perplexity-apiPerplexity API gives LLM answers grounded in live web search, with cited sources. Use when you need up-to-date information in AI responses, research assistants, fact-checking, current events coverage, or any task requiring knowledge beyond an LLM's training cutoff. Returns cited sources alongside answers.
Independent GitHub snapshot · Automated classification · Original documentation governs
Perplexity's API returns LLM answers grounded in live web search, with citations. Sonar Chat Completions (/chat/completions, models sonar, sonar-pro, sonar-reasoning-pro) reached end of support on 27 September 2026: sync and streaming calls are still being served by reformulating them as Agent API requests, but async requests no longer work. New code should use the Agent API (client.responses.create). sonar-reasoning and r1-1776 are deprecated.
pip install perplexityai # Python
npm install @perplexity-ai/perplexity_ai # TypeScript
export PERPLEXITY_API_KEY="pplx-..." # read automatically by the SDK
Pick a preset (tuned model + search depth) or a specific model.
from perplexity import Perplexity
client = Perplexity() # uses PERPLEXITY_API_KEY
response = client.responses.create(
preset="fast",
input="What changed in the latest Python release?",
)
print(response.output_text)
| Preset | Replaces | Tools | Use for |
|---|---|---|---|
fast | sonar, sonar-pro | web_search | quick factual lookups, minimal latency |
low | sonar-reasoning-pro | web_search, fetch_url | everyday questions needing current info |
medium | (new) | web_search, fetch_url | multi-step research across many sources |
high | sonar-deep-research | web_search, fetch_url | exhaustive, institutional-grade research |
xhigh | (new) | web_search, finance_search, sandbox | open-ended agentic work with code execution |
Presets are dynamic: Perplexity tunes the model behind each name over time. Copy a preset's values inline if you need frozen behavior, and override any single parameter (model, tools, max_steps) while keeping the rest.
response = client.responses.create(
model="openai/gpt-5.6-sol",
input="Summarize this week's AI regulation news in the EU.",
tools=[{"type": "web_search"}],
instructions="Use web_search for current events. Keep queries brief. Cite sources.",
max_output_tokens=2048,
)
print(response.output_text)
The Agent API also exposes models from Anthropic, Google and xAI under provider/model ids; check the models page for the current list.
print(response.output_text)
for r in response.search_results: # title, url, date, snippet
print(r.title, r.url)
# Inline citation annotations live on the message content
for item in response.output:
if item.type == "message":
for part in item.content:
for note in getattr(part, "annotations", []) or []:
print(note)
for event in client.responses.create(preset="fast", input="Top tech news today", stream=True):
if event.type == "response.output_text.delta":
print(event.delta, end="")
job = client.responses.create(preset="high", input="Full market analysis of EU battery makers", background=True)
Use background=True for long jobs and poll by response id; this replaces async Sonar requests.
# before
client.chat.completions.create(model="sonar", messages=[{"role": "user", "content": q}])
# after
client.responses.create(preset="fast", input=q)
messages/choices become input/output; max_tokens becomes max_output_tokens, search_domain_filter and search_recency_filter move into the web_search tool's filters, and reasoning_effort becomes reasoning.effort. search_language_filter, stream_mode, video results and regex response_format have no equivalent. Read text from response.output_text instead of choices[0].message.content. For multi-turn chats pass earlier turns in input as the docs describe for conversation context.
import Perplexity from '@perplexity-ai/perplexity_ai';
const client = new Perplexity();
const response = await client.responses.create({ preset: 'low', input: 'Compare Postgres 17 and 18 release notes' });
console.log(response.output_text);
Request: "Answer 'which EU countries passed AI laws this year' and list the sources."
response = client.responses.create(preset="low", input="Which EU countries passed national AI laws this year?")
print(response.output_text)
for r in response.search_results:
print("-", r.title, r.url)
Result: a cited paragraph, then one line per source page.
Request: "Make my lookup tolerant of 429s."
import time
import perplexity
def ask(q, retries=3):
for attempt in range(retries):
try:
return client.responses.create(preset="fast", input=q).output_text
except perplexity.RateLimitError:
time.sleep(2 ** attempt)
raise RuntimeError("rate limit retries exhausted")
Result: the call backs off 1s, 2s, 4s before giving up.
/chat/completions or the openai SDK with base_url="https://api.perplexity.ai"; it works only through a compatibility layer being phased out.fast is cheapest, high/xhigh cost far more.response.usage for cost.POST https://api.perplexity.ai/v1/agent.