Principle:Mistralai Client python Streaming Chat Completion
| Knowledge Sources | |
|---|---|
| Domains | NLP, Streaming, LLM_Inference |
| Last Updated | 2026-02-15 14:00 GMT |
Overview
A streaming interaction pattern that receives language model output incrementally via Server-Sent Events, enabling real-time token-by-token display.
Description
Streaming Chat Completion extends the standard chat completion pattern by returning tokens incrementally as they are generated, rather than waiting for the complete response. This uses the Server-Sent Events (SSE) protocol over HTTP, where the server sends a stream of events containing partial response chunks. Each chunk contains a delta with the next token(s). This pattern significantly reduces perceived latency for end users, as they see output appearing in real-time.
Usage
Use this principle when building interactive chat interfaces, real-time assistants, or any application where the user benefits from seeing the response as it is generated. Not appropriate for batch processing or when the full response is needed before any processing occurs.
Theoretical Basis
Streaming uses the SSE protocol:
- Client sends a POST request with stream: true
- Server responds with Content-Type: text/event-stream
- Each SSE event contains a JSON-encoded chunk with delta.content
- A final chunk with finish_reason signals completion
- The connection closes after the final event
# Pseudocode for streaming consumption
for event in sse_stream:
delta = event.data.choices[0].delta
if delta.content:
display(delta.content) # Show token immediately
if event.data.choices[0].finish_reason:
break
stream.close()