# Rerankers ```json metadata { "title": "Rerankers", "description": "", "categories": null, "tableOfContents": {"sections":[{"children":[{"id":"using-the-cross-encoder-reranker","title":"Using the Cross-Encoder Reranker"},{"id":"rerank-documents-with-hfcrossencoderreranker","title":"Rerank documents with HFCrossEncoderReranker"},{"id":"using-the-cohere-reranker","title":"Using the Cohere Reranker"},{"id":"rerank-documents-with-coherereranker","title":"Rerank documents with CohereReranker"},{"id":"working-with-semi-structured-documents","title":"Working with semi-structured documents"},{"id":"using-the-voyageai-reranker","title":"Using the VoyageAI Reranker"},{"id":"rerank-documents-with-voyageaireranker","title":"Rerank documents with VoyageAIReranker"}],"id":"simple-reranking","title":"Simple Reranking"}]} , "codeExamples": [] } ``` In this notebook, we will show how to use RedisVL to rerank search results (documents or chunks or records) based on the input query. Today RedisVL supports reranking through: - A re-ranker that uses pre-trained [Cross-Encoders](https://sbert.net/examples/applications/cross-encoder/README.html) which can use models from [Hugging Face cross encoder models](https://huggingface.co/cross-encoder) or Hugging Face models that implement a cross encoder function ([example: BAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)). - The [Cohere /rerank API](https://docs.cohere.com/docs/rerank-2). - The [VoyageAI /rerank API](https://docs.voyageai.com/docs/reranker). Before running this notebook, be sure to: 1. Have installed ``redisvl`` and have that environment active for this notebook. 2. Have a running Redis Stack instance with RediSearch > 2.4 active. For example, you can run Redis Stack locally with Docker: ```bash docker run -d -p 6379:6379 -p 8001:8001 redis/redis-stack:latest ``` This will run Redis on port 6379 and RedisInsight at http://localhost:8001. ```python # import necessary modules import os ``` ## Simple Reranking Reranking provides a relevance boost to search results generated by traditional (lexical) or semantic search strategies. As a simple demonstration, take the passages and user query below: ```python query = "What is the capital of the United States?" docs = [ "Carson City is the capital city of the American state of Nevada. At the 2010 United States Census, Carson City had a population of 55,274.", "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that are a political division controlled by the United States. Its capital is Saipan.", "Charlotte Amalie is the capital and largest city of the United States Virgin Islands. It has about 20,000 people. The city is on the island of Saint Thomas.", "Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district. The President of the USA and many major national government offices are in the territory. This makes it the political center of the United States of America.", "Capital punishment (the death penalty) has existed in the United States since before the United States was a country. As of 2017, capital punishment is legal in 30 of the 50 states. The federal government (including the United States military) also uses capital punishment." ] ``` The goal of reranking is to provide a more fine-grained quality improvement to initial search results. With RedisVL, this would likely be results coming back from a search operation like full text or vector. ### Using the Cross-Encoder Reranker To use the cross-encoder reranker we initialize an instance of `HFCrossEncoderReranker` passing a suitable model (if no model is provided, the `cross-encoder/ms-marco-MiniLM-L-6-v2` model is used): ```python from redisvl.utils.rerank import HFCrossEncoderReranker cross_encoder_reranker = HFCrossEncoderReranker("BAAI/bge-reranker-base") ``` ### Rerank documents with HFCrossEncoderReranker With the obtained reranker instance we can rerank and truncate the list of documents based on relevance to the initial query. ```python results, scores = cross_encoder_reranker.rank(query=query, docs=docs) ``` ```python for result, score in zip(results, scores): print(score, " -- ", result) ``` 0.07461125403642654 -- {'content': 'Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district. The President of the USA and many major national government offices are in the territory. This makes it the political center of the United States of America.'} 0.05220315232872963 -- {'content': 'Charlotte Amalie is the capital and largest city of the United States Virgin Islands. It has about 20,000 people. The city is on the island of Saint Thomas.'} 0.3802368640899658 -- {'content': 'Carson City is the capital city of the American state of Nevada. At the 2010 United States Census, Carson City had a population of 55,274.'