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import os
import hydra
import aiflows
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 serving
from aiflows.workers import run_dispatch_worker_thread
from aiflows.messages import FlowMessage
from aiflows.interfaces import KeyInterface
from aiflows.utils.colink_utils import start_colink_server
from aiflows import flow_verse
dependencies = [
{
"url": "aiflows/FunSearchFlowModule",
"revision": os.path.abspath("../")
}
]
flow_verse.sync_dependencies(dependencies)
logging.set_verbosity_debug()
if __name__ == "__main__":
cl = start_colink_server()
serving.recursive_serve_flow(
cl=cl,
flow_class_name="flow_modules.aiflows.FunSearchFlowModule.EvaluatorFlow",
flow_endpoint="EvaluatorFlow",
)
run_dispatch_worker_thread(cl)
config_overrides = read_yaml_file(os.path.join(".", "demo.yaml"))
funsearch_proxy = serving.get_flow_instance(
cl=cl,
flow_endpoint="EvaluatorFlow",
config_overrides=config_overrides,
)
data = {
'artifact': \
'def solve_function(input) -> str:\n """Attempt at solving the problem given the input input and returns the predicted output (see the top of the file for problem description)"""\n return \'YES\'\n'
}
input_message = funsearch_proxy.package_input_message(data = data)
funsearch_proxy.send_message(input_message)
future = funsearch_proxy.get_reply_future(input_message)
response = future.get_data()
print("~~~Response~~~")
print(response)
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