QwkSearch API Client

Overview

QwkSearch API provides three core services for AI-powered research and content analysis:

1. Content Extraction - Extract structured content and citations from any URL
2. Language Generation - Generate AI responses using multiple language model providers
3. Web Search - Search the web using metasearch engine across 100+ sources

Complete Example: Research Pipeline

Combine all three endpoints to create a complete research pipeline:

import * as qwk from 'qwksearch-api-client';

async function researchTopic(topic) {
  // 1. Search for relevant articles
  const searchResults = await qwk.searchWeb({
    query: {
      q: topic,
      cat: 'science',
      recency: 'month'
    }
  });

  console.log(`Found ${searchResults.results.length} results`);

  // 2. Extract content from top 3 results
  const articles = await Promise.all(
    searchResults.results.slice(0, 3).map(async (result) => {
      const content = await qwk.extractContent({
        query: {
          url: result.url
        }
      });
      return content;
    })
  );

  // 3. Generate summary of all articles
  const combinedText = articles
    .map(a => `${a.title}\n\n${a.html}`)
    .join('\n\n---\n\n');

  const summary = await qwk.writeLanguage({
    body: {
      provider: 'groq',
      key: process.env.GROQ_API_KEY,
      agent: 'summarize-bullets',
      article: combinedText
    }
  });

  return {
    searchResults: searchResults.results,
    articles,
    summary: summary.content
  };
}

// Run the research pipeline
researchTopic('quantum computing applications')
  .then(results => {
    console.log('Research Summary:');
    console.log(results.summary);
  });

API Endpoints

1. Extract Content (/extract)

Extract structured content, citations, and metadata from any URL including articles, PDFs, and YouTube videos.

Features

• Main Content Detection: Combines Mozilla Readability and Postlight Mercury algorithms with 100+ custom adapters
• HTML Standardization: Transforms complex HTML into simplified reading-mode format
• YouTube Transcripts: Retrieves complete video transcripts with timestamps
• PDF Processing: Extracts formatted text and infers heading hierarchy
• Citation Extraction: Identifies author names, publication dates, sources, and titles
• Author Formatting: Validates against 90,000+ name database for proper citation formatting

Request

GET /extract?url={url}&images={boolean}&links={boolean}

Parameters:

| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | url | string (uri) | Yes | - | URL to extract content from | | images | boolean | No | true | Include images in output | | links | boolean | No | true | Include hyperlinks in output | | formatting | boolean | No | true | Preserve text formatting | | absoluteURLs | boolean | No | true | Convert relative URLs to absolute | | timeout | integer | No | 5 | HTTP request timeout (1-30 seconds) |

2. Generate Language (/agents)

Generate AI responses using various language model providers with pre-built agent templates.

Language Intelligence Providers (LIPs)

| Provider | Model Families | Cost (1M Output) | Valuation | |----------|----------------|------------------|-----------| | Groq | Llama, DeepSeek, Gemini, Mistral | $0.79 | $2.8B | | Ollama | llama, mistral, mixtral, gemma, qwen, deepseek | $0 (local) | - | | OpenAI | o1, o4, gpt-4, gpt-4-turbo, gpt-4-omni | $8.00 | $300B | | Anthropic | Claude Sonnet, Opus, Haiku | $15.00 | $61.5B | | TogetherAI | Llama, Mistral, Qwen, DeepSeek | $0.90 | $3.3B | | Perplexity | Sonar, Sonar Deep Research | $15.00 | $18B | | XAI | Grok, Grok Vision | $15.00 | $80B | | Google | Gemini | $10.00 | - | | Cloudflare | Llama, Gemma, Mistral, Phi, Qwen | $2.25 | $62.3B |

Agent Templates

| Agent | Context Variables | Description | |-------|------------------|-------------| | question | query, chat_history | Answer questions with conversation context | | summarize-bullets | article | Create bullet-point summaries | | summarize | article | Generate narrative summaries | | suggest-followups | chat_history, article | Suggest follow-up questions (returns string[]) | | answer-cite-sources | context, chat_history, query | Answer with source citations | | query-resolution | chat_history, query | Resolve ambiguous queries | | knowledge-graph-nodes | query, article | Extract knowledge graph nodes | | summary-longtext | summaries | Summarize multiple summaries |

