Open AI is an AI tool just like Dialogflow which enables the users to interact using AI. From replying to users to generating images, you can use OpenAI for a variety of tasks.
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Integrating OpenAI's ChatGPT with UChat can provides numerous benefits to businesses looking to engage with their customers across various channels.
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1. Visit https://platform.openai.com
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2. Login using your credentials.
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Your account has successfully been connected with UChat.
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OpenAI Native Actions
UChat gives a lot of actions with OpenAI which users can use for their needs.
We will now discuss them in detail one by one.
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Create Text Completion
Text completion offers the functionality of sending prompts to OpenAI in textual form and based on the prompt receiving an answer.
Input:
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Input:
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Prompt: This is your main input for which you want the AI to give you an answer or output of. This can be a question, an instruction, etc.
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Best of Completions: This returns the best possible response(s) for your prompt. It defaults to 1. This works with the Number of Completion field to choose the best possible answer from a group of responses.
Response:
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Map the response to custom field
You can select the text under the choices, and then you can see the JSON Path selected, and then you can save the response into your own user custom field, and then use this response in your flow builder.
Sample Response Data
| Code Block |
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{
"id": "cmpl-6zchlUy0OiAjX91LHOPBcZjuXaDgE",
"object": "text_completion",
"created": 1680144809,
"model": "text-davinci-003",
"choices": [
{
"text": " 1. Understand Your Target Audience - Before you begin any marketing campaign, it’s important to have a clear understanding of who you’re targeting with your message. Researching and understanding your target audience will help you create campaigns specifically tailored to their interests. 2. Leverage Social Media - Social media has become one of the most effective ways to communicate with your target audience. Utilizing social media channels such as Facebook, Twitter, and Instagram can help you build",
"index": 0,
"logprobs": null,
"finish_reason": "length"
}
],
"usage": {
"prompt_tokens": 4,
"completion_tokens": 100,
"total_tokens": 104
}
} |
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Prompt tokens : The number of tokens used to complete the task.
Best Practices:
Sometimes the completed response you get back seems to be cut off. This is due to the lack of the number of tokens required for the completion of the task. Simply adjusting the value of Max tokens inside the input fields will fix this issue.
It is also advised to adjust values like temperature, the number of completions, best of completions, etc to your use case by means of split testing. Every use case is unique and you should want the best possible utilisation of the resources available.
Image Generation
Image Generation is used to generate images based on the user-input prompts. This feature will generate the best possible image that matches your given prompt.
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Input:
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Prompt : This is your main input for which you want the AI to generate an image for you. This can be a question, an instruction etc.
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256x256
1024x1024
Response:
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Sample Response Data
| Code Block |
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{
"created": 1680145479,
"data": [
{
"url": "https://oaidalleapiprodscus.blob.core.windows.net/private/org-2FEbJIRL7GXfKmGw2BT9wh9b/user-nk6UUN7L9nFqzGEw67uTMonD/img-FhZpxMrCbiDBR4O62e7pPF08.png?st=2023-03-30T02%3A04%3A39Z&se=2023-03-30T04%3A04%3A39Z&sp=r&sv=2021-08-06&sr=b&rscd=inline&rsct=image/png&skoid=6aaadede-4fb3-4698-a8f6-684d7786b067&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2023-03-29T17%3A40%3A49Z&ske=2023-03-30T17%3A40%3A49Z&sks=b&skv=2021-08-06&sig=4DF0dw/peG7FSVMUml4ShuQP98T0xECW1gE%2BeutdRAw%3D"
}
]
} |
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Url : The public URL for your image(s).
Best Practices:
Generating Images consume more computational power and hence the replies can be a delayed based on the prompts you give.
AI is a developing field and hence the images produced can be quite inaccurate given the complexity of the prompts provided. Hence finding the correct prompt complexity can sometimes be a challenge.
Speech to Text
Speech-to-text action is used when you want to convert audio input into text. This has variety of use cases such as implementation in IVRs.
