List of Queries for vector search with Elasticsearch

[jais001]

I Have a list of queries and want to perform a semantic search on all these queries. Normally I would have to write a for loop to perform a semantic search on all these queries individually. Are there any retrievers in langchain that will take a list of queries to perform a semantic search on elasticsearch?

[dosubot[bot]]

🤖

Yes, LangChain does provide a way to perform a semantic search on a list of queries in Elasticsearch without having to use a for loop for individual queries. The MultiQueryRetriever class in LangChain is designed to handle multiple queries at once.

Here is a brief overview of how it works:

1. The MultiQueryRetriever class is initialized with a BaseRetriever instance, an LLMChain instance, a boolean for verbosity, and a parser key.

2. It has a method generate_queries that takes a user query as input and generates a list of similar queries using the language model chain (llm_chain).

3. The retrieve_documents method takes this list of queries and retrieves documents for each query using the retriever.

4. Finally, the unique_union method takes a list of documents and returns a list of unique documents.

Here is the relevant code:

class MultiQueryRetriever(BaseRetriever):
    retriever: BaseRetriever
    llm_chain: LLMChain
    verbose: bool = True
    parser_key: str = "lines"

    def generate_queries(
        self, question: str, run_manager: CallbackManagerForRetrieverRun
    ) -> List[str]:
        response = self.llm_chain(
            {"question": question}, callbacks=run_manager.get_child()
        )
        lines = getattr(response["text"], self.parser_key, [])
        if self.verbose:
            logger.info(f"Generated queries: {lines}")
        return lines

    def retrieve_documents(
        self, queries: List[str], run_manager: CallbackManagerForRetrieverRun
    ) -> List[Document]:
        documents = []
        for query in queries:
            docs = self.retriever.get_relevant_documents(
                query, callbacks=run_manager.get_child()
            )
            documents.extend(docs)
        return documents

    def unique_union(self, documents: List[Document]) -> List[Document]:
        return _unique_documents(documents)

    def _get_relevant_documents(
        self,
        query: str,
        *,
        run_manager: CallbackManagerForRetrieverRun,
    ) -> List[Document]:
        queries = self.generate_queries(query, run_manager)
        documents = self.retrieve_documents(queries, run_manager)
        return self.unique_union(documents)

You can find more details in the MultiQueryRetriever class implementation.

Please note that while MultiQueryRetriever can handle multiple queries at once, you would need to check its specific implementation or documentation to confirm if it supports semantic search with Elasticsearch.

Sources

• libs/langchain/langchain/retrievers/init.py
• libs/langchain/langchain/vectorstores/elasticsearch.py
• libs/langchain/langchain/retrievers/multi_query.py

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