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import { ClientOptions, OpenAI } from 'openai';
import { ChatCompletionMessageParam } from 'openai/resources';
enum GPTCallType {
SUMMARY = 'summary',
COMPLETION = 'completion',
EDIT = 'edit',
MERMAID='mermaid'
}
type GPTCallOpts = {
model: string;
maxTokens: number;
temp: number;
prompt: string;
};
const callTypeMap: { [type: string]: GPTCallOpts } = {
summary: { model: 'gpt-3.5-turbo-instruct', maxTokens: 256, temp: 0.5, prompt: 'Summarize this text in simpler terms: ' },
edit: { model: 'gpt-3.5-turbo-instruct', maxTokens: 256, temp: 0.5, prompt: 'Reword this: ' },
completion: { model: 'gpt-3.5-turbo-instruct', maxTokens: 256, temp: 0.5, prompt: '' },
mermaid:{model:'gpt-4-turbo',maxTokens:2048,temp:0,prompt:"Write this in mermaid code and only give me the mermaid code (Heres an example of changing color of a pie chart to help you pie title Example \"Red\": 20 \"Blue\": 50 \"Green\": 30 %%{init: {'theme': 'base', 'themeVariables': {'pie1': '#0000FF', 'pie2': '#00FF00', 'pie3': '#FF0000'}}}%% keep in mind that pie1 is the highest since its sorted in descending order. Heres an example of a mindmap: mindmap root((mindmap)) Origins Long history ::icon(fa fa-book) Popularisation British popular psychology author Tony Buzan Research On effectivness<br/>and features On Automatic creation Uses Creative techniques Strategic planning Argument mapping Tools Pen and paper Mermaid. "}
};
/**`
* Calls the OpenAI API.
*
* @param inputText Text to process
* @returns AI Output
*/
const gptAPICall = async (inputText: string, callType: GPTCallType) => {
if (callType === GPTCallType.SUMMARY) inputText += '.';
const opts: GPTCallOpts = callTypeMap[callType];
try {
const configuration: ClientOptions = {
apiKey: "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",
dangerouslyAllowBrowser: true,
};
const openai = new OpenAI(configuration);
let messages: ChatCompletionMessageParam[] = [
{ role: 'system', content: opts.prompt },
{ role: 'user', content: inputText },
];
const response = await openai.chat.completions.create({
model: opts.model,
messages: messages,
temperature: opts.temp,
max_tokens: opts.maxTokens,
});
const content = response.choices[0].message.content;
return content;
} catch (err) {
console.log(err);
return 'Error connecting with API.';
}
};
const gptImageCall = async (prompt: string, n?: number) => {
try {
const configuration: ClientOptions = {
apiKey: process.env.OPENAI_KEY,
dangerouslyAllowBrowser: true,
};
const openai = new OpenAI(configuration);
const response = await openai.images.generate({
prompt: prompt,
n: n ?? 1,
size: '1024x1024',
});
return response.data.map((data: any) => data.url);
// return response.data.data[0].url;
} catch (err) {
console.error(err);
return;
}
};
export { gptAPICall, gptImageCall, GPTCallType };
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