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Team Workflow aggiornato #37

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Berack96 merged 16 commits from 19-team-instructions into main 2025-10-20 22:05:58 +02:00
Conversation 3 Commits 16 Files Changed 19 +75 -76
4 changed files with 75 additions and 76 deletions
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4
src/app/agents/__init__.py
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@@ -1,4 +1,4 @@
from app.agents.predictor import PredictorInput, PredictorOutput
from app.agents.pipeline import Pipeline, PipelineInputs, PipelineEvent
copilot-pull-request-reviewer[bot] commented 2025-10-20 18:05:29 +02:00 (Migrated from github.com)
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PipelineInputs is imported twice from different modules, which will cause the second import to shadow the first. Remove the duplicate import from line 1.

from app.agents.pipeline import Pipeline, PipelineEvent
`PipelineInputs` is imported twice from different modules, which will cause the second import to shadow the first. Remove the duplicate import from line 1. ```suggestion from app.agents.pipeline import Pipeline, PipelineEvent ```
from app.agents.core import PipelineInputs, QueryOutputs
__all__ = ["PredictorInput", "PredictorOutput", "Pipeline", "PipelineInputs", "PipelineEvent"]
__all__ = ["Pipeline", "PipelineInputs", "PipelineEvent", "QueryOutputs"]

72
src/app/agents/core.py Normal file
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@@ -0,0 +1,72 @@
from pydantic import BaseModel
from app.configs import AppConfig
class QueryOutputs(BaseModel):
response: str
is_ok: bool
class PipelineInputs:
"""
Classe necessaria per passare gli input alla Pipeline.
Serve per raggruppare i parametri e semplificare l'inizializzazione.
"""
def __init__(self, configs: AppConfig | None = None) -> None:
"""
Inputs per la Pipeline di agenti.
Setta i valori di default se non specificati.
"""
self.configs = configs if configs else AppConfig()
agents = self.configs.agents
self.team_model = self.configs.get_model_by_name(agents.team_model)
self.team_leader_model = self.configs.get_model_by_name(agents.team_leader_model)
self.predictor_model = self.configs.get_model_by_name(agents.predictor_model)
self.strategy = self.configs.get_strategy_by_name(agents.strategy)
self.user_query = ""
# ======================
# Dropdown handlers
# ======================
def choose_team_leader(self, index: int):
"""
Sceglie il modello LLM da usare per il Team Leader.
"""
self.leader_model = self.configs.models.all_models[index]
def choose_team(self, index: int):
"""
Sceglie il modello LLM da usare per il Team.
"""
self.team_model = self.configs.models.all_models[index]
def choose_strategy(self, index: int):
"""
copilot-pull-request-reviewer[bot] commented 2025-10-20 18:05:28 +02:00 (Migrated from github.com)
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Variable assignment uses team_leader_model instead of leader_model as mentioned in the method's docstring. The docstring should be updated or the variable name should be consistent.

Variable assignment uses `team_leader_model` instead of `leader_model` as mentioned in the method's docstring. The docstring should be updated or the variable name should be consistent.
copilot-pull-request-reviewer[bot] commented 2025-10-20 21:51:58 +02:00 (Migrated from github.com)
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The choose_team_leader method assigns to self.team_leader_model but the initialization in __init__ uses a different assignment pattern via get_model_by_name(). This inconsistency means the model assignment won't have the same validation and could break if index is out of bounds. Use self.team_leader_model = self.configs.models.all_models[index] with proper validation or use the same pattern as __init__.

        model_list = self.configs.models.all_models
        if 0 <= index < len(model_list):
            model_name = model_list[index].name
            self.team_leader_model = self.configs.get_model_by_name(model_name)
        else:
            raise IndexError(f"Model index {index} out of range for team leader selection.")
The `choose_team_leader` method assigns to `self.team_leader_model` but the initialization in `__init__` uses a different assignment pattern via `get_model_by_name()`. This inconsistency means the model assignment won't have the same validation and could break if `index` is out of bounds. Use `self.team_leader_model = self.configs.models.all_models[index]` with proper validation or use the same pattern as `__init__`. ```suggestion model_list = self.configs.models.all_models if 0 <= index < len(model_list): model_name = model_list[index].name self.team_leader_model = self.configs.get_model_by_name(model_name) else: raise IndexError(f"Model index {index} out of range for team leader selection.") ```
Sceglie la strategia da usare per il Team.
"""
self.strategy = self.configs.strategies[index]
# ======================
# Helpers
# ======================
copilot-pull-request-reviewer[bot] commented 2025-10-20 21:51:59 +02:00 (Migrated from github.com)
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The choose_team method has the same issue as choose_team_leader: it directly indexes into all_models without validation, which could raise an IndexError if the index is invalid. Consider adding bounds checking or using a safer retrieval method.

