File size: 2,424 Bytes
5374a2d | 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 | import evoagentx.workflow.operators as operator
import examples.aflow.mbpp_new_full.optimized.round_4.prompt as prompt_custom
from evoagentx.models.model_configs import LLMConfig
from evoagentx.benchmark.benchmark import Benchmark
from evoagentx.models.model_utils import create_llm_instance
class Workflow:
def __init__(
self,
name: str,
llm_config: LLMConfig,
benchmark: Benchmark
):
self.name = name
self.llm = create_llm_instance(llm_config)
self.benchmark = benchmark
self.custom = operator.Custom(self.llm)
self.custom_code_generate = operator.CustomCodeGenerate(self.llm)
self.test = operator.Test(self.llm)
self.sc_ensemble = operator.ScEnsemble(self.llm)
self.revise_custom = operator.Custom(self.llm)
self.logging_enabled = True # Added flag to enable/disable logging
async def log(self, message: str):
if self.logging_enabled:
print(message) # Simple logging output, can be replaced with advanced logging
async def __call__(self, problem: str, entry_point: str):
await self.log(f"Starting to generate solutions for the problem: {problem}")
solution_candidates = []
for _ in range(3):
await self.log("Generating solution candidate...")
solution = await self.custom_code_generate(problem=problem, entry_point=entry_point, instruction=prompt_custom.GENERATE_PYTHON_CODE_PROMPT)
solution_candidates.append(solution['response'])
await self.log(f"Generated solution candidate: {solution['response']}")
final_solution = await self.sc_ensemble(solutions=solution_candidates, problem=problem)
await self.log(f"Final solution selected: {final_solution['response']}")
test_result = await self.test(problem=problem, solution=final_solution['response'], entry_point=entry_point, benchmark=self.benchmark)
if not test_result['result']:
await self.log("Test failed, revising solution...")
revision_response = await self.revise_custom(input=problem + " Current Solution: " + final_solution['response'], instruction=prompt_custom.REVISE_PROMPT)
await self.log(f"Revised solution: {revision_response['response']}")
return revision_response['response']
return final_solution['response']
|