Building Agentic Workflows for Restaurant Discovery

import { tool } from 'ai';
import { z } from 'zod';

const getLocationTool = tool({
  description: 'Get user location coordinates',
  parameters: z.object({
    address: z.string().describe('Address or "current location"'),
  }),
  execute: async ({ address }) => {
    // Use geocoding API
    const coords = await geocode(address);
    return { lat: coords.lat, lng: coords.lng };
  },
});

const searchRestaurantsTool = tool({
  description: 'Search restaurants by criteria',
  parameters: z.object({
    location: z.object({
      lat: z.number(),
      lng: z.number(),
    }),
    cuisine: z.string().optional(),
    mealType: z.enum(['breakfast', 'lunch', 'dinner']).optional(),
    features: z.array(z.string()).optional(),
    priceRange: z.enum(['$', '$$', '$$$', '$$$$']).optional(),
    radius: z.number().default(5), // miles
  }),
  execute: async (params) => {
    // Query restaurant database/API
    const results = await queryRestaurants(params);
    return results;
  },
});

import { generateText } from 'ai';

async function findRestaurants(query: string) {
  const { text, toolCalls } = await generateText({
    model: 'gpt-4',
    prompt: `You are a restaurant discovery assistant. 
    Help the user find restaurants based on their query: "${query}"
    
    Use the available tools to:
    1. Get the user's location
    2. Search for restaurants matching their criteria
    3. Provide detailed recommendations`,
    tools: {
      getLocation: getLocationTool,
      searchRestaurants: searchRestaurantsTool,
    },
    maxSteps: 5, // Allow multi-step reasoning
  });

  return { recommendations: text, toolCalls };
}

// Example: "Find Indian lunch buffets under $20 near downtown"

const result = await findRestaurants(
  "Find Indian lunch buffets under $20 near downtown Seattle"
);

// Agent reasoning:
// 1. Extract location: "downtown Seattle"
// 2. Call getLocation({ address: "downtown Seattle" })
// 3. Extract criteria: cuisine=Indian, mealType=lunch, 
//    features=["buffet"], priceRange="$-$$"
// 4. Call searchRestaurants with all parameters
// 5. Format and return top recommendations