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Fix Issue #12 tests and add OpenBrain repo guidance

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Agent Zero
2026-03-19 13:19:50 -04:00
parent 03e8f246d1
commit 1b42989dbb
4 changed files with 241 additions and 47 deletions
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74
src/tools/mod.rs
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@@ -15,31 +15,50 @@ pub fn get_tool_definitions() -> Vec<Value> {
vec![
json!({
"name": "store",
"description": "Store a memory with automatic embedding generation",
"description": "Store a memory with automatic embedding generation and keyword extraction. The memory will be associated with the agent_id for isolated retrieval.",
"inputSchema": {
"type": "object",
"properties": {
"content": {"type": "string"},
"agent_id": {"type": "string"},
"metadata": {"type": "object"}
"content": {
"type": "string",
"description": "The text content to store as a memory"
},
"agent_id": {
"type": "string",
"description": "Unique identifier for the agent storing the memory (default: 'default')"
},
"metadata": {
"type": "object",
"description": "Optional metadata to attach to the memory"
}
},
"required": ["content"]
}
}),
json!({
"name": "batch_store",
"description": "Store multiple memories in a single call (1-50 entries)",
"description": "Store multiple memories with automatic embedding generation and keyword extraction. Accepts 1-50 entries and stores them atomically in a single transaction.",
"inputSchema": {
"type": "object",
"properties": {
"agent_id": {"type": "string"},
"agent_id": {
"type": "string",
"description": "Unique identifier for the agent storing the memories (default: 'default')"
},
"entries": {
"type": "array",
"description": "Array of 1-50 memory entries to store atomically",
"items": {
"type": "object",
"properties": {
"content": {"type": "string"},
"metadata": {"type": "object"}
"content": {
"type": "string",
"description": "The text content to store as a memory"
},
"metadata": {
"type": "object",
"description": "Optional metadata to attach to the memory"
}
},
"required": ["content"]
}
@@ -50,27 +69,48 @@ pub fn get_tool_definitions() -> Vec<Value> {
}),
json!({
"name": "query",
"description": "Query memories by semantic similarity",
"description": "Query stored memories using semantic similarity search. Returns the most relevant memories based on the query text.",
"inputSchema": {
"type": "object",
"properties": {
"query": {"type": "string"},
"agent_id": {"type": "string"},
"limit": {"type": "integer"},
"threshold": {"type": "number"}
"query": {
"type": "string",
"description": "The search query text"
},
"agent_id": {
"type": "string",
"description": "Agent ID to search within (default: 'default')"
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return (default: 10)"
},
"threshold": {
"type": "number",
"description": "Minimum similarity threshold 0.0-1.0 (default: 0.5)"
}
},
"required": ["query"]
}
}),
json!({
"name": "purge",
"description": "Delete memories by agent_id",
"description": "Delete memories for an agent. Can delete all memories or those before a specific timestamp.",
"inputSchema": {
"type": "object",
"properties": {
"agent_id": {"type": "string"},
"before": {"type": "string"},
"confirm": {"type": "boolean"}
"agent_id": {
"type": "string",
"description": "Agent ID whose memories to delete (required)"
},
"before": {
"type": "string",
"description": "Optional ISO8601 timestamp - delete memories created before this time"
},
"confirm": {
"type": "boolean",
"description": "Must be true to confirm deletion"
}
},
"required": ["agent_id", "confirm"]
}