OpenAI/gpt-6-astra-web-search

gpt-6-astra-web-search

Try GPT 6 Astra API by OpenAI for complex research, web search, and evidence-based analysis through Flaq AI's stable, affordable API with streaming responses.

Web Search

Related Gpt 6 Astra Models

gpt-6-astra-text-to-texttext-to-text

gpt-6-astra-image-to-textimage-to-text

gpt-6-astra-web-searchweb-search

gpt-6-astra-file-analysisfile-analysis

Documentation

API Examples

JavaScriptPythoncURL

Submit Example

const response = await fetch('https://api.flaq.ai/api/v1/chat/completions', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer YOUR_API_KEY',
    Accept: 'text/event-stream',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'gpt-6-astra-web-search',
    messages: [
      {
        role: 'user',
        content: 'Find the latest public information about Flaq AI and summarize it for a product brief.'
      }
    ],
    stream: true,
    max_tokens: 2048
  })
});

const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
let assistantText = '';

while (true) {
  const { done, value } = await reader.read();
  if (done) break;

  buffer += decoder.decode(value, { stream: true });
  const frames = buffer.split('\n\n');
  buffer = frames.pop() || '';

  for (const frame of frames) {
    const lines = frame.split('\n').filter(Boolean);
    let eventName = 'message';
    const dataLines = [];

    for (const line of lines) {
      if (line.startsWith('event:')) {
        eventName = line.slice(6).trim();
      } else if (line.startsWith('data:')) {
        dataLines.push(line.replace(/^data:\s*/, ''));
      }
    }

    const raw = dataLines.join('\n').trim();
    if (raw === '[DONE]') {
      console.log('\nFinal text:', assistantText);
      continue;
    }

    let payload;
    try {
      payload = JSON.parse(raw);
    } catch {
      continue;
    }

    if (eventName === 'error' || payload.error) {
      const msg = payload.error?.message ?? payload.message ?? 'Chat request failed';
      throw new Error(msg);
    }

    const delta = payload.choices?.[0]?.delta;
    if (delta?.content) {
      assistantText += delta.content;
      console.log(assistantText);
    }
  }
}

Submit Example

import json
import requests

response = requests.post(
    'https://api.flaq.ai/api/v1/chat/completions',
    headers={
        'Authorization': 'Bearer YOUR_API_KEY',
        'Accept': 'text/event-stream',
        'Content-Type': 'application/json',
    },
    json={
        'model': 'gpt-6-astra-web-search',
        'messages': [
            {
                'role': 'user',
                'content': 'Find the latest public information about Flaq AI and summarize it for a product brief.',
            }
        ],
        'stream': True,
        'max_tokens': 2048,
    },
    stream=True,
)

response.raise_for_status()

event_name = 'message'
assistant_text = ''

for raw_line in response.iter_lines(decode_unicode=True):
    if not raw_line:
        event_name = 'message'
        continue

    if raw_line.startswith('event:'):
        event_name = raw_line.replace('event:', '', 1).strip()
        continue

    if raw_line.startswith('data:'):
        raw_data = raw_line.replace('data:', '', 1).strip()
        if raw_data == '[DONE]':
            print('\nFinal text:', assistant_text)
            continue

        payload = json.loads(raw_data)

        if event_name == 'error' or payload.get('error'):
            error = payload.get('error') or payload
            raise RuntimeError(error.get('message', 'Chat request failed'))

        choices = payload.get('choices') or []
        if choices:
            delta = choices[0].get('delta') or {}
            content = delta.get('content')
            if content:
                assistant_text += content
                print(content, end='', flush=True)

Submit Example

curl -N -X POST "https://api.flaq.ai/api/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Accept: text/event-stream" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6-astra-web-search",
    "messages": [
      {
        "role": "user",
        "content": "Find the latest public information about Flaq AI and summarize it for a product brief."
      }
    ],
    "stream": true,
    "max_tokens": 2048
  }'

Start a new chat

Send a message to begin.

GPT 6 Astra Web Search Pricing

Parameters	Price	Original Price	Discount

Token: input	$10.0000 per 1M input tokens	-	Standard
Token: output	$50.0000 per 1M output tokens	-	Standard

README

In-Depth Research GPT 6 Astra Web Search API (OpenAI Evidence-Based Analysis)

GPT 6 Astra Web Search API combines OpenAI's flagship GPT-6 Astra reasoning with web retrieval for complex research on Flaq AI. This web search API integration helps developers and professional teams investigate live questions, compare public sources, and synthesize evidence-based answers from conversation messages.

Key Features of GPT 6 Astra Web Search API

Flagship Research Reasoning: Apply GPT-6 Astra to investigations that need current public information plus careful synthesis, not a single-link lookup.
Source Comparison: Set retrieved material side by side so teams can see agreement, conflict, and gaps before they act.
Evidence-Based Synthesis: Turn scattered web findings into briefs, options, and structured analysis for professional review.
Mixed Research Context: Add supported images or documents when a search question depends on a screenshot, brief, or source file.
Conversation-Aware Follow-Up: Narrow, expand, or redirect an investigation across follow-up messages without dropping the original question.
Streaming Research Output: Deliver search-grounded text incrementally through a stable, cost-effective Flaq AI API workflow.

How to Use GPT 6 Astra Web Search API for In-Depth Research on Flaq AI

Input: A research question in conversation messages, with optional supported images and documents when extra context helps.
Output: Text answers, comparisons, and research briefs grounded in retrieved public information plus any attached context.
Output Length: Set a maximum output token budget for short updates or longer syntheses.
Streaming: Receive the response in increments.
Capabilities: Current-information research, source comparison, evidence-based synthesis, and follow-up investigation through GPT 6 Astra Web Search API integration.

Best Use Cases for GPT 6 Astra Web Search API Integration

Market and Competitor Intelligence: Investigate public product changes, positioning, and category movement, then attach a brief or screenshot when the question is specific.
Technical and Scientific Scans: Gather current documentation, papers, and vendor material, then compress the findings into a usable research note.
Policy and News Analysis: Track evolving public developments and compare how different sources describe the same event.
Due Diligence Support: Check public claims against retrieved material and any uploaded evidence the reviewer already holds.
Research Copilots: Build assistants that iterate on a live question, keep context, and return decision-ready summaries rather than raw link lists.

Note Keep prompts, attachments, and search tasks within OpenAI usage policies, Flaq AI terms, and applicable website rules. If a request fails, narrow the question, remove restricted material, and try again.

GPT 6 Astra Web Search vs Competitors: Comparative Analysis

GPT 6 Astra vs. GPT 5.6 Sol Web Search
GPT 5.6 Sol Web Search is the previous OpenAI flagship research API on Flaq AI. GPT 6 Astra is the current flagship when the investigation needs newer GPT reasoning on top of web retrieval.
GPT 6 Astra vs. Claude Fable 5.1 Web Search
Claude Fable 5.1 Web Search on Flaq AI is a text-only research route. GPT 6 Astra Web Search can include supported images and documents with the question, which matters when the investigation starts from a screenshot, memo, or source file.
GPT 6 Astra vs. Gemini Grounded Search
Gemini search workflows sit naturally in Google-centered products. GPT 6 Astra Web Search API is the OpenAI flagship option for teams that want live research and source comparison through Flaq AI.
GPT 6 Astra vs. Search-First Answer Engines
Search-first engines optimize for rapid web answers and link-forward summaries. GPT 6 Astra Web Search emphasizes flagship reasoning over retrieved material, which is a better fit when the product needs synthesis and follow-up rather than a standalone search box.