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.utils.general_helpers import quick_load 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": "aiflows/HumanStandardInputFlowModule", "revision": "4ff043522c89a964ea3a928ce09811c51a2b5b98"}, {"url": "aiflows/ChatFlowModule", "revision": "297c90d08087d9ff3139521f11d1a48d7dc63ed4"}, {"url": "Tachi67/AbstractBossFlowModule", "revision": "main"}, {"url": "Tachi67/MemoryReadingFlowModule", "revision": "main"}, {"url": "Tachi67/PlanWriterFlowModule", "revision": "main"}, {"url": "Tachi67/ExtendLibraryFlowModule", "revision": "main"}, {"url": "Tachi67/RunCodeFlowModule", "revision": "main"}, {"url": "Tachi67/ReplanningFlowModule", "revision": "main"}, {"url": "Tachi67/CoderFlowModule", "revision": "main"}, {"url": "Tachi67/JarvisFlowModule", "revision": "main"}, ] from aiflows import flow_verse flow_verse.sync_dependencies(dependencies) def set_up_memfiles(cfg): code_lib_file_loc = os.path.join(current_dir, "library.py") jarvis_plan_file_loc = os.path.join(current_dir, "plan_jarvis.txt") jarvis_logs_file_loc = os.path.join(current_dir, "logs_jarvis.txt") coder_plan_file_loc = os.path.join(current_dir, "plan_coder.txt") coder_logs_file_loc = os.path.join(current_dir, "logs_coder.txt") extlib_plan_file_loc = os.path.join(current_dir, "plan_extlib.txt") extlib_logs_file_loc = os.path.join(current_dir, "logs_extlib.txt") with open(code_lib_file_loc, 'w') as file: pass with open(jarvis_plan_file_loc, 'w') as file: pass with open(jarvis_logs_file_loc, 'w') as file: pass with open(coder_plan_file_loc, 'w') as file: pass with open(coder_logs_file_loc, 'w') as file: pass with open(extlib_plan_file_loc, 'w') as file: pass with open(extlib_logs_file_loc, 'w') as file: pass memfiles_jarvis = {} memfiles_coder = {} memfiles_extlib = {} memfiles_writecode_interactivecoder = {} memfiles_writecode_test = {} memfiles_jarvis["plan"] = jarvis_plan_file_loc memfiles_jarvis["logs"] = jarvis_logs_file_loc memfiles_coder["plan"] = coder_plan_file_loc memfiles_coder["logs"] = coder_logs_file_loc memfiles_coder["code_library"] = code_lib_file_loc memfiles_extlib["plan"] = extlib_plan_file_loc memfiles_extlib["logs"] = extlib_logs_file_loc memfiles_extlib["code_library"] = code_lib_file_loc memfiles_writecode_interactivecoder["code_library"] = code_lib_file_loc memfiles_writecode_test["code_library"] = code_lib_file_loc cfg["memory_files"] = memfiles_jarvis cfg["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["Coder"]["memory_files"] = memfiles_coder cfg["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["Coder"]["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["extend_library"]["memory_files"] = memfiles_extlib cfg["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["Coder"]["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["extend_library"]["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["write_code"][ "subflows_config"]["Executor"]["subflows_config"]["write_code"][ "memory_files"] = memfiles_writecode_interactivecoder cfg["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["Coder"]["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["extend_library"]["subflows_config"]["CtrlExMem"]["subflows_config"]["Executor"]["subflows_config"]["write_code"][ "subflows_config"]["Executor"]["subflows_config"]["test"]["memory_files"] = memfiles_writecode_test 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 current_dir = os.getcwd() cfg_path = os.path.join(current_dir, "JarvisFlow.yaml") cfg = read_yaml_file(cfg_path) # ~~~ setting api information into config ~~~ quick_load(cfg, api_information) # ~~~ setting memory files into config ~~~ set_up_memfiles(cfg) # ~~~ instantiating the flow and input data ~~~ JarvisFlow = hydra.utils.instantiate(cfg, _recursive_=False, _convert_="partial") input_data = { # "goal": "fetch a random joke from the internet and send the joke" # "from haolongli_neko@outlook.com to leonardli2333@gmail.com, you can find the password of the sender " # "email in the environment variable 'EMAIL_PASSWORD'" #"goal": "When was Michael Jordan born?" "goal": "Download tesla's stock prices from 2022-01-01 to 2022-06-01, plot the prices." } input_message = InputMessage.build( data_dict=input_data, src_flow="Launcher", dst_flow=JarvisFlow.name ) # ~~~ calling the flow ~~~ output_message = JarvisFlow(input_message) # ~~~ printing the output ~~~ print(output_message)