Use casesRecipes

Restaurant Ordering & Table Booking

Let diners browse your menu, filter by dietary needs, book a table, or place a takeout order — with upsell prompts baked into the flow.

DifficultyBeginner
TrackBuilder Track
ChannelsWhatsAppWeb Chat
IntegrationsGoogle Calendar (availability)Menu (knowledge base)

What you'll build

An agent that handles diner interactions end to end: menu questions, dietary filtering, table reservations checked against Google Calendar, and takeout orders with upsell prompts at the point of order.

Customer journey

A diner uses WhatsApp or Web Chat to browse the menu, filter allergens, book a table, or place takeout. The agent confirms availability via Google Calendar and sends order details to the kitchen integration.

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See Deploying and testing channels for connect and test steps per channel.

Prerequisites

  • BimpeAI account with an API key (sk_…)
  • Read Anatomy of a workflow agent first — this recipe skips steps covered there
  • Google Calendar connected in the Console dashboard (see Step 4)

Steps

1. Find or create the workflow

import { BimpeAI } from "@bimpeai/sdk";

const bimpe = new BimpeAI({ apiKey: process.env.BIMPEAI_API_KEY! });

const page = await bimpe.workflows.list({ scope: "public", search: "restaurant" });
const workflow = page.data[0];
console.log(workflow.id, workflow.name);
import os
from bimpeai import BimpeAI

client = BimpeAI(api_key=os.environ["BIMPEAI_API_KEY"])

page = client.workflows.list(scope="public", search="restaurant")
workflow = page.data[0]
print(workflow.id, workflow.name)

Or build a new workflow from scratch with workflows.create instead of finding one. name and system_prompt are required; it returns the new Workflow whose id you bind the agent to. See Anatomy of a workflow agent for the full set of optional fields like rules and flows.

const workflow = await bimpe.workflows.create({
  name: "Restaurant assistant",
  system_prompt: "You help diners browse the menu, filter by dietary needs, book tables, and place takeout orders.",
});
console.log(workflow.id);
workflow = client.workflows.create(
    name="Restaurant assistant",
    system_prompt="You help diners browse the menu, filter by dietary needs, book tables, and place takeout orders.",
)
print(workflow.id)

2. Create the agent

const agent = await bimpe.agents.create(
  {
    name: "Restaurant assistant",
    description: "Helps guests browse the menu, check dietary options, book tables, and place takeout orders.",
    workflow_id: workflow.id,
  },
  { idempotencyKey: "create-restaurant-agent-v1" },
);

console.log(agent.id);
agent = client.agents.create(
    name="Restaurant assistant",
    description="Helps guests browse the menu, check dietary options, book tables, and place takeout orders.",
    workflow_id=workflow.id,
    idempotency_key="create-restaurant-agent-v1",
)

print(agent.id)

3. Add knowledge bases (optional)

Knowledge bases are optional; an agent whose workflow and integrations already cover everything it needs to say can skip this step. This recipe uses one to ground the agent in the details it must quote accurately.

Add the menu and booking policy so the agent can answer accurately without hallucinating prices or dietary details.

// Menu with dietary flags
await bimpe.agents.knowledgeBases.create(agent.id, {
  type: "text",
  name: "Menu",
  content:
    "Starters:\n" +
    "  Bruschetta — £6.50 — vegan, gluten-free option available\n" +
    "  Chicken wings — £8.00 — contains gluten\n" +
    "Mains:\n" +
    "  Margherita pizza — £12.00 — vegetarian\n" +
    "  Pasta arrabbiata — £10.50 — vegan, contains gluten\n" +
    "  Grilled salmon — £16.00 — gluten-free\n" +
    "Desserts:\n" +
    "  Tiramisu — £6.00 — contains dairy, gluten\n" +
    "  Sorbet — £4.50 — vegan, gluten-free",
});

// Booking policy
await bimpe.agents.knowledgeBases.create(agent.id, {
  type: "text",
  name: "Booking policy",
  content:
    "Tables available Tuesday to Sunday, 12:00–22:00.\n" +
    "Maximum party size: 12. Groups over 8 require a £10 per head deposit.\n" +
    "Cancellations must be made 24 hours in advance.",
});
# Menu with dietary flags
client.agents.knowledge_bases.create(agent.id, {
    "type": "text",
    "name": "Menu",
    "content": (
        "Starters:\n"
        "  Bruschetta — £6.50 — vegan, gluten-free option available\n"
        "  Chicken wings — £8.00 — contains gluten\n"
        "Mains:\n"
        "  Margherita pizza — £12.00 — vegetarian\n"
        "  Pasta arrabbiata — £10.50 — vegan, contains gluten\n"
        "  Grilled salmon — £16.00 — gluten-free\n"
        "Desserts:\n"
        "  Tiramisu — £6.00 — contains dairy, gluten\n"
        "  Sorbet — £4.50 — vegan, gluten-free"
    ),
})

