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/**
* Test Fixtures Index
*
* Centralized fixture exports for RuvBot tests
*/
// Agent Fixtures
export const agentFixtures = {
basicAgent: {
id: 'agent-001',
name: 'Test Agent',
type: 'coder' as const,
status: 'idle' as const,
capabilities: ['code-generation', 'code-review'],
config: {
model: 'claude-sonnet-4',
temperature: 0.7,
maxTokens: 4096
},
metadata: {
createdAt: new Date('2024-01-01'),
updatedAt: new Date('2024-01-01'),
version: '1.0.0'
}
},
researcherAgent: {
id: 'agent-002',
name: 'Research Agent',
type: 'researcher' as const,
status: 'idle' as const,
capabilities: ['web-search', 'document-analysis', 'summarization'],
config: {
model: 'claude-sonnet-4',
temperature: 0.5,
maxTokens: 8192
},
metadata: {
createdAt: new Date('2024-01-01'),
updatedAt: new Date('2024-01-01'),
version: '1.0.0'
}
},
testerAgent: {
id: 'agent-003',
name: 'Tester Agent',
type: 'tester' as const,
status: 'idle' as const,
capabilities: ['test-generation', 'test-execution', 'coverage-analysis'],
config: {
model: 'claude-haiku-3',
temperature: 0.3,
maxTokens: 4096
},
metadata: {
createdAt: new Date('2024-01-01'),
updatedAt: new Date('2024-01-01'),
version: '1.0.0'
}
}
};
// Session Fixtures
export const sessionFixtures = {
basicSession: {
id: 'session-001',
tenantId: 'tenant-001',
userId: 'user-001',
channelId: 'C12345678',
threadTs: '1234567890.123456',
status: 'active' as const,
context: {
conversationHistory: [],
workingDirectory: '/workspace',
activeAgents: []
},
metadata: {
createdAt: new Date('2024-01-01'),
lastActiveAt: new Date('2024-01-01'),
messageCount: 0
}
},
activeSession: {
id: 'session-002',
tenantId: 'tenant-001',
userId: 'user-001',
channelId: 'C12345678',
threadTs: '1234567890.654321',
status: 'active' as const,
context: {
conversationHistory: [
{ role: 'user', content: 'Hello', timestamp: new Date() },
{ role: 'assistant', content: 'Hi there!', timestamp: new Date() }
],
workingDirectory: '/workspace/project',
activeAgents: ['agent-001']
},
metadata: {
createdAt: new Date('2024-01-01'),
lastActiveAt: new Date('2024-01-02'),
messageCount: 2
}
}
};
// Memory Fixtures
export const memoryFixtures = {
shortTermMemory: {
id: 'mem-001',
sessionId: 'session-001',
type: 'short-term' as const,
key: 'current-task',
value: { task: 'implement feature', priority: 'high' },
embedding: new Float32Array(384).fill(0.1),
metadata: {
createdAt: new Date(),
expiresAt: new Date(Date.now() + 3600000),
accessCount: 1
}
},
longTermMemory: {
id: 'mem-002',
sessionId: null,
tenantId: 'tenant-001',
type: 'long-term' as const,
key: 'coding-pattern-react',
value: { pattern: 'functional-components', examples: [] },
embedding: new Float32Array(384).fill(0.2),
metadata: {
createdAt: new Date('2024-01-01'),
expiresAt: null,
accessCount: 42
}
},
vectorMemory: {
id: 'mem-003',
tenantId: 'tenant-001',
type: 'vector' as const,
key: 'codebase-embeddings',
value: { path: '/src/index.ts', summary: 'Main entry point' },
embedding: new Float32Array(384).map(() => Math.random() - 0.5),
metadata: {
createdAt: new Date(),
expiresAt: null,
accessCount: 10
}
}
};
// Skill Fixtures
export const skillFixtures = {
codeGenerationSkill: {
id: 'skill-001',
name: 'code-generation',
version: '1.0.0',
description: 'Generate code based on natural language descriptions',
inputSchema: {
type: 'object',
properties: {
language: { type: 'string' },
description: { type: 'string' },
context: { type: 'object' }
},
required: ['language', 'description']
},
outputSchema: {
type: 'object',
properties: {
code: { type: 'string' },
explanation: { type: 'string' }
}
},
executor: 'wasm://skills/code-generation',
timeout: 30000
},
testGenerationSkill: {
id: 'skill-002',
name: 'test-generation',
version: '1.0.0',
description: 'Generate tests for given code',
inputSchema: {
type: 'object',
properties: {
code: { type: 'string' },
framework: { type: 'string' },
coverage: { type: 'string' }
},
required: ['code']
},
outputSchema: {
type: 'object',
properties: {
tests: { type: 'string' },
coverage: { type: 'number' }
}
},
executor: 'wasm://skills/test-generation',
timeout: 60000
},
vectorSearchSkill: {
id: 'skill-003',
name: 'vector-search',
version: '1.0.0',
description: 'Search vector embeddings using RuVector',
inputSchema: {
type: 'object',
properties: {
query: { type: 'string' },
topK: { type: 'number' },
threshold: { type: 'number' }
},
required: ['query']
},
outputSchema: {
type: 'object',
properties: {
results: { type: 'array' },
scores: { type: 'array' }
}
},
executor: 'native://ruvector/search',
timeout: 5000
}
};
// Slack Event Fixtures
export const slackFixtures = {
messageEvent: {
type: 'message',
channel: 'C12345678',
user: 'U12345678',
text: 'Hello, bot!',
ts: '1234567890.123456',
team: 'T12345678',
event_ts: '1234567890.123456'
},
appMentionEvent: {
type: 'app_mention',
channel: 'C12345678',
user: 'U12345678',
text: '<@U_BOT> help me with this code',
ts: '1234567890.123456',
team: 'T12345678',
event_ts: '1234567890.123456'
},
threadReplyEvent: {
type: 'message',
channel: 'C12345678',
user: 'U12345678',
text: 'This is a reply',
ts: '1234567890.654321',
thread_ts: '1234567890.123456',
team: 'T12345678',
event_ts: '1234567890.654321'
}
};
// Tenant Fixtures
export const tenantFixtures = {
basicTenant: {
id: 'tenant-001',
name: 'Acme Corp',
slackTeamId: 'T12345678',
status: 'active' as const,
plan: 'pro',
config: {
maxAgents: 10,
maxSessions: 100,
features: ['code-generation', 'vector-search']
},
metadata: {
createdAt: new Date('2024-01-01'),
updatedAt: new Date('2024-01-01')
}
},
enterpriseTenant: {
id: 'tenant-002',
name: 'Enterprise Inc',
slackTeamId: 'T87654321',
status: 'active' as const,
plan: 'enterprise',
config: {
maxAgents: 100,
maxSessions: 1000,
features: ['code-generation', 'vector-search', 'custom-skills', 'sso']
},
metadata: {
createdAt: new Date('2024-01-01'),
updatedAt: new Date('2024-01-01')
}
}
};