Frameworks
Framework integration for the Agentuity JavaScript SDK
The Agentuity JavaScript SDK provides a flexible and powerful way to integrate other frameworks with your Agent.
The following frameworks are currently supported:
Using Frameworks with Agentuity
To use a framework with Agentuity, choose the framework template when creating a new project.
agentuity create
When you select one of the framework templates, the Agentuity CLI will install the necessary dependencies and create a new project with the framework already configured.
Vercel AI SDK
Example Agent using Vercel AI SDK:
import type { AgentContext, AgentRequest, AgentResponse } from '@agentuity/sdk';
import { anthropic } from '@ai-sdk/anthropic';
import { generateObject } from 'ai';
import { z } from 'zod';
export default async function Agent(
req: AgentRequest,
resp: AgentResponse,
ctx: AgentContext
) {
const prompt =
(await req.data.text()) ?? 'Recommend dinner spots in Austin, TX';
// Get user intent
const userIntent = await generateObject({
model: anthropic('claude-3-7-sonnet-latest'),
system: `
You serve as a central hub that routes user requests to the right
AI agent based on the user's intent. Classify the user's intent
and select the best agent to handle it.
`,
schema: z.object({
agentType: z.enum(['LocalGuide']),
}),
prompt,
});
// Route to appropriate agent based on intent
if (userIntent.object?.agentType === 'LocalGuide') {
return await resp.handoff(
{ name: 'LocalGuide' },
{
data: prompt,
contentType: 'text/plain',
}
);
}
return resp.text("Sorry, I don't know how to help with that.");
}Mastra
Example Agent using Mastra:
import type { AgentContext, AgentRequest, AgentResponse } from '@agentuity/sdk';
import { anthropic } from '@ai-sdk/anthropic';
import { Agent } from '@mastra/core/agent';
export default async function AgentuityAgent(
req: AgentRequest,
resp: AgentResponse,
ctx: AgentContext
) {
const prompt =
(await req.data.text()) ?? 'Recommend dinner spots in Austin, TX';
// Get user intent
const agent = new Agent({
name: 'Concierge',
model: anthropic('claude-3-7-sonnet-latest'),
instructions: `
You serve as a central hub that routes user requests to the right
AI agent based on the user's intent. Classify the user's intent and
select the best agent (for now, just "LocalGuide") to handle it.
Respond ONLY with the agent name.
`,
});
const result = await agent.generate(prompt, { maxSteps: 5 });
const userIntent = result.text?.trim();
// Route to appropriate agent based on intent
if (userIntent === 'LocalGuide') {
return await resp.handoff(
{ name: 'LocalGuide' },
{
data: prompt,
contentType: 'text/plain',
}
);
}
return resp.text("Sorry, I don't know how to help with that.");
}LangChain
Example Agent using LangChain:
import type { AgentContext, AgentRequest, AgentResponse } from '@agentuity/sdk';
import { anthropic } from '@ai-sdk/anthropic';
import { Agent } from '@mastra/core/agent';
export default async function AgentuityAgent(
req: AgentRequest,
resp: AgentResponse,
ctx: AgentContext
) {
const prompt =
(await req.data.text()) ?? 'Recommend dinner spots in Austin, TX';
// Get user intent
const agent = new Agent({
name: 'Concierge',
model: anthropic('claude-3-7-sonnet-latest'),
instructions: `
You serve as a central hub that routes user requests to the right
AI agent based on the user's intent. Classify the user's intent and
select the best agent (for now, just "LocalGuide") to handle it.
Respond ONLY with the agent name.
`,
});
const result = await agent.generate(prompt, { maxSteps: 5 });
const userIntent = result.text?.trim();
// Route to appropriate agent based on intent
if (userIntent === 'LocalGuide') {
return await resp.handoff(
{ name: 'LocalGuide' },
{
data: prompt,
contentType: 'text/plain',
}
);
}
return resp.text("Sorry, I don't know how to help with that.");
}Need Help?
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