File size: 2,146 Bytes
4462cc9 7a5b123 4462cc9 7a5b123 d9d05c8 4462cc9 a8d8d40 4462cc9 7a5b123 4462cc9 7a5b123 d9d05c8 4462cc9 8261d86 4462cc9 8d743fd 4462cc9 8d743fd 4462cc9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
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
from aiflows.utils.general_helpers import quick_load
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/ContentWriterFlowModule", "revision": "main"},
{"url": "Tachi67/InteractivePlanGenFlowModule", "revision": "main"},
{"url": "Tachi67/PlanWriterFlowModule", "revision": "main"},
{"url": "aiflows/ChatFlowModule", "revision": "297c90d08087d9ff3139521f11d1a48d7dc63ed4"},
]
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
current_dir = os.getcwd()
cfg_path = os.path.join(current_dir, "PlanWriterFlow.yaml")
cfg = read_yaml_file(cfg_path)
# ~~~ setting api information into config ~~~
quick_load(cfg, api_information)
# ~~~ instantiating the flow and input data ~~~
PlanWriterFlow = 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
mem_files = {"plan": plan_file_location}
input_data = {
"goal": "create a function that adds two numbers and returns the result",
"memory_files": mem_files
}
input_message = InputMessage.build(
data_dict=input_data,
src_flow="Launcher",
dst_flow=PlanWriterFlow.name
)
# ~~~ calling the flow ~~~
output_message = PlanWriterFlow(input_message)
|