Request

POST /agents
Content-Type: application/json

{
  "provider": "groq",
  "key": "your-api-key",
  "agent": "question",
  "model": "llama-3.3-70b-versatile",
  "query": "What is quantum computing?",
  "temperature": 1.0,
  "html": true
}

Body Parameters:

| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | provider | string | Yes | - | LIP provider: groq, openai, anthropic, together, xai, google, perplexity, ollama, cloudflare | | key | string | Yes | - | API key for the provider | | agent | string | No | question | Agent template name | | model | string | No | llama-4-maverick-17b | Model name for the provider | | html | boolean | No | true | Format response as HTML (true) or Markdown (false) | | temperature | number | No | 1.0 | 0-1: deterministic, 1-2: creative | | query | string | No | - | Query text for certain agents | | chat_history | string | No | - | Conversation history for certain agents | | article | string | No | - | Article text for summarization agents |

Response

200 OK

{
  "content": "Generated response in HTML or Markdown format",
  "extract": {
    "structured": "data"
  }
}

Example Usage

import * as qwk from 'qwksearch-api-client';

// Question answering
const response = await qwk.writeLanguage({
  body: {
    provider: 'groq',
    key: process.env.GROQ_API_KEY,
    agent: 'question',
    query: 'Explain neural networks',
    temperature: 0.7
  }
});

const { content } = response;
console.log(content);

// Summarize article
const summary = await qwk.writeLanguage({
  body: {
    provider: 'anthropic',
    key: process.env.ANTHROPIC_API_KEY,
    agent: 'summarize-bullets',
    article: articleText,
    html: false // Get Markdown
  }
});

// Answer with citations
const answer = await qwk.writeLanguage({
  body: {
    provider: 'openai',
    key: process.env.OPENAI_API_KEY,
    agent: 'answer-cite-sources',
    query: 'What causes climate change?',
    context: 'Scientific articles about greenhouse gases...',
    temperature: 0.5
  }
});
console.log(answer.content);

3. Search Web (/search)

Search the web using metasearch engine aggregating 100+ search sources.

Features

• Privacy-Focused: No tracking or personal data collection
• Multiple Categories: General, news, videos, images, science, files, IT
• Recency Filters: Filter by day, week, month, year
• Multi-Language: Support for various languages
• Diverse Sources: Aggregates from 100+ search engines
• Search index exceeds 100,000,000 GB covering 130 trillion pages
• Uses 200+ ranking factors including keywords, backlinks, page speed

Request

GET /search?q={query}&cat={category}&recency={filter}&lang={language}

Parameters:

| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | q | string | Yes | - | Search query string | | cat | string | No | general | Category: general, news, videos, images, science, files, it | | recency | string | No | all | Time filter: all, day, week, month, year | | safesearch | boolean | No | false | Block adult content | | public | boolean | No | false | Use public server instances | | page | integer | No | 1 | Pagination for results | | lang | string | No | en-US | Language code |

Response

200 OK

{
  "results": [
    {
      "title": "Search result title",
      "url": "https://example.com/page",
      "snippet": "Text snippet around the query...",
      "domain": "example.com",
      "favicon": "https://example.com/favicon.ico",
      "path": "/page",
      "engines": "google,bing"
    }
  ]
}

Installation

NPM Package

npm install qwksearch-api-client

Links

• Documentation: airesearch.js.org

• Demo: qwksearch.com

• GitHub: github.com/vtempest/ai-research-agent

• OpenAPI Spec: View Full Specification

• LLM Training Example

• LangChain ReactAgent Tools

• Hugging Face Tutorials

• OpenAI Cookbook

• Transformer Overview

• Building Transformer Guide

• PyTorch Overview

• SearXNG Overview