# Booking policy
client.agents.knowledge_bases.create(agent.id, {
    "type": "text",
    "name": "Booking policy",
    "content": (
        "Tables available Tuesday to Sunday, 12:00–22:00.\n"
        "Maximum party size: 12. Groups over 8 require a £10 per head deposit.\n"
        "Cancellations must be made 24 hours in advance."
    ),
})

4. Connect channels and integrations (dashboard)

Google Calendar and channels are configured in the dashboard

The API cannot create channel connections, but integrations can now be configured through it; see Configuring integrations. Connect your messaging channels on the Deploy screen and Google Calendar on the Integrations screen of the Console dashboard. The SDK lists what is active but cannot modify channel connections.

  1. In the Console dashboard, pick your agent from the switcher at the top, then open Deploy.
  2. Under Messaging & Chat, click Connect on the WhatsApp card and follow the prompts to link your WhatsApp Business number.
  3. Under Messaging & Chat, click Connect on the Web Chat Widget card to add the widget to your restaurant website.
  4. Open Integrations, find Google Calendar, and click Connect. The agent uses it to check table availability in real time.

Connect WhatsApp

Customers message your WhatsApp Business number for support and transactions.

  1. Open the Deploy screen in the Console dashboard and select your agent.
  2. Under Messaging & Chat, click Connect on the WhatsApp card.
  3. Follow the prompts to link your WhatsApp Business number.
  4. Once connected, customers can message your business number and the agent replies within WhatsApp's 24-hour session window.

Full reference: Deploying and testing channels.

Connect Web Chat

Visitors use the chat widget embedded on your website or app.

  1. Open Deploy and select your agent.
  2. Under Messaging & Chat, click Connect on the Web Chat Widget card.
  3. Copy the embed snippet and paste it into your site's HTML before the closing body tag.
  4. Publish your site — the chat bubble appears in the corner and routes messages to this agent.

Full reference: Deploying and testing channels.

Also on Instagram and Messenger: the same Deploy → Connect flow applies. Testers use the Deploy panel links or getTestCode deep links for each network. Instagram · Messenger

5. Test your agent

Before going live, exercise the agent on a test channel. Fetch the test code (created on first request), then test on WhatsApp — share the deep link or start message with a human tester, or inject a message from your server.

Test WhatsApp

Human tester: fetch the test code with agents.getTestCode (or use the Deploy panel). Share the deep link or start <code> message with a tester.

SDK injection: call conversations.send with is_test_channel: true and the matching channel_type.

Full reference: Deploying and testing channels.

Test Web Chat

Playground: open Playground → Chat in the dashboard for a quick sanity check.

SDK injection: call conversations.send with channel_type: "webchat" and a stable channel_user_id, or set is_test_channel: true before go-live.

Full reference: Deploying and testing channels.

const { channels } = await bimpe.agents.getTestCode(agent.id);
// A tester opens channels.whatsapp.url, or sends channels.whatsapp.start_message
// to channels.whatsapp.phone_number, to open a 24-hour test window.
console.log(channels.whatsapp.start_message, channels.whatsapp.url);

// Or inject a test message yourself:
await bimpe.conversations.send(agent.id, {
  message: "A table for two at 7pm tonight?",
  channel_type: "whatsapp",
  channel_user_id: "<tester-whatsapp-number>",
  is_test_channel: true,
});
test_code = client.agents.get_test_code(agent.id)
# A tester opens .url, or sends .start_message to .phone_number, to open a 24-hour window.
print(test_code.channels.whatsapp.start_message, test_code.channels.whatsapp.url)

# Or inject a test message yourself:
client.conversations.send(
    agent.id,
    message="A table for two at 7pm tonight?",
    channel_type="whatsapp",
    channel_user_id="<tester-whatsapp-number>",
    is_test_channel=True,
)

See Test your agent for the other test channels and the pause-AI rule.

