> ## Documentation Index
> Fetch the complete documentation index at: https://openrouter.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Web Search
> Real-time web search integration with the Responses API
The Responses API supports web search integration, allowing models to access real-time information from the internet and provide responses with proper citations and annotations.
**Deprecated Plugin Approach**
The web search plugin (`plugins: [{ id: "web" }]`) shown below is deprecated. Use the [`openrouter:web_search` server tool](/docs/guides/features/server-tools/web-search) instead, which works with both the Chat Completions and Responses APIs via the `tools` array.
## Web Search Plugin
Enable web search using the `plugins` parameter:
```typescript title="TypeScript" lines theme={null}
const response = await fetch('https://openrouter.ai/api/v1/responses', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'openai/o4-mini',
input: 'What is OpenRouter?',
plugins: [{ id: 'web', max_results: 3 }],
max_output_tokens: 9000,
}),
});
const result = await response.json();
console.log(result);
```
```python title="Python" lines theme={null}
import requests
response = requests.post(
'https://openrouter.ai/api/v1/responses',
headers={
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
json={
'model': 'openai/o4-mini',
'input': 'What is OpenRouter?',
'plugins': [{'id': 'web', 'max_results': 3}],
'max_output_tokens': 9000,
}
)
result = response.json()
print(result)
```
```bash title="cURL" lines theme={null}
curl -X POST https://openrouter.ai/api/v1/responses \
-H "Authorization: Bearer YOUR_OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/o4-mini",
"input": "What is OpenRouter?",
"plugins": [{"id": "web", "max_results": 3}],
"max_output_tokens": 9000
}'
```
## Plugin Configuration
Configure web search behavior:
| Parameter | Type | Description |
| ----------------- | --------- | --------------------------------------------------------------------------------- |
| `id` | string | **Required.** Must be "web" |
| `engine` | string | Search engine: `"native"`, `"exa"`, `"firecrawl"`, `"parallel"`, or omit for auto |
| `max_results` | integer | Maximum search results to retrieve (1–25; 1–20 for Perplexity; default 5) |
| `include_domains` | string\[] | Restrict results to these domains (supports wildcards like `*.substack.com`) |
| `exclude_domains` | string\[] | Exclude results from these domains |
See the [Web Search plugin docs](/docs/guides/features/plugins/web-search) for full details on engine selection, domain filter compatibility, and pricing.
## X Search Filters (SpaceXAI only)
When using SpaceXAI models (e.g. `x-ai/grok-4.1-fast`),
you can pass `x_search_filter` as a top-level
request parameter to filter X/Twitter search
results:
```json lines theme={null}
{
"model": "x-ai/grok-4.1-fast",
"input": "What are people saying about AI?",
"plugins": [{ "id": "web" }],
"x_search_filter": {
"allowed_x_handles": ["OpenRouterAI"],
"from_date": "2025-01-01",
"enable_image_understanding": true
}
}
```
| Parameter | Type | Description |
| ---------------------------- | --------- | ---------------------------------------------- |
| `allowed_x_handles` | string\[] | Only include posts from these handles (max 20) |
| `excluded_x_handles` | string\[] | Exclude posts from these handles (max 20) |
| `from_date` | string | Start date (ISO 8601, e.g. `"2025-01-01"`) |
| `to_date` | string | End date (ISO 8601, e.g. `"2025-12-31"`) |
| `enable_image_understanding` | boolean | Analyze images in posts |
| `enable_video_understanding` | boolean | Analyze videos in posts |
`allowed_x_handles` and `excluded_x_handles` are
mutually exclusive. See the
[Web Search plugin docs](/docs/guides/features/plugins/web-search#x-search-filters-spacexai-only)
for full details.
## Structured Message with Web Search
Use structured messages for more complex queries:
```typescript title="TypeScript" expandable lines theme={null}
const response = await fetch('https://openrouter.ai/api/v1/responses', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'openai/o4-mini',
input: [
{
type: 'message',
role: 'user',
content: [
{
type: 'input_text',
text: 'What was a positive news story from today?',
},
],
},
],
plugins: [{ id: 'web', max_results: 2 }],
max_output_tokens: 9000,
}),
});
const result = await response.json();
console.log(result);
```
```python title="Python" expandable lines theme={null}
import requests
response = requests.post(
'https://openrouter.ai/api/v1/responses',
headers={
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
json={
'model': 'openai/o4-mini',
'input': [
{
'type': 'message',
'role': 'user',
'content': [
{
'type': 'input_text',
'text': 'What was a positive news story from today?',
},
],
},
],
'plugins': [{'id': 'web', 'max_results': 2}],
'max_output_tokens': 9000,
}
)
result = response.json()
print(result)
```
## Online Model Variants
**Deprecated**
The `:online` variant is deprecated. Use the [`openrouter:web_search` server tool](/docs/guides/features/server-tools/web-search) instead.
