File size: 22,612 Bytes
aef804e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 | """
Canvas-Episodic Memory Integration Tests
Tests the complete flow from canvas presentation to episodic memory:
- Canvas presentation → Episode creation with canvas_context
- LLM summary generation → EpisodeSegment.canvas_context
- Feedback submission → Episode.feedback_ids update
- Canvas-aware episode retrieval
- Feedback-weighted retrieval
Coverage:
- CanvasAudit → Episode.canvas_ids linkage
- AgentFeedback → Episode.feedback_ids linkage
- EpisodeSegment.canvas_context enrichment
- LLM canvas summary generation
- Canvas type filtering in retrieval
"""
import pytest
from unittest.mock import Mock, AsyncMock, patch, MagicMock
from sqlalchemy.orm import Session
from datetime import datetime, timezone, timedelta
import uuid
import asyncio
from typing import Dict, Any
from core.models import (
CanvasAudit, AgentExecution, AgentFeedback, Episode,
EpisodeSegment, AgentRegistry, User
)
from core.episode_segmentation_service import EpisodeSegmentationService
from core.episode_retrieval_service import EpisodeRetrievalService
from core.llm.canvas_summary_service import CanvasSummaryService
from tests.factories.canvas_factory import CanvasAuditFactory
from tests.factories.agent_factory import AutonomousAgentFactory
from tests.factories.user_factory import UserFactory
class TestCanvasEpisodeIntegration:
"""Test canvas presentation → episode creation integration."""
@pytest.fixture
def segmentation_service(self, db_session: Session):
"""Create episode segmentation service."""
return EpisodeSegmentationService(db_session)
@pytest.fixture
def retrieval_service(self, db_session: Session):
"""Create episode retrieval service."""
return EpisodeRetrievalService(db_session)
@pytest.fixture
def canvas_summary_service(self, db_session: Session):
"""Create canvas summary service with mock LLM."""
mock_llm = Mock()
mock_llm.generate = AsyncMock(return_value="Agent presented workflow approval form with revenue data")
return CanvasSummaryService(llm_service=mock_llm)
def test_canvas_presentation_creates_episode_with_canvas_ids(
self, db_session: Session, segmentation_service: EpisodeSegmentationService
):
"""Test that canvas presentations are linked to episodes via canvas_ids."""
# Create agent and user
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create canvas audit entries for a session
session_id = str(uuid.uuid4())
canvas_audits = [
CanvasAuditFactory(
canvas_type="sheets",
component_type="data_grid",
action="present",
agent_id=agent.id,
user_id=user.id,
session_id=session_id,
audit_metadata={"revenue": 1200000, "growth": 15},
_session=db_session
),
CanvasAuditFactory(
canvas_type="generic",
component_type="line_chart",
action="present",
agent_id=agent.id,
user_id=user.id,
session_id=session_id,
_session=db_session
)
]
db_session.add_all(canvas_audits)
db_session.commit()
# Create episode from session
episode = segmentation_service.create_episode_from_session(
session_id=session_id,
agent_id=agent.id,
user_id=user.id
)
# Verify canvas_ids are populated
assert episode is not None
assert len(episode.canvas_ids) == 2
assert episode.canvas_action_count == 2
# Verify canvas audits have episode_id backlink
for canvas_id in episode.canvas_ids:
canvas = db_session.query(CanvasAudit).filter(
CanvasAudit.id == canvas_id
).first()
assert canvas is not None
assert canvas.episode_id == episode.id
def test_llm_canvas_summary_enriches_segment_context(
self, db_session: Session, canvas_summary_service: CanvasSummaryService
):
"""Test that LLM summaries enrich episode segment canvas_context."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create canvas audit
canvas_audit = CanvasAuditFactory(
canvas_type="orchestration",
component_type="workflow_board",
action="present",
agent_id=agent.id,
user_id=user.id,
audit_metadata={
"workflow_id": "wf-123",
"approval_amount": 1500000,
"approvers": ["manager", "director"]
},
_session=db_session
)
