Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Search the web and get AI-synthesized answers with cited sources.
POST https://www.ninjachat.ai/api/v1/search
Authorization: Bearer nj_sk_YOUR_API_KEY
Content-Type: application/json
{
"query": "latest developments in AI safety",
"include_answer": true,
"max_results": 10
}
{
"object": "search.results",
"query": "latest developments in AI safety",
"answer": "Recent developments in AI safety include...",
"sources": [
{
"url": "https://example.com/article",
"title": "AI Safety Progress in 2026",
"content": "Summary of the article...",
"published_date": "2026-03-01"
}
],
"images": [],
"follow_up_questions": [
"What are the key AI safety organizations?",
"How does RLHF improve AI safety?"
],
"provider": "...",
"cost_usd": 0.05,
"request_id": "req_..."
}
answer (null when include_answer is false). Sources are in sources[]; published_date is null when the source has no date. images is a list of { url, description } populated when include_images is true. provider names the search backend that served the request, and cost_usd is the flat per-query price.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
query | string | Yes | — | Search query. Max 2,000 chars. |
group | string | No | web | web or news |
max_results | integer | No | 10 | Number of sources (1–20) |
search_depth | string | No | basic | basic (fast) or advanced (deeper) |
topic | string | No | general | general, news, or finance |
include_answer | boolean | No | true | Generate an AI-synthesized answer |
include_images | boolean | No | false | Include image results |
result = client.search.query(
query="latest developments in AI safety",
group="news",
search_depth="advanced",
include_answer=True,
max_results=10,
)
print(result["answer"])
for source in result["sources"][:3]:
print(f"- {source['title']}: {source['url']}")
const result = await client.search.query({
query: "latest developments in AI safety",
group: "news",
search_depth: "advanced",
include_answer: true,
max_results: 10,
});
console.log(result.answer);
for (const source of result.sources.slice(0, 3)) {
console.log(`- ${source.title}: ${source.url}`);
}
curl https://www.ninjachat.ai/api/v1/search \
-H "Authorization: Bearer $NINJACHAT_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query":"latest developments in AI safety",
"group":"news",
"search_depth":"advanced",
"include_answer":true,
"max_results":10
}'
| Group | What it searches | Use for |
|---|---|---|
web | General web | Default. Most use cases. |
news | Recent news articles | News aggregation, current events |
# 1. Search for context
results = client.search.query(query="What is quantum computing?")
# 2. Feed to a chat model with sources as context
context = "\n".join(f"- {s['title']}: {s['content']}" for s in results["sources"][:5])
response = client.responses.create(
model="gpt-5.6-luna",
instructions=f"Answer using these sources:\n{context}",
input="Explain quantum computing with citations",
)
print(response["output_text"])