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https://github.com/bytedance/deer-flow.git
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e3179cd54d
Phase 2-B: run persistence + event storage + token tracking. - ORM models: RunRow (with token fields), ThreadMetaRow, RunEventRow - RunRepository implements RunStore ABC via SQLAlchemy ORM - ThreadMetaRepository with owner access control - DbRunEventStore with trace content truncation and cursor pagination - JsonlRunEventStore with per-run files and seq recovery from disk - RunJournal (BaseCallbackHandler) captures LLM/tool/lifecycle events, accumulates token usage by caller type, buffers and flushes to store - RunManager now accepts optional RunStore for persistent backing - Worker creates RunJournal, writes human_message, injects callbacks - Gateway deps use factory functions (RunRepository when DB available) - New endpoints: messages, run messages, run events, token-usage - ThreadCreateRequest gains assistant_id field - 92 tests pass (33 new), zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
231 lines
8.9 KiB
Python
231 lines
8.9 KiB
Python
"""Tests for RunJournal callback handler.
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Uses MemoryRunEventStore as the backend for direct event inspection.
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"""
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import asyncio
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from unittest.mock import MagicMock
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from uuid import uuid4
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import pytest
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from deerflow.runtime.events.store.memory import MemoryRunEventStore
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from deerflow.runtime.journal import RunJournal
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@pytest.fixture
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def journal_setup():
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store = MemoryRunEventStore()
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on_complete_data = {}
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def on_complete(**data):
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on_complete_data.update(data)
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j = RunJournal("r1", "t1", store, on_complete=on_complete, flush_threshold=100)
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return j, store, on_complete_data
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def _make_llm_response(content="Hello", usage=None):
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"""Create a mock LLM response with a message."""
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msg = MagicMock()
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msg.content = content
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msg.tool_calls = []
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msg.response_metadata = {"model_name": "test-model"}
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msg.usage_metadata = usage
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gen = MagicMock()
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gen.message = msg
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response = MagicMock()
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response.generations = [[gen]]
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return response
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class TestLlmCallbacks:
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@pytest.mark.anyio
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async def test_on_llm_end_produces_trace_event(self, journal_setup):
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j, store, _ = journal_setup
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run_id = uuid4()
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j.on_llm_start({}, [], run_id=run_id, tags=["lead_agent"])
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j.on_llm_end(_make_llm_response("Hi"), run_id=run_id, tags=["lead_agent"])
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await j.flush()
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events = await store.list_events("t1", "r1")
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trace_events = [e for e in events if e["event_type"] == "llm_end"]
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assert len(trace_events) == 1
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assert trace_events[0]["category"] == "trace"
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@pytest.mark.anyio
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async def test_on_llm_end_lead_agent_produces_ai_message(self, journal_setup):
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j, store, _ = journal_setup
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run_id = uuid4()
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j.on_llm_start({}, [], run_id=run_id, tags=["lead_agent"])
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j.on_llm_end(_make_llm_response("Answer"), run_id=run_id, tags=["lead_agent"])
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await j.flush()
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messages = await store.list_messages("t1")
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assert len(messages) == 1
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assert messages[0]["event_type"] == "ai_message"
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assert messages[0]["content"] == "Answer"
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@pytest.mark.anyio
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async def test_on_llm_end_subagent_no_ai_message(self, journal_setup):
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j, store, _ = journal_setup
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run_id = uuid4()
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j.on_llm_start({}, [], run_id=run_id, tags=["subagent:research"])
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j.on_llm_end(_make_llm_response("Sub answer"), run_id=run_id, tags=["subagent:research"])
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await j.flush()
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messages = await store.list_messages("t1")
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assert len(messages) == 0
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@pytest.mark.anyio
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async def test_token_accumulation(self, journal_setup):
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j, store, on_complete_data = journal_setup
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usage1 = {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15}
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usage2 = {"input_tokens": 20, "output_tokens": 10, "total_tokens": 30}
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j.on_llm_start({}, [], run_id=uuid4(), tags=["lead_agent"])
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j.on_llm_end(_make_llm_response("A", usage=usage1), run_id=uuid4(), tags=["lead_agent"])
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j.on_llm_start({}, [], run_id=uuid4(), tags=["lead_agent"])
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j.on_llm_end(_make_llm_response("B", usage=usage2), run_id=uuid4(), tags=["lead_agent"])
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assert j._total_input_tokens == 30
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assert j._total_output_tokens == 15
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assert j._total_tokens == 45
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assert j._llm_call_count == 2
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@pytest.mark.anyio
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async def test_caller_token_classification(self, journal_setup):
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j, store, _ = journal_setup
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usage = {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15}
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j.on_llm_start({}, [], run_id=uuid4(), tags=["lead_agent"])
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j.on_llm_end(_make_llm_response("A", usage=usage), run_id=uuid4(), tags=["lead_agent"])
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j.on_llm_start({}, [], run_id=uuid4(), tags=["subagent:research"])
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j.on_llm_end(_make_llm_response("B", usage=usage), run_id=uuid4(), tags=["subagent:research"])
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j.on_llm_start({}, [], run_id=uuid4(), tags=["middleware:summarization"])
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j.on_llm_end(_make_llm_response("C", usage=usage), run_id=uuid4(), tags=["middleware:summarization"])
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assert j._lead_agent_tokens == 15
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assert j._subagent_tokens == 15
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assert j._middleware_tokens == 15
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@pytest.mark.anyio
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async def test_usage_metadata_none_no_crash(self, journal_setup):
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j, store, _ = journal_setup
