src/app/agents/pipeline.py

@@ -1,9 +1,7 @@
 import logging
-from agno.run.agent import RunOutput
 from app.agents.models import AppModels
 from app.agents.team import create_team_with
-from app.agents.predictor import PREDICTOR_INSTRUCTIONS, PredictorInput, PredictorOutput, PredictorStyle
-from app.base.markets import ProductInfo
+from app.agents.predictor import PREDICTOR_INSTRUCTIONS, PredictorOutput, PredictorStyle
 
 logging = logging.getLogger(__name__)
 
@@ -79,40 +77,3 @@ class Pipeline:
             raise ValueError("Team output is not a string")
         logging.info(f"Team finished")
         return team_outputs.content
-
-        # # Step 2: aggregazione output strutturati
-        # all_products: list[ProductInfo] = []
-        # sentiments: list[str] = []
-
-        # for agent_output in team_outputs.member_responses:
-        #     if isinstance(agent_output, RunOutput) and agent_output.metadata is not None:
-        #         keys = agent_output.metadata.keys()
-        #         if "products" in keys:
-        #             all_products.extend(agent_output.metadata["products"])
-        #         if "sentiment_news" in keys:
-        #             sentiments.append(agent_output.metadata["sentiment_news"])
-        #         if "sentiment_social" in keys:
-        #             sentiments.append(agent_output.metadata["sentiment_social"])
-
-        # aggregated_sentiment = "\n".join(sentiments)
-
-        # # Step 3: invocazione Predictor
-        # predictor_input = PredictorInput(
-        #     data=all_products,
-        #     style=self.style,
-        #     sentiment=aggregated_sentiment
-        # )
-
-        # result = self.predictor.run(predictor_input) # type: ignore
-        # if not isinstance(result.content, PredictorOutput):
-        #     return "❌ Errore: il modello non ha restituito un output valido."
-        # prediction: PredictorOutput = result.content
-
-        # Step 4: restituzione strategia finale
-        # portfolio_lines = "\n".join(
-        #     [f"{item.asset} ({item.percentage}%): {item.motivation}" for item in prediction.portfolio]
-        # )
-        # return (
-        #     f"📊 Strategia ({self.style.value}): {prediction.strategy}\n\n"
-        #     f"💼 Portafoglio consigliato:\n{portfolio_lines}"
-        # )