Python SDK for the Verdikt Evaluation API
Project description
verdikt-sdk
Python SDK for Verdikt — a standalone AI evaluation service that decouples evaluation and LLM/human judging from the application being evaluated.
Installation
pip install verdikt-sdk
Usage
from verdikt_sdk import EvaluationClient
from verdikt_sdk.models import EvaluationType, Question
from yalc import LLMModel
client = EvaluationClient(
base_url="https://your-verdikt-instance.com",
client_id="your-client-id",
client_secret="your-client-secret",
)
# Register your app (idempotent — safe to call on every deploy)
await client.create_app(slug="my-app", name="My App")
# Sync questions to the dataset (idempotent)
await client.add_questions("my-app", [
Question(question="What is the capital of France?", human_answer="Paris"),
])
# Run an evaluation cycle
await client.run_evaluation(
app_slug="my-app",
app_version="v1.2.0",
callback=my_llm_function, # async fn(question: str) -> str
evaluation_type=EvaluationType.LLM_ONLY,
llm_judge_models=[LLMModel.gpt_4o_mini],
)
run_evaluation calls your callback concurrently for every question in the dataset, then submits all answers to Verdikt for judgment.
Authentication
The SDK authenticates via Zitadel OAuth2 client credentials. Create a machine user in your Zitadel project and pass its client_id and client_secret to EvaluationClient.
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