OpenAI-compatible answers grounded in the live web
Stream cited factual answers with zero prompt engineering or fragile search tool loops. Save up to 80% of agent context window tokens.
from parallel import Parallel
client = Parallel(api_key="PARALLEL_API_KEY")
# Drop-in synthesized research with OpenAI compatibility
response = client.responses.create(
question="Compare Apple M4 Max memory bandwidth and unified architecture to Nvidia RTX 5090",
stream=True
)
for chunk in response:
print(chunk.delta, end="", flush=True)
print("\n\nVerified Citations:")
for citation in response.citations:
print(f"[{citation.id}] {citation.title} - {citation.url}")Why developers choose Responses API
Drop-in OpenAI Compatibility
Switch the base URL in your existing LangChain, LlamaIndex, or OpenAI SDK setup and get instant web research without code rewrites.
Context Window Optimization
Eliminate 30,000+ tokens of raw HTML search results. Responses API returns concise, cited prose consuming under 800 tokens.
Real-Time Streaming
First token latency in under 1.5 seconds with Server-Sent Events (SSE) streaming directly into your conversational chat UI.
Verifiable Inline Footnotes
Every factual claim includes bracketed footnote citations linking to primary source publisher pages with Basis confidence scores.
Built for enterprise, secure by design
SOC 2 Type II certified, GDPR compliant, and strict Zero Data Retention (ZDR) guarantees. Your confidential queries and internal data never touch model training.