db_session.add(canvas_audit)
db_session.commit()
# Generate LLM summary
summary = asyncio.run(canvas_summary_service.generate_summary(
canvas_type="orchestration",
canvas_state={
"workflow_id": "wf-123",
"approval_amount": 1500000,
"approvers": ["manager", "director"]
},
agent_task="Approve workflow",
user_interaction="submit"
))
# Verify LLM summary is semantically rich
assert summary is not None
assert len(summary) > 50 # Should be 50-100 words
assert "workflow" in summary.lower()
assert "approval" in summary.lower()
def test_feedback_submission_updates_episode_feedback_ids(
self, db_session: Session, segmentation_service: EpisodeSegmentationService
):
"""Test that feedback submissions update episode feedback_ids."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create episode
episode = Episode(
id=str(uuid.uuid4()),
agent_id=agent.id,
user_id=user.id,
workspace_id="default",
title="Test Episode",
canvas_ids=[],
feedback_ids=[],
aggregate_feedback_score=None
)
db_session.add(episode)
db_session.commit()
# Submit feedback
feedback = AgentFeedback(
id=str(uuid.uuid4()),
agent_id=agent.id,
user_id=user.id,
episode_id=episode.id,
feedback_type="thumbs_up",
rating=None,
created_at=datetime.now(timezone.utc)
)
db_session.add(feedback)
db_session.commit()
# Refresh episode
db_session.refresh(episode)
# Verify feedback_ids updated
assert len(episode.feedback_ids) == 1
assert feedback.id in episode.feedback_ids
def test_canvas_type_filtering_in_retrieval(
self, db_session: Session, segmentation_service: EpisodeSegmentationService,
retrieval_service: EpisodeRetrievalService
):
"""Test retrieving episodes filtered by canvas type."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create episodes with different canvas types
session_sheets = str(uuid.uuid4())
canvas_sheets = CanvasAuditFactory(
canvas_type="sheets",
action="present",
agent_id=agent.id,
user_id=user.id,
session_id=session_sheets,
_session=db_session
)
db_session.add(canvas_sheets)
db_session.commit()
episode_sheets = segmentation_service.create_episode_from_session(
session_id=session_sheets,
agent_id=agent.id,
user_id=user.id
)
session_charts = str(uuid.uuid4())
canvas_charts = CanvasAuditFactory(
canvas_type="generic",
component_type="line_chart",
action="present",
agent_id=agent.id,
user_id=user.id,
session_id=session_charts,
_session=db_session
)
db_session.add(canvas_charts)
db_session.commit()
episode_charts = segmentation_service.create_episode_from_session(
session_id=session_charts,
agent_id=agent.id,
user_id=user.id
)
# Retrieve episodes by canvas type
result = asyncio.run(retrieval_service.retrieve_by_canvas_type(
agent_id=agent.id,
canvas_type="sheets",
limit=10
))
# Should return only sheets episodes
assert len(result) >= 1
assert any(ep.id == episode_sheets.id for ep in result)
def test_feedback_weighted_retrieval(
self, db_session: Session, segmentation_service: EpisodeSegmentationService,
retrieval_service: EpisodeRetrievalService
):
"""Test that positive feedback boosts episode relevance."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create episode with positive feedback
session_id = str(uuid.uuid4())
canvas = CanvasAuditFactory(
canvas_type="sheets",
action="present",
agent_id=agent.id,
user_id=user.id,
session_id=session_id,
_session=db_session
)
db_session.add(canvas)
db_session.commit()
episode = segmentation_service.create_episode_from_session(
session_id=session_id,
agent_id=agent.id,
user_id=user.id
)
# Add positive feedback
feedback = AgentFeedback(
id=str(uuid.uuid4()),
agent_id=agent.id,
user_id=user.id,
episode_id=episode.id,
feedback_type="rating",
rating=5,
created_at=datetime.now(timezone.utc)
)
db_session.add(feedback)
db_session.commit()
# Refresh episode to get aggregate score
db_session.refresh(episode)
# Verify aggregate score is positive
assert episode.aggregate_feedback_score is not None
assert episode.aggregate_feedback_score > 0
class TestCanvasSummaryServiceIntegration:
"""Test LLM canvas summary service integration."""
