +156,7 @@ def retry_on_exception(func):
         if 'function_buffer' in args[0]:
             del args[0]['function_buffer']
 
-    def retry_wrapper(*args, **kwargs):
+    def wrapper(*args, **kwargs):
         while True:
             try:
                 # spinner_stop(spinner)
@@ -237,7 +237,7 @@ def retry_on_exception(func):
                 if user_message != '':
                     return {}
 
-    return retry_wrapper
+    return wrapper
 
 
 @retry_on_exception
@@ -291,8 +291,9 @@ def stream_gpt_completion(data, req_type, project):
     model = os.getenv('MODEL_NAME', 'gpt-4')
     endpoint = os.getenv('ENDPOINT')
 
-    logger.info(f'> Request model: {model} ({data["model"]})\n'
-                + '\n'.join([f"{message['role']}: {message['content']}" for message in data['messages']]))
+    logger.info(f'> Request model: {model} ({data["model"]} in data)')
+    if logger.isEnabledFor(logging.DEBUG):
+        logger.debug('\n'.join([f"{message['role']}: {message['content']}" for message in data['messages']]))
 
     if endpoint == 'AZURE':
         # If yes, get the AZURE_ENDPOINT from .ENV file
@@ -401,7 +402,7 @@ def stream_gpt_completion(data, req_type, project):
     #     logger.info(f'Response via function call: {function_calls["arguments"]}')
     #     function_calls['arguments'] = load_data_to_json(function_calls['arguments'])
     #     return return_result({'function_calls': function_calls}, lines_printed)
-    logger.info(f'< Response message: {gpt_response}')
+    logger.info('<<<<<<<<<< LLM Response <<<<<<<<<<\n%s\n<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<', gpt_response)
 
     if expecting_json:
         gpt_response = clean_json_response(gpt_response)