Piotr Oleszczyk
cfd2485b7e
Enable on-demand INCI retrieval in /routines/suggest through Gemini function calling so detailed ingredient data is fetched only when needed. Persist and normalize tool_trace data in AI logs to make function-call behavior directly inspectable via /ai-logs endpoints.
44 lines
1.3 KiB
Python
44 lines
1.3 KiB
Python
import uuid
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from typing import Any, cast
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from innercontext.models.ai_log import AICallLog
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def test_list_ai_logs_normalizes_tool_trace_string(client, session):
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log = AICallLog(
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id=uuid.uuid4(),
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endpoint="routines/suggest",
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model="gemini-3-flash-preview",
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success=True,
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)
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log.tool_trace = cast(
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Any,
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'{"mode":"function_tools","events":[{"function":"get_product_inci"}]}',
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)
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session.add(log)
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session.commit()
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response = client.get("/ai-logs")
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assert response.status_code == 200
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data = response.json()
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assert len(data) == 1
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assert data[0]["tool_trace"]["mode"] == "function_tools"
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assert data[0]["tool_trace"]["events"][0]["function"] == "get_product_inci"
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def test_get_ai_log_normalizes_tool_trace_string(client, session):
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log = AICallLog(
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id=uuid.uuid4(),
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endpoint="routines/suggest",
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model="gemini-3-flash-preview",
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success=True,
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)
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log.tool_trace = cast(Any, '{"mode":"function_tools","round":1}')
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session.add(log)
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session.commit()
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response = client.get(f"/ai-logs/{log.id}")
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assert response.status_code == 200
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payload = response.json()
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assert payload["tool_trace"]["mode"] == "function_tools"
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assert payload["tool_trace"]["round"] == 1
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