Streaming

Stream tokens from a chat completion as they arrive

Stream LLM responses token by token with a unified async interface that works across Claude, OpenAI, and Ollama without changing your code.

Edition

Community — runs on the OSS / Community SDK edition.

What this demonstrates

Difficulty: Intermediate 🟦 · LLM · Streaming

• Summary: Streaming chat completion with real-time output
• Scenario: Stream tokens from a chat completion as they arrive
• tech_tags in manifest: LLM, Streaming — example id streaming in conformance/examples_manifest.json.

Prerequisites

• SDK: Use an installed SDK tree (NXUSKIT_SDK_DIR, NXUSKIT_LIB_PATH as needed); test-examples.sh resolves Go/Rust/Python deps from that tree only — see README.md, scripts/setup-sdk.sh, and scripts/test-examples.sh.
• Languages in this example: go, python, rust (paths under this directory; Python may live under a sibling python/ or shared reference per Language Implementations).
• Models: Set cloud provider API keys and/or run Ollama locally when you execute the Run steps (interactive flags like --help / --verbose are documented below).

Real-World Application

Real-time chat interface, live transcription display

Technologies

LLM, Streaming

Language Implementations

Language	Path	Status
Rust	rust/	Available
Go	go/	Available
Python	python/	Available

Build

Attach an installed SDK (NXUSKIT_SDK_DIR). See the repository README.md and scripts/test-examples.sh.

# From `/examples/patterns/streaming`:
cd rust && cargo build
cd go && make build
cd python && python3 main.py --help

Run

Rust

cd rust
cargo run

Go

cd go
make build && bin/streaming

Python

cd python
python main.py