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from functional import *
class ChoiceStrategy(metaclass=ABCMeta):
def __init__(self, choice):
self.choice = choice
self.delta = choice['delta']
@abstractmethod
def support(self):
pass
@abstractmethod
def execute(self, bot_backend: BotBackend, history: List, whether_exit: bool):
pass
class RoleChoiceStrategy(ChoiceStrategy):
def support(self):
return 'role' in self.delta
def execute(self, bot_backend: BotBackend, history: List, whether_exit: bool):
bot_backend.set_assistant_role_name(assistant_role_name=self.delta['role'])
return history, whether_exit
class ContentChoiceStrategy(ChoiceStrategy):
def support(self):
return 'content' in self.delta and self.delta['content'] is not None
# null value of content often occur in function call:
# {
# "role": "assistant",
# "content": null,
# "function_call": {
# "name": "python",
# "arguments": ""
# }
# }
def execute(self, bot_backend: BotBackend, history: List, whether_exit: bool):
bot_backend.add_content(content=self.delta.get('content', ''))
history[-1][1] = bot_backend.content
return history, whether_exit
class NameFunctionCallChoiceStrategy(ChoiceStrategy):
def support(self):
return 'function_call' in self.delta and 'name' in self.delta['function_call']
def execute(self, bot_backend: BotBackend, history: List, whether_exit: bool):
python_function_dict = bot_backend.jupyter_kernel.available_functions
additional_tools = bot_backend.additional_tools
bot_backend.set_function_name(function_name=self.delta['function_call']['name'])
bot_backend.copy_current_bot_history(bot_history=history)
if bot_backend.function_name not in python_function_dict and bot_backend.function_name not in additional_tools:
history.append(
[
None,
f'GPT attempted to call a function that does '
f'not exist: {bot_backend.function_name}\n '
]
)
whether_exit = True
return history, whether_exit
class ArgumentsFunctionCallChoiceStrategy(ChoiceStrategy):
def support(self):
return 'function_call' in self.delta and 'arguments' in self.delta['function_call']
def execute(self, bot_backend: BotBackend, history: List, whether_exit: bool):
bot_backend.add_function_args_str(function_args_str=self.delta['function_call']['arguments'])
if bot_backend.function_name == 'python': # handle hallucinatory function calls
"""
In practice, we have noticed that GPT, especially GPT-3.5, may occasionally produce hallucinatory
function calls. These calls involve a non-existent function named `python` with arguments consisting
solely of raw code text (not a JSON format).
"""
temp_code_str = bot_backend.function_args_str
bot_backend.update_code_str(code_str=temp_code_str)
bot_backend.update_display_code_block(
display_code_block="\n🔴Working:\n```python\n{}\n```".format(temp_code_str)
)
history = copy.deepcopy(bot_backend.bot_history)
history[-1][1] += bot_backend.display_code_block
elif bot_backend.function_name == 'execute_code':
temp_code_str = parse_json(function_args=bot_backend.function_args_str, finished=False)
if temp_code_str is not None:
bot_backend.update_code_str(code_str=temp_code_str)
bot_backend.update_display_code_block(
display_code_block="\n🔴Working:\n```python\n{}\n```".format(
temp_code_str
)
)
history = copy.deepcopy(bot_backend.bot_history)
history[-1][1] += bot_backend.display_code_block
else:
history = copy.deepcopy(bot_backend.bot_history)
history[-1][1] += bot_backend.display_code_block
else:
pass
return history, whether_exit
class FinishReasonChoiceStrategy(ChoiceStrategy):
def support(self):
return self.choice['finish_reason'] is not None
def execute(self, bot_backend: BotBackend, history: List, whether_exit: bool):
if bot_backend.content:
bot_backend.add_gpt_response_content_message()
bot_backend.update_finish_reason(finish_reason=self.choice['finish_reason'])
if bot_backend.finish_reason == 'function_call':
if bot_backend.function_name in bot_backend.jupyter_kernel.available_functions:
history, whether_exit = self.handle_execute_code_finish_reason(
bot_backend=bot_backend, history=history, whether_exit=whether_exit
