e18976fdb2
Dockerized web app (FastAPI + React + PostgreSQL) for scoping client ratecards against the GMAL master asset database. Features: - GMAL data ingestion from Excel (390 assets, 120 roles, 5 model types) - AI-powered document parsing and asset extraction (Claude Opus 4.6) - AI matching engine with parallel batching, confidence scoring, caveats - Ratecard builder with hours x volume calculation - Excel and PDF export - GMAL browser and inline editor - AI cost tracking per project (persisted to DB) - Debug panel for AI call inspection - Dark theme UI with gold (#FFC407) accent Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
"""Build ratecards from confirmed matches."""
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import logging
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from sqlalchemy import select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models.gmal import GmalHours, ModelType
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from app.models.project import Project, ClientAsset, Match, RatecardLine
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logger = logging.getLogger(__name__)
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async def build_ratecard(db: AsyncSession, project: Project) -> list[RatecardLine]:
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"""Build a ratecard for a project from its confirmed (selected) matches.
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For each selected match, looks up the hours per role from gmal_hours
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for the project's model type, multiplies by volume, and creates ratecard lines.
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Returns the created RatecardLine objects.
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"""
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# Clear existing ratecard lines for this project
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existing = await db.execute(
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select(RatecardLine).where(RatecardLine.project_id == project.id)
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)
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for line in existing.scalars().all():
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await db.delete(line)
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await db.flush()
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# Get all client assets with their selected matches
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assets_result = await db.execute(
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select(ClientAsset).where(ClientAsset.project_id == project.id)
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)
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client_assets = assets_result.scalars().all()
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lines = []
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for client_asset in client_assets:
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# Get the selected match for this asset
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match_result = await db.execute(
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select(Match).where(
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Match.client_asset_id == client_asset.id,
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Match.is_selected == True,
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)
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)
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selected_match = match_result.scalar_one_or_none()
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if not selected_match:
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logger.warning(f"No selected match for client asset {client_asset.id}: {client_asset.raw_name}")
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continue
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# Get hours for this GMAL asset and model type
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hours_result = await db.execute(
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select(GmalHours).where(
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GmalHours.gmal_asset_id == selected_match.gmal_asset_id,
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GmalHours.model_type == project.model_type,
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)
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)
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gmal_hours = hours_result.scalars().all()
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for gh in gmal_hours:
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total = round(float(gh.hours) * client_asset.volume, 2)
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line = RatecardLine(
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project_id=project.id,
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client_asset_id=client_asset.id,
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gmal_asset_id=selected_match.gmal_asset_id,
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role_id=gh.role_id,
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base_hours=float(gh.hours),
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volume=client_asset.volume,
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total_hours=total,
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)
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db.add(line)
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lines.append(line)
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await db.flush()
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logger.info(f"Built ratecard with {len(lines)} lines for project {project.id}")
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return lines
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