Input:
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File Url : This is the URL for the audio that you want to convert to text. Make sure that the url is a public hosted url ending with audio formats such as mp3. mpeg etc
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Language : The language you want the speech to be converted into. We use ISO-639-1 format which means you need to put languages as ‘en’, ‘es’ etc.
Response:
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Sample Response Data
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{
"text": "Welcome to Rensen. This is a test to see if everything works well. And if the IVR can guide you to your work."
} |
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Text : The text which is converted from the speech.
Best Practices:
You can convert speech to text quite accurately using this feature. It is considered a best practice to provide the audio in the same language as that of the desired output for more accurate results and latency.
Translate Audio to English
Translate audio to English action is used when you want to convert audio input into text in english language. This has a variety of use cases such as implementation in IVRs.
Input:
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File Url : This is the URL for the audio that you want to convert to text. Make sure that the url is a public hosted url ending with audio formats such as mp3. mpeg etc
| Note |
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Please note the url need to start with https:// and end with mp3, or mp4, mpeg, mpga, m4a,wav, webm |
Response:
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Sample Response Data
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{
"text": "Welcome to Rensen. This is a test to see if everything works well. And if the IVR can guide you to your work."
} |
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Text: The text which is converted from the speech.
Best Practices:
Experimenting with different formats of audio can provide more (or less) accurate results. This is simply due to the quality of the audio provided so make sure you split test with different formats to achieve the best possible format for your use case.
Create Chat Completion - ChatGPT
Chat completion offers a functionality of sending prompts to OpenAI in textual form and based on the prompt receive an answer. This is similar to text completion action but it uses ChatGPT which is 10x faster and cheaper as well.
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Input:
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System Message : This is an optional field and is used to provide additional context about you or your business when completing chats.
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Best of Completions : This returns the best possible response(s) for your prompt. It is default to 1. This works with Number of Completion field to choose the best possible answer from a group of responses.
Response:
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Sample Response Data
| Code Block |
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{
"id": "chatcmpl-6zef5zEUdDzTx8VKu2r4gkIJfVcBE",
"object": "chat.completion",
"created": 1680152331,
"model": "gpt-3.5-turbo-0301",
"usage": {
"prompt_tokens": 18,
"completion_tokens": 100,
"total_tokens": 118
},
"choices": [
{
"message": {...}, // 2 keys
"finish_reason": "length",
"index": 0
}
],
"messages": [
{
"role": "user",
"content": "can you help me with planting a mango tree?"
},
{
"role": "assistant",
"content": "Of course! Here are some steps to plant a mango tree: 1. Choose a spot: Mango trees need plenty of sunlight and well-draining soil. They also need protection from strong winds, so choose a spot that's sheltered. 2. Prepare the soil: Mango trees prefer slightly acidic soil, with a pH between 5.5 and 7. If your soil is too alkaline, add sulfur or peat moss to lower the pH. If it's too acidic, add lime"
}
]
} |
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Message: This is a JSON for complete conversation that has happened between the user and the assistant.
Best Practices:
Chat completion action enables you to provide JSON input as well hence you can save the complete conversation between the users and the assistant in a JSON to give more focused and contextual replies related to that conversation.
| Note |
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Since chat completion takes more input, the token consumption can be higher that text completion. |
Clear Remembered Chat History
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User cases: ChatGPT
How to fine tune ChatGPT for your business
If you use openAI embedding along with ChatGPT, you can train the chatGPT to answer your business related questions with complete ease!
Check the video below to learn how to implement this in your own business.
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Generate the chatbot flow using A.I
Have you ever imagined that with a simple instruction like “create a flow to order pizza” and then UChat can generate the whole flow automatically for you.
Everything is done with ChatGPT & UChat.
Check the video below to explore this feature to get you started easily with UChat.
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Power up your live chat with the AI assistant
Have you ever think that you can use smart A.I assistant to using openAI embedding to generate the suggestion replies automatically?