Some models have built-in web search capabilities using the `:online` variant:
```typescript title="TypeScript" lines theme={null}
const response = await fetch('https://openrouter.ai/api/v1/responses', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'openai/o4-mini:online',
input: 'What was a positive news story from today?',
max_output_tokens: 9000,
}),
});
const result = await response.json();
console.log(result);
```
```python title="Python" lines theme={null}
import requests
response = requests.post(
'https://openrouter.ai/api/v1/responses',
headers={
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
json={
'model': 'openai/o4-mini:online',
'input': 'What was a positive news story from today?',
'max_output_tokens': 9000,
}
)
result = response.json()
print(result)
```
## Response with Annotations
Web search responses include citation annotations:
```json expandable lines theme={null}
{
"id": "resp_1234567890",
"object": "response",
"created_at": 1234567890,
"model": "openai/o4-mini",
"output": [
{
"type": "message",
"id": "msg_abc123",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "OpenRouter is a unified API for accessing multiple Large Language Model providers through a single interface. It allows developers to access 100+ AI models from providers like OpenAI, Anthropic, Google, and others with intelligent routing and automatic failover.",
"annotations": [
{
"type": "url_citation",
"url": "https://openrouter.ai/docs",
"start_index": 0,
"end_index": 85
},
{
"type": "url_citation",
"url": "https://openrouter.ai/models",
"start_index": 120,
"end_index": 180
}
]
}
]
}
],
"usage": {
"input_tokens": 15,
"output_tokens": 95,
"total_tokens": 110
},
"status": "completed"
}
```
## Annotation Types
Web search responses can include different annotation types:
### URL Citation
```json lines theme={null}
{
"type": "url_citation",
"url": "https://example.com/article",
"start_index": 0,
"end_index": 50,
"content": "Excerpt from the web page..."
}
```
## Complex Search Queries
Handle multi-part search queries:
```typescript title="TypeScript" expandable lines theme={null}
const response = await fetch('https://openrouter.ai/api/v1/responses', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'openai/o4-mini',
input: [
{
type: 'message',
role: 'user',
content: [
{
type: 'input_text',
text: 'Compare OpenAI and Anthropic latest models',
},
],
},
],
plugins: [{ id: 'web', max_results: 5 }],
max_output_tokens: 9000,
}),
});
const result = await response.json();
console.log(result);
```
```python title="Python" expandable lines theme={null}
import requests
response = requests.post(
'https://openrouter.ai/api/v1/responses',
headers={
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
json={
'model': 'openai/o4-mini',
'input': [
{
'type': 'message',
'role': 'user',
'content': [
{
'type': 'input_text',
'text': 'Compare OpenAI and Anthropic latest models',
},
],
},
],
'plugins': [{'id': 'web', 'max_results': 5}],
'max_output_tokens': 9000,
}
)
result = response.json()
print(result)
```
## Web Search in Conversation
Include web search in multi-turn conversations:
```typescript title="TypeScript" expandable lines theme={null}
const response = await fetch('https://openrouter.ai/api/v1/responses', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'openai/o4-mini',
input: [
{
type: 'message',
role: 'user',
content: [
{
type: 'input_text',
text: 'What is the latest version of React?',
},
],
},
{
type: 'message',
id: 'msg_1',
status: 'in_progress',
role: 'assistant',
content: [
{
type: 'output_text',
text: 'Let me search for the latest React version.',
annotations: [],
},
],
},
{
type: 'message',
role: 'user',
content: [
{
type: 'input_text',
text: 'Yes, please find the most recent information',
},
],
},
],
plugins: [{ id: 'web', max_results: 2 }],
max_output_tokens: 9000,
}),
});
const result = await response.json();
console.log(result);
```
```python title="Python" expandable lines theme={null}
import requests
response = requests.post(
'https://openrouter.ai/api/v1/responses',
headers={
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
json={
'model': 'openai/o4-mini',
'input': [
{
'type': 'message',
'role': 'user',
'content': [
{
'type': 'input_text',
'text': 'What is the latest version of React?',
},
],
},
{
'type': 'message',
'id': 'msg_1',
'status': 'in_progress',
'role': 'assistant',
'content': [
{
'type': 'output_text',
'text': 'Let me search for the latest React version.',
'annotations': [],
},
],
},
{
'type': 'message',
'role': 'user',
'content': [
{
'type': 'input_text',
'text': 'Yes, please find the most recent information',
},
],
},
],
'plugins': [{'id': 'web', 'max_results': 2}],
'max_output_tokens': 9000,
}
)
result = response.json()
print(result)
