EvaluatorModel.predict:v10
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import weave
rag_engine = weave.storage.artifact_path_ref('rag_engine').get()
@weave.op()
async def get_eval_record(
question: str,
) -> dict:
response = await rag_engine.agenerate(question)
sources = response["sources"]
sources = [source["highlights"][0] for source in sources]
return {
"generated_answer": response["answer"],
"retrieved_contexts": sources,
"answer_in_context": response["answerInContext"],
}
@weave.op()
async def predict(self, question: str) -> dict:
# Model logic goes here
prediction = await get_eval_record(question)
return prediction