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Updated 3 months ago

how can I include a reranker in my retriever?

how can I include a reranker in my retriever?
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Please stand by @theoxd as I search the knowledge base. I normally take about 20 seconds or so. :wave:
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To include a reranker in your retriever, you need to set up a query engine with a reranker. Here are some examples of how to do this using different rerankers:

  1. LLMRerank: This reranker uses a Language Model (LLM) to rerank the retrieved nodes. Here's an example of how to set it up:
Plain Text
from llama_index import ServiceContext, VectorStoreIndex
from llama_index.postprocessor import LLMRerank
from llama_index.query_engine import RetrieverQueryEngine
from llama_index.retrievers import VectorIndexRetriever
from llama_index.vector_stores.google.generativeai import GoogleVectorStore, google_service_context
from llama_index.response_synthesizers.google.generativeai import GoogleTextSynthesizer

store = GoogleVectorStore.from_corpus(corpus_id=SESSION_CORPUS_ID)
index = VectorStoreIndex.from_vector_store(vector_store=store, service_context=google_service_context)

response_synthesizer = GoogleTextSynthesizer.from_defaults(temperature=0.2, answer_style=GenerateAnswerRequest.AnswerStyle.ABSTRACTIVE)

reranker = LLMRerank(
    top_n=10,
    service_context=ServiceContext.from_defaults(llm=gemini, embed_model=None),
)

query_engine = RetrieverQueryEngine.from_args(
    retriever=VectorIndexRetriever(index=index, similarity_top_k=20),
    node_postprocessors=[reranker],
    response_synthesizer=response_synthesizer,
)

(Source: GitHub ())

  1. SentenceTransformerRerank: This reranker uses a Sentence Transformer model for reranking. Here's an example of how to set it up:
Plain Text
from llama_index.postprocessor import SentenceTransformerRerank

reranker = SentenceTransformerRerank(top_n=4, model="BAAI/bge-reranker-base")

(Source: GitHub ())
After setting up the reranker, you can use it in your query engine as shown in the first example. The node_postprocessors argument of the RetrieverQueryEngine.from_args method is where you pass in the reranker.

Remember to replace SESSION_CORPUS_ID and gemini with your actual corpus ID and LLM, respectively.
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