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245"""Progress tracking models for the remediation pipeline.
These models track fine-grained progress within the "processing" job status,
allowing the UI to show detailed status updates during the remediation pipeline.
"""
from datetime import UTC, datetime
from typing import Any, Literal
from pydantic import BaseModel, ConfigDict, Field
# Valid substatuses within the "processing" status
VALID_SUBSTATUSES: dict[str, list[str]] = {
"processing": [
"analyzing", # Phase 1: Sonnet analysis
"extracting", # Phase 2: Haiku extraction
"specializing", # Phase 3: Specialized agents
"consolidating", # Phase 4: Observations → Proposals
"awaiting_review", # Phase 5: Human review
"applying", # Phase 6: Applying approved edits
]
}
# Type alias for substatus literals
SubstatusType = Literal[
"analyzing",
"extracting",
"specializing",
"consolidating",
"awaiting_review",
"applying",
]
class RemediationProgress(BaseModel):
"""Progress tracking for remediation pipeline.
Provides fine-grained progress information within the "processing" status.
Used by the job service to track pipeline state and by the UI to show
detailed progress to users.
Attributes:
substatus: Current phase within processing
observation_count: Total observations generated
proposal_count: Total proposals generated
pending_proposals: Proposals awaiting review
approved_proposals: Proposals approved by reviewer
rejected_proposals: Proposals rejected by reviewer
applied_proposals: Proposals successfully applied
manual_observations: Observations requiring manual attention
analysis_model: Model used for analysis phase
extraction_model: Model used for extraction phase
analysis_completed_at: When analysis phase completed
extraction_completed_at: When extraction phase completed
review_started_at: When human review began
Example:
>>> progress = RemediationProgress(
... substatus="awaiting_review",
... observation_count=12,
... proposal_count=8,
... pending_proposals=6,
... manual_observations=2
... )
"""
substatus: SubstatusType = Field(
default="analyzing",
description="Current phase within processing"
)
# Counts
observation_count: int = Field(
default=0,
ge=0,
description="Total observations generated"
)
proposal_count: int = Field(
default=0,
ge=0,
description="Total proposals generated"
)
pending_proposals: int = Field(
default=0,
ge=0,
description="Proposals awaiting review"
)
approved_proposals: int = Field(
default=0,
ge=0,
description="Proposals approved by reviewer"
)
rejected_proposals: int = Field(
default=0,
ge=0,
description="Proposals rejected by reviewer"
)
applied_proposals: int = Field(
default=0,
ge=0,
description="Proposals successfully applied"
)
manual_observations: int = Field(
default=0,
ge=0,
description="Observations requiring manual attention"
)
# Model tracking
analysis_model: str | None = Field(
default=None,
description="Model used for analysis phase (e.g., claude-sonnet-4-5)"
)
extraction_model: str | None = Field(
default=None,
description="Model used for extraction phase (e.g., claude-haiku-4-5)"
)
# Timestamps
analysis_completed_at: datetime | None = Field(
default=None,
description="When analysis phase completed"
)
extraction_completed_at: datetime | None = Field(
default=None,
description="When extraction phase completed"
)
review_started_at: datetime | None = Field(
default=None,
description="When human review began"
)
def is_valid_substatus_transition(
self,
current_status: str,
new_substatus: str
) -> bool:
"""Check if substatus is valid for given job status.
Args:
current_status: Current job status (e.g., "processing")
new_substatus: Substatus to validate
Returns:
True if substatus is valid for the job status
"""
valid_substatuses = VALID_SUBSTATUSES.get(current_status, [])
return new_substatus in valid_substatuses
def update_counts_from_lists(
self,
observations: list[Any],
proposals: list[Any],
) -> "RemediationProgress":
"""Update counts based on observation and proposal lists.
Convenience method to recalculate all counts from the current
state of observations and proposals.
Args:
observations: List of Observation objects
proposals: List of Proposal objects
Returns:
Self with updated counts
"""
self.observation_count = len(observations)
self.manual_observations = sum(
1 for o in observations if getattr(o, "route", None) == "manual"
)
self.proposal_count = len(proposals)
self.pending_proposals = sum(
1 for p in proposals if getattr(p, "status", None) == "pending"
)
self.approved_proposals = sum(
1 for p in proposals if getattr(p, "status", None) == "approved"
)
self.rejected_proposals = sum(
1 for p in proposals if getattr(p, "status", None) == "rejected"
)
self.applied_proposals = sum(
1 for p in proposals if getattr(p, "status", None) == "applied"
)
return self
def mark_analysis_complete(self, model: str) -> "RemediationProgress":
"""Mark analysis phase as complete.
Args:
model: Model used for analysis
Returns:
Self with updated fields
"""
self.substatus = "extracting"
self.analysis_model = model
self.analysis_completed_at = datetime.now(UTC)
return self
def mark_extraction_complete(self, model: str) -> "RemediationProgress":
"""Mark extraction phase as complete.
Args:
model: Model used for extraction
Returns:
Self with updated fields
"""
self.substatus = "specializing"
self.extraction_model = model
self.extraction_completed_at = datetime.now(UTC)
return self
def mark_ready_for_review(self) -> "RemediationProgress":
"""Mark pipeline as ready for human review.
Returns:
Self with updated fields
"""
self.substatus = "awaiting_review"
self.review_started_at = datetime.now(UTC)
return self
model_config = ConfigDict(
json_schema_extra={
"example": {
"substatus": "awaiting_review",
"observation_count": 12,
"proposal_count": 8,
"pending_proposals": 6,
"approved_proposals": 0,
"rejected_proposals": 0,
"applied_proposals": 0,
"manual_observations": 2,
"analysis_model": "claude-sonnet-4-5",
"extraction_model": "claude-haiku-4-5",
"analysis_completed_at": "2024-12-10T10:32:00Z",
"extraction_completed_at": "2024-12-10T10:34:00Z",
"review_started_at": "2024-12-10T10:35:00Z"
}
}
)