DeepSeek/deepseek-v4-pro-text-to-text
deepseek-v4-pro-text-to-text
Free to try DeepSeek v4 Pro Text API for high-quality text reasoning, writing, coding help, and stable production LLM workflows.
Text Chat
Related Deepseek V4 Pro Models
API Examples
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: 'deepseek-v4-pro-text-to-text',
messages: [
{
role: 'user',
content: 'Hello'
}
],
stream: true,
max_tokens: 500,
top_p: 0.5,
top_k: 1
})
});
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': 'deepseek-v4-pro-text-to-text',
'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)
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": "deepseek-v4-pro-text-to-text",
"messages": [
{
"role": "user",
"content": "Hello"
}
],
"stream": true,
"max_tokens": 500,
"top_p": 0.5,
"top_k": 1
}'
DeepSeek v4 Pro Text to Text Pricing
| Parameters | Price | Original Price | Discount |
|---|
README
Professional DeepSeek v4 Pro Text-to-Text API (Advanced LLM Integration)
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.
Key Features of DeepSeek v4 Pro Text-to-Text API
- Advanced Text Generation: Generate polished responses for reasoning, writing, coding support, summarization, content production, and workflow automation.
- Pro-Quality LLM Output: Use DeepSeek v4 Pro for tasks that benefit from stronger reasoning depth, more careful language, and higher-quality response structure.
- Token-Based API Billing: Build scalable text products with credit usage based on input and output tokens, suitable for production chat and automation systems.
- Developer-Friendly Integration: Add DeepSeek v4 Pro to applications through Flaq AI's stable chat completions route.
- Flexible Prompt Control: Guide tone, format, task boundaries, and response style through system and user messages.
- Production Workflow Coverage: Support assistants, internal tools, content systems, coding helpers, research workflows, and business automation.
How to Use DeepSeek v4 Pro Text-to-Text API for LLM Generation on Flaq AI
- Input: Chat messages, system instructions, task context, and optional generation controls.
- Output: High-quality text responses delivered through DeepSeek v4 Pro Text-to-Text API integration.
- Conversation Control: Supports prompt-based direction for reasoning style, formatting, tone, task scope, and multi-turn context.
- Capabilities: Text-to-text generation, reasoning, writing, summarization, coding assistance, structured output, and scalable LLM automation through DeepSeek v4 API access.
Best Use Cases for DeepSeek v4 Pro Text-to-Text API Integration
- Advanced AI Assistants: Build chat assistants that need reliable reasoning, polished answers, and consistent task execution.
- Writing & Content Workflows: Generate drafts, rewrite copy, summarize materials, and support editorial production at scale.
- Coding & Technical Support: Help users reason through code, explain errors, draft snippets, and improve technical documentation.
- Business Automation: Power internal copilots, workflow agents, support tools, and knowledge-base interactions.
- Research & Analysis: Turn long context, notes, or structured prompts into clear summaries, comparisons, and recommendations.
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.
DeepSeek v4 Pro Text-to-Text vs Competitors: Comparative Analysis
- DeepSeek v4 Pro vs. DeepSeek v4 Flash Text-to-Text DeepSeek v4 Flash prioritizes faster and more affordable text generation. DeepSeek v4 Pro is positioned for stronger output quality, deeper reasoning, and more demanding production workflows.
- DeepSeek v4 Pro vs. DeepSeek v4 Pro Web Search DeepSeek v4 Pro Web Search adds web-connected retrieval for current-information workflows. DeepSeek v4 Pro Text-to-Text focuses on model-only responses for writing, reasoning, coding, and automation.
- DeepSeek v4 Pro vs. GPT Text Models GPT text models provide broad general-purpose generation. DeepSeek v4 Pro gives teams a DeepSeek-powered alternative with managed API access and strong text-to-text performance.
- DeepSeek v4 Pro vs. Claude Text Models Claude is known for careful long-form writing. DeepSeek v4 Pro is useful for developers who need advanced LLM output across reasoning, coding, and structured production tasks.
- DeepSeek v4 Pro vs. Qwen Text Models Qwen text models provide Alibaba-powered LLM workflows. DeepSeek v4 Pro offers a DeepSeek route for teams comparing model behavior, quality, and cost across providers.
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