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import weave
from ..retrieval import SimilarityMetric
from .llm_client import LLMClient
class MedQAAssistant(weave.Model):
"""Cuming"""
llm_client: LLMClient
retriever: weave.Model
top_k_chunks: int = 2
retrieval_similarity_metric: SimilarityMetric = SimilarityMetric.COSINE
@weave.op()
def predict(self, query: str) -> str:
retrieved_chunks = self.retriever.predict(
query, top_k=self.top_k_chunks, metric=self.retrieval_similarity_metric
)
retrieved_chunks = [chunk["text"] for chunk in retrieved_chunks]
system_prompt = """
You are a medical expert. You are given a query and a list of chunks from a medical document.
"""
return self.llm_client.predict(
system_prompt=system_prompt, user_prompt=retrieved_chunks
)
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