a8151fbe66
Backend Tests: - Add pytest configuration with async support (conftest.py) - Add model tests: User, Conversation, Message, TokenUsage, Session, UserMemory - Add configuration tests: Settings validation and environment variables - Add API tests: Health endpoint and future endpoint stubs - Add database tests: Connection, transactions, query execution Phase 1 Foundation: - FastAPI application structure with main.py - SQLAlchemy async models for all entities - Alembic migrations setup - Configuration management via Pydantic Settings - Logging system (English only) - Docker multi-stage builds for backend - Docker Compose orchestration (PostgreSQL, Redis, backend) - Frontend React + TypeScript structure - Dark & Gold theme CSS implementation - Environment configuration examples All code and comments in English as per requirements. Tests cover model relationships, cascade deletes, and constraints. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
"""
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Message model for storing individual chat messages
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"""
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from sqlalchemy import Column, String, Text, Integer, DateTime, JSON, ForeignKey, CheckConstraint
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from sqlalchemy.dialects.postgresql import UUID
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from sqlalchemy.orm import relationship
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from sqlalchemy.sql import func
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import uuid
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from app.database import Base
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class Message(Base):
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"""
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Message model representing a single message in a conversation
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"""
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__tablename__ = "messages"
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True)
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conversation_id = Column(
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UUID(as_uuid=True),
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ForeignKey("conversations.id", ondelete="CASCADE"),
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nullable=False,
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index=True
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)
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# OpenAI Responses API response_id
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openai_response_id = Column(String(255), index=True)
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# Message content
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role = Column(String(50), nullable=False) # user, assistant, system
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content = Column(Text, nullable=False)
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# Token count for this message
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token_count = Column(Integer, default=0)
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# Timestamp
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created_at = Column(DateTime(timezone=True), server_default=func.now(), nullable=False, index=True)
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# JSON field for metadata (file_search_results, etc.)
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metadata = Column(JSON, default=dict, nullable=False)
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# Relationships
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conversation = relationship("Conversation", back_populates="messages")
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token_usage_records = relationship("TokenUsage", back_populates="message")
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# Constraints
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__table_args__ = (
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CheckConstraint(
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"role IN ('user', 'assistant', 'system')",
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name="check_message_role"
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),
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)
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def __repr__(self):
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return f"<Message {self.id} - {self.role}>"
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