initial commit

.gitignore

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+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-extension
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

config/ner.js

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+export const ner = ({text_input = '', description = '', domain = '', labels = '', examples = []}) => {
+
+    if(!text_input) throw new Error('input is required');
+
+    const _domain = `${domain ? `${domain} domain` : ''}`;
+    const _label = `${labels ? `following predefined entity types: ${labels}` : 'entity types'}`;
+    const _example = examples && examples.length > 0 ? `Examples: ${ examples.map(ex => `Input ${ex.sentence} Output [${ex.sentence}]`)  }` : ''
+    return `
+        ${description} 
+        You are a highly intelligent and accurate ${_domain} Named-entity recognition(NER) system. You take Passage as input and your task is to recognize and extract specific types of ${_domain} named entities in that given passage and classify into a set of ${_label}.
+        Your output format is only {{ output_format|default("[{{'T': type of entity from predefined entity types, 'E': entity in the input text}},...,{{'branch' : Appropriate branch of the passage ,'group': Appropriate Group of the passage}}]") }} form, no other form.
+        ${_example}
+        Input: ${text_input}
+        Output:
+    `
+}

examples/example.ts

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+import { ner } from "../config/ner"
+import { OpenAI } from "../models/openai"
+import { Prompter } from "../promptify"
+
+const model = OpenAI('api_key')
+
+const prompt = ner({
+    text_input : '',
+    description : '',
+    domain : '',
+    labels : '',
+    examples : []
+})
+
+const result = Prompter(model, prompt)

models/openai.js

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+export const OpenAI = (key) => {
+    if(!key) throw new Error('Open AI key is required')
+
+    // Logic to validate `apiKey`
+}