@pytest.fixture
def mock_llm_service(self):
"""Create mock LLM service."""
mock_llm = Mock()
mock_llm.generate = AsyncMock(return_value="Agent presented Q4 revenue chart showing $1.2M with 15% growth")
return mock_llm
@pytest.fixture
def canvas_summary_service(self, mock_llm_service):
"""Create canvas summary service."""
return CanvasSummaryService(llm_service=mock_llm_service)
def test_summary_caching_by_canvas_state(
self, canvas_summary_service: CanvasSummaryService, mock_llm_service
):
"""Test that identical canvas states use cached summaries."""
canvas_state = {
"revenue": 1200000,
"growth": 15,
"quarter": "Q4"
}
# First call should hit LLM
summary1 = asyncio.run(canvas_summary_service.generate_summary(
canvas_type="sheets",
canvas_state=canvas_state,
agent_task="Show revenue"
))
# Second call with same state should use cache
summary2 = asyncio.run(canvas_summary_service.generate_summary(
canvas_type="sheets",
canvas_state=canvas_state,
agent_task="Show revenue"
))
# Verify LLM was called only once
assert mock_llm_service.generate.call_count == 1
assert summary1 == summary2
def test_fallback_to_metadata_on_llm_failure(
self, canvas_summary_service: CanvasSummaryService, mock_llm_service
):
"""Test that metadata extraction is used when LLM fails."""
# Make LLM fail
mock_llm_service.generate = AsyncMock(side_effect=Exception("LLM error"))
canvas_state = {
"revenue": 1200000,
"growth": 15
}
# Should fall back to metadata extraction
summary = asyncio.run(canvas_summary_service.generate_summary(
canvas_type="sheets",
canvas_state=canvas_state,
agent_task="Show revenue",
timeout_seconds=2
))
# Verify metadata fallback was used
assert summary is not None
assert "sheets" in summary.lower()
def test_all_canvas_types_supported(
self, canvas_summary_service: CanvasSummaryService, mock_llm_service
):
"""Test that all 7 canvas types are supported."""
canvas_types = ["generic", "docs", "email", "sheets", "orchestration", "terminal", "coding"]
for canvas_type in canvas_types:
is_supported = canvas_summary_service.is_canvas_type_supported(canvas_type)
assert is_supported, f"Canvas type {canvas_type} should be supported"
def test_semantic_richness_scoring(
self, canvas_summary_service: CanvasSummaryService
):
"""Test semantic richness score calculation."""
# Rich summary with business context
rich_summary = "Agent presented $1.2M workflow approval requiring board consent due to budget exceeding threshold"
score = canvas_summary_service._calculate_semantic_richness(rich_summary)
assert score > 0.5 # Should be relatively high
def test_hallucination_detection(
self, canvas_summary_service: CanvasSummaryService
):
"""Test hallucination detection in summaries."""
canvas_state = {
"workflow_id": "wf-123",
"amount": 50000
}
# Summary with hallucinated workflow ID
hallucinated_summary = "Agent presented workflow wf-456 with amount $50000"
has_hallucination = canvas_summary_service._detect_hallucination(
hallucinated_summary,
canvas_state
)
assert has_hallucination is True
# Summary without hallucination
valid_summary = "Agent presented workflow wf-123 with amount $50000"
has_hallucination = canvas_summary_service._detect_hallucination(
valid_summary,
canvas_state
)
assert has_hallucination is False
class TestCanvasContextRetrieval:
"""Test canvas context retrieval from episodes."""
@pytest.fixture
def retrieval_service(self, db_session: Session):
"""Create episode retrieval service."""
return EpisodeRetrievalService(db_session)
def test_retrieve_episode_with_canvas_context(
self, db_session: Session, retrieval_service: EpisodeRetrievalService
):
"""Test retrieving episode with canvas context included."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create episode with canvas context
episode = Episode(
id=str(uuid.uuid4()),
agent_id=agent.id,
user_id=user.id,
workspace_id="default",
title="Sales Analysis",
canvas_ids=[str(uuid.uuid4()), str(uuid.uuid4())],
feedback_ids=[],
canvas_action_count=2
)
db_session.add(episode)
# Create canvas audits
for canvas_id in episode.canvas_ids:
canvas = CanvasAudit(
id=canvas_id,
workspace_id="default",
agent_id=agent.id,
user_id=user.id,
canvas_id=canvas_id,
canvas_type="sheets",
component_type="data_grid",
action="present",
audit_metadata={"revenue": 1200000}
)
db_session.add(canvas)
db_session.commit()
# Retrieve episode with canvas context
result = asyncio.run(retrieval_service.retrieve_episode(
episode_id=episode.id,
agent_id=agent.id,
include_canvas=True
))
# Verify canvas context is included
assert result is not None
