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12 changes: 6 additions & 6 deletions 11-Reranker/04-FlashRank-Reranker.ipynb
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"\n",
"## Overview\n",
"\n",
"> [FlashRank](https://github.com/PrithivirajDamodaran/FlashRank) is an ultra-lightweight and ultra-fast Python library designed to add reranking to existing search and `retrieval` pipelines. It is based on state-of-the-art (`SoTA`) `cross-encoders`.\n",
"> [FlashRank](https://github.com/PrithivirajDamodaran/FlashRank) is an ultra-lightweight and ultra-fast Python library designed to add reranking to existing search and **retrieval** pipelines. It is based on state-of-the-art (**SoTA**) **cross-encoders**.\n",
"\n",
"This notebook introduces the use of `FlashRank-Reranker` within the LangChain framework, showcasing how to apply reranking techniques to improve the quality of search or `retrieval` results. It provides practical code examples and explanations for integrating `FlashRank` into a LangChain pipeline, highlighting its efficiency and effectiveness. The focus is on leveraging `FlashRank`'s capabilities to enhance the ranking of outputs in a streamlined and scalable way.\n",
"This notebook introduces the use of `FlashRank-Reranker` within the LangChain framework, showcasing how to apply reranking techniques to improve the quality of search or **retrieval** results. It provides practical code examples and explanations for integrating `FlashRank` into a LangChain pipeline, highlighting its efficiency and effectiveness. The focus is on leveraging `FlashRank`'s capabilities to enhance the ranking of outputs in a streamlined and scalable way.\n",
"\n",
"### Table of Contents\n",
"\n",
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"id": "7d83ee066d91fb4f",
"metadata": {},
"source": [
"You can alternatively set OPENAI_API_KEY in .env file and load it.\n",
"You can alternatively set OPENAI_API_KEY in `.env` file and load it.\n",
"\n",
"[Note] This is not necessary if you've already set OPENAI_API_KEY in previous steps."
]
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"source": [
"## FlashrankRerank\n",
"\n",
"Load data for a simple example and create a retriever."
"Load data for a simple example and create a **retriever**."
]
},
{
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"id": "ea07e244c9171d26",
"metadata": {},
"source": [
"Now, let's wrap the base `retriever` with a `ContextualCompressionRetriever` and use `FlashrankRerank` as the compressor."
"Now, let's wrap the base **retriever** with a `ContextualCompressionRetriever` and use `FlashrankRerank` as the compressor."
]
},
{
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"id": "4a147fc787860bac",
"metadata": {},
"source": [
"Compare the results after reanker is applied."
"Compare the results after reranker is applied."
]
},
{
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