Files
nifodea/infrastructure/ai/assistant.py
T
oqyude 541a76835f T5: Dependency Injection — services через composition root
- AssistantService теперь принимает ForecastService в конструкторе
  (раньше создавал new ForecastService() внутри analyze/advice)
- infrastructure/cli/main.py: _build_services() — composition root,
  собирает граф ForecastService, ScenarioService, AssistantService, CurrencyConverter
- Все CLI-команды используют _build_services(model) вместо прямого new
- test_ai.py: обновлён под новый контракт AssistantService

Tests: 67/67 pass.
2026-10-08 16:53:04 +03:00

80 lines
2.6 KiB
Python

import json
from decimal import Decimal
from infrastructure.ai import prompts
from domain import CurrencyConverter, FinancialModel
from application.forecast import ForecastService
class AssistantError(Exception):
pass
class _DecimalEncoder(json.JSONEncoder):
"""JSON-сериализатор: Decimal → str (для AI-промптов)."""
def default(self, o):
if isinstance(o, Decimal):
return str(o)
return super().default(o)
class AssistantService:
def __init__(
self,
model: FinancialModel,
forecast_service: ForecastService,
converter: CurrencyConverter | None = None,
display_currency: str | None = None,
):
self.model = model
self.forecast_service = forecast_service
self.converter = converter or CurrencyConverter(model.exchange_rates)
self.display_currency = display_currency or model.base_currency
def analyze(self, months: int = 12) -> dict:
forecast_result = self.forecast_service.forecast_cashflow(months)
summary = self.forecast_service.summary(months)
prompt = prompts.format_context(
model_json=json.dumps(self.model.to_dict(), indent=2, ensure_ascii=False, cls=_DecimalEncoder),
forecast_json=json.dumps(forecast_result, indent=2, ensure_ascii=False, cls=_DecimalEncoder),
months=months,
base_currency=self.model.base_currency,
display_currency=self.display_currency,
)
return {
"prompt": prompt,
"summary": summary,
"forecast": forecast_result,
"ai_response": None,
}
def advice(self, question: str, months: int = 12) -> dict:
forecast_result = self.forecast_service.forecast_cashflow(months)
prompt = prompts.ADVICE_PROMPT.format(
model_json=json.dumps(self.model.to_dict(), indent=2, ensure_ascii=False, cls=_DecimalEncoder),
forecast_json=json.dumps(forecast_result, indent=2, ensure_ascii=False, cls=_DecimalEncoder),
question=question,
base_currency=self.model.base_currency,
display_currency=self.display_currency,
)
return {
"prompt": prompt,
"ai_response": None,
}
def compare_scenarios(self, scenarios_json: str) -> dict:
prompt = prompts.SCENARIO_COMPARISON_PROMPT.format(
scenarios_json=scenarios_json,
base_currency=self.model.base_currency,
display_currency=self.display_currency,
)
return {
"prompt": prompt,
"ai_response": None,
}