bc778ce7af
Iterative Prompting: - Chat box on Match Review tab for natural language refinement - "re-run under 70%" / "ignore zero volume" / "set all volumes to 1" - Claude interprets instruction into structured actions - Actions: rematch_below_threshold, rematch_specific, delete_assets, set_volume - Re-matches affected assets automatically after refinement - Chat log shows instruction history RFP/Brief Analysis: - New "Brief Analysis" tab between Upload and Match Review - Extracts: summary, objectives, KPIs, channels, audiences, deliverable categories, constraints, timeline, budget, complexity assessment - Generates prioritized discovery questions (Red/Amber/Green) - Questions include category, rationale, and priority level - Stored as JSON in project.brief_analysis field - Uploaded files now saved to data dir for re-analysis - Re-analyze button to refresh analysis Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
115 lines
2.4 KiB
Python
115 lines
2.4 KiB
Python
from pydantic import BaseModel
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from datetime import datetime
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class ProjectCreate(BaseModel):
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name: str
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client_name: str | None = None
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description: str | None = None
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model_type: str = "current_oplus"
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class ProjectUpdate(BaseModel):
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name: str | None = None
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client_name: str | None = None
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description: str | None = None
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model_type: str | None = None
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class ProjectOut(BaseModel):
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id: int
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name: str
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client_name: str | None
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description: str | None
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model_type: str
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status: str
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source_filename: str | None
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parse_stage: str | None = None
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has_brief_analysis: bool = False
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ai_input_tokens: int = 0
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ai_output_tokens: int = 0
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ai_cost_usd: float = 0
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ai_call_count: int = 0
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created_at: datetime
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updated_at: datetime
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asset_count: int = 0
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class Config:
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from_attributes = True
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class ClientAssetOut(BaseModel):
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id: int
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project_id: int
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raw_name: str | None
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raw_description: str | None
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volume: int
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sort_order: int | None
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class Config:
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from_attributes = True
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class ClientAssetUpdate(BaseModel):
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raw_name: str | None = None
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raw_description: str | None = None
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volume: int | None = None
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class MatchOut(BaseModel):
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id: int
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client_asset_id: int
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gmal_asset_id: int
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gmal_id: str | None = None
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gmal_name: str | None = None
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gmal_unique_name: str | None = None
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confidence: str
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confidence_score: float | None
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ai_reasoning: str | None
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caveat_text: str | None
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is_selected: bool
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rank: int
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class Config:
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from_attributes = True
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class MatchSelectRequest(BaseModel):
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is_selected: bool = True
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class ManualMatchRequest(BaseModel):
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gmal_asset_id: int
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class RatecardLineOut(BaseModel):
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id: int
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client_asset_id: int
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client_asset_name: str | None = None
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gmal_asset_id: int
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gmal_id: str | None = None
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role_id: int
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role_title: str | None = None
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discipline: str | None = None
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base_hours: float | None
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volume: int
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total_hours: float | None
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manual_override: float | None
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notes: str | None
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class Config:
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from_attributes = True
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class RatecardLineUpdate(BaseModel):
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manual_override: float | None = None
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notes: str | None = None
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class RatecardSummary(BaseModel):
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project_id: int
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project_name: str
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model_type: str
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total_assets: int
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total_hours: float
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lines: list[RatecardLineOut]
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