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from datetime import datetime
from typing import List, Optional
from sqlmodel import SQLModel, Field, Column
from sqlalchemy import JSON
class Script(SQLModel, table=True, extend_existing=True):
id: Optional[int] = Field(default=None, primary_key=True)
creator: str
content_type: str
tone: str
title: str
hook: str
beats: List[str] = Field(sa_column=Column(JSON))
voiceover: str
caption: str
hashtags: List[str] = Field(sa_column=Column(JSON))
cta: str
compliance: str = "pass" # pass | warn | fail
source: str = "ai" # ai | manual | import
is_reference: bool = False # mark imported examples as references
# --- NEW: cached aggregates from ratings (all optional) ---
score_overall: Optional[float] = None # 1..5 (avg)
score_hook: Optional[float] = None # 1..5 (avg)
score_originality: Optional[float] = None # 1..5 (avg)
score_style_fit: Optional[float] = None # 1..5 (avg)
score_safety: Optional[float] = None # 1..5 (avg)
ratings_count: int = 0
created_at: datetime = Field(default_factory=datetime.utcnow)
updated_at: datetime = Field(default_factory=datetime.utcnow)
class Revision(SQLModel, table=True, extend_existing=True):
id: Optional[int] = Field(default=None, primary_key=True)
script_id: int = Field(index=True)
label: str
field: str
before: str
after: str
created_at: datetime = Field(default_factory=datetime.utcnow)
# NEW: store every rating event so you keep history
class Rating(SQLModel, table=True, extend_existing=True):
id: Optional[int] = Field(default=None, primary_key=True)
script_id: int = Field(index=True)
rater: str = "human" # optional: store user/email
overall: float # 1..5
hook: Optional[float] = None
originality: Optional[float] = None
style_fit: Optional[float] = None
safety: Optional[float] = None
notes: Optional[str] = None
created_at: datetime = Field(default_factory=datetime.utcnow)
# RAG Enhancement Models
class Embedding(SQLModel, table=True, extend_existing=True):
id: Optional[int] = Field(default=None, primary_key=True)
script_id: int = Field(index=True)
part: str = Field(index=True) # 'full', 'hook', 'beats', 'caption'
vector: List[float] = Field(sa_column=Column(JSON))
meta: dict = Field(sa_column=Column(JSON))
created_at: datetime = Field(default_factory=datetime.utcnow)
class AutoScore(SQLModel, table=True, extend_existing=True):
id: Optional[int] = Field(default=None, primary_key=True)
script_id: int = Field(index=True)
overall: float
hook: float
originality: float
style_fit: float
safety: float
confidence: float = 0.8 # LLM judge confidence
notes: Optional[str] = None
created_at: datetime = Field(default_factory=datetime.utcnow)
class PolicyWeights(SQLModel, table=True, extend_existing=True):
id: Optional[int] = Field(default=None, primary_key=True)
persona: str = Field(index=True)
content_type: str = Field(index=True)
# Retrieval weights
semantic_weight: float = 0.45
bm25_weight: float = 0.25
quality_weight: float = 0.20
freshness_weight: float = 0.10
# Generation params
temp_low: float = 0.4
temp_mid: float = 0.7
temp_high: float = 0.95
# Performance tracking
success_rate: float = 0.0
total_generations: int = 0
updated_at: datetime = Field(default_factory=datetime.utcnow)
class StyleCard(SQLModel, table=True, extend_existing=True):
id: Optional[int] = Field(default=None, primary_key=True)
persona: str = Field(index=True)
content_type: str = Field(index=True)
exemplar_hooks: List[str] = Field(sa_column=Column(JSON))
exemplar_beats: List[str] = Field(sa_column=Column(JSON))
exemplar_captions: List[str] = Field(sa_column=Column(JSON))
negative_patterns: List[str] = Field(sa_column=Column(JSON))
constraints: dict = Field(sa_column=Column(JSON))
updated_at: datetime = Field(default_factory=datetime.utcnow) |