# Install v1 Beta packages
npm install @mastra/core@beta @mastra/hono@beta
npm install @ai-sdk/openai  # or other provider
npm install zod hono @hono/node-server

// src/mastra/tools/weather-tool.ts
import { createTool } from "@mastra/core/tools";
import { z } from "zod";

export const weatherTool = createTool({
  id: "get-weather",
  description: "Fetches current weather for a location",
  inputSchema: z.object({
    location: z.string().describe("City name, e.g., 'Seattle'"),
  }),
  outputSchema: z.object({
    temperature: z.number(),
    conditions: z.string(),
  }),
  // v1 Beta signature: (inputData, context)
  execute: async (inputData, context) => {
    const { location } = inputData;
    const { abortSignal } = context;

    if (abortSignal?.aborted) throw new Error("Aborted");

    // Fetch weather data...
    return { temperature: 72, conditions: "sunny" };
  },
});

// src/mastra/agents/weather-agent.ts
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
import { weatherTool } from "../tools/weather-tool.js";

export const weatherAgent = new Agent({
  name: "weather-agent",
  instructions: "You are a helpful weather assistant.",
  model: openai("gpt-4o-mini"),
  tools: { weatherTool },  // Object, not array
});

// src/mastra/index.ts
import { Mastra } from "@mastra/core/mastra";
import { weatherAgent } from "./agents/weather-agent.js";

export const mastra = new Mastra({
  agents: { weatherAgent },
});

// src/index.ts
import { serve } from "@hono/node-server";
import { Hono } from "hono";
import { MastraServer } from "@mastra/hono";
import { mastra } from "./mastra/index.js";

const app = new Hono();
const server = new MastraServer({ app, mastra });
await server.init();

app.get("/", (c) => c.text("Mastra + Hono Server"));

serve({ fetch: app.fetch, port: 3000 });
console.log("Server running at http://localhost:3000");
// Agent endpoint: POST /api/agents/weather-agent/generate

import { Agent } from "@mastra/core/agent";

const agent = new Agent({
  name: "my-agent",                           // Required: unique identifier
  instructions: "You are a helpful assistant.", // Required: system prompt
  model: openai("gpt-4o-mini"),               // Required: LLM model
  tools: { weatherTool, searchTool },         // Optional: object with named tools
});

// Model routing (1113+ models from 53 providers)
model: "openai/gpt-4o-mini"
model: "anthropic/claude-3-5-sonnet"
model: "google/gemini-2.5-flash"

// Model fallbacks for resilience
model: [
  { model: "anthropic/claude-3-opus", maxRetries: 3 },
  { model: "openai/gpt-4o", maxRetries: 2 },
  { model: "google/gemini-pro", maxRetries: 1 },
]

// Agent execution with memory
const response = await agent.generate("Remember my name is Alex", {
  memory: {
    thread: "conversation-123",   // Isolates conversation
    resource: "user-456",         // Associates with user
  },
});

// v1 Beta: execute(inputData, context)
execute: async (inputData, context) => {
  const { location } = inputData;  // First parameter: parsed input
  const { mastra, runtimeContext, abortSignal } = context;  // Second: context

  // Access nested agents via mastra
  const helper = mastra?.getAgent("helperAgent");

  // Always check abort signal for long operations
  if (abortSignal?.aborted) throw new Error("Aborted");

  return { temperature: 72, conditions: "sunny" };
}

// WRONG for v1 Beta:
execute: async ({ context }) => { ... }  // This is stable 0.24.x signature

import { createWorkflow, createStep } from "@mastra/core/workflows";

const step1 = createStep({
  id: "step-1",
  inputSchema: z.object({ message: z.string() }),
  outputSchema: z.object({ formatted: z.string() }),
  execute: async ({ inputData }) => {
    // inputData = workflow input (for first step)
    return { formatted: inputData.message.toUpperCase() };
  },
});

const step2 = createStep({
  id: "step-2",
  inputSchema: z.object({ formatted: z.string() }),  // MUST match step1 output
  outputSchema: z.object({ emphasized: z.string() }),
  execute: async ({ inputData }) => {
    // inputData = step1's return value directly
    return { emphasized: `${inputData.formatted}!!!` };
  },
});

const workflow = createWorkflow({
  id: "my-workflow",
  inputSchema: z.object({ message: z.string() }),     // MUST match step1 input
  outputSchema: z.object({ emphasized: z.string() }), // MUST match final output
})
  .then(step1)
  .then(step2)
  .commit();

execute: async ({
  inputData,      // Previous step's output (or workflow input for step 1)
  getStepResult,  // Access ANY step's output by ID
  getInitData,    // Get original workflow input
  mastra,         // Access agents, tools, storage
}) => {
  const step1Result = getStepResult("step-1");
  const originalInput = getInitData();
  return { result: inputData.formatted };
}

import { MastraServer } from "@mastra/hono";

const app = new Hono();
const server = new MastraServer({ app, mastra });
await server.init();

// Endpoints auto-registered:
// POST /api/agents/{agent-name}/generate
// POST /api/agents/{agent-name}/stream
// POST /api/workflows/{workflow-id}/start

const server = new MastraServer({
  app,
  mastra,
  prefix: "/v1/ai"  // Routes at /v1/ai/agents/...
});

import { registerApiRoute } from "@mastra/core/server";

registerApiRoute("/my-custom-route", {
  method: "POST",
  handler: async (c) => {
    const mastra = c.get("mastra");
    const agent = mastra.getAgent("my-agent");
    const result = await agent.generate("Hello");
    return c.json({ response: result.text });
  },
});