DeepSeek/deepseek-v4-pro-web-search
deepseek-v4-pro-web-search
Free to try DeepSeek v4 Pro Web Search API for text-only grounded research, current answers, and search-augmented reasoning.
Web Search
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-web-search',
messages: [
{
role: 'user',
content: 'What date is it today?'
}
],
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-web-search',
'messages': [
{
'role': 'user',
'content': 'What date is it today?',
}
],
'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-web-search",
"messages": [
{
"role": "user",
"content": "What date is it today?"
}
],
"stream": true,
"max_tokens": 500,
"top_p": 0.5,
"top_k": 1
}'
DeepSeek v4 Pro Web Search Pricing
| Parameters | Price | Original Price | Discount |
|---|
README
Professional DeepSeek v4 Pro Web Search API (Search-Augmented LLM Integration)
DeepSeek v4 Pro Web Search API on Flaq AI provides advanced LLM access with web search capability for developers building research, answer engines, market intelligence tools, and current-information assistants. This DeepSeek web search API integration combines high-quality text generation with search-augmented context through a stable managed route. It is designed for products that need stronger reasoning, live information retrieval, and production-ready responses without building separate search and LLM infrastructure.
Key Features of DeepSeek v4 Pro Web Search API
- Search-Augmented Responses: Generate answers that can use web search context for current-information tasks, research workflows, and knowledge discovery.
- Pro-Quality Reasoning: Use DeepSeek v4 Pro behavior for more demanding analysis, synthesis, comparison, and structured response generation.
- Token-Based API Billing: Build scalable web-connected LLM products with credit usage based on input and output tokens.
- Research-Friendly Output: Support summaries, comparisons, explanations, briefings, and decision-support content grounded in retrieved context.
- Prompt-Guided Control: Guide the model's tone, format, query intent, answer depth, and response structure through chat messages.
- Developer-Friendly Integration: Add DeepSeek web search workflows to applications through Flaq AI's stable chat completions route.
How to Use DeepSeek v4 Pro Web Search API for Search-Augmented Answers on Flaq AI
- Input: Chat messages, research questions, task instructions, and optional generation controls.
- Output: Search-augmented text responses delivered through DeepSeek v4 Pro Web Search API integration.
- Search Control: Supports prompt-guided current-information workflows, topic exploration, comparison, market research, and answer synthesis.
- Capabilities: Web search assistance, research summarization, current-information answers, analysis, structured output, and scalable LLM automation through DeepSeek v4 API access.
Best Use Cases for DeepSeek v4 Pro Web Search API Integration
- AI Search Assistants: Build products that answer user questions with web-connected context and polished response quality.
- Market & Competitor Research: Summarize companies, products, trends, launches, and public information for business workflows.
- Current Information Workflows: Support news-aware, event-aware, or time-sensitive answers where model-only knowledge is not enough.
- Knowledge Discovery Tools: Generate explainers, briefings, comparisons, and summaries from search-augmented context.
- Research Automation: Power agents and internal tools that combine retrieval, synthesis, and structured reporting.
Note Please ensure prompts, retrieved content usage, and generated text comply with DeepSeek and Flaq AI safety requirements. If an error occurs, revise the request, narrow the topic, or adjust generation settings and try again.
DeepSeek v4 Pro Web Search vs Competitors: Comparative Analysis
- DeepSeek v4 Pro Web Search vs. DeepSeek v4 Pro Text-to-Text DeepSeek v4 Pro Text-to-Text focuses on model-only language generation. DeepSeek v4 Pro Web Search adds retrieval support for current-information, research, and search-augmented answer workflows.
- DeepSeek v4 Pro Web Search vs. DeepSeek v4 Flash Web Search DeepSeek v4 Flash Web Search prioritizes faster and more affordable search-augmented responses. DeepSeek v4 Pro Web Search is positioned for stronger reasoning, richer synthesis, and higher-quality research output.
- DeepSeek v4 Pro Web Search vs. Perplexity API Perplexity is known for search-native answer experiences. DeepSeek v4 Pro Web Search gives developers a DeepSeek-powered alternative through Flaq AI's managed API route.
- DeepSeek v4 Pro Web Search vs. GPT Web Search Workflows GPT web workflows provide broad search-augmented generation. DeepSeek v4 Pro Web Search offers another model option for teams comparing reasoning style, cost, and output quality.
- DeepSeek v4 Pro Web Search vs. Qwen Web Search Models Qwen web search models provide Alibaba-powered retrieval workflows. DeepSeek v4 Pro Web Search gives teams a DeepSeek route for research, current answers, and structured synthesis.