import os import hydra import aiflows from aiflows.flow_launchers import FlowLauncher from aiflows.backends.api_info import ApiInfo from aiflows.utils.general_helpers import read_yaml_file, quick_load_api_keys from aiflows import logging from aiflows.flow_cache import CACHING_PARAMETERS, clear_cache from aiflows.utils import serve_utils from aiflows.workers import run_dispatch_worker_thread from aiflows.messages import FlowMessage from aiflows.interfaces import KeyInterface 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() from aiflows import flow_verse # ~~~ Load Flow dependecies from FlowVerse ~~~ dependencies = [ {"url": "aiflows/ControllerExecutorFlowModule", "revision": os.getcwd()}, ] flow_verse.sync_dependencies(dependencies) if __name__ == "__main__": # ~~~ Set the API information ~~~ # OpenAI backend api_information = [ApiInfo(backend_used="openai", api_key=os.getenv("OPENAI_API_KEY"))] # Azure backend # api_information = [ApiInfo(backend_used = "azure", # api_base = os.getenv("AZURE_API_BASE"), # api_key = os.getenv("AZURE_OPENAI_KEY"), # api_version = os.getenv("AZURE_API_VERSION") )] FLOW_MODULES_PATH = "./" jwt = os.getenv("COLINK_JWT") addr = os.getenv("LOCAL_COLINK_ADDRESS") cl = serve_utils.start_colink_component( "Reverse Number Demo", {"jwt": jwt, "addr": addr} ) # path_to_output_file = "output.jsonl" # Uncomment this line to save the output to disk root_dir = "." cfg_path = os.path.join(root_dir, "demo.yaml") cfg = read_yaml_file(cfg_path) # put the API information in the config serve_utils.recursive_serve_flow( cl = cl, flow_type="ReAct_served", default_config=cfg, default_state=None, default_dispatch_point="coflows_dispatch", ) #in case you haven't started the dispatch worker thread, uncomment #run_dispatch_worker_thread(cl, dispatch_point="coflows_dispatch", flow_modules_base_path=FLOW_MODULES_PATH) quick_load_api_keys(cfg, api_information, key="api_infos") # ~~~ Get the data ~~~ # This can be a list of samples # data = {"id": 0, "goal": "Answer the following question: What is the population of Canada?"} # Uses wikipedia # data = {"id": 0, "goal": "Answer the following question: Who was the NBA champion in 2023?"} data = { "id": 0, "goal": "Answer the following question: What is the profession and date of birth of Michael Jordan?", } # ~~~ Run inference ~~~ proxy_flow = serve_utils.recursive_mount( cl=cl, client_id="local", flow_type="ReAct_served", config_overrides=cfg, initial_state=None, dispatch_point_override=None, ) # ~~~ Print the output ~~~ input_message = FlowMessage( data= data, src_flow="Coflows team", dst_flow=proxy_flow, is_input_msg=True ) future = proxy_flow.ask(input_message) print(future.get_data())