How to use chatGPT APIs for conversational AI

Conversational AI is the technology that enables machines to understand and communicate with humans using natural language. It can power applications such as chatbots, voice assistants, smart speakers, and more. Conversational AI can provide various benefits for businesses and users, such as improving customer service, increasing engagement, enhancing productivity, and generating insights.

However, building conversational AI applications can be challenging and time-consuming. It requires a lot of data, skills, and resources to create natural and coherent dialogues that can handle different scenarios and user intents. Moreover, it can be difficult to maintain and update conversational AI applications as user expectations and business needs evolve.

That's where chatGPT APIs come in. ChatGPT APIs are a set of APIs that allow developers to easily integrate chatGPT and GPT-4 models into their apps and products. ChatGPT and GPT-4 are language models that are optimized for conversational interfaces. They can generate natural and engaging responses based on user input, context, and preferences.

In this article, we will explain what chatGPT APIs are, how they work, what benefits they offer, how to use them, and how much they cost.

What are chatGPT APIs?

ChatGPT APIs are a new dedicated API for interacting with the chatGPT and GPT-4 models. Both sets of models are currently in preview. This API is the preferred method for accessing these models. It is also the only way to access the new GPT-4 models.

ChatGPT APIs are designed to be used in a loop, where you send a message from the user to the model, receive a response from the model, and repeat until the conversation ends. The API expects an array of messages as input, where each message is a dictionary that contains a "role" and some "content". The role can be either "user" or "assistant", depending on who is speaking. The content is the text of the message.

The API returns a response that contains a "choice" array with one element. The element is a dictionary that contains a "message" dictionary with two keys: "role" and "content". The role is always "assistant", and the content is the text of the response generated by the model.

Here is an example of how to use the chatGPT completion API in Python:

import os
import openai

openai.api_type = "azure"
openai.api_version = "2023-03-15-preview"
openai.api_base = os.getenv("OPENAI_API_BASE") # Your Azure OpenAI resource's endpoint value.
openai.api_key = os.getenv("OPENAI_API_KEY")
messages = [] # Initialize an empty array of messages

while True:
# Get user input
user_input = input("User: ")
# Add user message to messages array
messages.append({"role": "user", "content": user_input})
# Call chatGPT completion API with messages array
response = openai.ChatCompletion.create(
engine="gpt-35-turbo", # The deployment name you chose when you deployed the ChatGPT or GPT-4 model.
messages=messages
)
# Get assistant message from response
assistant_message = response["choices"][0]["message"]["content"]
# Print assistant message
print("Assistant:", assistant_message)
# Add assistant message to messages array
messages.append({"role": "assistant", "content": assistant_message})

This code will create a simple conversation loop where you can type anything as the user and get a response from the assistant.

How do chatGPT APIs work?

ChatGPT APIs work by leveraging the power of chatGPT and GPT-4 models. These models are based on GPT-4, which is a large language model that can generate text based on any input. GPT-4 uses deep neural networks to learn from billions of words from various sources on the internet. It can predict what words are likely to come next in a sequence based on probability.

However, chatGPT and GPT-4 models are not just text-in and text-out models. They are conversation-in and message-out models. They are optimized for conversational interfaces by using additional techniques such as:

•  Dialogue state tracking: This technique allows the model to keep track of the context and history of the conversation, such as user goals, preferences

•  Response generation: This technique allows the model to generate natural and engaging responses based on user input, context, and preferences. The model can also use different styles, tones, and emotions to suit different situations and personalities.

•  Response selection: This technique allows the model to choose the best response among multiple candidates generated by the model. The model can use various criteria to rank and filter the responses, such as relevance, coherence, diversity, and politeness.

By using these techniques, chatGPT and GPT-4 models can create more human-like and personalized conversations with users.

What are the benefits of chatGPT APIs?

ChatGPT APIs offer several benefits for developers and users, such as:

•  Ease of use: ChatGPT APIs are easy to use and integrate with any app or product. You don't need to write any complex code or logic to handle different scenarios and user intents. You just need to send and receive messages in a simple format.

•  Cross-platform compatibility: ChatGPT APIs can work across multiple platforms and devices, such as mobile, web, desktop, and smart speakers. You don't need to write separate code for each platform or device. You can use the same codebase for all of them.

•  Cost-effectiveness: ChatGPT APIs are cost-effective and scalable. You don't need to pay for expensive servers or infrastructure to run your conversational AI applications. You only pay for what you use based on the number of tokens processed by the API. You can also scale up or down your usage depending on your demand.

•  Model improvement: ChatGPT APIs are constantly improving and updating with new features and capabilities. You don't need to worry about maintaining or updating your conversational AI applications. You can always access the latest and best version of the models through the API.

How to use chatGPT APIs?

To use chatGPT APIs, you need to follow these steps:

•  Sign up for a free account on OpenAI's website.

•  Apply for access to chatGPT and GPT-4 models by filling out this form.

•  Create an Azure OpenAI resource endpoint and an API key on your Azure portal.

•  Choose a deployment name for your chatGPT or GPT-4 model.

•  Install the openai package in your Python environment with pip install openai.

•  Use the chatGPT completion API in your Python code as shown in the example above.

How much do chatGPT APIs cost?

ChatGPT APIs are priced based on the number of tokens processed by the API. A token is a unit of text that is roughly equivalent to a word or a punctuation mark. The price per token depends on the model you choose and the plan you subscribe to.

The base plan is free and gives you 10K tokens per month. The plus plan costs $20 per month and gives you 100K tokens per month with priority access. The pro plan costs $100 per month and gives you 1M tokens per month with dedicated capacity.

The price per token for each model is as follows:

| Model | Base | Plus | Pro |

|-------|------|------|-----|

| gpt-35-turbo | $0.0004 | $0.0003 | $0.0002 |

| gpt-4 | $0.0008 | $0.0006 | $0.0004 |

| gpt-4-32k | $0.0016 | $0.0012 | $0.0008 |

You can also use the pricing calculator on OpenAI's website to estimate your monthly cost based on your usage.

Conclusion

ChatGPT APIs are a powerful and easy way to create conversational AI applications using chatGPT and GPT-4 models. They can help you build natural and engaging dialogues with your users across multiple platforms and devices. They can also help you save time and money on development and maintenance.

If you are interested in using chatGPT APIs for your app or product, you can sign up for a free account on OpenAI's website and apply for access to chatGPT and GPT-4 models. You can also check out some of the examples and tutorials on how to use chatGPT APIs effectively.

We hope this article has given you a comprehensive overview of chatGPT APIs and how they work. If you have any questions or feedback, please feel free to contact us.