        all_models = self.configs.models.all_models
        if not (0 <= index < len(all_models)):
            raise ValueError(f"Invalid index {index} for team models. Must be between 0 and {len(all_models)-1}.")
        self.team_model = all_models[index]
The `choose_team` method has the same issue as `choose_team_leader`: it directly indexes into `all_models` without validation, which could raise an `IndexError` if the index is invalid. Consider adding bounds checking or using a safer retrieval method. ```suggestion all_models = self.configs.models.all_models if not (0 <= index < len(all_models)): raise ValueError(f"Invalid index {index} for team models. Must be between 0 and {len(all_models)-1}.") self.team_model = all_models[index] ```
def list_models_names(self) -> list[str]:
"""
Restituisce la lista dei nomi dei modelli disponibili.
"""
return [model.label for model in self.configs.models.all_models]
def list_strategies_names(self) -> list[str]:
"""
Restituisce la lista delle strategie disponibili.
"""
return [strat.label for strat in self.configs.strategies]

59
src/app/agents/pipeline.py
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@@ -12,7 +12,7 @@ from agno.workflow.workflow import Workflow
from app.api.tools import *
from app.agents.prompts import *
from app.configs import AppConfig
from app.agents.core import PipelineInputs
logging = logging.getLogger("pipeline")
@@ -28,63 +28,6 @@ class PipelineEvent(str, Enum):
return event == self.value or (WorkflowRunEvent.step_completed and step_name == self.value)
class PipelineInputs:
"""
Classe necessaria per passare gli input alla Pipeline.
Serve per raggruppare i parametri e semplificare l'inizializzazione.
"""
def __init__(self, configs: AppConfig | None = None) -> None:
"""
Inputs per la Pipeline di agenti.
Setta i valori di default se non specificati.
"""
self.configs = configs if configs else AppConfig()
agents = self.configs.agents
self.team_model = self.configs.get_model_by_name(agents.team_model)
self.team_leader_model = self.configs.get_model_by_name(agents.team_leader_model)
self.predictor_model = self.configs.get_model_by_name(agents.predictor_model)
self.strategy = self.configs.get_strategy_by_name(agents.strategy)
self.user_query = ""
# ======================
# Dropdown handlers
# ======================
def choose_team_leader(self, index: int):
"""
Sceglie il modello LLM da usare per il Team Leader.
"""
self.leader_model = self.configs.models.all_models[index]
def choose_team(self, index: int):
"""
Sceglie il modello LLM da usare per il Team.
"""
self.team_model = self.configs.models.all_models[index]
def choose_strategy(self, index: int):
"""
Sceglie la strategia da usare per il Team.
"""
self.strategy = self.configs.strategies[index]
# ======================
# Helpers
# ======================
def list_models_names(self) -> list[str]:
"""
Restituisce la lista dei nomi dei modelli disponibili.
"""
return [model.label for model in self.configs.models.all_models]
def list_strategies_names(self) -> list[str]:
"""
Restituisce la lista delle strategie disponibili.
"""
return [strat.label for strat in self.configs.strategies]
class Pipeline:
"""
Coordina gli agenti di servizio (Market, News, Social) e il Predictor finale.

16
src/app/agents/predictor.py
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@@ -1,16 +0,0 @@
from pydantic import BaseModel, Field
from app.api.core.markets import ProductInfo
class PredictorInput(BaseModel):
data: list[ProductInfo] = Field(..., description="Market data as a list of ProductInfo")
style: str = Field(..., description="Prediction style")
sentiment: str = Field(..., description="Aggregated sentiment from news and social analysis")
class ItemPortfolio(BaseModel):
asset: str = Field(..., description="Name of the asset")
percentage: float = Field(..., description="Percentage allocation to the asset")
motivation: str = Field(..., description="Motivation for the allocation")
class PredictorOutput(BaseModel):
strategy: str = Field(..., description="Concise operational strategy in Italian")
portfolio: list[ItemPortfolio] = Field(..., description="List of portfolio items with allocations")