Merge HF Space remote history

backend/models/__init__.py

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+"""
+MEXAR Models Package
+Import all models in correct order to resolve relationships.
+"""
+
+# Import in correct order to resolve relationships
+from models.user import User
+from models.agent import Agent, CompilationJob
+from models.conversation import Conversation, Message
+from models.chunk import DocumentChunk
+
+__all__ = [
+    "User",
+    "Agent", 
+    "CompilationJob",
+    "Conversation",
+    "Message",
+    "DocumentChunk"
+]

backend/models/agent.py

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+from sqlalchemy import Column, Integer, String, Text, DateTime, ForeignKey
+from sqlalchemy.sql import func
+from sqlalchemy.orm import relationship
+from sqlalchemy.dialects.postgresql import JSONB
+from core.database import Base
+
+
+class Agent(Base):
+    """AI Agent with all metadata stored in Supabase"""
+    __tablename__ = "agents"
+
+    id = Column(Integer, primary_key=True, index=True)
+    user_id = Column(Integer, ForeignKey("users.id", ondelete="CASCADE"), nullable=False)
+    name = Column(String, nullable=False)
+    domain = Column(String, nullable=True)
+    system_prompt = Column(Text, nullable=False)
+    
+    # All metadata stored in Supabase (no filesystem)
+    domain_keywords = Column(JSONB, nullable=True)
+    domain_signature = Column(JSONB, nullable=True)
+    prompt_analysis = Column(JSONB, nullable=True)
+    knowledge_graph_json = Column(JSONB, nullable=True)
+    compilation_stats = Column(JSONB, nullable=True)
+    
+    status = Column(String, default="initializing")  # initializing, compiling, ready, failed
+    storage_path = Column(String, nullable=True)  # Deprecated, kept for compatibility
+    chunk_count = Column(Integer, default=0)
+    entity_count = Column(Integer, default=0)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    
+    # Relationships
+    user = relationship("User", backref="agents")
+    compilation_jobs = relationship("CompilationJob", back_populates="agent", cascade="all, delete-orphan")
+    conversations = relationship("Conversation", back_populates="agent", cascade="all, delete-orphan")
+    chunks = relationship("DocumentChunk", back_populates="agent", cascade="all, delete-orphan")
+
+
+class CompilationJob(Base):
+    """Background job for agent compilation"""
+    __tablename__ = "compilation_jobs"
+
+    id = Column(Integer, primary_key=True, index=True)
+    agent_id = Column(Integer, ForeignKey("agents.id", ondelete="CASCADE"), nullable=False)
+    status = Column(String, default="queued")  # queued, processing, completed, failed
+    progress = Column(Integer, default=0)
+    current_step = Column(String, nullable=True)
+    error_message = Column(Text, nullable=True)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    completed_at = Column(DateTime(timezone=True), nullable=True)
+
+    agent = relationship("Agent", back_populates="compilation_jobs")

backend/models/chunk.py

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+from sqlalchemy import Column, Integer, String, Text, DateTime, ForeignKey, Index
+from sqlalchemy.sql import func
+from sqlalchemy.orm import relationship, mapped_column
+from sqlalchemy.dialects.postgresql import TSVECTOR
+from pgvector.sqlalchemy import Vector
+from core.database import Base
+
+
+class DocumentChunk(Base):
+    """Document chunk with embedding for RAG retrieval"""
+    __tablename__ = "document_chunks"
+
+    id = Column(Integer, primary_key=True, index=True)
+    agent_id = Column(Integer, ForeignKey("agents.id", ondelete="CASCADE"), nullable=False)
+    content = Column(Text, nullable=False)
+    source = Column(String, nullable=True)
+    chunk_index = Column(Integer, nullable=True)
+    section_title = Column(String, nullable=True)
+    token_count = Column(Integer, nullable=True)
+    
+    # 384 dimensions for bge-small-en-v1.5 (unifying for MEXAR Ultimate)
+    embedding = mapped_column(Vector(384))
+    
+    # Full-text search column
+    content_tsvector = Column(TSVECTOR)
+    
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+
+    agent = relationship("Agent", back_populates="chunks")

backend/models/conversation.py

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+
+from sqlalchemy import Column, Integer, String, Text, DateTime, ForeignKey, JSON, Float
+from sqlalchemy.sql import func
+from sqlalchemy.orm import relationship
+from core.database import Base
+
+class Conversation(Base):
+    __tablename__ = "conversations"
+
+    id = Column(Integer, primary_key=True, index=True)
+    agent_id = Column(Integer, ForeignKey("agents.id", ondelete="CASCADE"), nullable=False)
+    user_id = Column(Integer, ForeignKey("users.id", ondelete="CASCADE"), nullable=False)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    updated_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
+
+    # Relationships
+    agent = relationship("Agent", back_populates="conversations")
+    messages = relationship("Message", back_populates="conversation", cascade="all, delete-orphan")
+
+class Message(Base):
+    __tablename__ = "messages"
+
+    id = Column(Integer, primary_key=True, index=True)
+    conversation_id = Column(Integer, ForeignKey("conversations.id", ondelete="CASCADE"), nullable=False)
+    role = Column(String, nullable=False)  # user, assistant
+    content = Column(Text, nullable=False)
+    
+    # Advanced features
+    multimodal_data = Column(JSON, nullable=True)  # Images, audio paths
+    explainability_data = Column(JSON, nullable=True)  # Reasoning traces
+    confidence = Column(Float, nullable=True)
+    
+    timestamp = Column(DateTime(timezone=True), server_default=func.now())
+    
+    conversation = relationship("Conversation", back_populates="messages")

backend/models/user.py

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+
+from sqlalchemy import Column, Integer, String, DateTime, JSON, Boolean
+from sqlalchemy.sql import func
+from sqlalchemy.orm import relationship
+from core.database import Base
+
+class User(Base):
+    __tablename__ = "users"
+
+    id = Column(Integer, primary_key=True, index=True)
+    email = Column(String, unique=True, index=True, nullable=False)
+    password = Column(String, nullable=False)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    last_login = Column(DateTime(timezone=True), nullable=True)
+    preferences = Column(JSON, default={})
+    
+    # Relationships
+    conversations = relationship("Conversation", backref="user", cascade="all, delete-orphan")