Self-hostable LLM client
for restaurant tech.
A thin Python library that talks to any OpenAI-compatible /v1/chat/completions endpoint — with menu Q&A, dish classification, and order parsing built on top. No vendor lock-in. No egress you don't control.
from chenki import ChenkiClient
client = ChenkiClient() # free HF Space by default
answer = client.ask_about_menu(
menu, "any nut-free desserts?"
)
print(answer.text)Restaurant-domain helpers
Not another chat wrapper.
The primitives a restaurant actually ships — typed, testable, and built on top of any model you point it at.
ask_about_menuMenu Q&A
Answer guest questions against your menu — allergens, pairings, substitutions — grounded in your data, not the model's guesses.
classify_dishDish classification
Tag dishes by cuisine, course, dietary flags. Returns typed dataclasses.
parse_order_textOrder parsing
Turn free-text orders into structured line items.
prompt-injection-safeSafe by default
Helpers wrap user text in guarded prompts, so a hostile menu note can't hijack the model.
Get started
Install in one line.
One runtime dependency (httpx). Python 3.10+.
30-second example
from chenki import ChenkiClient, Message
client = ChenkiClient()
reply = client.chat([Message(role="user", content="Hello!")])
print(reply.text)Live backend
Try it right here.
The default backend is a free Hugging Face Space running Qwen 2.5 1.5B Instruct (Q4_K_M) behind llama.cpp. Cold start ~30 s; ~20 tok/s after.
Embedded from huggingface.co/spaces/brianchenhao/chenki-llm
Architecture
How it works.
Install the client
pip install chenki. One runtime dep (httpx). No vendor SDK lock-in.
Point at any OpenAI-compatible endpoint
ChenkiClient() defaults to the free chenki-llm Space. Or pass your own — Ollama, vLLM, llama.cpp, LM Studio, or OpenAI itself.
Use the restaurant helpers
ask_about_menu, classify_dish, parse_order_text — typed dataclasses, prompt-injection-safe by default.
Your app
Adopter's Python
- ChenkiClient
- ask_about_menu
- classify_dish
chenki-llm · HF Space
Any OpenAI backend
- Qwen 2.5 1.5B Q4_K_M
- llama.cpp :server
- OpenAI-compatible API
Self-hosters deploy their own Space with the included server/Dockerfile — same image, same API, zero third-party egress.
chenki.com · coming soon
Be first in line.
Hosted playground, managed endpoints, and a proper dashboard are on the way. Drop your email and we'll let you in early.
No spam. One email at launch, then nothing else.