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DeepSeek VL enables developers to build applications that can see, interpret, and reason about images. Through a simple API, you can integrate capabilities such as:
This guide walks through how to integrate the DeepSeek VL API, including setup, request structure, examples, and best practices.
Before integrating:
DeepSeek VL is typically accessed via a vision endpoint:
POST https://api.deepseek.international/v1/vision
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
{
"image_url": "https://example.com/image.jpg",
"prompt": "Describe the image in detail"
}
| Parameter | Type | Description |
|---|---|---|
image_url | string | Publicly accessible image |
prompt | string | Instruction for the model |
mode (optional) | string | Task type (e.g., ocr, analyze) |
output_format (optional) | string | text or json |
import requests
url = "https://api.deepseek.international/v1/vision"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
data = {
"image_url": "https://example.com/invoice.jpg",
"prompt": "Extract invoice number, date, and total in JSON format"
}
response = requests.post(url, headers=headers, json=data)
print(response.json())
import fetch from "node-fetch";
const response = await fetch("https://api.deepseek.international/v1/vision", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
body: JSON.stringify({
image_url: "https://example.com/chart.png",
prompt: "Analyze this chart and summarize key trends"
})
});
const data = await response.json();
console.log(data);
curl -X POST https://api.deepseek.international/v1/vision \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image_url": "https://example.com/ui.png",
"prompt": "Identify UI elements and suggest improvements"
}'
{
"image_url": "invoice.jpg",
"prompt": "Extract invoice_id, date, vendor, and total_amount in JSON"
}
Use Cases:
{
"image_url": "sales-chart.png",
"prompt": "Summarize trends, compare categories, and detect anomalies"
}
{
"image_url": "diagram.png",
"prompt": "Explain what this diagram represents"
}
{
"image_url": "dashboard.png",
"prompt": "Analyze this UI and suggest usability improvements"
}
Typical response:
{
"id": "vision-xyz123",
"model": "deepseek-vl",
"output": "The chart shows steady growth with a sharp increase in Q4..."
}
{
"output": {
"invoice_id": "INV-1024",
"date": "2025-10-01",
"total_amount": 1240.00
}
}
Use explicit prompts:
“Return the result strictly in JSON format with keys: invoice_id, date, total_amount”
Workflow:
/vision → extract data/reason → analyze insightsExample:
For large-scale workloads:
| Error Code | Cause | Solution |
|---|---|---|
| 401 Unauthorized | Invalid API key | Verify credentials |
| 400 Bad Request | Invalid payload | Check JSON structure |
| 429 Rate Limit | Too many requests | Implement retries/backoff |
| 500 Server Error | Internal issue | Retry request |
Instead of:
“Analyze this image”
Use:
“Extract all invoice fields and return structured JSON”
For production systems:
| Factor | Impact |
|---|---|
| Image size | Larger images increase latency |
| Prompt complexity | Longer prompts = slower responses |
| Concurrency | Use batching for scale |
Use it when:
DeepSeek VL API provides a developer-friendly entry point into multimodal AI, enabling applications to move from:
“Processing images” → “Understanding visual information”
With minimal setup, you can build:
To integrate the DeepSeek VL API, you need to send a POST request to the /vision endpoint with your API key, image input, and a prompt. You can use standard HTTP requests or SDKs in Python and Node.js. The API returns either natural language output or structured JSON, depending on your prompt.
The DeepSeek VL API supports a wide range of image types, including:
Documents (invoices, receipts, PDFs)
Charts and graphs
UI screenshots
Photos and real-world images
For best results, images should be high-quality, well-lit, and clearly structured, as input quality directly affects accuracy.
Yes, DeepSeek VL can return structured JSON outputs when prompted correctly. By specifying fields in your prompt (e.g., “extract invoice_id, date, total_amount in JSON”), you can integrate results directly into databases, workflows, or automation pipelines without additional parsing.