Create a Powerful OpenAI Assistant using Function Calling

Table of Contents

1. Introduction
2. Understanding Assistants
   1. How Assistants work
   2. Example of Assistants in action
3. Setting up OpenAI Assistant
   1. Creating an OpenAI client
   2. Initializing the Assistant
   3. Adding instructions and functions
4. Building the Flight Assistant App
   1. Creating the Flight Assistant
   2. Providing instructions to the Assistant
   3. Adding the get flight details function
   4. Fetching the Assistant using the client
   5. Starting a conversation with the Assistant
   6. Running an example query
   7. Retrieving the run status and outputs
   8. Using the tool outputs to generate a response
   9. Fetching the final message from the Assistant
5. Conclusion

How OpenAI Assistants Work: A Step-by-Step Guide to Building a Flight Assistant App

In this article, we will explore how OpenAI Assistants work and provide a step-by-step guide to building a Flight Assistant app using OpenAI's GPT-3.5 model. Assistants are designed to Interact with users and perform specific tasks by leveraging the power of AI. They can be trained to understand user queries, call functions, fetch data from external sources, and generate responses Based on that data. By following this guide, You will learn how to set up an OpenAI Assistant, define instructions and functions, and Create a conversational app that can fetch live flight data.

Introduction

OpenAI Assistants are AI-powered models that can understand user queries and perform tasks by calling functions and fetching data from external sources. In this article, we will focus on building a Flight Assistant app that can fetch live flight data based on user queries. We will walk you through the process step by step, from setting up the Assistant to retrieving the final response.

Understanding Assistants

How Assistants work

Before diving into the implementation details, it's important to understand how Assistants work. When a user interacts with an Assistant, they ask a question or provide a prompt. The Assistant recognizes that it needs to call a specific function based on the provided prompt and identifies the necessary parameters for that function. In the case of fetching live flight data, the parameter might be the flight number. The Assistant then calls the function, passing the identified parameters as inputs. The function itself can be written using any language and hosted in a cloud service. Once the function is invoked, the response is passed back to the Assistant, which generates a Relevant and informative response for the user.

Example of Assistants in action

To better understand the concept, let's see an example of how Assistants work. Suppose we have built a Flight Assistant app that can fetch live flight details. A user might ask, "When does flight VS3 arrive?" The Assistant, upon receiving this prompt, will identify the necessary parameter (flight number) and call the get flight details function. The function, hosted in the cloud, will fetch the live flight data for flight VS3 and return it to the Assistant. The Assistant will then use this data to generate a response, such as "The flight with number VS3 has already landed, arrived on November 12, 2023, at 11:28 a.m. UTC." This response is based on the actual data fetched from today.

Setting up OpenAI Assistant

Creating an OpenAI client

To get started with OpenAI Assistants, you need to create an OpenAI client. This client allows you to interact with OpenAI's API and perform various actions. In Python, you can create the client by installing the OpenAI Package and initializing it with your API key.

import openai

openai.api_key = "YOUR_API_KEY"

Replace "YOUR_API_KEY" with your actual OpenAI API Key.

Initializing the Assistant

Once you have the OpenAI client set up, the next step is to initialize the Assistant. You can create an Assistant using code or through the OpenAI platform. If you prefer to use the platform, log in to platform.openai.com, click on the Assistants button, and create a new Assistant. You can then retrieve the Assistant ID from the platform.

Adding instructions and functions

After creating the Assistant, you need to provide instructions and define any necessary functions. Instructions help the Assistant understand what actions to take based on specific Prompts. For example, you can instruct the Assistant to use the "get flight details" function when asked about a flight. You can also specify the expected parameters and their types, such as the flight number being a required STRING parameter.

Building the Flight Assistant App

Now that we have set up the OpenAI Assistant, let's proceed with building the Flight Assistant app step by step.

Creating the Flight Assistant

Start by fetching the Assistant using the OpenAI client and the Assistant ID. This allows you to access and interact with the Assistant from your code.

Providing instructions to the Assistant

Once the Assistant is retrieved, you can start a conversation with it by creating a new thread. Provide a prompt or question to the Assistant, like "When is the expected landing time for flight number VS3?" This prompt will be used to call the appropriate function and fetch the live flight data.

Adding the get flight details function

To fetch live flight data, you need to define a function called get flight details. This function takes the flight number as input and returns a string with all the relevant information about the flight. In this case, you might extract the landing date, estimated runtime, and airline name from the live data.

Fetching the Assistant using the client

To interact with the Assistant, you need to fetch it using the client. This ensures that your code is connected to the Assistant and can send and receive messages.

Running an example query

After fetching the Assistant, you can run an example query to see how it performs. Provide a prompt such as "When is the expected landing time for flight VS3?" and observe the response generated by the Assistant.

Retrieving the run status and outputs

To check the status of a run and retrieve its outputs, you can use the OpenAI client's run.retrieve() method. This allows you to monitor the progress of the Assistant and get the required outputs for further processing.

Using the tool outputs to generate a response

Once you have the required outputs from the run, you can use them to generate a response. In the case of the Flight Assistant app, you can extract the flight details from the outputs and construct a Meaningful response for the user.

Fetching the final message from the Assistant

To retrieve the final message from the Assistant, use the OpenAI client's Threads.messages.list() method. This will fetch the latest message in the conversation and provide you with the response generated by the Assistant.

Conclusion

In this article, we have explored how OpenAI Assistants work and learned how to build a Flight Assistant app using OpenAI's GPT-3.5 model. We have covered the steps involved in setting up an Assistant, defining instructions and functions, and creating a conversational app that can fetch live flight data. By following this guide, you can leverage the power of OpenAI Assistants to build your own AI-powered apps for various tasks. Experiment with different prompts, functions, and data sources to create unique and useful applications with Assistants.