```
## Streaming Web Search
Monitor web search progress with streaming:
```typescript title="TypeScript" expandable lines theme={null}
const response = await fetch('https://openrouter.ai/api/v1/responses', {
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'openai/o4-mini',
input: [
{
type: 'message',
role: 'user',
content: [
{
type: 'input_text',
text: 'What is the latest news about AI?',
},
],
},
],
plugins: [{ id: 'web', max_results: 2 }],
stream: true,
max_output_tokens: 9000,
}),
});
const reader = response.body?.getReader();
const decoder = new TextDecoder();
while (true) {
const { done, value } = await reader.read();
if (done) break;
const chunk = decoder.decode(value);
const lines = chunk.split('\n');
for (const line of lines) {
if (line.startsWith('data: ')) {
const data = line.slice(6);
if (data === '[DONE]') return;
try {
const parsed = JSON.parse(data);
if (parsed.type === 'response.output_item.added' &&
parsed.item?.type === 'message') {
console.log('Message added');
}
if (parsed.type === 'response.completed') {
const annotations = parsed.response?.output
?.find(o => o.type === 'message')
?.content?.find(c => c.type === 'output_text')
?.annotations || [];
console.log('Citations:', annotations.length);
}
} catch (e) {
// Skip invalid JSON
}
}
}
}
```
```python title="Python" expandable lines theme={null}
import requests
import json
response = requests.post(
'https://openrouter.ai/api/v1/responses',
headers={
'Authorization': 'Bearer YOUR_OPENROUTER_API_KEY',
'Content-Type': 'application/json',
},
json={
'model': 'openai/o4-mini',
'input': [
{
'type': 'message',
'role': 'user',
'content': [
{
'type': 'input_text',
'text': 'What is the latest news about AI?',
},
],
},
],
'plugins': [{'id': 'web', 'max_results': 2}],
'stream': True,
'max_output_tokens': 9000,
},
stream=True
)
for line in response.iter_lines():
if line:
line_str = line.decode('utf-8')
if line_str.startswith('data: '):
data = line_str[6:]
if data == '[DONE]':
break
try:
parsed = json.loads(data)
if (parsed.get('type') == 'response.output_item.added' and
parsed.get('item', {}).get('type') == 'message'):
print('Message added')
if parsed.get('type') == 'response.completed':
output = parsed.get('response', {}).get('output', [])
message = next((o for o in output if o.get('type') == 'message'), {})
content = message.get('content', [])
text_content = next((c for c in content if c.get('type') == 'output_text'), {})
annotations = text_content.get('annotations', [])
print(f'Citations: {len(annotations)}')
except json.JSONDecodeError:
continue
```
## Annotation Processing
Extract and process citation information:
```typescript title="TypeScript" lines theme={null}
function extractCitations(response: any) {
const messageOutput = response.output?.find((o: any) => o.type === 'message');
const textContent = messageOutput?.content?.find((c: any) => c.type === 'output_text');
const annotations = textContent?.annotations || [];
return annotations
.filter((annotation: any) => annotation.type === 'url_citation')
.map((annotation: any) => ({
url: annotation.url,
text: textContent.text.slice(annotation.start_index, annotation.end_index),
startIndex: annotation.start_index,
endIndex: annotation.end_index,
}));
}
const result = await response.json();
const citations = extractCitations(result);
console.log('Found citations:', citations);
```
```python title="Python" expandable lines theme={null}
def extract_citations(response_data):
output = response_data.get('output', [])
message_output = next((o for o in output if o.get('type') == 'message'), {})
content = message_output.get('content', [])
text_content = next((c for c in content if c.get('type') == 'output_text'), {})
annotations = text_content.get('annotations', [])
text = text_content.get('text', '')
citations = []
for annotation in annotations:
if annotation.get('type') == 'url_citation':
citations.append({
'url': annotation.get('url'),
'text': text[annotation.get('start_index', 0):annotation.get('end_index', 0)],
'start_index': annotation.get('start_index'),
'end_index': annotation.get('end_index'),
})
return citations
result = response.json()
citations = extract_citations(result)
print(f'Found citations: {citations}')
```
## Best Practices
1. **Limit results**: Use appropriate `max_results` to balance quality and speed
2. **Handle annotations**: Process citation annotations for proper attribution
3. **Query specificity**: Make search queries specific for better results
4. **Error handling**: Handle cases where web search might fail
5. **Rate limits**: Be mindful of search rate limits
## Next Steps
* Learn about [Tool Calling](./tool-calling) integration
* Explore [Reasoning](./reasoning) capabilities
* Review [Basic Usage](./basic-usage) fundamentals