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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.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 [email protected] to [email protected], 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) |