Claude Code Guide
Set up Flaq AI Claude models and explore Claude Code skills
Free to try Grok 4 API for LLM reasoning, writing, coding help, analysis, and summaries. Stable xAI access for production AI workflows. Use stable GPT, Claude, and other LLM APIs for agents, chatbots, research, coding, automation, and production-ready intelligent applications.
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: 'grok-4-text-to-text',
messages: [
{
role: 'user',
content: 'Explain the key differences between REST and GraphQL APIs.'
}
],
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);
}
}
}
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': 'grok-4-text-to-text',
'messages': [
{
'role': 'user',
'content': 'Explain the key differences between REST and GraphQL APIs.',
}
],
'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)
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": "grok-4-text-to-text",
"messages": [
{
"role": "user",
"content": "Explain the key differences between REST and GraphQL APIs."
}
],
"stream": true,
"max_tokens": 2048
}'
| Parameters | Price | Original Price | Discount |
|---|
Grok 4 Text-to-Text API on Flaq AI provides xAI model access for professional language workflows that need reliable reasoning, conversational output, and production-ready integration. This Grok API route helps developers build chat, writing, analysis, coding, and automation features with flexible conversation context and practical output controls. It is designed for teams that want managed xAI text capability without handling provider-specific infrastructure.
Note Please ensure prompts and application workflows comply with xAI safety and usage guidelines. If an error occurs, review the input for restricted content, simplify the request, and try again.
Grok 4 vs. GPT Models
GPT models offer OpenAI-native behavior and broad ecosystem familiarity. Grok 4 gives teams an xAI route for managed text generation and conversational product features.
Grok 4 vs. Claude Opus
Claude Opus is strong for careful writing and complex analysis. Grok 4 provides an xAI alternative for teams that want flexible chat and text-to-text workflows on Flaq AI.
Grok 4 vs. Gemini
Gemini models are attractive for Google-native use cases. Grok 4 focuses on xAI model behavior and managed text generation through a stable API route.
Grok 4 vs. Qwen
Qwen models provide strong Alibaba language workflows and multilingual value. Grok 4 is useful for teams that want xAI-powered text generation in their model mix.
Grok 4 vs. Llama
Llama models give developers open-model deployment control. Grok 4 removes hosting complexity and provides managed API access for production text features.
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