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Enhance RAG with Contextual Compression (#103)
* contextual_compression_in_RAG * update main Readme * new_changes --------- Co-authored-by: kaushal07wick <[email protected]>
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# 🔍Search engine using SAM & CLIP | ||
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<a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Contextual-Compression-with-RAG/main.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | ||
[](https://medium.com/etoai/enhance-rag-integrate-contextual-compression-and-filtering-for-precision-a29d4a810301) | ||
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### 🎫 Enhance RAG: Integrate Contextual Compression and Filtering for Precision. | ||
Follow the Colab Notebook for full code. | ||
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## Interface 🌟 | ||
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1. Load the Model from Huggingface. | ||
2. Instantiate Contextual Compressor from Langchain. | ||
3. Create a pipeline with different retrieving filters. | ||
4. Get the answer using QA chain. |
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