@markprompt/core - npm Package Compare versions

Comparing version 0.4.6 to 0.5.0

dist/index.d.ts

@@ -1,52 +0,4 @@
-import type { OpenAIModelId } from './types.js';
-export type { OpenAIModelId };
-export type Options = {
-    /** URL at which to fetch completions */
-    completionsUrl?: string;
-    /** Message returned when the model does not have an answer */
-    iDontKnowMessage?: string;
-    /** The OpenAI model to use */
-    model?: OpenAIModelId;
-    /** The prompt template */
-    promptTemplate?: string;
-    /** The model temperature */
-    temperature?: number;
-    /** The model top P */
-    topP?: number;
-    /** The model frequency penalty */
-    frequencyPenalty?: number;
-    /** The model present penalty */
-    presencePenalty?: number;
-    /** The max number of tokens to include in the response */
-    maxTokens?: number;
-    /** 	The number of sections to include in the prompt context */
-    sectionsMatchCount?: number;
-    /** The similarity threshold between the input question and selected sections */
-    sectionsMatchThreshold?: number;
-    /** AbortController signal */
-    signal?: AbortSignal;
-};
-export declare const MARKPROMPT_COMPLETIONS_URL = "https://api.markprompt.com/v1/completions";
-export declare const STREAM_SEPARATOR = "___START_RESPONSE_STREAM___";
-export declare const DEFAULT_MODEL: OpenAIModelId;
-export declare const DEFAULT_I_DONT_KNOW_MESSAGE = "Sorry, I am not sure how to answer that.";
-export declare const DEFAULT_REFERENCES_HEADING = "Answer generated from the following pages:";
-export declare const DEFAULT_LOADING_HEADING = "Fetching relevant pages...";
-export declare const DEFAULT_PROMPT_TEMPLATE = "You are a very enthusiastic company representative who loves to help people! Given the following sections from the documentation (preceded by a section id), answer the question using only that information, outputted in Markdown format. If you are unsure and the answer is not explicitly written in the documentation, say \"{{I_DONT_KNOW}}\".\n\nContext sections:\n---\n{{CONTEXT}}\n\nQuestion: \"{{PROMPT}}\"\n\nAnswer (including related code snippets if available):";
-export declare const DEFAULT_TEMPERATURE = 0.1;
-export declare const DEFAULT_TOP_P = 1;
-export declare const DEFAULT_FREQUENCY_PENALTY = 0;
-export declare const DEFAULT_PRESENCE_PENALTY = 0;
-export declare const DEFAULT_MAX_TOKENS = 500;
-export declare const DEFAULT_SECTIONS_MATCH_COUNT = 10;
-export declare const DEFAULT_SECTIONS_MATCH_THRESHOLD = 0.5;
-/**
- * @param {string} prompt - Prompt to submit to the model
- * @param {string} projectKey - The key of your project
- * @param {(answerChunk: string) => void} onAnswerChunk - Answers come in via streaming. This function is called when a new chunk arrives
- * @param {(references: string[]) => void} onReferences - This function is called when a chunk includes references.
- * @param {(error: Error) => void} onError - called when an error occurs
- * @param {Options} [options] - Optional options object
- */
-export declare function submitPrompt(prompt: string, projectKey: string, onAnswerChunk: (answerChunk: string) => boolean | undefined | void, onReferences: (references: string[]) => void, onError: (error: Error) => void, options?: Options): Promise<void>;
+export { submitPrompt, type SubmitPromptOptions, MARKPROMPT_COMPLETIONS_URL, STREAM_SEPARATOR, DEFAULT_MODEL, DEFAULT_I_DONT_KNOW_MESSAGE, DEFAULT_REFERENCES_HEADING, DEFAULT_LOADING_HEADING, DEFAULT_PROMPT_TEMPLATE, DEFAULT_TEMPERATURE, DEFAULT_TOP_P, DEFAULT_FREQUENCY_PENALTY, DEFAULT_PRESENCE_PENALTY, DEFAULT_MAX_TOKENS, DEFAULT_SECTIONS_MATCH_COUNT, DEFAULT_SECTIONS_MATCH_THRESHOLD, } from './prompt.js';
+export { submitSearchQuery, type SubmitSearchQueryOptions } from './search.js';
+export { type OpenAIModelId, type SearchResult, type SearchResultSection, type SearchResultsResponse, } from './types.js';
 //# sourceMappingURL=index.d.ts.map

