Contextual Reranker
This is a Llama_index package that calls Contextual's /rerank endpoint. It will rank a list of documents according to their relevance to a query.
The total request cannot exceed 400,000 tokens. The combined length of any document, instruction and the query must not exceed 4,000 tokens. Email rerank-feedback@contextual.ai with any feedback or questions.
Usage
from llama_index.postprocessor.contextual_rerank import ContextualRerank
from llama_index.core.schema import NodeWithScore, TextNode
nodes = [
NodeWithScore(node=TextNode(text="the capital of france is paris")),
NodeWithScore(
node=TextNode(text="the capital of the United States is Washington DC")
),
]
query = "What is the capital of France?"
contextual_rerank = ContextualRerank(
api_key="key-...",
model="ctxl-rerank-en-v1-instruct",
top_n=2,
)
response = contextual_rerank.postprocess_nodes(nodes, query_str=query)
for node in response:
print(node)
1 maintainer
Metadata
1 maintainer
Release files for llama-index-postprocessor-contextual-rerank 0.4.0
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Release files / llama_index_postprocessor_contextual_rerank-0.4.0.tar.gz
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Release files / llama_index_postprocessor_contextual_rerank-0.4.0-py3-none-any.whl
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