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import json
from copy import deepcopy
from typing import Any, Dict, List
from flow_modules.aiflows.ChatFlowModule import ChatAtomicFlow
from dataclasses import dataclass
class PlanGeneratorAtomicFlow(ChatAtomicFlow):
def __init__(
self,
code_file_location: str,
**kwargs):
super().__init__(**kwargs)
self.hint_for_model = """
Make sure your response is in the following format:
Response Format:
{
"plan": "Python printable string of the plan corresponding to the goal",
}
"""
self.code_file_location = code_file_location
self.original_system_template = self.system_message_prompt_template.template
@classmethod
def instantiate_from_config(cls, config):
flow_config = deepcopy(config)
kwargs = {"flow_config": flow_config}
# ~~~ Set up prompts ~~~
kwargs.update(cls._set_up_prompts(flow_config))
kwargs.update(cls._set_up_backend(flow_config))
# ~~~ Set up code file location
code_file_location = flow_config["code_file_location"]
kwargs.update({"code_file_location": code_file_location})
# ~~~ Instantiate flow ~~~
return cls(**kwargs)
def _get_library_function_signatures(self):
import importlib.util
try:
spec = importlib.util.spec_from_file_location("code_library", self.code_file_location)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
ret = ''
import inspect
for name, obj in inspect.getmembers(module):
if inspect.isfunction(obj):
ret += f"{name}: {inspect.signature(obj)}\n"
return ret
except FileNotFoundError:
return 'There is no function available yet.'
def _update_prompt_and_input(self, input_data: Dict[str, Any]):
if 'goal' in input_data:
input_data['goal'] += self.hint_for_model
function_signatures_to_append = self._get_library_function_signatures()
self.system_message_prompt_template.template = \
self.original_system_template + "\n\n" + f"Here are the available functions at {self.code_file_location}\n" \
+ function_signatures_to_append + "\n"
def run(self, input_data: Dict[str, Any]) -> Dict[str, Any]:
self._update_prompt_and_input(input_data)
api_output = super().run(input_data)["api_output"].strip()
try:
response = json.loads(api_output)
return response
except json.decoder.JSONDecodeError:
new_input_data = input_data.copy()
new_input_data['goal'] += ("The previous respond cannot be parsed with json.loads, Make sure your next "
"response is solely in JSON format.")
new_api_output = super().run(new_input_data)["api_output"].strip()
return json.loads(new_api_output)
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