from sqlalchemy import Boolean, Column, Integer, String, DateTime, Text, Float, ForeignKey, JSON
from sqlalchemy.orm import relationship
from sqlalchemy.sql import func
from app.db.database import Base


class User(Base):
    __tablename__ = "users"
    
    id = Column(Integer, primary_key=True, index=True)
    username = Column(String, unique=True, index=True, nullable=False)
    email = Column(String, unique=True, index=True, nullable=False)
    hashed_password = Column(String, nullable=False)
    full_name = Column(String, nullable=True)
    is_active = Column(Boolean, default=True)
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    last_login = Column(DateTime(timezone=True), nullable=True)
    
    # Relationships
    files = relationship("UserFile", back_populates="owner")
    interactions = relationship("UserInteraction", back_populates="user")
    preferences = relationship("UserPreference", back_populates="user")
    reminders = relationship("Reminder", back_populates="user")


class UserFile(Base):
    __tablename__ = "user_files"
    
    id = Column(Integer, primary_key=True, index=True)
    filename = Column(String, nullable=False)
    original_name = Column(String, nullable=False)
    file_path = Column(String, nullable=False)
    file_type = Column(String, nullable=False)  # pdf, txt, docx, image, etc.
    file_size = Column(Integer, nullable=False)
    mime_type = Column(String, nullable=True)
    
    # Content analysis
    content_summary = Column(Text, nullable=True)
    extracted_text = Column(Text, nullable=True)
    categories = Column(JSON, nullable=True)  # List of auto-detected categories
    tags = Column(JSON, nullable=True)  # User-defined tags
    
    # Metadata
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
    last_accessed = Column(DateTime(timezone=True), nullable=True)
    access_count = Column(Integer, default=0)
    
    # Relationships
    owner_id = Column(Integer, ForeignKey("users.id"))
    owner = relationship("User", back_populates="files")


class UserInteraction(Base):
    __tablename__ = "user_interactions"
    
    id = Column(Integer, primary_key=True, index=True)
    interaction_type = Column(String, nullable=False)  # query, file_upload, search, etc.
    query = Column(Text, nullable=True)
    response = Column(Text, nullable=True)
    context = Column(JSON, nullable=True)  # Additional context data
    
    # Quality metrics
    response_time = Column(Float, nullable=True)
    user_feedback = Column(Integer, nullable=True)  # -1, 0, 1 (negative, neutral, positive)
    was_helpful = Column(Boolean, nullable=True)
    
    # Learning data
    used_files = Column(JSON, nullable=True)  # List of file IDs used in response
    search_terms = Column(JSON, nullable=True)
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    
    # Relationships
    user_id = Column(Integer, ForeignKey("users.id"))
    user = relationship("User", back_populates="interactions")


class UserPreference(Base):
    __tablename__ = "user_preferences"
    
    id = Column(Integer, primary_key=True, index=True)
    preference_type = Column(String, nullable=False)  # response_style, categories, etc.
    preference_key = Column(String, nullable=False)
    preference_value = Column(JSON, nullable=False)
    confidence_score = Column(Float, default=0.5)  # How confident we are about this preference
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
    
    # Relationships
    user_id = Column(Integer, ForeignKey("users.id"))
    user = relationship("User", back_populates="preferences")


class Reminder(Base):
    __tablename__ = "reminders"
    
    id = Column(Integer, primary_key=True, index=True)
    title = Column(String, nullable=False)
    description = Column(Text, nullable=True)
    reminder_time = Column(DateTime(timezone=True), nullable=False)
    is_completed = Column(Boolean, default=False)
    is_recurring = Column(Boolean, default=False)
    recurrence_pattern = Column(String, nullable=True)  # daily, weekly, monthly
    
    # Context for AI suggestions
    context_files = Column(JSON, nullable=True)  # Related file IDs
    auto_generated = Column(Boolean, default=False)  # Was this generated by AI?
    priority = Column(Integer, default=1)  # 1-5 priority scale
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
    
    # Relationships
    user_id = Column(Integer, ForeignKey("users.id"))
    user = relationship("User", back_populates="reminders")


class LearningPattern(Base):
    __tablename__ = "learning_patterns"
    
    id = Column(Integer, primary_key=True, index=True)
    pattern_type = Column(String, nullable=False)  # time_based, topic_based, etc.
    pattern_data = Column(JSON, nullable=False)
    confidence_score = Column(Float, default=0.0)
    usage_count = Column(Integer, default=0)
    success_rate = Column(Float, default=0.0)
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
    
    # Relationships
    user_id = Column(Integer, ForeignKey("users.id"))


class DocumentEmbedding(Base):
    __tablename__ = "document_embeddings"
    
    id = Column(Integer, primary_key=True, index=True)
    file_id = Column(Integer, ForeignKey("user_files.id"))
    chunk_index = Column(Integer, nullable=False)  # For large documents split into chunks
    chunk_text = Column(Text, nullable=False)
    embedding_id = Column(String, nullable=False)  # ID in vector database
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    
    # Relationships
    file = relationship("UserFile")