6. Go live

Once channels are connected, the agent is ready to handle diners. Verify the integration is connected before opening for service:

const integrations = await bimpe.agents.integrations.list(agent.id);
console.log("Integrations:", integrations.map((i) => i.name));
integrations = client.agents.integrations.list(agent.id)
print("Integrations:", [i.name for i in integrations])

Full example

import { BimpeAI } from "@bimpeai/sdk";

const bimpe = new BimpeAI({ apiKey: process.env.BIMPEAI_API_KEY! });

// 1. Find workflow
const page = await bimpe.workflows.list({ scope: "public", search: "restaurant" });
const workflow = page.data[0];

// 2. Create agent
const agent = await bimpe.agents.create(
  {
    name: "Restaurant assistant",
    description: "Helps guests browse the menu, check dietary options, book tables, and place takeout orders.",
    workflow_id: workflow.id,
  },
  { idempotencyKey: "create-restaurant-agent-v1" },
);

// 3. Add knowledge bases
await bimpe.agents.knowledgeBases.create(agent.id, {
  type: "text",
  name: "Menu",
  content:
    "Margherita pizza — £12.00 — vegetarian\n" +
    "Pasta arrabbiata — £10.50 — vegan, contains gluten\n" +
    "Tiramisu — £6.00 — contains dairy, gluten",
});

await bimpe.agents.knowledgeBases.create(agent.id, {
  type: "text",
  name: "Booking policy",
  content:
    "Tables available Tuesday to Sunday, 12:00–22:00.\n" +
    "Maximum party size: 12.",
});

// 4. Verify integrations (connected via dashboard)
const integrations = await bimpe.agents.integrations.list(agent.id);
console.log("Agent ID:", agent.id);
console.log("Integrations:", integrations.map((i) => i.name));

// 5. Stream messages in a web chat conversation
const controller = new AbortController();

for await (const event of bimpe.conversations.messages.stream(
  agent.id,
  "<conversation_id>",
  { signal: controller.signal },
)) {
  console.log(event.role, event.message);
}
import os
from bimpeai import BimpeAI

client = BimpeAI(api_key=os.environ["BIMPEAI_API_KEY"])

# 1. Find workflow
page = client.workflows.list(scope="public", search="restaurant")
workflow = page.data[0]

# 2. Create agent
agent = client.agents.create(
    name="Restaurant assistant",
    description="Helps guests browse the menu, check dietary options, book tables, and place takeout orders.",
    workflow_id=workflow.id,
    idempotency_key="create-restaurant-agent-v1",
)

# 3. Add knowledge bases
client.agents.knowledge_bases.create(agent.id, {
    "type": "text",
    "name": "Menu",
    "content": (
        "Margherita pizza — £12.00 — vegetarian\n"
        "Pasta arrabbiata — £10.50 — vegan, contains gluten\n"
        "Tiramisu — £6.00 — contains dairy, gluten"
    ),
})

client.agents.knowledge_bases.create(agent.id, {
    "type": "text",
    "name": "Booking policy",
    "content": "Tables available Tuesday to Sunday, 12:00–22:00.\nMaximum party size: 12.",
})

# 4. Verify integrations (connected via dashboard)
integrations = client.agents.integrations.list(agent.id)
print("Agent ID:", agent.id)
print("Integrations:", [i.name for i in integrations])

# 5. Stream messages in a web chat conversation
for event in client.conversations.messages.stream(agent.id, "<conversation_id>"):
    print(event.role, event.message)

Deploy and go live

Go-live checklist

  • Store your API key in BIMPEAI_API_KEY (server-side only).
  • Confirm Google Calendar appears in integrations.list or is connected in the dashboard.
  • Confirm Kitchen/POS system appears in integrations.list or is connected in the dashboard.
  • Verify WhatsApp is connected on the Deploy screen (agents.channels.list shows it enabled).
  • Verify Web Chat is connected on the Deploy screen (agents.channels.list shows it enabled).
  • Set Escalation Email under Settings → Agent if humans must take over.
  • Switch the agent to live with updateLiveStatus / update_live_status.
  • Monitor the Conversations screen (or stream via SDK) after launch.

After go-live

Confirm Google Calendar before accepting bookings. Refresh menu KB when the seasonal menu changes.

Variations

  • Add a daily specials knowledge base entry and update it each morning via a scheduled script.
  • Strengthen upselling by listing pairing suggestions for each main dish in the menu KB.
  • Add a loyalty programme text entry so the agent can explain points accrual and redemption.

Product Recommendation Agent

Deliver personalised product suggestions through web chat or WhatsApp by grounding the agent in your product catalogue knowledge base.

Returns & Refund Processing Agent

Handle return requests, check eligibility against your order management system, track refund status, and schedule replacements.

On this page

What you'll buildCustomer journeyPrerequisitesSteps1. Find or create the workflow2. Create the agent3. Add knowledge bases (optional)4. Connect channels and integrations (dashboard)5. Test your agent6. Go liveFull exampleDeploy and go liveGo-live checklistAfter go-liveVariations