Claude Code Guide
Set up Flaq AI Claude models and explore Claude Code skills
Free to try DeepSeek v4 Pro 0813 Text API for high-quality text reasoning, writing, coding help, and stable production LLM workflows.
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: 'deepseek-v4-pro-text-to-text-0813',
messages: [
{
role: 'user',
content: 'Hello'
}
],
stream: true,
max_tokens: 500,
top_p: 0.5,
top_k: 1
})
});
if (!response.ok) {
const errorBody = await response.json().catch(() => null);
throw new Error(errorBody?.error?.message ?? errorBody?.message ?? `HTTP ${response.status}`);
}
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(/\r?\n\r?\n/);
buffer = frames.pop() || '';
for (const frame of frames) {
const lines = frame.split(/\r?\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': 'deepseek-v4-pro-text-to-text-0813',
'messages': [
{
'role': 'user',
'content': 'Hello',
}
],
'stream': True,
'max_tokens': 500,
'top_p': 0.5,
'top_k': 1,
},
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": "deepseek-v4-pro-text-to-text-0813",
"messages": [
{
"role": "user",
"content": "Hello"
}
],
"stream": true,
"max_tokens": 500,
"top_p": 0.5,
"top_k": 1
}'
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.flaq.ai/api/v1'
});
const stream = await client.chat.completions.create({
model: 'deepseek-v4-pro-text-to-text-0813',
messages: [
{
role: 'user',
content: 'Hello'
}
],
stream: true,
max_tokens: 500
});
for await (const chunk of stream) {
const content = chunk.choices[0]?.delta?.content;
if (content) process.stdout.write(content);
}
from openai import OpenAI
client = OpenAI(
api_key='YOUR_API_KEY',
base_url='https://api.flaq.ai/api/v1',
)
stream = client.chat.completions.create(
model='deepseek-v4-pro-text-to-text-0813',
messages=[
{
'role': 'user',
'content': 'Hello',
}
],
stream=True,
max_tokens=500,
)
for chunk in stream:
if not chunk.choices:
continue
content = chunk.choices[0].delta.content
if content:
print(content, end='', flush=True)
OPENAI_BASE_URL="https://api.flaq.ai/api/v1"
curl -N -X POST "$OPENAI_BASE_URL/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Accept: text/event-stream" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-pro-text-to-text-0813",
"messages": [
{
"role": "user",
"content": "Hello"
}
],
"stream": true,
"max_tokens": 500
}'
| Parameters | Price | Original Price | Discount |
|---|
DeepSeek v4 Pro Text-to-Text API on Flaq AI provides advanced LLM access for developers building reasoning, writing, coding, analysis, and automation workflows. This DeepSeek API integration turns user messages into high-quality text responses through a stable managed route with token-based billing. It is designed for products that need stronger response quality, reliable instruction following, and production-ready text generation without managing model infrastructure.
Note Please ensure prompts and generated content comply with DeepSeek and Flaq AI safety requirements. If an error occurs, revise the request, reduce unsupported content, or adjust generation settings and try again.
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