update ensemble example

examples/ags/w_action_node/graph.py

@@ -5,7 +5,7 @@
 
 from metagpt.llm import LLM 
 
-from examples.ags.w_action_node.operator import Generate, GenerateCode, Review, Revise, Ensemble
+from examples.ags.w_action_node.operator import Generate, GenerateCode, Review, Revise, Ensemble, ScEnsemble
 
 class Graph:
     def __init__(self, name:str, llm:LLM) -> None:
@@ -25,22 +25,41 @@ class HumanEvalGraph(Graph):
         self.review = Review(llm=llm, criteria=criteria)
         self.revise = Revise(llm=llm)
         self.ensemble = Ensemble(llm=llm)
+        self.scensemble = ScEnsemble(llm=llm)
     
-    async def __call__(self, problem:str, ensemble_count:int = 2):
-        # TODO Ensemble Implamentation
+    # async def __call__(self, problem:str, ensemble_count:int = 2):
+    #     solution_list = []
+    #     for _ in range(ensemble_count):
+    #         solution = await self.single_solve(problem, 3)
+    #         solution_list.append(solution)
+    #     solution = await self.ensemble(solution_list, problem)
+    #     return solution
+
+    async def __call__(self, problem:str):
         solution_list = []
-        for _ in range(ensemble_count):
-            solution = await self.single_solve(problem, 3)
+        for _ in range(3):
+            solution = await self.generate_code(problem)
             solution = solution.get('code_solution')
             solution_list.append(solution)
         solution = await self.ensemble(solution_list, problem)
         return solution
     
+    # async def __call__(self, problem:str):
+    #     solution_list = []
+    #     for _ in range(3):
+    #         solution = await self.generate_code(problem)
+    #         solution = solution.get('code_solution')
+    #         solution_list.append(solution)
+    #     solution = await self.scensemble(solution_list, problem)
+    #     return solution
+    
     async def single_solve(self, problem:str, max_loop:int):
         solution = await self.generate_code(problem)
+        solution = solution.get('code_solution')
         for _ in range(max_loop):
             review_feedback = await self.review(problem, solution)
             if review_feedback['review_result']:
                 break
             solution = await self.revise(problem, solution, review_feedback['feedback'])
+            solution = solution.get('revised_solution')
         return solution

examples/ags/w_action_node/operator.py

@@ -65,6 +65,21 @@ class Revise(Operator):
 
 class Ensemble(Operator):
 
+    def __init__(self, name:str ="Ensembler", llm: LLM = LLM()):
+        super().__init__(name, llm)
+
+    async def __call__(self, solutions:List, problem_description):
+        solution_text = ""
+        for solution in solutions:
+            solution_text += str(solution) + "\n"
+        prompt = ENSEMBLE_PROMPT.format(solutions=solution_text, problem_description=problem_description)
+        node = await ActionNode.from_pydantic(EnsembleOp).fill(context=prompt, llm=self.llm)
+        response = node.instruct_content.model_dump()
+        return response
+    
+
+class ScEnsemble(Operator):
+
     def __init__(self, name:str ="Ensembler", llm: LLM = LLM()):
         super().__init__(name, llm)
 

examples/ags/w_action_node/operator_an.py

@@ -4,7 +4,6 @@
 # @Desc    : action nodes for operator
 
 from pydantic import BaseModel, Field
-from metagpt.actions.action_node import ActionNode
 
 class GenerateOp(BaseModel):
     solution: str = Field(default="", description="Your Solution for this problem")
@@ -21,3 +20,6 @@ class ReviseOp(BaseModel):
 
 class EnsembleOp(BaseModel):
     final_solution: str = Field(default="", description="Final ensemble solution for this problem")
+
+class ScEnsembleOp(BaseModel):
+    solution_number: int = Field(default="", description="Choose The Best Solution Between These, and outp[ut the solution number")

examples/ags/w_action_node/prompt.py

@@ -25,6 +25,6 @@ Then output the revised solution.
 """
 
 ENSEMBLE_PROMPT = """
-For the question described as {problem_description},
-please ensemble the following solutions: {solutions}, and provide an ensemble solution.
+For the question described as {problem_description}, Solutions: {solutions}
+Please select the solution that appears most frequently from these options and ensemble this to provide best solution.
 """