5e0a148b96
- Wire token usage from LLM agents through pipeline context to DB and frontend - Agents 2 and 4 accumulate input/output tokens and cost into PipelineContext - job_tasks.py saves token totals to locale instance after pipeline completion - Monitoring cards show total tokens and estimated cost instead of broken 0/0 - Make feedback highlighting bolder: colored card borders, stronger button states - Add estimated cost display to dashboard job cards - Add Help page with full documentation and link in sidebar navigation - Comprehensive README with ASCII architecture diagrams Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
144 lines
3.7 KiB
Python
144 lines
3.7 KiB
Python
"""Pipeline data contracts - Pydantic models for inter-agent communication."""
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from typing import Any
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from pydantic import BaseModel
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class TMEntry(BaseModel):
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"""A single Translation Memory entry."""
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seg_key: str
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date: str
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en: str
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lc: str
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tx: str
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nt: str = ""
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channel: str = ""
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sub_channel: str = ""
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_text: str = ""
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model_config = {"from_attributes": True}
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class SourceLineContract(BaseModel):
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"""A parsed source line from the input xlsx."""
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line_id: str
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row_order: int
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en_gb: str
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copy_type: str | None = None
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creative_guidance: str | None = None
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visual_ref: str | None = None
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char_limit: str | None = None
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is_display_format: bool = False
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class FileManifest(BaseModel):
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"""Manifest of all files loaded for a job."""
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tm_files: list[str] = []
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glossary_file: str | None = None
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blacklist_file: str | None = None
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tov_global_file: str | None = None
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tov_supplement_file: str | None = None
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locale_considerations_file: str | None = None
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date_pct_formats_file: str | None = None
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class JobParams(BaseModel):
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"""Parameters for a transcreation job."""
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job_id: str
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client_id: str
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locale_code: str
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channel: str
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sub_channel: str | None = None
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programme: str
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campaign_name: str
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context_prompt: str | None = None
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class ParsedJob(BaseModel):
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"""Output of Agent 1 (Validator): validated job parameters + source."""
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job_params: JobParams
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source_lines: list[SourceLineContract]
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file_manifest: FileManifest
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class ConfirmedMatch(BaseModel):
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"""A confirmed TM match for a source line."""
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seg_key: str
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pass_found: int
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date: str
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en: str
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tx: str
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nt: str = ""
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channel: str = ""
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sub_channel: str = ""
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is_cross_channel: bool = False
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class TMSweepResult(BaseModel):
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"""TM sweep results for a single source line."""
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line_id: str
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confirmed_matches: list[ConfirmedMatch] = []
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pass_4_triggered: bool = False
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pass_4_result: ConfirmedMatch | None = None
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no_match: bool = False
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class RankingDeclaration(BaseModel):
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"""Ranking decision for a single source line."""
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line_id: str
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winning_entry: ConfirmedMatch | None = None
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runner_ups: list[ConfirmedMatch] = []
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confidence_tier: str = "low"
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option_count: int = 3
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is_new_creative_line: bool = False
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notes: str = ""
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class DraftOption(BaseModel):
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"""A single draft transcreation option."""
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text: str
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backtranslation: str
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rationale: str
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class DraftOutput(BaseModel):
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"""Transcreation draft output for a single source line."""
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line_id: str
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option_1: DraftOption
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option_2: DraftOption | None = None
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option_3: DraftOption | None = None
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tm_entries_cited: list[str] = []
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adaptations_applied: list[str] = []
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class ComplianceViolation(BaseModel):
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"""A single compliance violation found during checking."""
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type: str
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option_affected: int
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description: str
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severity: str = "warning"
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class ComplianceResult(BaseModel):
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"""Compliance check result for a single source line."""
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line_id: str
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passed: bool
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violations: list[ComplianceViolation] = []
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character_counts: dict[str, int] = {}
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class PipelineContext(BaseModel):
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"""Full pipeline context passed between agents."""
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job_params: JobParams
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source_lines: list[SourceLineContract] = []
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file_manifest: FileManifest = FileManifest()
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tm_sweep_results: list[TMSweepResult] = []
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ranking_declarations: list[RankingDeclaration] = []
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draft_outputs: list[DraftOutput] = []
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compliance_results: list[ComplianceResult] = []
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# Token usage accumulators (updated by agents after each LLM call)
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total_input_tokens: int = 0
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total_output_tokens: int = 0
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total_estimated_cost: float = 0.0
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