from basalt import Basalt
from basalt.observability import ObserveKind, observe, start_observe

basalt = Basalt(
    api_key="your-api-key",
    enabled_instruments=["openai", "chromadb"],  # optional
)

@observe(name="Retrieve", kind=ObserveKind.RETRIEVAL)
def retrieve(query: str) -> list[str]:
    # Your vector DB call here (auto-instrumented if enabled)
    return ["doc1", "doc2"]

@observe(name="Generate", kind=ObserveKind.GENERATION)
def generate(query: str, docs: list[str]) -> str:
    # Your LLM call here (auto-instrumented if enabled)
    return "..."

@start_observe(feature_slug="qa", name="Answer question")
def answer(question: str) -> str:
    docs = retrieve(question)
    return generate(question, docs)

prompt = basalt.prompts.get_sync(
    slug="support-answer",
    tag="production",
    variables={"question": question, "context": "\\n".join(docs)},
)
output = call_llm(prompt.text)

from basalt.observability import EvaluationConfig, evaluator, start_observe

@evaluator(slugs=["quality", "toxicity"], config=EvaluationConfig(sample_rate=0.1))
@start_observe(feature_slug="support", name="Handle request")
def handle_request(...):
    ...