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Streaming RAG

Streaming RAG is an architectural pattern that delivers incremental LLM response chunks to the end-user in real-time as they are generated, rather than waiting for the complete synthesis of retrieved context into a final answer. This optimizes the Time to First Token (TTFT) by bypassing the linear bottleneck of full-sequence generation in conversational AI agents.

Definition

Streaming RAG is an architectural pattern that delivers incremental LLM response chunks to the end-user in real-time as they are generated, rather than waiting for the complete synthesis of retrieved context into a final answer. This optimizes the Time to First Token (TTFT) by bypassing the linear bottleneck of full-sequence generation in conversational AI agents.

Disambiguation

Refers to the incremental delivery of response tokens, not real-time data ingestion into a vector database.

Visual Metaphor

"A digital ticker tape displaying a message character-by-character as it is typed, rather than waiting for a full telegram to be printed and delivered."

Key Tools
LangChain (LCEL)LlamaIndexFastAPI (StreamingResponse)OpenAI SDK (stream=True)Server-Sent Events (SSE)
Related Connections

Conceptual Overview

Streaming RAG is an architectural pattern that delivers incremental LLM response chunks to the end-user in real-time as they are generated, rather than waiting for the complete synthesis of retrieved context into a final answer. This optimizes the Time to First Token (TTFT) by bypassing the linear bottleneck of full-sequence generation in conversational AI agents.

Disambiguation

Refers to the incremental delivery of response tokens, not real-time data ingestion into a vector database.

Visual Analog

A digital ticker tape displaying a message character-by-character as it is typed, rather than waiting for a full telegram to be printed and delivered.

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