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Agent search

AgentSearchReader #

Bases: BaseReader

AgentSearch reader.

Source code in llama-index-integrations/readers/llama-index-readers-agent-search/llama_index/readers/agent_search/base.py 
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class AgentSearchReader(BaseReader):
    """AgentSearch reader."""

    def __init__(
        self,
        api_base: Optional[str] = None,
        api_key: Optional[str] = None,
    ):
        """Initialize with parameters."""
        import_err_msg = (
            "`agent-search` package not found, please run `pip install agent-search`"
        )
        try:
            import agent_search  # noqa: F401
        except ImportError:
            raise ImportError(import_err_msg)

        from agent_search import SciPhi

        self._client = SciPhi(api_base=api_base, api_key=api_key)

    def load_data(
        self,
        query: str,
        search_provider: str = "bing",
        llm_model: str = "SciPhi/Sensei-7B-V1",
    ) -> List[Document]:
        """
        Load data from AgentSearch, hosted by SciPhi.

        Args:
            collection_name (str): Name of the Milvus collection.
            query_vector (List[float]): Query vector.
            limit (int): Number of results to return.

        Returns:
            List[Document]: A list of documents.
        """
        rag_response = self._client.get_search_rag_response(
            query=query, search_provider=search_provider, llm_model=llm_model
        )
        return [Document(text=rag_response.pop("response"), metadata=rag_response)]

load_data #

load_data(query: str, search_provider: str = 'bing', llm_model: str = 'SciPhi/Sensei-7B-V1') -> List[Document]

Load data from AgentSearch, hosted by SciPhi.

Parameters:

Name Type Description Default
collection_name str

Name of the Milvus collection.

 required
query_vector List[float]

Query vector.

 required
limit int

Number of results to return.

 required

Returns:

Type Description
List[Document]

List[Document]: A list of documents.
Source code in llama-index-integrations/readers/llama-index-readers-agent-search/llama_index/readers/agent_search/base.py 
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def load_data(
    self,
    query: str,
    search_provider: str = "bing",
    llm_model: str = "SciPhi/Sensei-7B-V1",
) -> List[Document]:
    """
    Load data from AgentSearch, hosted by SciPhi.

    Args:
        collection_name (str): Name of the Milvus collection.
        query_vector (List[float]): Query vector.
        limit (int): Number of results to return.

    Returns:
        List[Document]: A list of documents.
    """
    rag_response = self._client.get_search_rag_response(
        query=query, search_provider=search_provider, llm_model=llm_model
    )
    return [Document(text=rag_response.pop("response"), metadata=rag_response)]