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import evoagentx.workflow.operators as operator |
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import examples.aflow.scicode.optimized.round_4.prompt as prompt_custom |
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from evoagentx.models.model_configs import LLMConfig |
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from evoagentx.benchmark.benchmark import Benchmark |
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from evoagentx.models.model_utils import create_llm_instance |
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class Workflow: |
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def __init__( |
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self, |
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name: str, |
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llm_config: LLMConfig, |
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benchmark: Benchmark |
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): |
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self.name = name |
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self.llm = create_llm_instance(llm_config) |
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self.benchmark = benchmark |
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self.custom = operator.Custom(self.llm) |
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self.custom_code_generate = operator.CustomCodeGenerate(self.llm) |
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self.test = operator.Test(self.llm) |
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async def __call__(self, problem: str, entry_point: str): |
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""" |
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Implementation of the workflow |
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Generate code and validate it using tests, with a retry mechanism. |
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""" |
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solution = await self.custom_code_generate(problem=problem, entry_point=entry_point, instruction=prompt_custom.GENERATE_PYTHON_CODE_PROMPT) |
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test_result = await self.test(problem=problem, solution=solution['response'], entry_point=entry_point, benchmark=self.benchmark) |
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retry_count = 0 |
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while not test_result['result'] and retry_count < 2: |
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retry_count += 1 |
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solution = await self.custom_code_generate(problem=problem, entry_point=entry_point, instruction=prompt_custom.GENERATE_PYTHON_CODE_PROMPT) |
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test_result = await self.test(problem=problem, solution=solution['response'], entry_point=entry_point, benchmark=self.benchmark) |
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if test_result['result']: |
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return solution['response'] |
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else: |
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return "Solution failed after retries." |
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