/**
* Tool handler for creating a new agent in the Letta system
*/
export async function handleCreateAgent(server, args) {
try {
// Validate arguments
if (!args.name || !args.description || typeof args.name !== 'string' || typeof args.description !== 'string') {
throw new Error('Invalid arguments: name and description must be strings');
}
const model = args.model ?? 'openai/gpt-4';
const embedding = args.embedding ?? 'openai/text-embedding-ada-002';
// Agent configuration
const agentConfig = {
name: args.name,
description: args.description,
agent_type: "memgpt_agent",
model: model,
llm_config: {
model: model.split('/')[1],
model_endpoint_type: model.split('/')[0],
context_window: 16000,
max_tokens: 1000,
temperature: 0.7,
frequency_penalty: 0.5,
presence_penalty: 0.5,
functions_config: {
allow: true,
functions: []
}
},
embedding: embedding,
parameters: {
context_window: 16000,
max_tokens: 1000,
temperature: 0.7,
presence_penalty: 0.5,
frequency_penalty: 0.5
},
core_memory: {}
};
// Headers for API requests
const headers = server.getApiHeaders();
// Create agent
const createAgentResponse = await server.api.post('/agents', agentConfig, { headers });
const agentId = createAgentResponse.data.id;
// Update headers with agent ID
headers['user_id'] = agentId;
// Get agent info for the response
const agentInfo = await server.api.get(`/agents/${agentId}`, { headers });
const capabilities = agentInfo.data.tools?.map((t) => t.name) ?? [];
return {
content: [{
type: 'text',
text: JSON.stringify({
success: true,
message: `Agent ${args.name} created successfully with ID: ${agentId}`,
agent_id: agentId,
capabilities,
}, null, 2),
}],
};
} catch (error) {
return server.createErrorResponse(error);
}
}
/**
* Tool definition for create_agent
*/
export const createAgentToolDefinition = {
name: 'create_agent',
description: 'Create a new Letta agent with specified configuration',
inputSchema: {
type: 'object',
properties: {
name: {
type: 'string',
description: 'Name of the new agent',
},
description: {
type: 'string',
description: 'Description of the agent\'s purpose/role',
},
model: {
type: 'string',
description: 'The model to use for the agent',
default: 'openai/gpt-4',
},
embedding: {
type: 'string',
description: 'The embedding model to use',
default: 'openai/text-embedding-ada-002',
},
},
required: ['name', 'description'],
},
};
