How can I add ChatGPT to my web site?

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How can I add ChatGPT to my web site?

ChatGPT is a powerful chatbot platform powered by machine learning and AI. Whether you’re looking to monitor user conversations or automate customer service, ChatGPT can be embedded on your website so that visitors can have real-time interactions with an intelligent chatbot. Integrating ChatGPT is easy and efficient, allowing your website to become interfaced with cutting edge AI technology within minutes. ChatGPT is the perfect way for businesses to drive engagement and collect valuable data from customer conversations in order to advance their product roadmap and streamline services.

 

Different ways you can add ChatGPT to your website

There are a few different ways you can add ChatGPT to your website, depending on your specific requirements and the tools and frameworks you are using. Here are a few options:

1. Use an API: OpenAI has an API that you can use to access ChatGPT. To use the API, you will need to sign up for an API key and then use it to make API calls from your website. You’ll need to write some code to send and receive the API calls, but you can find many examples and libraries in different languages that can help.
2. Use a pre-built library or SDK: Some developers have created libraries or software development kits (SDKs) that make it easier to use ChatGPT in your website. For example, Hugging Face provides a JavaScript library that you can use to integrate ChatGPT with your website.
3. Embed a pre-built chatbot: There are a few pre-built chatbots available that are built using ChatGPT and that you can embed in your website. For example, Botfront.io allows you to create a chatbot using the GPT-3 language model.

Requirements

Please note, to use ChatGPT or GPT-3 model, the OpenAI’s API requires a commercial or research agreement to be in place. As well some of the services may require paid subscription, so it’s recommended to check the pricing and terms of use in advance.

It’s also important to note that building a chatbot with GPT-3 or other language models can require some level of skill, mainly related to data science and natural language processing. If you have little or no experience with it, it may be better to seek professional help.

Integration

ChatGPT makes it easy to integrate artificial intelligence (AI) into your web site with just a few clicks. It employs machine learning technology to allow users to easily embed a natural language processing (NLP) chatbot into their website. ChatGPT learns from conversations, providing customers with an engaging and useful experience when visiting your site. ChatGPT will make your website stand out and provide visitors with an enjoyable experience that they won’t soon forget.

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How can I add ChatGPT to my web site?: Here are 10 use cases of ChatGPT based Apps

1. Connect your ChatGPT with your Whatsapp.
Link: http://bit.ly/3ZfmyzC

2. ChatGPT Writer : It use ChatGPT to generate emails or replies based on your prompt!
Link: http://bit.ly/3vGB3if

3. WebChatGPT: WebChatGPT ( http://bit.ly/3CsA210) gives you relevant results from the web!

4. YouTube Summary with ChatGPT: It generate text summaries of any YouTube video!
Link: http://bit.ly/3QhismB

5. TweetGPT: It uses ChatGPT to write your tweets, reply, comment, etc.
Link: http://bit.ly/3k0vOY4

6. Search GPT: It display the ChatGPT response alongside Google Search results
Link: http://bit.ly/3X8GySx

7. ChatGPT or all search engines: You can now view ChatGPT responses on Google and Bing!
Link: http://bit.ly/3QlH2Tl

8. Save all your Prompts?: The `ChatGPT History` extension has you covered!
Link: http://bit.ly/3ijtDP8

9. Remake a video: Just pick a video you liked and visit https://lnkd.in/e_GD2reT to get its transcript. Once done, bring that back to Chat GPT and tell it to summarize the transcript. Read the summary and make a video on that yourself.

10. Search what people are Prompting with FlowGPT
Link: https://flowgpt.com

#searchengines #people #building #google #comment #video #writer

Create code to call to the OpenAI API using a natural language instruction.

With Python

import os
import openai

openai.api_key = os.getenv(“OPENAI_API_KEY”)

response = openai.Completion.create(
model=”code-davinci-002″,
prompt=”\”\”\”\nUtil exposes the following:\nutil.openai() -> authenticates & returns the openai module, which has the following functions:\nopenai.Completion.create(\n prompt=\”<my prompt>\”, # The prompt to start completing from\n max_tokens=123, # The max number of tokens to generate\n temperature=1.0 # A measure of randomness\n echo=True, # Whether to return the prompt in addition to the generated completion\n)\n\”\”\”\nimport util\n\”\”\”\nCreate an OpenAI completion starting from the prompt \”Once upon an AI\”, no more than 5 tokens. Does not include the prompt.\n\”\”\”\n”,
temperature=0,
max_tokens=64,
top_p=1.0,
frequency_penalty=0.0,
presence_penalty=0.0,
stop=[“\”\”\””]
)

With NodeJS

const { Configuration, OpenAIApi } = require(“openai”);

const configuration = new Configuration({
apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);

const response = await openai.createCompletion({
model: “code-davinci-002”,
prompt: “\”\”\”\nUtil exposes the following:\nutil.openai() -> authenticates & returns the openai module, which has the following functions:\nopenai.Completion.create(\n prompt=\”<my prompt>\”, # The prompt to start completing from\n max_tokens=123, # The max number of tokens to generate\n temperature=1.0 # A measure of randomness\n echo=True, # Whether to return the prompt in addition to the generated completion\n)\n\”\”\”\nimport util\n\”\”\”\nCreate an OpenAI completion starting from the prompt \”Once upon an AI\”, no more than 5 tokens. Does not include the prompt.\n\”\”\”\n”,
temperature: 0,
max_tokens: 64,
top_p: 1.0,
frequency_penalty: 0.0,
presence_penalty: 0.0,
stop: [“\”\”\””],
});

