44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
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from typing import Any, List, Optional
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from langchain_core.callbacks import CallbackManagerForRetrieverRun
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from langchain_core.documents import Document
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from langchain_core.retrievers import BaseRetriever
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from pydantic import model_validator
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class MetalRetriever(BaseRetriever):
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"""`Metal API` retriever."""
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client: Any
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"""The Metal client to use."""
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params: Optional[dict] = None
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"""The parameters to pass to the Metal client."""
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@model_validator(mode="before")
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@classmethod
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def validate_client(cls, values: dict) -> Any:
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"""Validate that the client is of the correct type."""
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from metal_sdk.metal import Metal
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if "client" in values:
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client = values["client"]
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if not isinstance(client, Metal):
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raise ValueError(
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"Got unexpected client, should be of type metal_sdk.metal.Metal. "
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f"Instead, got {type(client)}"
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)
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values["params"] = values.get("params", {})
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return values
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def _get_relevant_documents(
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self, query: str, *, run_manager: CallbackManagerForRetrieverRun
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) -> List[Document]:
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results = self.client.search({"text": query}, **self.params)
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final_results = []
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for r in results["data"]:
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metadata = {k: v for k, v in r.items() if k != "text"}
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final_results.append(Document(page_content=r["text"], metadata=metadata))
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return final_results
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