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    @markprompt/core

`@markprompt/core` is the core library for Markprompt, a conversational AI component for your website, trained on your data.


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increased by7.86%
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Markprompt Core

@markprompt/core is the core library for Markprompt, a conversational AI component for your website, trained on your data.

It contains core functionality for Markprompt and allows you to build abstractions on top of it.


Installation

npm install @markprompt/core

In browsers with esm.sh:

<script type="module">
  import {
    submitChat,
    submitSearchQuery,
    submitFeedback,
  } from 'https://esm.sh/@markprompt/core';
</script>

Usage

import { submitChat } from '@markprompt/core';

for await (const chunk of submitChat(
  [{ content: 'What is Markprompt?', role: 'user' }],
  'YOUR-PROJECT-KEY',
  {
    model: 'gpt-4-turbo-preview',
    systemPrompt: 'You are a helpful AI assistant'
  }
)) {
  console.debug(chunk);
}

API

submitChat(messages: ChatMessage[], projectKey: string, options?)

Submit a prompt to the Markprompt Completions API.

Arguments
  • messages (ChatMessage[]): Chat messages to submit to the model
  • projectKey (string): Project key for the project
  • options (SubmitChatOptions): Optional parameters
Options

All options are optional.

  • conversationId (string): Conversation ID
  • iDontKnowMessage (string): Message returned when the model does not have an answer
  • model (OpenAIModelId): The OpenAI model to use
  • systemPrompt (string): The prompt template
  • temperature (number): The model temperature
  • topP (number): The model top P
  • frequencyPenalty (number): The model frequency penalty
  • presencePenalty (number): The model present penalty
  • maxTokens (number): The max number of tokens to include in the response
  • sectionsMatchCount (number): The number of sections to include in the prompt context
  • sectionsMatchThreshold (number): The similarity threshold between the
  • signal (AbortSignal): AbortController signal
  • tools: (OpenAI.ChatCompletionTool[]): A list of tools the model may call
  • tool_choice: (OpenAI.ChatCompletionToolChoiceOption): Controls which (if any) function is called by the model
Returns

A promise that resolves when the response is fully handled.

submitSearchQuery(query, projectKey, options?)

Submit a search query to the Markprompt Search API.

Arguments
  • query (string): Search query
  • projectKey (string): Project key for the project
  • options (object): Optional parameters
Options
  • limit (number): Maximum amount of results to return
  • signal (AbortSignal): AbortController signal
Returns

A list of search results.

submitFeedback(feedback, projectKey, options?)

Submit feedback to the Markprompt Feedback API about a specific prompt.

Arguments
  • feedback (object): Feedback to submit
  • feedback.feedback (object): Feedback data
  • feedback.feedback.vote ("1" | "-1" | "escalated"): Vote
  • feedback.promptId (string): Prompt ID
  • projectKey (string): Project key for the project
  • options (object): Optional parameters
  • options.onFeedbackSubmitted (function): Callback function when feedback is submitted
  • options.signal (AbortSignal): AbortController signal
Returns

A promise that resolves when the feedback is submitted. Has no return value.

Documentation

The full documentation for the package can be found on the Markprompt docs.

Community

Authors

This library is created by the team behind Markprompt (@markprompt).

License

MIT © Markprompt

FAQs

Last updated on 20 Apr 2024

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