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huanghuoguoguo
175 lines
10 KiB
Python
175 lines
10 KiB
Python
import sqlalchemy
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from .base import Base
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class MonitoringTrace(Base):
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"""End-to-end monitoring trace records"""
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__tablename__ = 'monitoring_traces'
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trace_id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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started_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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ended_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=True, index=True)
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duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=True) # milliseconds
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status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False, index=True) # running, success, error
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name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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query_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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attributes = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
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class MonitoringSpan(Base):
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"""Trace span records for pipeline, RAG, model, plugin and tool operations"""
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__tablename__ = 'monitoring_spans'
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span_id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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trace_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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parent_span_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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kind = sqlalchemy.Column(sqlalchemy.String(80), nullable=False, index=True)
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status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False, index=True)
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started_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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ended_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=True)
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duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=True) # milliseconds
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message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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attributes = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
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error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
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class MonitoringMessage(Base):
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"""Monitoring message records"""
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__tablename__ = 'monitoring_messages'
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id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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message_content = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
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session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error, pending
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level = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # info, warning, error, debug
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platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
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runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # Runner name for this query
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variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # Query variables as JSON string
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role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user') # user, assistant
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class MonitoringLLMCall(Base):
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"""LLM call records"""
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__tablename__ = 'monitoring_llm_calls'
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id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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input_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
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output_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
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total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
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duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # milliseconds
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cost = sqlalchemy.Column(sqlalchemy.Float, nullable=True)
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status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error
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bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
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message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True) # Associated message ID
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class MonitoringSession(Base):
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"""Session tracking records"""
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__tablename__ = 'monitoring_sessions'
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session_id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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message_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
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start_time = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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last_activity = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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is_active = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=True, index=True)
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platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
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class MonitoringError(Base):
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"""Error log records"""
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__tablename__ = 'monitoring_errors'
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id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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error_type = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
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bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
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pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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stack_trace = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
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message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True) # Associated message ID
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class MonitoringEmbeddingCall(Base):
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"""Embedding call records"""
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__tablename__ = 'monitoring_embedding_calls'
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id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
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prompt_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
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total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
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duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # milliseconds
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input_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # Number of input texts
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status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error
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error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
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# Optional context fields
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knowledge_base_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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query_text = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # For retrieval calls
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session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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call_type = sqlalchemy.Column(sqlalchemy.String(50), nullable=True) # embedding, retrieve
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class MonitoringFeedback(Base):
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"""User feedback records (like/dislike) from AI Bot conversations"""
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__tablename__ = 'monitoring_feedback'
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id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
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timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
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feedback_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, unique=True, index=True)
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feedback_type = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # 1=like, 2=dislike
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feedback_content = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # User feedback text
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inaccurate_reasons = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # JSON list of inaccurate reasons
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# Context fields
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bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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stream_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
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user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
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platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # e.g., wecom
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