mirror of
https://github.com/Monadical-SAS/reflector.git
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Merge branch 'main' into feat/durable
This commit is contained in:
@@ -1,12 +1,14 @@
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"""Tests for LLM parse error recovery using llama-index Workflow"""
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from time import monotonic
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from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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from pydantic import BaseModel, Field
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from workflows.errors import WorkflowRuntimeError
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from workflows.errors import WorkflowRuntimeError, WorkflowTimeoutError
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from reflector.llm import LLM, LLMParseError, StructuredOutputWorkflow
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from reflector.utils.retry import RetryException
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class TestResponse(BaseModel):
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@@ -355,3 +357,132 @@ class TestNetworkErrorRetries:
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# Only called once - Workflow doesn't retry network errors
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assert mock_settings.llm.acomplete.call_count == 1
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class TestWorkflowTimeoutRetry:
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"""Test timeout retry mechanism in get_structured_response"""
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@pytest.mark.asyncio
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async def test_timeout_retry_succeeds_on_retry(self, test_settings):
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"""Test that WorkflowTimeoutError triggers retry and succeeds"""
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llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
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call_count = {"count": 0}
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async def workflow_run_side_effect(*args, **kwargs):
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call_count["count"] += 1
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if call_count["count"] == 1:
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raise WorkflowTimeoutError("Operation timed out after 120 seconds")
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return {
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"success": TestResponse(
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title="Test", summary="Summary", confidence=0.95
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)
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}
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with (
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patch("reflector.llm.StructuredOutputWorkflow") as mock_workflow_class,
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patch("reflector.llm.TreeSummarize") as mock_summarize,
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patch("reflector.llm.Settings") as mock_settings,
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):
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mock_workflow = MagicMock()
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mock_workflow.run = AsyncMock(side_effect=workflow_run_side_effect)
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mock_workflow_class.return_value = mock_workflow
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mock_summarizer = MagicMock()
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mock_summarize.return_value = mock_summarizer
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mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
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mock_settings.llm.acomplete = AsyncMock(
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return_value=make_completion_response(
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'{"title": "Test", "summary": "Summary", "confidence": 0.95}'
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)
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)
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result = await llm.get_structured_response(
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prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
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)
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assert result.title == "Test"
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assert result.summary == "Summary"
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assert call_count["count"] == 2
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@pytest.mark.asyncio
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async def test_timeout_retry_exhausts_after_max_attempts(self, test_settings):
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"""Test that timeout retry stops after max attempts"""
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llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
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call_count = {"count": 0}
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async def workflow_run_side_effect(*args, **kwargs):
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call_count["count"] += 1
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raise WorkflowTimeoutError("Operation timed out after 120 seconds")
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with (
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patch("reflector.llm.StructuredOutputWorkflow") as mock_workflow_class,
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patch("reflector.llm.TreeSummarize") as mock_summarize,
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patch("reflector.llm.Settings") as mock_settings,
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):
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mock_workflow = MagicMock()
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mock_workflow.run = AsyncMock(side_effect=workflow_run_side_effect)
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mock_workflow_class.return_value = mock_workflow
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mock_summarizer = MagicMock()
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mock_summarize.return_value = mock_summarizer
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mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
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mock_settings.llm.acomplete = AsyncMock(
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return_value=make_completion_response(
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'{"title": "Test", "summary": "Summary", "confidence": 0.95}'
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)
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)
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with pytest.raises(RetryException, match="Retry attempts exceeded"):
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await llm.get_structured_response(
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prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
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)
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assert call_count["count"] == 3
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@pytest.mark.asyncio
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async def test_timeout_retry_with_backoff(self, test_settings):
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"""Test that exponential backoff is applied between retries"""
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llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
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call_times = []
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async def workflow_run_side_effect(*args, **kwargs):
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call_times.append(monotonic())
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if len(call_times) < 3:
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raise WorkflowTimeoutError("Operation timed out after 120 seconds")
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return {
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"success": TestResponse(
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title="Test", summary="Summary", confidence=0.95
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)
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}
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with (
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patch("reflector.llm.StructuredOutputWorkflow") as mock_workflow_class,
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patch("reflector.llm.TreeSummarize") as mock_summarize,
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patch("reflector.llm.Settings") as mock_settings,
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):
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mock_workflow = MagicMock()
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mock_workflow.run = AsyncMock(side_effect=workflow_run_side_effect)
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mock_workflow_class.return_value = mock_workflow
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mock_summarizer = MagicMock()
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mock_summarize.return_value = mock_summarizer
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mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
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mock_settings.llm.acomplete = AsyncMock(
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return_value=make_completion_response(
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'{"title": "Test", "summary": "Summary", "confidence": 0.95}'
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)
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)
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result = await llm.get_structured_response(
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prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
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)
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assert result.title == "Test"
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if len(call_times) >= 2:
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time_between_calls = call_times[1] - call_times[0]
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assert (
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time_between_calls >= 1.5
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), f"Expected ~2s backoff, got {time_between_calls}s"
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@@ -266,7 +266,11 @@ async def mock_summary_processor():
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# When flush is called, simulate summary generation by calling the callbacks
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async def flush_with_callback():
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mock_summary.flush_called = True
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from reflector.processors.types import FinalLongSummary, FinalShortSummary
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from reflector.processors.types import (
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ActionItems,
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FinalLongSummary,
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FinalShortSummary,
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)
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if hasattr(mock_summary, "_callback"):
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await mock_summary._callback(
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@@ -276,12 +280,19 @@ async def mock_summary_processor():
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await mock_summary._on_short_summary(
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FinalShortSummary(short_summary="Test short summary", duration=10.0)
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)
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if hasattr(mock_summary, "_on_action_items"):
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await mock_summary._on_action_items(
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ActionItems(action_items={"test": "action item"})
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)
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mock_summary.flush = flush_with_callback
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def init_with_callback(transcript=None, callback=None, on_short_summary=None):
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def init_with_callback(
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transcript=None, callback=None, on_short_summary=None, on_action_items=None
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):
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mock_summary._callback = callback
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mock_summary._on_short_summary = on_short_summary
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mock_summary._on_action_items = on_action_items
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return mock_summary
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mock_summary_class.side_effect = init_with_callback
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