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llama-index postprocessor dashscope-rerank integration

Project description

LlamaIndex Postprocessor Integration: DashScope-Rerank

The llama-index-postprocessor-dashscope-rerank package contains LlamaIndex integrations for the gte-rerank series models provided by Alibaba Tongyi Laboratory.

Installation

pip install --upgrade llama-index llama-index-core llama-index-postprocessor-dashscope-rerank

Setup

Get started:

  1. Obtain the API-KEY from the Alibaba Cloud ModelStudio platform.
  2. Set API-KEY
export DASHSCOPE_API_KEY=YOUR_DASHSCOPE_API_KEY

Example:

from llama_index.core.data_structs import Node
from llama_index.core.schema import NodeWithScore
from llama_index.postprocessor.dashscope_rerank import DashScopeRerank

nodes = [
    NodeWithScore(node=Node(text="text1"), score=0.7),
    NodeWithScore(node=Node(text="text2"), score=0.8),
]

dashscope_rerank = DashScopeRerank(top_n=5)
results = dashscope_rerank.postprocess_nodes(nodes, query_str="<user query>")
for res in results:
    print("Text: ", res.node.get_content(), "Score: ", res.score)

output

Text:  text1 Score:  0.25589250620997755
Text:  text2 Score:  0.18071043165292258

Parameters

Name Type Description Default
model str model name gte-rerank
top_n int The number of top documents to be returned in the ranking; if not specified, all candidate documents will be returned. If the specified top_n value exceeds the number of input candidate documents, all documents will be returned. 3
return_documents bool Whether to return the original text for each document in the returned sorted result list, with the default value being False. False
api_key str The DashScope api key. None

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