With curl:

curl https://api.openai.com/v1/completions \
-H “Content-Type: application/json” \
-H “Authorization: Bearer $OPENAI_API_KEY” \
-d ‘{
“model”: “code-davinci-002”,
“prompt”: “\”\”\”\nUtil exposes the following:\nutil.openai() -> authenticates & returns the openai module, which has the following functions:\nopenai.Completion.create(\n prompt=\”<my prompt>\”, # The prompt to start completing from\n max_tokens=123, # The max number of tokens to generate\n temperature=1.0 # A measure of randomness\n echo=True, # Whether to return the prompt in addition to the generated completion\n)\n\”\”\”\nimport util\n\”\”\”\nCreate an OpenAI completion starting from the prompt \”Once upon an AI\”, no more than 5 tokens. Does not include the prompt.\n\”\”\”\n”,
“temperature”: 0,
“max_tokens”: 64,
“top_p”: 1.0,
“frequency_penalty”: 0.0,
“presence_penalty”: 0.0,
“stop”: [“\”\”\””]
}’

With Json:

{
“model”: “code-davinci-002”,
“prompt”: “\”\”\”\nUtil exposes the following:\nutil.openai() -> authenticates & returns the openai module, which has the following functions:\nopenai.Completion.create(\n prompt=\”<my prompt>\”, # The prompt to start completing from\n max_tokens=123, # The max number of tokens to generate\n temperature=1.0 # A measure of randomness\n echo=True, # Whether to return the prompt in addition to the generated completion\n)\n\”\”\”\nimport util\n\”\”\”\nCreate an OpenAI completion starting from the prompt \”Once upon an AI\”, no more than 5 tokens. Does not include the prompt.\n\”\”\”\n”,
“temperature”: 0,
“max_tokens”: 64,
“top_p”: 1.0,
“frequency_penalty”: 0.0,
“presence_penalty”: 0.0,
“stop”: [“\”\”\””]
}

https://pub.towardsai.net/build-chatgpt-like-chatbots-with-customized-knowledge-for-your-websites-using-simple-programming-f393206c6626

https://www.codeproject.com/Articles/5350454/Chat-GPT-in-JavaScript

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Is ChatGPT API free?

 

Cost: While ChatGPT is open source and free to the public, ChatGPT-professional requires payment.

 

 

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ChatGPT vs BARD 

 

Trying to compare two chatbots that are entering into search engine business
#chatgpt #chatgpt3 #chatgptplus #bard #google #ai #future #searchengine #chatbots #chatbot #business

 

What do you think about ChatGPT vs Google?

By Jérôme Cukier, Staff Software Engineer at Google (2020-present)

 

When Google took off, its key characteristic was that it was very very fast compared to its competition. The quality of the results was also impressive, and, as could be expected, it was very reliable and highly available.

That in itself didn’t make it a better product than Yahoo, which for years dominated the search engine market and which was the de facto home page to the internet, even after Google became a household name. However, this was enough to start the narrative that there was something special about Google that others just couldn’t do quite as well.

ChatGPT is not fast, is often wrong, and as a service is very unreliable. It’s down approximately 50% of the times I’m trying to use it. The technology behind it is not rocket science, that said they have a few things going for them. First, they trained a very large language model (LLM). The cost of this operation in terms of machine is massive. Google search can crawl the web and update their index all the time but the resources needed to train a LLM as big as GPT-3 are phenomenal. Second, they have a product. Microsoft, Meta, Google all could have released something similar and sooner, but didn’t. As a result, OpenAI just like Google ~23 years before it has a narrative going for them.

People’s perception of Google search

People’s perception of Google search is that it’s a service that will return 10 blue links to a query which is a list of keywords, that’s a bit unfair because for years this is neither what search results or search queries are, but then again Google has not been able to correct that impression. On the other hand, journalists know that there is a demand for stories that present ChatGPT as an all-powerful oracle that can do many things and whose output cannot be distinguished from actual people and these stories have kept coming – again, just like stories about Google in the early 2000s then about Facebook in the mid aughts.

ChatGPT is still not able to do what Google does.

The most common queries are about the weather, opening hours of businesses, shopping and lottery results. Those things however trite are completely out of bound for ChatGPT which doesn’t have a live connection with the real world. But then there are many things that a LLM-backed chatbot can do (or even better, that specific products supported by LLMs can do) which Google or other big tech companies just don’t offer.

ChatGPT is just one of many services that are threatening the role of Google not just as a search engine but as a central platform. It’s also very preliminary, after GPT3 will come GPT4, after ChatGPT will come waves of products with GPT APIs. So the landscape is going to change significantly over the next couple of years.

GPT-1 vs GPT2 vs GPT-3 vs GPT-4

GPT-1, GPT-2 and GPT-3 can handle text inputs with sizes varying from 117M to 175B parameters.

GPT-4 is multi-modal i.e., it can handle both image and text inputs. The size of GPT-4 model is not revealed by OpenAI.
Kalyan Kalyanks

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Chatting with ChatGPT is fun and informative — I’ve been chit-chatting with it for past time and exploring some new ideas to learn. But these are more casual use cases and the novelty can quickly wean off, especially when you realize that it can generate hallucinations.

WOW GPT-4 is here. It blows ChatGPT out of the water.

GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks.

GPT-4’s improvements are evident in the system’s performance on a number of tests and benchmarks, including the Uniform Bar Exam, LSAT, SAT Math, and SAT Evidence-Based Reading & Writing exams. In the exams mentioned, GPT-4 scored in the 88th percentile and above, and a full list of exams and the system’s scores can be seen GPT-4

Image is a multimodal chatbot like ChatGPT4.

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#artificialintelligence #chatgpt4 #chatgpt #innovation

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