Rerank

Introduction

Rerank is a semantic search tool that improves search quality with a semantic-based reranking system which can contextualize the meaning of a user’s query beyond keyword relevance. This tool works best with look up tool as a ranker after the initial retrieval. The list of current supported ranking method is as follows.

Name	Description
BM25	BM25 is an open source ranking algorithm to measure the relevance of documents to a given query
Scaled Score Fusion	Scaled Score Fusion calculates a scaled relevance score.
Cohere Rerank	Cohere Rerank is the market’s leading reranking model used for semantic search and retrieval-augmented generation (RAG).

Requirements

• For AzureML users, the tool is installed in default image, you can use the tool without extra installation.

• For local users,

  pip install promptflow-vectordb

Prerequisites

BM25 and Scaled Score Fusion are included as default reranking methods. To use cohere rerank model, you should create serverless deployment to the model, and establish connection between the tool and the resource as follows.

• Add Serverless Model connection. Fill “API base” and “API key” field to your serverless deployment.

Inputs

Name	Type	Description	Required
query	string	the question relevant to your input documents	Yes
ranker_parameters	string	the type of ranking methods to use	Yes
result_groups	object	the list of document chunks to rerank. Normally this is output from lookup	Yes
top_k	int	the maximum number of relevant documents to return	No

Outputs

Return Type	Description
text	text of the entity
metadata	metadata like file path and url
additional_fields	metadata and rerank score

Output

[
  {
      "text": "sample text",
      "metadata":
      {
          "filepath": "sample_file_path",
          "metadata_json_string": "meta_json_string"
          "title": "",
          "url": ""
      },
      "additional_fields":
      {
          "filepath": "sample_file_path",
          "metadata_json_string": "meta_json_string"
          "title": "",
          "url": "",
          "@promptflow_vectordb.reranker_score": 0.013795365
      }
  }
]