This will increase your customer support efficiency and lower your customer support cost.
Check the video to learn how to set this up.
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OpenAI Training Reply to Facebook and Instagram post comments
Have you ever think to use openAI to reply to your Facebook, Instagram post comments automatically, and most importantly the reply will be highly relevant and accurate to your own business.
The reason is that we are using openAI embedding to get the highly relevant answers from your own business database, and this can be done automatically, learn how to set up from the video below:
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Clear Remembered Chat History
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Clear remembered history is used to delete or clear the system field where the chat history for chatGPT is stored.
This action will help you to reset the chat history.
| Note |
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The system field has a max character limit of 20000 characters after which it deletes the oldest key-pair value from the JSON in order to make room for newer values |
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OpenAI gives you the ability to provide a knowledge base of your use case or business for the AI to generate responses from. This enables the AI to give more accurate, contextual as well as particular answers instead of filtering them from the internet.
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Create An Embedding:
To create an embedding, go into the Integrations and select OpenAI
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Now import the CSV file containing the embeddings and your embeddings will be created.be created. If you have special characters like : è à ì ù, please select to “Import from csv without preview”
| Note |
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Make sure that the first rows of all columns should be the input fields name such as type, heading, text etc. and none of them should start with a capital letter. |
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Introduction : This is used to provide more context to the prompt making the prompt more accurate and helps in raising the embedding match score.
Response:
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Sample Response Data
| Code Block |
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{
"status": "ok",
"result": {
"heading": "Free trial",
"text": "UChat offer 14 days free trial. No credit card required, you can access to all the pro features. You can sign up here: https://www.uchat.com.au/register",
"score": 0.903164959234692,
"input": "Free trial for uchat",
"completion": " Yes, UChat offers a 14-day free trial. No credit card is required and you can access all the pro features. You can sign up here: https://www.uchat.com.au/register."
}
} |
Embedding : The heading of the embedding the prompt is best matched to.
Text : The text of the embedding the prompt is best matched to.
Text : The text of the embedding the prompt is best matched to.
Input : The prompt that you input for embedding search.
Score : This is the % of the match between prompt and the embeddings available. You can use this score determine whether the following prompt should be used for completion or is not sufficient and will give inaccurate answers. It is observed that a score of 0.79 and above gives the best possible embedding match. However this is an empirical value and you used split test for your use case in order to obtain best possible answers.
Completion : This is the output or the completion of the prompt the user input.prompt is best matched to.
Input : The prompt that you input for embedding search.
Score : This is the % of the match between prompt and the embeddings available. You can use this score determine whether the following prompt should be used for completion or is not sufficient and will give inaccurate answers. It is observed that a score of 0.79 and above gives the best possible embedding match. However this is an empirical value and you used split test for your use case in order to obtain best possible answers.
Completion : This is the output or the completion of the prompt the user input.
Using openAI embedding to reply your Facebook & Instagram comments
If you are running ads or have viral post on your Facebook page or Instagram. You may not have the time to attend those comments.
You don’t want to always reply some generic replies, and also you want to the reply is highly relevant to your business questions.
That’s why you need to use openAI embedding to provide highly relevant replies automated.
Check the video below to learn how to do it with UChat:
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Video tutorial for openAI integration & ChatGPT integration
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OpenAI -Using embedding to build your business knowledgebase
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OpenAI Training Reply to Facebook and Instagram post comments
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ChatGPT integration mini course
OpenAI & ChatGPT integration with UChat
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ChatGPT is Live!!!
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How to fine tune ChatGPT for your business
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Create chatbot flows with ChatGPT!
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Power up your live chat with the AI assistant
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ChatGPT updates System message and saving chat history
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https://www.youtube.com/watch?v=3e1jskSitQQ&list=PLYV-IhQ_GwTMnMzNG9gzVVPl1T-HfHfoY&pp=gAQB