| import evoagentx.workflow.operators as operator |
| import examples.aflow.mbpp.optimized.round_8.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.ensemble = operator.ScEnsemble(self.llm) |
| self.alternative_fallback = operator.Custom(self.llm) |
| self.generated_solutions_log = [] |
|
|
| async def __call__(self, problem: str, entry_point: str): |
| """ |
| Implementation of the workflow |
| Custom operator to generate anything you want. |
| But when you want to get standard code, you should use custom_code_generate operator. |
| """ |
| |
| solution = await self.custom_code_generate(problem=problem, entry_point=entry_point, instruction=prompt_custom.GENERATE_PYTHON_CODE_PROMPT) |
| self.generated_solutions_log.append(solution['response']) |
| |
| test_result = await self.test(problem=problem, solution=solution['response'], entry_point=entry_point, benchmark=self.benchmark) |
| |
| if not test_result['result']: |
| unique_solutions = set() |
| while len(unique_solutions) < 3: |
| feedback = f"Last solution failed: {test_result['solution']}.\nPrevious errors: {test_result['error_logs']}." |
| fallback_solution = await self.custom_code_generate(problem=problem, entry_point=entry_point, instruction=prompt_custom.GENERATE_PYTHON_CODE_WITH_FEEDBACK_PROMPT + feedback) |
| |
| |
| self.generated_solutions_log.append(fallback_solution['response']) |
| |
| |
| if fallback_solution['response'] not in unique_solutions: |
| unique_solutions.add(fallback_solution['response']) |
| |
| |
| fallback_results = await asyncio.gather(*(self.test(problem=problem, solution=fallback, entry_point=entry_point, benchmark=self.benchmark) for fallback in unique_solutions)) |
| valid_fallbacks = [res['solution'] for res in fallback_results if res['result']] |
| |
| if valid_fallbacks: |
| |
| final_fallback = await self.custom(input=problem + f" Verify this solution: {valid_fallbacks[0]}.", instruction=prompt_custom.VERIFY_SOLUTION_PROMPT) |
| return final_fallback['response'] |
|
|
| |
| alternative_solution = await self.alternative_fallback(input=problem, instruction=prompt_custom.GENERATE_PYTHON_CODE_PROMPT) |
| self.generated_solutions_log.append(alternative_solution['response']) |
| ensemble_result = await self.ensemble(solutions=[solution['response']] + list(unique_solutions) + [alternative_solution['response']], problem=problem) |
| return ensemble_result['response'] |
|
|
| return test_result['solution'] |
|
|