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YODA Chatbot

Yoda Chabot contains the source code for using and displaying Eden AI Yoda Chatbot in your website. The repository contains two branches: main and embed. The former holds the iframe source code, and it's deplyed on github pages. The latter holds the embed code for using the chatbot in your website. We will describe each of the branches content here after.

YODA Chatbot iframe (main branch)

YODA ChatBot

The main branch contains essentially the iframe source code for displaying the ChatBot in the bottom right corner of the user website.

YODA Chatbot embed code (embed branch)

The YODA Chatbot embed branch contains the javascript code minified that allows the create and display an iframe holding the YODA Chatbot in your website for your users.

Usability

To be able to use Eden AI YODA Chatbot you have to:

  • Create an Ask Yoda project.
  • Upload your data either from a file, a text content or from an url.
  • Copy this code into your HTML body:
<script src="https://cdn.jsdelivr.net/gh/edenai/yodabot@0dc64f2/embed.js?project={project_id}&provider={your_llm_provider}&model={your_llm_model}&k={k}"></script>
  • change the project_id with your project uuid available in your Ask Yoda project.
  • You can also optionally provider the llm_provider, the llm_model and also the parameter k?
  • you can also add some optional parameters:
    • title: defined an title than replace the default title
    • message: defined a message who appear first in chat.
    • color: change logo’s color. you can enter “red”,”black”,”blue” ect… and you can add color code ex: “#FF0000”. WARNING !!! color parameter must be a last parameter in the URL.
  • the url should look like this:
  • <script src="https://cdn.jsdelivr.net/gh/edenai/yodabot@0dc64f2/embed.js?project={project_id}&provider=mistral&model=small&k=1&title=my customized bot&message=hello i’m customized bot&color=red"></script>
  • Users accessing your website will now be able to use your trained YODA Chatbot and ask their questions and receive responses depending on data the Chatbot had been training on.

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