rilixai
Rilix AI SDK and CLI package.
rilixai gives developers the tools to define optimization specs,
validate them locally, upload datasets, configure hosted run environments,
launch optimization runs, and inspect results from code or the CLI.
Customer specs import contract types directly from rilixai:
from rilixai import Case, CaseDataLoader, CaseResult, CaseScore, Spec, spec
Hosted model-selection rollouts also expose a generic OpenAI-compatible target:
from rilixai import RolloutContext, inference_target
def build_eval_client(runtime: RolloutContext):
target = inference_target(runtime)
return YourFrameworkClient(
base_url=target.base_url,
api_key=target.api_key,
model=target.model,
)
Call inference_target only in the evaluation path when runtime.model is
set. Ordinary dry-runs and production application calls should retain the
application's existing model and client defaults.
Metadata
Release files for rilixai 0.3.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rilixai-0.3.3.tar.gz | 112.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rilixai-0.3.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 247.8 kB
Release files / rilixai-0.3.3.tar.gz
| Download URL | rilixai-0.3.3.tar.gz |
|---|---|
| Size | 112.4 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / rilixai-0.3.3-py3-none-any.whl
| Download URL | rilixai-0.3.3-py3-none-any.whl |
|---|---|
| Size | 135.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
uv/0.9.4
|