ReplanningFlowModule / run_replanning.py
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Update run_replanning.py
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import os
import hydra
from aiflows.backends.api_info import ApiInfo
from aiflows.messages import InputMessage
from aiflows.utils.general_helpers import read_yaml_file
from aiflows import logging
from aiflows.flow_cache import CACHING_PARAMETERS, clear_cache
CACHING_PARAMETERS.do_caching = False # Set to True in order to disable caching
# clear_cache() # Uncomment this line to clear the cache
logging.set_verbosity_debug()
logging.auto_set_dir()
dependencies = [
{"url": "Tachi67/ReplanningFlowModule", "revision": "main"},
{"url": "Tachi67/PlanGeneratorFlowModule", "revision": "main"},
{"url": "Tachi67/InteractivePlanGenFlowModule", "revision": "main"},
{"url": "Tachi67/PlanWriterFlowModule", "revision": "main"},
{"url": "Tachi67/PlanFileEditFlowModule", "revision": "main"},
{"url": "Tachi67/ParseFeedbackFlowModule", "revision": "main"},
{"url": "aiflows/HumanStandardInputFlowModule", "revision": "4ff043522c89a964ea3a928ce09811c51a2b5b98"}
]
from aiflows import flow_verse
flow_verse.sync_dependencies(dependencies)
if __name__ == "__main__":
# ~~~ make sure to set the openai api key in the envs ~~~
key = os.getenv("OPENAI_API_KEY")
api_information = [ApiInfo(backend_used="openai", api_key=os.getenv("OPENAI_API_KEY"))]
path_to_output_file = None
# ~~~ setting api information into config ~~~
current_dir = os.getcwd()
cfg_path = os.path.join(current_dir, "ReplanningFlow.yaml")
cfg = read_yaml_file(cfg_path)
cfg["subflows_config"]["Controller"]["backend"]["api_infos"] = api_information
cfg["subflows_config"]["Executor"]["subflows_config"]["write_plan"]["subflows_config"]["PlanGenerator"]["backend"]["api_infos"] = api_information
# ~~~ instantiating the flow and input data ~~~
ReplanningFlow = hydra.utils.instantiate(cfg, _recursive_=False, _convert_="partial")
# ~~~ creating the plan file location (of the upper level flow e.g. ExtLib)
plan_file_location = os.path.join(current_dir, "ExtLib_plan.txt")
with open(plan_file_location, 'w') as file:
pass
input_data = {
"goal": "data source OpenWeatherMap is deprecated",
"plan": "1. Write a function that fetches today's weather at Lausanne from OpenWeatherMap. \n 2. Write a funtion that prints the fetched data in a formatted way.",
"plan_file_location": plan_file_location
}
input_message = InputMessage.build(
data_dict=input_data,
src_flow="Launcher",
dst_flow=ReplanningFlow.name
)
# ~~~ calling the flow ~~~
output_message = ReplanningFlow(input_message)