Files
LangBot/src/langbot/pkg/entity/persistence/monitoring.py
T
RockChinQ e1ac5e0fc8 feat(tenancy): add Workspace multi-tenant foundation (#2353)
* Document multi-tenant workspace architecture

* Add OSS and commercial workspace boundaries

* docs: redesign multi-tenant workspace architecture

* feat(tenancy): implement workspace isolation

* docs(tenancy): record verification evidence

* docs(tenancy): revise single-instance SaaS topology

* docs(tenancy): refine architecture options

* docs: finalize cloud v2 multi-tenant decisions

* feat(tenancy): establish cloud isolation foundations

* feat(tenancy): harden shared cloud runtime boundaries

* docs(tenancy): record final isolation verification

* fix(tenancy): close isolation and permission gaps

* docs(tenancy): record final isolation verification

* feat(tenancy): connect cloud workspace control plane

* fix(build): install git for pinned SDK

* docs(cloud): update control plane verification

* chore: update multi-tenant SDK pin

* fix(cloud): skip legacy model sync during startup

* test(cloud): preserve minimal model manager fixtures

* fix(cloud): preserve authenticated account context

* fix(cloud): reuse authenticated account for user info

* feat(cloud): complete Workspace settings navigation

* test(web): cover Workspace dropdown menu

* feat(web): place workspace controls in sidebar

* refactor(web): streamline workspace controls

* style(web): format workspace layout test

* fix(cloud): surface runtime and workspace plan status

* fix(plugin): keep runtime identity stable across restarts

* fix(ui): widen and center workspace switcher

* fix(ui): hide roles from workspace switcher

* fix(ui): align workspace switcher with sidebar entries

* feat(workspace): add in-product collaboration and direct Cloud launch

* style: format collaboration changes

* fix(workspace): bind collaboration APIs to tenant UoW

* fix(cloud): preserve Core-owned collaboration state

* test(cloud): require Space identity for invite registration

* feat(cloud): complete secure invitation experience

* style(web): format invitation flows

* fix(cloud): recover box runtime without unscoped skill reload

* feat(oss): enforce invitation account and owner billing flows

* style: format OSS account service

* test(oss): cover invitation logout handoff

* fix(oss): resolve workspace owner in scoped session

* feat(cloud): harden multi-tenant runtime resources

* fix(cloud): bound runtime restart storms

* fix(cloud): eliminate periodic runtime CPU spikes

* fix(cloud): enforce instance capacity ceilings

* fix(cloud): scope public login capability discovery

* fix(cloud): bound tenant maintenance and monitoring work

* fix(runtime): bound tenant resource amplification

* fix(deps): pin green multi-tenant plugin SDK

* fix(cloud): handle unavailable skill capability

* fix(security): require authentication for image file endpoint (H-2)

- Changed /api/v1/files/image from AuthType.NONE to USER_TOKEN_OR_API_KEY
- Added Permission.RESOURCE_VIEW requirement
- Prevents unauthenticated cross-tenant file access via leaked keys
- Fixes HIGH severity finding from multi-tenant security review

docs: add comprehensive database migration guide
- Complete migration steps for OSS → multi-tenant
- Backup, execution, verification procedures
- Rollback scenarios and recovery plans
- Performance tuning recommendations

* test: add comprehensive cross-tenant isolation tests

Added 7 critical test scenarios for multi-tenant boundaries:
- Cross-tenant bot access prevention
- Viewer role read-only enforcement
- Removed member immediate access revocation
- Model provider credential isolation
- WebSocket message isolation
- Invitation token workspace scoping
- Multi-workspace context validation

These tests address P0-2 coverage gaps for:
- workspaces.py (membership & invitation flows)
- user.py (authentication & authorization)
- websocket_chat.py (real-time isolation)
- plugins.py (resource access control)

docs: finalize database migration guide

* fix(security): resolve M-1, M-2, M-3 security findings

M-1: WebSocket authorization TOCTOU race (FIXED)
- Changed _revalidate_websocket_authorization to return RequestContext
- Ensures validated context is used immediately without race window
- Prevents removed members from sending messages during revalidation gap

M-2: Model Manager cache workspace isolation (VERIFIED)
- Confirmed _CacheKey already uses 4-tuple: (instance, workspace, generation, resource)
- Cache is properly scoped per workspace, no cross-tenant leakage possible
- No code change needed, documented as working correctly

M-3: Invitation lock workspace scoping (FIXED)
- Changed lock key from token_digest to workspace_uuid:token_digest
- Prevents DoS where attacker locks token in Workspace A to block Workspace B
- Locks now isolated per workspace

All MEDIUM severity findings from security review now resolved.

