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.ai_config_defaults.json
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182 lines (182 loc) · 7.25 KB
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{
"_metadata": {
"generated_at": "2025-10-23T11:15:54.739693",
"environment": "production",
"project_key": "multi-agent-chatbot",
"config_count": 3
},
"configs": {
"security-agent": {
"enabled": true,
"model": {
"name": "claude-3-5-haiku-20241022",
"parameters": {}
},
"provider": {
"name": "Anthropic"
},
"instructions": "You are a privacy agent that REMOVES direct PII. Focus on clearly personal identifiers:\n\nEmail addresses\nPhone numbers\nSocial Security Numbers\nFull names (but not generic titles)\nStreet addresses\nCredit card numbers\nDriver's license numbers\n\nResponse Format:\n\ndetected: true if any PII was found, false otherwise\ntypes: array of PII types found (e.g., ['email', 'name', 'phone'])\nredacted: the input text with PII replaced by [REDACTED], keeping the text readable and natural\n\nExamples:\n\nInput: \"I work at Acme Corp in Berlin as a manager\"\n\nOutput: detected=false, types=[], redacted='I work at Acme Corp in Berlin as a manager'\n\n\nInput: \"Contact John Smith at john@email.com or 555-1234\"\n\nOutput: detected=true, types=['name', 'email', 'phone'], redacted='Contact [REDACTED] at [REDACTED] or [REDACTED]'\n\n\nInput: \"The CEO from Microsoft contacted me\"\n\nOutput: detected=false, types=[], redacted='The CEO from Microsoft contacted me'"
},
"supervisor-agent": {
"enabled": true,
"model": {
"name": "claude-3-7-sonnet-latest",
"parameters": {}
},
"provider": {
"name": "Anthropic"
},
"instructions": " You are an intelligent routing supervisor for a multi-agent system. Your primary job is to assess whether user input likely contains PII (personally identifiable information) to determine the most efficient processing route.\nPII Assessment:\n Analyze the user input and provide:\n - likely_contains_pii: boolean assessment\n - confidence: confidence score (0.0 to 1.0)\n - reasoning: clear explanation of your decision\n - recommended_route: either 'security_agent' or 'support_agent'\n\n Route to SECURITY_AGENT** if the text likely contains:\n - Email addresses, phone numbers, addresses\n - Names (first/last names, usernames)\n - Financial information (credit cards, SSNs, account numbers)\n - Sensitive personal data\n\n **Route to SUPPORT_AGENT** if the text appears to be:\n - General questions without personal details\n - Technical queries\n - Search requests\n - Educational content requests\n\n Analyze this user input and recommend the optimal route:\n"
},
"support-agent": {
"enabled": true,
"model": {
"name": "claude-3-5-haiku-20241022",
"parameters": {
"tools": [
{
"description": "Simple keyword search through knowledge base",
"name": "search_v1",
"parameters": {
"additionalProperties": false,
"properties": {
"query": {
"description": "Search query for keyword matching",
"type": "string"
},
"top_k": {
"description": "Number of results to return",
"type": "number"
}
},
"required": [
"query"
],
"type": "object"
},
"type": "function"
},
{
"description": "Semantic search using vector embeddings",
"name": "search_v2",
"parameters": {
"additionalProperties": false,
"properties": {
"query": {
"description": "Search query for semantic matching",
"type": "string"
},
"top_k": {
"description": "Number of results to return",
"type": "number"
}
},
"required": [
"query"
],
"type": "object"
},
"type": "function"
},
{
"description": "Reorders results by relevance using BM25 algorithm",
"name": "reranking",
"parameters": {
"additionalProperties": false,
"properties": {
"query": {
"description": "Original query for scoring",
"type": "string"
},
"results": {
"description": "Results to rerank",
"type": "array"
}
},
"required": [
"query",
"results"
],
"type": "object"
},
"type": "function"
}
]
}
},
"provider": {
"name": "Anthropic"
},
"instructions": "You are a helpful assistant with access to RAG tools: search_v1 (basic search), search_v2 (semantic vector search), and reranking (BM25 relevance scoring). When search results are available, prioritize information from those results over your general knowledge. Provide balanced, well-researched responses for international users.",
"tools": [
{
"description": "Simple keyword search through knowledge base",
"name": "search_v1",
"parameters": {
"additionalProperties": false,
"properties": {
"query": {
"description": "Search query for keyword matching",
"type": "string"
},
"top_k": {
"description": "Number of results to return",
"type": "number"
}
},
"required": [
"query"
],
"type": "object"
},
"type": "function"
},
{
"description": "Semantic search using vector embeddings",
"name": "search_v2",
"parameters": {
"additionalProperties": false,
"properties": {
"query": {
"description": "Search query for semantic matching",
"type": "string"
},
"top_k": {
"description": "Number of results to return",
"type": "number"
}
},
"required": [
"query"
],
"type": "object"
},
"type": "function"
},
{
"description": "Reorders results by relevance using BM25 algorithm",
"name": "reranking",
"parameters": {
"additionalProperties": false,
"properties": {
"query": {
"description": "Original query for scoring",
"type": "string"
},
"results": {
"description": "Results to rerank",
"type": "array"
}
},
"required": [
"query",
"results"
],
"type": "object"
},
"type": "function"
}
]
}
}
}