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