tests/agents/test_predictor.py

@@ -1,57 +0,0 @@
-import pytest
-from app.agents import AppModels
-from app.agents.predictor import PredictorInput, PredictorOutput, PredictorStyle
-from app.agents.prompts import PREDICTOR_INSTRUCTIONS
-from app.api.core.markets import ProductInfo
-
-def unified_checks(model: AppModels, input: PredictorInput) -> None:
-    llm = model.get_agent(PREDICTOR_INSTRUCTIONS, output_schema=PredictorOutput) # type: ignore[arg-type]
-    result = llm.run(input) # type: ignore
-    content = result.content
-
-    assert isinstance(content, PredictorOutput)
-    assert content.strategy not in (None, "", "null")
-    assert isinstance(content.strategy, str)
-    assert isinstance(content.portfolio, list)
-    assert len(content.portfolio) > 0
-    for item in content.portfolio:
-        assert item.asset not in (None, "", "null")
-        assert isinstance(item.asset, str)
-        assert item.percentage >= 0.0
-        assert item.percentage <= 100.0
-        assert isinstance(item.percentage, (int, float))
-        assert item.motivation not in (None, "", "null")
-        assert isinstance(item.motivation, str)
-    # La somma delle percentuali deve essere esattamente 100
-    total_percentage = sum(item.percentage for item in content.portfolio)
-    assert abs(total_percentage - 100) < 0.01  # Permette una piccola tolleranza per errori di arrotondamento
-
-class TestPredictor:
-
-    def inputs(self) -> PredictorInput:
-        data: list[ProductInfo] = []
-        for symbol, price in [("BTC", 60000.00), ("ETH", 3500.00), ("SOL", 150.00)]:
-            product_info = ProductInfo()
-            product_info.symbol = symbol
-            product_info.price = price
-            data.append(product_info)
-
-        return PredictorInput(data=data, style=PredictorStyle.AGGRESSIVE, sentiment="positivo")
-
-    def test_gemini_model_output(self):
-        inputs = self.inputs()
-        unified_checks(AppModels.GEMINI, inputs)
-
-    def test_ollama_qwen_4b_model_output(self):
-        inputs = self.inputs()
-        unified_checks(AppModels.OLLAMA_QWEN_4B, inputs)
-
-    @pytest.mark.slow
-    def test_ollama_qwen_latest_model_output(self):
-        inputs = self.inputs()
-        unified_checks(AppModels.OLLAMA_QWEN, inputs)
-
-    @pytest.mark.slow
-    def test_ollama_gpt_oss_model_output(self):
-        inputs = self.inputs()
-        unified_checks(AppModels.OLLAMA_GPT, inputs)

tests/tools/test_market_tool.py

@@ -1,5 +1,5 @@
 import pytest
-from app.api.markets import MarketAPIsTool
+from app.api.tools import MarketAPIsTool
 
 
 @pytest.mark.tools

tests/tools/test_news_tool.py

@@ -1,5 +1,5 @@
 import pytest
-from app.api.news import NewsAPIsTool
+from app.api.tools import NewsAPIsTool
 
 
 @pytest.mark.tools

tests/tools/test_socials_tool.py

@@ -1,5 +1,5 @@
 import pytest
-from app.api.social import SocialAPIsTool
+from app.api.tools import SocialAPIsTool
 
 
 @pytest.mark.tools