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j.on_llm_start({}, [], run_id=uuid4(), tags=["lead_agent"])
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j.on_llm_end(_make_llm_response("No usage", usage=None), run_id=uuid4(), tags=["lead_agent"])
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# Should not raise
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await j.flush()
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@pytest.mark.anyio
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async def test_latency_tracking(self, journal_setup):
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j, store, _ = journal_setup
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run_id = uuid4()
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j.on_llm_start({}, [], run_id=run_id, tags=["lead_agent"])
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j.on_llm_end(_make_llm_response("Fast"), run_id=run_id, tags=["lead_agent"])
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await j.flush()
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events = await store.list_events("t1", "r1")
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llm_end = [e for e in events if e["event_type"] == "llm_end"][0]
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assert "latency_ms" in llm_end["metadata"]
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assert llm_end["metadata"]["latency_ms"] is not None
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class TestLifecycleCallbacks:
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@pytest.mark.anyio
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async def test_on_chain_end_triggers_on_complete(self, journal_setup):
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j, store, on_complete_data = journal_setup
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j.on_chain_start({}, {}, run_id=uuid4(), parent_run_id=None)
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j.on_chain_end({}, run_id=uuid4(), parent_run_id=None)
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assert "total_tokens" in on_complete_data
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assert "message_count" in on_complete_data
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@pytest.mark.anyio
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async def test_nested_chain_ignored(self, journal_setup):
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j, store, on_complete_data = journal_setup
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parent_id = uuid4()
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j.on_chain_start({}, {}, run_id=uuid4(), parent_run_id=parent_id)
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j.on_chain_end({}, run_id=uuid4(), parent_run_id=parent_id)
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await j.flush()
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events = await store.list_events("t1", "r1")
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lifecycle = [e for e in events if e["category"] == "lifecycle"]
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assert len(lifecycle) == 0
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class TestToolCallbacks:
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@pytest.mark.anyio
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async def test_tool_start_end_produce_trace(self, journal_setup):
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j, store, _ = journal_setup
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j.on_tool_start({"name": "web_search"}, "query", run_id=uuid4())
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j.on_tool_end("results", run_id=uuid4(), name="web_search")
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await j.flush()
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events = await store.list_events("t1", "r1")
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types = {e["event_type"] for e in events}
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assert "tool_start" in types
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assert "tool_end" in types
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class TestCustomEvents:
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@pytest.mark.anyio
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async def test_summarization_event(self, journal_setup):
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j, store, _ = journal_setup
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j.on_custom_event(
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"summarization",
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{"summary": "Context was summarized.", "replaced_count": 5, "replaced_message_ids": ["a", "b"]},
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run_id=uuid4(),
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)
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await j.flush()
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events = await store.list_events("t1", "r1")
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trace = [e for e in events if e["event_type"] == "summarization"]
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assert len(trace) == 1
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messages = await store.list_messages("t1")
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assert len(messages) == 1
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assert messages[0]["event_type"] == "summary"
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class TestBufferFlush:
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@pytest.mark.anyio
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async def test_flush_threshold(self, journal_setup):
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j, store, _ = journal_setup
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j._flush_threshold = 3
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j.on_tool_start({"name": "a"}, "x", run_id=uuid4())
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j.on_tool_start({"name": "b"}, "x", run_id=uuid4())
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# Buffer has 2 events, not yet flushed
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assert len(j._buffer) == 2
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j.on_tool_start({"name": "c"}, "x", run_id=uuid4())
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# Buffer should have been flushed (threshold=3 triggers flush)
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# Give the async task a chance to complete
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await asyncio.sleep(0.1)
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events = await store.list_events("t1", "r1")
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assert len(events) >= 3
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class TestIdentifyCaller:
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def test_lead_agent_tag(self, journal_setup):
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j, _, _ = journal_setup
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assert j._identify_caller({"tags": ["lead_agent"]}) == "lead_agent"
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def test_subagent_tag(self, journal_setup):
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j, _, _ = journal_setup
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assert j._identify_caller({"tags": ["subagent:research"]}) == "subagent:research"
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def test_middleware_tag(self, journal_setup):
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j, _, _ = journal_setup
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assert j._identify_caller({"tags": ["middleware:summarization"]}) == "middleware:summarization"
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def test_no_tags_returns_unknown(self, journal_setup):
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j, _, _ = journal_setup
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assert j._identify_caller({"tags": []}) == "unknown"
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assert j._identify_caller({}) == "unknown"
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class TestPublicMethods:
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@pytest.mark.anyio
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async def test_set_first_human_message(self, journal_setup):
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j, _, _ = journal_setup
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j.set_first_human_message("Hello world")
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assert j._first_human_msg == "Hello world"
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@pytest.mark.anyio
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async def test_get_completion_data(self, journal_setup):
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j, _, _ = journal_setup
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j._total_tokens = 100
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j._msg_count = 5
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data = j.get_completion_data()
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assert data["total_tokens"] == 100
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assert data["message_count"] == 5
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