b284cadb86
Implemented simple authentication for testing and admin panel for user management: Backend: - Add simple email/password login for test users (admin@test.local, user@test.local) - Implement RBAC (Role-Based Access Control) with Permission enum - Create admin endpoints for user management and system analytics - Add bcrypt password hashing for test users - Create script to generate test users in database Frontend: - Add SimpleLogin component for test authentication - Create AdminPanel with user management and system analytics - Add role-based navigation (Admin tab visible only for admins) - Update AuthContext to support both MSAL and simple login - Add API methods for admin operations Features: - Admins can view all users, manage roles, activate/deactivate accounts - Admins can view system-wide analytics (users, conversations, tokens, costs) - Regular users only see their own chats and usage - Role badges in UI show user role (user/admin/superadmin) Note: Simple authentication is for testing only. Production uses Azure AD MSAL. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
63 lines
2 KiB
Python
63 lines
2 KiB
Python
"""
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TokenUsage model for tracking OpenAI API token consumption
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"""
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from sqlalchemy import Column, String, Integer, Numeric, DateTime, JSON, ForeignKey
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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 TokenUsage(Base):
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"""
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TokenUsage model for tracking and analyzing token consumption and costs
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"""
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__tablename__ = "token_usage"
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True)
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user_id = Column(
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UUID(as_uuid=True),
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ForeignKey("users.id", ondelete="CASCADE"),
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nullable=False,
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index=True
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)
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conversation_id = Column(
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UUID(as_uuid=True),
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ForeignKey("conversations.id", ondelete="SET NULL"),
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index=True
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)
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message_id = Column(
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UUID(as_uuid=True),
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ForeignKey("messages.id", ondelete="SET NULL"),
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index=True
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)
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# Token counts
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prompt_tokens = Column(Integer, default=0, nullable=False)
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completion_tokens = Column(Integer, default=0, nullable=False)
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total_tokens = Column(Integer, default=0, nullable=False)
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# Model and cost information
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model = Column(String(100), nullable=False) # e.g., gpt-5-nano-2025-08-07
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cost_usd = Column(Numeric(10, 6), default=0.0, nullable=False) # Cost in USD
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# Operation type (chat, search, etc.)
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operation_type = Column(String(50))
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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 additional metadata
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meta_data = Column(JSON, default=dict, nullable=False)
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# Relationships
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user = relationship("User", back_populates="token_usage")
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conversation = relationship("Conversation", back_populates="token_usage")
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message = relationship("Message", back_populates="token_usage_records")
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def __repr__(self):
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return f"<TokenUsage {self.id} - {self.total_tokens} tokens>"
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