)
else:
history, whether_exit = self.handle_tool_finish_reason(
bot_backend=bot_backend, history=history, whether_exit=whether_exit
)
bot_backend.reset_gpt_response_log_values(exclude=['finish_reason'])
return history, whether_exit
def handle_execute_code_finish_reason(self, bot_backend: BotBackend, history: List, whether_exit: bool):
function_dict = bot_backend.jupyter_kernel.available_functions
try:
code_str = self.get_code_str(bot_backend)
bot_backend.update_code_str(code_str=code_str)
bot_backend.update_display_code_block(
display_code_block="\n🟢Finished:\n```python\n{}\n```".format(code_str)
)
history = copy.deepcopy(bot_backend.bot_history)
history[-1][1] += bot_backend.display_code_block
# function response
bot_backend.update_code_executing_state(code_executing=True)
text_to_gpt, content_to_display = function_dict[
bot_backend.function_name
](code_str)
bot_backend.update_code_executing_state(code_executing=False)
# add function call to conversion
bot_backend.add_function_call_response_message(function_response=text_to_gpt, save_tokens=True)
if bot_backend.interrupt_signal_sent:
bot_backend.append_system_msg(prompt='Code execution is manually stopped by user, no need to fix.')
add_code_execution_result_to_bot_history(
content_to_display=content_to_display, history=history, unique_id=bot_backend.unique_id
)
return history, whether_exit
except json.JSONDecodeError:
history.append(
[None, f"GPT generate wrong function args: {bot_backend.function_args_str}"]
)
whether_exit = True
return history, whether_exit
except KeyError as key_error:
history.append([None, f'Backend key_error: {key_error}'])
whether_exit = True
return history, whether_exit
except Exception as e:
history.append([None, f'Backend error: {e}'])
whether_exit = True
return history, whether_exit
@staticmethod
def handle_tool_finish_reason(bot_backend: BotBackend, history: List, whether_exit: bool):
function_dict = bot_backend.additional_tools
function_name = bot_backend.function_name
function = function_dict[function_name]['tool']
# parser function args
try:
kwargs = json.loads(bot_backend.function_args_str)
kwargs.update(function_dict[function_name]['additional_parameters'])
except json.JSONDecodeError:
history.append(
[None, f"GPT generate wrong function args: {bot_backend.function_args_str}"]
)
whether_exit = True
return history, whether_exit
else:
# function response
function_response, hypertext_to_display = function(**kwargs)
# add function call to conversion
bot_backend.add_function_call_response_message(function_response=function_response, save_tokens=False)
# add hypertext response to bot history
add_function_response_to_bot_history(hypertext_to_display=hypertext_to_display, history=history)
return history, whether_exit
@staticmethod
def get_code_str(bot_backend):
if bot_backend.function_name == 'python':
code_str = bot_backend.function_args_str
else:
code_str = parse_json(function_args=bot_backend.function_args_str, finished=True)
if code_str is None:
raise json.JSONDecodeError
return code_str
class ChoiceHandler:
strategies = [
RoleChoiceStrategy, ContentChoiceStrategy, NameFunctionCallChoiceStrategy,
ArgumentsFunctionCallChoiceStrategy, FinishReasonChoiceStrategy
]
def __init__(self, choice):
self.choice = choice
def handle(self, bot_backend: BotBackend, history: List, whether_exit: bool):
for Strategy in self.strategies:
strategy_instance = Strategy(choice=self.choice)
if not strategy_instance.support():
continue
history, whether_exit = strategy_instance.execute(
bot_backend=bot_backend,
history=history,
whether_exit=whether_exit
)
return history, whether_exit
def parse_response(chunk, history: List, bot_backend: BotBackend):
"""
:return: history, whether_exit
"""
whether_exit = False
if chunk['choices']:
choice = chunk['choices'][0]
choice_handler = ChoiceHandler(choice=choice)
history, whether_exit = choice_handler.handle(
history=history,
bot_backend=bot_backend,
whether_exit=whether_exit
)
return history, whether_exit
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