style(OptionHover.jsx): add descriptions for new types

feat(AgentSettings.jsx): change OptionHover type from 'temp' to 'func' and from 'temp' to 'skip'

Author: danny-avila

client/src/components/Endpoints/Plugins/AgentSettings.jsx

@@ -74,7 +74,7 @@ function Settings(props) {
                 </label>
                 <Switch id="functions-agent" checked={agent === 'functions'} onCheckedChange={onCheckedChangeAgent} disabled={readonly} className="mt-2 ml-4"/>
               </HoverCardTrigger>
-              <OptionHover type="temp" side="right" />
+              <OptionHover type="func" side="right" />
             </HoverCard>
             <HoverCard openDelay={500}>
               <HoverCardTrigger className='w-1/2 ml-[-60px]'>
@@ -86,7 +86,7 @@ function Settings(props) {
                 </label>
                 <Switch id="skip-completion" checked={skipCompletion === true} onCheckedChange={onCheckedChangeSkip} disabled={readonly} className="mt-2 ml-4"/>
               </HoverCardTrigger>
-              <OptionHover type="temp" side="right" />
+              <OptionHover type="skip" side="right" />
             </HoverCard>
           </div>
         </div>

client/src/components/Endpoints/Plugins/OptionHover.jsx

@@ -2,6 +2,8 @@ import { HoverCardPortal, HoverCardContent } from '~/components';
 
 const types = {
   temp: 'Higher values = more random, while lower values = more focused and deterministic. We recommend altering this or Top P but not both.',
+  func: 'Enable use of Plugins as OpenAI Functions',
+  skip: 'Enable skipping the completion step, which reviews the final answer and generated steps',
   max: "The max tokens to generate. The total length of input tokens and generated tokens is limited by the model's context length.",
   topp: 'An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We recommend altering this or temperature but not both.',
   freq: "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.",