Self-contained, runnable scripts that exercise the graphn Python
SDK against a real Graphn workspace. Each one is meant to be
copied + pasted into your editor and modified — they're not part of
the SDK's test suite.
v0.1.x covers custom-model import (HuggingFace + S3) and OpenAI-compatible inference only. Agents, knowledge bases, workflows, evals, datasets, and guardrails are not yet exposed through this SDK — see the main README scope section for the full list of what's in / out.
All examples expect the workspace credentials in the environment:
export GRAPHN_API_KEY=gn_...
export GRAPHN_WORKSPACE_ID=ws_...
pip install graphn
python examples/import_and_chat.py| Example | What it shows |
|---|---|
import_and_chat.py |
Full lifecycle from HuggingFace: validate → create → wait → chat → delete. The "hello world" of the SDK. |
import_from_s3.py |
Import weights from S3 — presigned URL or assume-role flavor — then chat. |
streaming.py |
Streaming chat completions (server-sent events). |
async_client.py |
Async equivalent of import_and_chat.py using graphn.AsyncClient. |
openai_compat.py |
Calling Graphn from the official openai Python SDK directly, for migrating existing code. |
If you want to add an example, keep it under ~80 lines, self-contained,
and runnable with a single python examples/your_example.py.