dist/index.js

@@ -1,105 +0,4 @@
-export const MARKPROMPT_COMPLETIONS_URL = 'https://api.markprompt.com/v1/completions';
-export const STREAM_SEPARATOR = '___START_RESPONSE_STREAM___';
-export const DEFAULT_MODEL = 'gpt-3.5-turbo';
-export const DEFAULT_I_DONT_KNOW_MESSAGE = 'Sorry, I am not sure how to answer that.';
-export const DEFAULT_REFERENCES_HEADING = 'Answer generated from the following pages:';
-export const DEFAULT_LOADING_HEADING = 'Fetching relevant pages...';
-export const DEFAULT_PROMPT_TEMPLATE = `You are a very enthusiastic company representative who loves to help people! Given the following sections from the documentation (preceded by a section id), answer the question using only that information, outputted in Markdown format. If you are unsure and the answer is not explicitly written in the documentation, say "{{I_DONT_KNOW}}".
-
-Context sections:
----
-{{CONTEXT}}
-
-Question: "{{PROMPT}}"
-
-Answer (including related code snippets if available):`;
-export const DEFAULT_TEMPERATURE = 0.1;
-export const DEFAULT_TOP_P = 1;
-export const DEFAULT_FREQUENCY_PENALTY = 0;
-export const DEFAULT_PRESENCE_PENALTY = 0;
-export const DEFAULT_MAX_TOKENS = 500;
-export const DEFAULT_SECTIONS_MATCH_COUNT = 10;
-export const DEFAULT_SECTIONS_MATCH_THRESHOLD = 0.5;
-/**
- * @param {string} prompt - Prompt to submit to the model
- * @param {string} projectKey - The key of your project
- * @param {(answerChunk: string) => void} onAnswerChunk - Answers come in via streaming. This function is called when a new chunk arrives
- * @param {(references: string[]) => void} onReferences - This function is called when a chunk includes references.
- * @param {(error: Error) => void} onError - called when an error occurs
- * @param {Options} [options] - Optional options object
- */
-export async function submitPrompt(prompt, projectKey, onAnswerChunk, onReferences, onError, options = {}) {
-    if (!projectKey) {
-        throw new Error('A projectKey is required.');
-    }
-    if (!prompt)
-        return;
-    const iDontKnowMessage = options.iDontKnowMessage ?? DEFAULT_I_DONT_KNOW_MESSAGE;
-    try {
-        const res = await fetch(options.completionsUrl ?? MARKPROMPT_COMPLETIONS_URL, {
-            method: 'POST',
-            headers: {
-                'Content-Type': 'application/json',
-            },
-            body: JSON.stringify({
-                prompt: prompt,
-                projectKey: projectKey,
-                iDontKnowMessage,
-                model: options?.model ?? DEFAULT_MODEL,
-                promptTemplate: options.promptTemplate,
-                temperature: options.temperature,
-                topP: options.topP,
-                frequencyPenalty: options.frequencyPenalty,
-                presencePenalty: options.presencePenalty,
-                maxTokens: options.maxTokens,
-                sectionsMatchCount: options.sectionsMatchCount,
-                sectionsMatchThreshold: options.sectionsMatchThreshold,
-            }),
-            signal: options.signal,
-        });
-        if (!res.ok || !res.body) {
-            const text = await res.text();
-            onAnswerChunk(iDontKnowMessage);
-            onError(new Error(text));
-            return;
-        }
-        const reader = res.body.getReader();
-        const decoder = new TextDecoder();
-        let done = false;
-        let startText = '';
-        let didHandleHeader = false;
-        while (!done) {
-            const { value, done: doneReading } = await reader.read();
-            done = doneReading;
-            const chunkValue = decoder.decode(value);
-            if (!didHandleHeader) {
-                startText = startText + chunkValue;
-                if (startText.includes(STREAM_SEPARATOR)) {
-                    const parts = startText.split(STREAM_SEPARATOR);
-                    try {
-                        onReferences(JSON.parse(parts[0]));
-                    }
-                    catch {
-                        // do nothing
-                    }
-                    if (parts[1]) {
-                        onAnswerChunk(parts[1]);
-                    }
-                    didHandleHeader = true;
-                }
-            }
-            else if (chunkValue) {
-                const shouldContinue = onAnswerChunk(chunkValue);
-                if (!shouldContinue) {
-                    // If callback returns false, it means it wishes
-                    // to interrupt the streaming.
-                    done = true;
-                }
-            }
-        }
-    }
-    catch (error) {
-        onError(error instanceof Error ? error : new Error(`${error}`));
-    }
-}
+export { submitPrompt, MARKPROMPT_COMPLETIONS_URL, STREAM_SEPARATOR, DEFAULT_MODEL, DEFAULT_I_DONT_KNOW_MESSAGE, DEFAULT_REFERENCES_HEADING, DEFAULT_LOADING_HEADING, DEFAULT_PROMPT_TEMPLATE, DEFAULT_TEMPERATURE, DEFAULT_TOP_P, DEFAULT_FREQUENCY_PENALTY, DEFAULT_PRESENCE_PENALTY, DEFAULT_MAX_TOKENS, DEFAULT_SECTIONS_MATCH_COUNT, DEFAULT_SECTIONS_MATCH_THRESHOLD, } from './prompt.js';
+export { submitSearchQuery } from './search.js';
+export {} from './types.js';
 //# sourceMappingURL=index.js.map