assert "canvas_context" in result
assert len(result["canvas_context"]) == 2
def test_retrieve_episode_with_feedback_context(
self, db_session: Session, retrieval_service: EpisodeRetrievalService
):
"""Test retrieving episode with feedback context included."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create episode
episode = Episode(
id=str(uuid.uuid4()),
agent_id=agent.id,
user_id=user.id,
workspace_id="default",
title="Task Completion",
canvas_ids=[],
feedback_ids=[str(uuid.uuid4())],
aggregate_feedback_score=0.75
)
db_session.add(episode)
# Create feedback
feedback = AgentFeedback(
id=episode.feedback_ids[0],
agent_id=agent.id,
user_id=user.id,
episode_id=episode.id,
feedback_type="thumbs_up",
created_at=datetime.now(timezone.utc)
)
db_session.add(feedback)
db_session.commit()
# Retrieve episode with feedback context
result = asyncio.run(retrieval_service.retrieve_episode(
episode_id=episode.id,
agent_id=agent.id,
include_feedback=True
))
# Verify feedback context is included
assert result is not None
assert "feedback_context" in result
assert len(result["feedback_context"]) == 1
def test_progressive_canvas_detail_levels(
self, db_session: Session, retrieval_service: EpisodeRetrievalService
):
"""Test progressive detail levels for canvas context."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create episode with full canvas context
episode = Episode(
id=str(uuid.uuid4()),
agent_id=agent.id,
user_id=user.id,
workspace_id="default",
title="Workflow Approval",
canvas_ids=[str(uuid.uuid4())],
feedback_ids=[],
canvas_action_count=1
)
db_session.add(episode)
# Create canvas audit with full context
canvas = CanvasAudit(
id=episode.canvas_ids[0],
workspace_id="default",
agent_id=agent.id,
user_id=user.id,
canvas_id=episode.canvas_ids[0],
canvas_type="orchestration",
component_type="workflow_board",
action="present",
audit_metadata={
"workflow_id": "wf-123",
"approval_amount": 1500000,
"approvers": ["manager", "director"]
}
)
db_session.add(canvas)
db_session.commit()
# Test summary detail level
result_summary = asyncio.run(retrieval_service.retrieve_episode(
episode_id=episode.id,
agent_id=agent.id,
include_canvas=True,
canvas_context_detail="summary"
))
assert "canvas_context" in result_summary
# Test full detail level
result_full = asyncio.run(retrieval_service.retrieve_episode(
episode_id=episode.id,
agent_id=agent.id,
include_canvas=True,
canvas_context_detail="full"
))
assert "canvas_context" in result_full
class TestCanvasEpisodeLifecycle:
"""Test canvas episode lifecycle and archival."""
@pytest.fixture
def segmentation_service(self, db_session: Session):
"""Create episode segmentation service."""
return EpisodeSegmentationService(db_session)
def test_canvas_data_preserved_through_archival(
self, db_session: Session, segmentation_service: EpisodeSegmentationService
):
"""Test that canvas context is preserved when episodes are archived."""
agent = AutonomousAgentFactory(_session=db_session)
user = UserFactory(_session=db_session)
db_session.commit()
# Create episode with canvas context
session_id = str(uuid.uuid4())
canvas = CanvasAuditFactory(
canvas_type="sheets",
action="present",
agent_id=agent.id,
user_id=user.id,
session_id=session_id,
audit_metadata={"revenue": 1200000},
_session=db_session
)
db_session.add(canvas)
db_session.commit()
episode = segmentation_service.create_episode_from_session(
session_id=session_id,
agent_id=agent.id,
user_id=user.id
)
# Create segment with canvas context
segment = EpisodeSegment(
id=str(uuid.uuid4()),
episode_id=episode.id,
agent_id=agent.id,
segment_type="canvas_presentation",
canvas_context={
"canvas_type": "sheets",
"presentation_summary": "Revenue data presented",
"critical_data_points": {"revenue": 1200000}
},
start_time=datetime.now(timezone.utc),
end_time=datetime.now(timezone.utc)
)
db_session.add(segment)
db_session.commit()
# Archive episode (soft delete)
episode.archived = True
episode.archived_at = datetime.now(timezone.utc)
db_session.commit()
# Retrieve archived episode
archived = db_session.query(Episode).filter(
Episode.id == episode.id,
Episode.archived == True
).first()
assert archived is not None
assert len(archived.canvas_ids) == 1
# Verify canvas context still accessible
archived_segment = db_session.query(EpisodeSegment).filter(
EpisodeSegment.episode_id == episode.id
).first()
assert archived_segment is not None
assert archived_segment.canvas_context is not None
assert archived_segment.canvas_context["canvas_type"] == "sheets"
|