[split-required] Split final 43 files (500-668 LOC) to complete refactoring
klausur-service (11 files): - cv_gutter_repair, ocr_pipeline_regression, upload_api - ocr_pipeline_sessions, smart_spell, nru_worksheet_generator - ocr_pipeline_overlays, mail/aggregator, zeugnis_api - cv_syllable_detect, self_rag backend-lehrer (17 files): - classroom_engine/suggestions, generators/quiz_generator - worksheets_api, llm_gateway/comparison, state_engine_api - classroom/models (→ 4 submodules), services/file_processor - alerts_agent/api/wizard+digests+routes, content_generators/pdf - classroom/routes/sessions, llm_gateway/inference - classroom_engine/analytics, auth/keycloak_auth - alerts_agent/processing/rule_engine, ai_processor/print_versions agent-core (5 files): - brain/memory_store, brain/knowledge_graph, brain/context_manager - orchestrator/supervisor, sessions/session_manager admin-lehrer (5 components): - GridOverlay, StepGridReview, DevOpsPipelineSidebar - DataFlowDiagram, sbom/wizard/page website (2 files): - DependencyMap, lehrer/abitur-archiv Other: nibis_ingestion, grid_detection_service, export-doclayout-onnx Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Benjamin Admin
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agent-core/sessions/session_models.py
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agent-core/sessions/session_models.py
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"""
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Session Models for Breakpilot Agents
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Data classes for agent sessions, checkpoints, and state tracking.
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"""
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from dataclasses import dataclass, field
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from datetime import datetime, timezone, timedelta
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from typing import Dict, Any, Optional, List
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from enum import Enum
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import uuid
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import logging
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logger = logging.getLogger(__name__)
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class SessionState(Enum):
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"""Agent session states"""
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ACTIVE = "active"
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PAUSED = "paused"
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COMPLETED = "completed"
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FAILED = "failed"
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@dataclass
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class SessionCheckpoint:
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"""Represents a checkpoint in an agent session"""
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name: str
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timestamp: datetime
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data: Dict[str, Any]
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def to_dict(self) -> Dict[str, Any]:
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return {
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"name": self.name,
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"timestamp": self.timestamp.isoformat(),
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"data": self.data
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}
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@classmethod
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def from_dict(cls, data: Dict[str, Any]) -> "SessionCheckpoint":
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return cls(
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name=data["name"],
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timestamp=datetime.fromisoformat(data["timestamp"]),
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data=data["data"]
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)
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@dataclass
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class AgentSession:
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"""
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Represents an active agent session.
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Attributes:
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session_id: Unique session identifier
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agent_type: Type of agent (tutor, grader, quality-judge, alert, orchestrator)
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user_id: Associated user ID
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state: Current session state
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created_at: Session creation timestamp
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last_heartbeat: Last heartbeat timestamp
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context: Session context data
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checkpoints: List of session checkpoints for recovery
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"""
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session_id: str = field(default_factory=lambda: str(uuid.uuid4()))
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agent_type: str = ""
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user_id: str = ""
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state: SessionState = SessionState.ACTIVE
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created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
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last_heartbeat: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
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context: Dict[str, Any] = field(default_factory=dict)
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checkpoints: List[SessionCheckpoint] = field(default_factory=list)
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metadata: Dict[str, Any] = field(default_factory=dict)
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def checkpoint(self, name: str, data: Dict[str, Any]) -> SessionCheckpoint:
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"""
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Creates a checkpoint for recovery.
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Args:
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name: Checkpoint name (e.g., "task_received", "processing_complete")
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data: Checkpoint data to store
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Returns:
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The created checkpoint
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"""
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checkpoint = SessionCheckpoint(
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name=name,
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timestamp=datetime.now(timezone.utc),
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data=data
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)
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self.checkpoints.append(checkpoint)
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logger.debug(f"Session {self.session_id}: Checkpoint '{name}' created")
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return checkpoint
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def heartbeat(self) -> None:
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"""Updates the heartbeat timestamp"""
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self.last_heartbeat = datetime.now(timezone.utc)
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def pause(self) -> None:
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"""Pauses the session"""
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self.state = SessionState.PAUSED
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self.checkpoint("session_paused", {"previous_state": "active"})
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def resume(self) -> None:
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"""Resumes a paused session"""
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if self.state == SessionState.PAUSED:
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self.state = SessionState.ACTIVE
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self.heartbeat()
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self.checkpoint("session_resumed", {})
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def complete(self, result: Optional[Dict[str, Any]] = None) -> None:
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"""Marks the session as completed"""
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self.state = SessionState.COMPLETED
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self.checkpoint("session_completed", {"result": result or {}})
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def fail(self, error: str, error_details: Optional[Dict[str, Any]] = None) -> None:
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"""Marks the session as failed"""
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self.state = SessionState.FAILED
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self.checkpoint("session_failed", {
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"error": error,
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"details": error_details or {}
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})
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def get_last_checkpoint(self, name: Optional[str] = None) -> Optional[SessionCheckpoint]:
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"""
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Gets the last checkpoint, optionally filtered by name.
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Args:
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name: Optional checkpoint name to filter by
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Returns:
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The last matching checkpoint or None
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"""
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if not self.checkpoints:
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return None
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if name:
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matching = [cp for cp in self.checkpoints if cp.name == name]
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return matching[-1] if matching else None
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return self.checkpoints[-1]
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def get_duration(self) -> timedelta:
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"""Returns the session duration"""
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end_time = datetime.now(timezone.utc)
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if self.state in (SessionState.COMPLETED, SessionState.FAILED):
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last_cp = self.get_last_checkpoint()
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if last_cp:
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end_time = last_cp.timestamp
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return end_time - self.created_at
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def to_dict(self) -> Dict[str, Any]:
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"""Serializes the session to a dictionary"""
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return {
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"session_id": self.session_id,
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"agent_type": self.agent_type,
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"user_id": self.user_id,
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"state": self.state.value,
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"created_at": self.created_at.isoformat(),
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"last_heartbeat": self.last_heartbeat.isoformat(),
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"context": self.context,
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"checkpoints": [cp.to_dict() for cp in self.checkpoints],
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"metadata": self.metadata
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}
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@classmethod
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def from_dict(cls, data: Dict[str, Any]) -> "AgentSession":
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"""Deserializes a session from a dictionary"""
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return cls(
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session_id=data["session_id"],
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agent_type=data["agent_type"],
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user_id=data["user_id"],
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state=SessionState(data["state"]),
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created_at=datetime.fromisoformat(data["created_at"]),
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last_heartbeat=datetime.fromisoformat(data["last_heartbeat"]),
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context=data.get("context", {}),
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checkpoints=[
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SessionCheckpoint.from_dict(cp)
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for cp in data.get("checkpoints", [])
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],
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metadata=data.get("metadata", {})
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)
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