generated from coulomb/repo-seed
tegwick
58e1bafce9
Introduces end-to-end token consumption tracking so agent work is visible as a cost/effort metric alongside tasks and workplans. - Migration o2j3k4l5m6n7: token_events table with FK indexes on task_id, workstream_id, repo_id, created_at - ORM model, Pydantic schemas (TokenEventCreate, TokenEventRead with computed tokens_total, TokenSummary) - Router: POST /token-events/, GET /token-events/ (7 filters), GET /token-events/summary/ (task|workstream|repo|commit|release scope) - MCP tools: record_token_event, get_token_summary (formatted table) - update_task_status enriched with optional tokens_in/tokens_out passthrough — one call creates status update + token event - Dashboard token-cost.md page: by-repo bar, by-workplan table, by-model bar, top-10 tasks by tokens - ralph-workplan skill updated with token reporting guidance and per-task heuristics for estimating counts - Tests: test_token_events.py + test_token_passthrough.py (182 pass) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
53 lines
1.2 KiB
Python
53 lines
1.2 KiB
Python
import uuid
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from datetime import datetime
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from pydantic import BaseModel, ConfigDict, computed_field
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class TokenEventCreate(BaseModel):
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tokens_in: int
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tokens_out: int
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task_id: uuid.UUID | None = None
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workstream_id: uuid.UUID | None = None
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repo_id: uuid.UUID | None = None
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session_id: str | None = None
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model: str | None = None
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agent: str | None = None
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ref_type: str | None = None
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ref_id: str | None = None
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note: str | None = None
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class TokenEventRead(BaseModel):
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model_config = ConfigDict(from_attributes=True)
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id: uuid.UUID
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tokens_in: int
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tokens_out: int
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task_id: uuid.UUID | None = None
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workstream_id: uuid.UUID | None = None
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repo_id: uuid.UUID | None = None
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session_id: str | None = None
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model: str | None = None
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agent: str | None = None
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ref_type: str | None = None
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ref_id: str | None = None
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note: str | None = None
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created_at: datetime
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@computed_field
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@property
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def tokens_total(self) -> int:
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return self.tokens_in + self.tokens_out
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class TokenSummary(BaseModel):
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scope: str
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scope_id: str
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tokens_in: int
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tokens_out: int
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tokens_total: int
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event_count: int
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by_model: dict[str, int]
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by_agent: dict[str, int]
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