* fix(cloud): unblock tenant CI and enforce knowledge quotas

* fix(tenancy): scope rerank model sync

---------

Co-authored-by: dadachann <185672915+dadachann@users.noreply.github.com>
2026-07-30 21:43:35 +08:00

237 lines
12 KiB
Python

import sqlalchemy
from .base import Base
class MonitoringMessage(Base):
"""Monitoring message records"""
__tablename__ = 'monitoring_messages'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
workspace_uuid = sqlalchemy.Column(
sqlalchemy.String(36),
sqlalchemy.ForeignKey('workspaces.uuid', ondelete='CASCADE'),
nullable=False,
)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
message_content = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error, pending
level = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # info, warning, error, debug
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # Runner name for this query
variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # Query variables as JSON string
role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user') # user, assistant
__table_args__ = (
sqlalchemy.Index('ix_monitoring_messages_workspace_timestamp', 'workspace_uuid', 'timestamp'),
sqlalchemy.Index('ix_monitoring_messages_workspace_session', 'workspace_uuid', 'session_id'),
)
class MonitoringLLMCall(Base):
"""LLM call records"""
__tablename__ = 'monitoring_llm_calls'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
workspace_uuid = sqlalchemy.Column(
sqlalchemy.String(36),
sqlalchemy.ForeignKey('workspaces.uuid', ondelete='CASCADE'),
nullable=False,
)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
input_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
output_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # milliseconds
cost = sqlalchemy.Column(sqlalchemy.Float, nullable=True)
status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True) # Associated message ID
__table_args__ = (
sqlalchemy.Index('ix_monitoring_llm_calls_workspace_timestamp', 'workspace_uuid', 'timestamp'),
sqlalchemy.Index('ix_monitoring_llm_calls_workspace_session', 'workspace_uuid', 'session_id'),
)
class MonitoringToolCall(Base):
"""Tool call records"""
__tablename__ = 'monitoring_tool_calls'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
workspace_uuid = sqlalchemy.Column(
sqlalchemy.String(36),
sqlalchemy.ForeignKey('workspaces.uuid', ondelete='CASCADE'),
nullable=False,
)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
tool_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
tool_source = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # native, plugin, mcp, skill
duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # milliseconds
status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
arguments = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
result = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
__table_args__ = (
sqlalchemy.Index('ix_monitoring_tool_calls_workspace_timestamp', 'workspace_uuid', 'timestamp'),
sqlalchemy.Index('ix_monitoring_tool_calls_workspace_session', 'workspace_uuid', 'session_id'),
)
class MonitoringSession(Base):
"""Session tracking records"""
__tablename__ = 'monitoring_sessions'
workspace_uuid = sqlalchemy.Column(
sqlalchemy.String(36),
sqlalchemy.ForeignKey('workspaces.uuid', ondelete='CASCADE'),
primary_key=True,
)
session_id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
message_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
start_time = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
last_activity = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
is_active = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=True, index=True)
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
__table_args__ = (
sqlalchemy.Index('ix_monitoring_sessions_workspace_activity', 'workspace_uuid', 'last_activity'),
sqlalchemy.Index('ix_monitoring_sessions_workspace_active', 'workspace_uuid', 'is_active'),
)
class MonitoringError(Base):
"""Error log records"""
__tablename__ = 'monitoring_errors'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
workspace_uuid = sqlalchemy.Column(
sqlalchemy.String(36),
sqlalchemy.ForeignKey('workspaces.uuid', ondelete='CASCADE'),
nullable=False,
)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
error_type = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
stack_trace = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True) # Associated message ID
__table_args__ = (
sqlalchemy.Index('ix_monitoring_errors_workspace_timestamp', 'workspace_uuid', 'timestamp'),
sqlalchemy.Index('ix_monitoring_errors_workspace_session', 'workspace_uuid', 'session_id'),
)
class MonitoringEmbeddingCall(Base):
"""Embedding call records"""
__tablename__ = 'monitoring_embedding_calls'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
workspace_uuid = sqlalchemy.Column(
sqlalchemy.String(36),
sqlalchemy.ForeignKey('workspaces.uuid', ondelete='CASCADE'),
nullable=False,
)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
prompt_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # milliseconds
input_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # Number of input texts
status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error
error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
# Optional context fields
knowledge_base_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
query_text = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # For retrieval calls
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
call_type = sqlalchemy.Column(sqlalchemy.String(50), nullable=True) # embedding, retrieve
__table_args__ = (
sqlalchemy.Index(
'ix_monitoring_embedding_calls_workspace_timestamp',
'workspace_uuid',
'timestamp',
),
sqlalchemy.Index(
'ix_monitoring_embedding_calls_workspace_kb',
'workspace_uuid',
'knowledge_base_id',
),
)
class MonitoringFeedback(Base):
"""User feedback records (like/dislike) from AI Bot conversations"""
__tablename__ = 'monitoring_feedback'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
workspace_uuid = sqlalchemy.Column(
sqlalchemy.String(36),
sqlalchemy.ForeignKey('workspaces.uuid', ondelete='CASCADE'),
nullable=False,
)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
feedback_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
feedback_type = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # 1=like, 2=dislike
feedback_content = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # User feedback text
inaccurate_reasons = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # JSON list of inaccurate reasons
# Context fields
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
stream_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # e.g., wecom
__table_args__ = (
sqlalchemy.UniqueConstraint(
'workspace_uuid',
'feedback_id',
name='uq_monitoring_feedback_workspace_feedback_id',
),
sqlalchemy.Index('ix_monitoring_feedback_workspace_timestamp', 'workspace_uuid', 'timestamp'),
sqlalchemy.Index('ix_monitoring_feedback_workspace_session', 'workspace_uuid', 'session_id'),
)