dist/index.test.js

 import { rest } from 'msw';
 import { setupServer } from 'msw/node';
 import { afterAll, afterEach, beforeAll, describe, expect, test, vi, } from 'vitest';
-import { MARKPROMPT_COMPLETIONS_URL, STREAM_SEPARATOR, submitPrompt, } from './index.js';
+import { submitPrompt } from './index.js';
+import { MARKPROMPT_COMPLETIONS_URL, STREAM_SEPARATOR } from './prompt.js';
 const encoder = new TextEncoder();
@@ -6,0 +7,0 @@ let response = [];

dist/types.d.ts

@@ -5,3 +5,31 @@ type OpenAIChatCompletionsModelId = 'gpt-4' | 'gpt-4-0314' | 'gpt-4-32k' | 'gpt-4-32k-0314' | 'gpt-3.5-turbo' | 'gpt-3.5-turbo-0301';
 export type RequiredKeys<T, K extends keyof T> = Required<Pick<T, K>> & Omit<T, K>;
+export type SearchResultSection = {
+    content: string;
+    meta?: {
+        leadHeading?: {
+            depth: number;
+            value: string;
+        };
+    };
+    score: number;
+};
+export type SearchResult = {
+    path: string;
+    meta: {
+        title: string;
+    };
+    source: {
+        type: 'github' | 'motif' | 'website' | 'file-upload' | 'api-upload';
+        data: {
+            url?: string;
+            domain?: string;
+        };
+    };
+    sections: SearchResultSection[];
+};
+export type SearchResultsResponse = {
+    project_id: string;
+    data: SearchResult[];
+};
 export {};
 //# sourceMappingURL=types.d.ts.map

package.json

 {
   "name": "@markprompt/core",
-  "version": "0.4.6",
+  "version": "0.5.0",
   "repository": {
@@ -5,0 +5,0 @@ "type": "git",

README.md

@@ -7,2 +7,28 @@ # `@markprompt/core`
 
+<br />
+<p align="center">
+  <a aria-label="NPM version" href="https://www.npmjs.com/package/@markprompt/core">
+    <img alt="" src="https://badgen.net/npm/v/@markprompt/core">
+  </a>
+  <a aria-label="License" href="https://github.com/motifland/markprompt-js/blob/main/packages/core/LICENSE">
+    <img alt="" src="https://badgen.net/npm/license/@markprompt/core">
+  </a>
+  <a aria-label="Coverage" href="https://app.codecov.io/gh/motifland/markprompt-js/tree/main/packages%2Fcore">
+    <img alt="" src="https://codecov.io/gh/motifland/markprompt-js/branch/main/graph/badge.svg" />
+  </a>
+</p>
+
+## Table of Contents
+
+- [Installation](#installation)
+- [Usage](#usage)
+- [API](#api)
+  - [`submitPrompt(prompt, projectKey, onAnswerChunk, onReferences, onError, options?)`](#submitpromptprompt-projectkey-onanswerchunk-onreferences-onerror-options)
+    - [Arguments](#arguments)
+    - [Options](#options)
+    - [Returns](#returns)
+- [Community](#community)
+- [Authors](#authors)
+- [License](#license)
+
 ## Installation
@@ -22,3 +48,3 @@
 
-# Usage
+## Usage
 
@@ -58,1 +84,50 @@ ```js
 ```
+
+## API
+
+### `submitPrompt(prompt, projectKey, onAnswerChunk, onReferences, onError, options?)`
+
+Submit a prompt the the Markprompt API.
+
+#### Arguments
+
+- `prompt` (`string`): Prompt to submit to the model
+- `projectKey` (`string`): The key of your project
+- `onAnswerChunk` (`function`): Answers come in via streaming. This function is called when a new chunk arrives
+- `onReferences` (`function`): This function is called when a chunk includes references.
+- `onError` (`function`): called when an error occurs
+- [`options`](#options) (`object`): Optional options object
+
+#### Options
+
+- `completionsUrl` (`string`): URL at which to fetch completions
+- `iDontKnowMessage` (`string`): Message returned when the model does not have an answer
+- `model` (`OpenAIModelId`): The OpenAI model to use
+- `promptTemplate` (`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 input question and selected sections
+- `signal` (`AbortSignal`): AbortController signal
+
+#### Returns
+
+A promise that resolves when the response is fully handled.
+
+## Community
+
+- [Twitter @markprompt](https://twitter.com/markprompt)
+- [Twitter @motifland](https://twitter.com/motifland)
+- [Discord](https://discord.gg/MBMh4apz6X)
+
+## Authors
+
+This library is created by the team behind [Motif](https://motif.land)
+([@motifland](https://twitter.com/motifland)).
+
+## License
+
+[MIT](./LICENSE) © [Motif](https://motif.land)

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38368

increased by40.05%

Number of package files

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increased by53.33%

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446

increased by46.71%

Number of lines in readme file

131

increased by133.93%

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