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🥖 A practical use case of custom LLM Agents: Hands-free POS 🚀

🧀 The Inspiration

I am a fan of the tasty Käsedings at Zeit für Brot and I've spent quite a bit of time hanging out at their busy Eberswalder spot. It's where my interest in the tasty breads collides with the reality of waiting in line.

I noticed and hypothesized that, to maintain hygiene, cashiers don't directly handle the food. There would be one cashier and one other staff working in a pair to deal with customers. The cashiers only manage orders and payments, leaving food handling to their peers.

➡️ This observation sparked an idea: What if we could make the ordering and payment process more efficient, enhancing customer satisfaction, streamlining staff workflow, and ultimately boosting Zeit für Brot's revenue (sorry for the buzzwords)?

💡 The Solution: The Integration of an LLM-agent

This solution proposes integrating a custom LLM agent into the Point of Sale (POS) system. The agent will translate the staff's orders into API requests, registering items in the POS system without manual entry.

Bakery Illustration Image by the Author


Workflow Simplified:

LLM Agent Architecture Image by the Author

👩‍💼 Staff-Customer Interaction: A staff member receives an order from a customer. He communicates with the LLM agent through his headset. The staff member can engage in conversation with the customer without needing to deactivate the headset, allowing for a seamless interaction. The LLM agent listens to the entire conversation, filtering out irrelevant chatter and focusing on the important details. This is facilitated by the use of specific “agent” and “please” cues (signposting), which enables the LLM agent to distinguish between casual conversation and a direct request for assistance.

Example:

- Customer A: Do you want to get an espresso and two cinnamon rolls?
- Customer B: I don’t know.
- Customer A: OK, I’ll decide then. I’ll get a baguette, a cappuccino, and two cheesecakes.
- Staff: Agent, add a baguette, a cappuccino, and two cheesecakes, please.
- Customer A: Sorry I changed my mind, I won’t get the baguette.
- Staff: Agent, remove the baguette, please.
- Staff: Agent, proceed to payment by card, please.

Example 2 Image by the Author

The API log shows the agent's actions in response to the staff's speech.

API log Image by the Author

  • The agent processes this speech, generating an API request to register the order.

  • In case of correction: If there's a change in the order, the staff can proceed with: "Agent, remove one cinnamon roll." The agent will adjust the order accordingly.

  • Upon finalizing the order, "Agent, proceed to payment with QR codes / cards please" prompts the agent to initiate the payment process, creating a smooth end-to-end transaction.

🚀 Give it a try

  • You can try the PoC Demo here.

  • Watch the demo here:

Custom LLM agent

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