} ### Using the Cohere Reranker To initialize the Cohere reranker you'll need to install the cohere library and provide the right Cohere API Key. ```python #!pip install cohere ``` ```python import getpass # setup the API Key api_key = os.environ.get("COHERE_API_KEY") or getpass.getpass("Enter your Cohere API key: ") ``` ```python from redisvl.utils.rerank import CohereReranker cohere_reranker = CohereReranker(limit=3, api_config={"api_key": api_key}) ``` ### Rerank documents with CohereReranker Below we will use the `CohereReranker` to rerank and truncate the list of documents above based on relevance to the initial query. ```python results, scores = cohere_reranker.rank(query=query, docs=docs) ``` ```python for result, score in zip(results, scores): print(score, " -- ", result) ``` 0.9990564 -- Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district. The President of the USA and many major national government offices are in the territory. This makes it the political center of the United States of America. 0.7516481 -- Capital punishment (the death penalty) has existed in the United States since before the United States was a country. As of 2017, capital punishment is legal in 30 of the 50 states. The federal government (including the United States military) also uses capital punishment. 0.08882029 -- The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that are a political division controlled by the United States. Its capital is Saipan. ### Working with semi-structured documents Often times the initial result set includes other metadata and components that could be used to steer the reranking relevancy. To accomplish this, we can set the `rank_by` argument and provide documents with those additional fields. ```python docs = [ { "source": "wiki", "passage": "Carson City is the capital city of the American state of Nevada. At the 2010 United States Census, Carson City had a population of 55,274." }, { "source": "encyclopedia", "passage": "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that are a political division controlled by the United States. Its capital is Saipan." }, { "source": "textbook", "passage": "Charlotte Amalie is the capital and largest city of the United States Virgin Islands. It has about 20,000 people. The city is on the island of Saint Thomas." }, { "source": "textbook", "passage": "Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district. The President of the USA and many major national government offices are in the territory. This makes it the political center of the United States of America." }, { "source": "wiki", "passage": "Capital punishment (the death penalty) has existed in the United States since before the United States was a country. As of 2017, capital punishment is legal in 30 of the 50 states. The federal government (including the United States military) also uses capital punishment." } ] ``` ```python results, scores = cohere_reranker.rank(query=query, docs=docs, rank_by=["passage", "source"]) ``` ```python for result, score in zip(results, scores): print(score, " -- ", result) ``` 0.9988121 -- {'source': 'textbook', 'passage': 'Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district. The President of the USA and many major national government offices are in the territory. This makes it the political center of the United States of America.'} 0.5974905 -- {'source': 'wiki', 'passage': 'Capital punishment (the death penalty) has existed in the United States since before the United States was a country. As of 2017, capital punishment is legal in 30 of the 50 states. The federal government (including the United States military) also uses capital punishment.'} 0.059101548 -- {'source': 'encyclopedia', 'passage': 'The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that are a political division controlled by the United States. Its capital is Saipan.'} ### Using the VoyageAI Reranker To initialize the VoyageAI reranker you'll need to install the voyaeai library and provide the right VoyageAI API Key. ```python #!pip install voyageai ``` ```python import getpass # setup the API Key api_key = os.environ.get("VOYAGE_API_KEY") or getpass.getpass("Enter your VoyageAI API key: ") ``` ```python from redisvl.utils.rerank import VoyageAIReranker reranker = VoyageAIReranker(model="rerank-lite-1", limit=3, api_config={"api_key": api_key})# Please check the available models at https://docs.voyageai.com/docs/reranker ``` ### Rerank documents with VoyageAIReranker Below we will use the `VoyageAIReranker` to rerank and also truncate the list of documents above based on relevance to the initial query. ```python results, scores = reranker.rank(query=query, docs=docs) ``` ```python for result, score in zip(results, scores): print(score, " -- ", result) ``` 0.796875 -- Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district. The President of the USA and many major national government offices are in the territory. This makes it the political center of the United States of America. 0.578125 -- Charlotte Amalie is the capital and largest city of the United States Virgin Islands. It has about 20,000 people. The city is on the island of Saint Thomas. 0.5625 -- Carson City is the capital city of the American state of Nevada. At the 2010 United States Census, Carson City had a population of 55,274.