Contextual RAG over webinar videos using Pinecone, Claude and AWS.
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Updated
Feb 11, 2025 - Python
Contextual RAG over webinar videos using Pinecone, Claude and AWS.
It is a case study of an intelligent agent for Ocean.
Enhance your RAG with Contextual Retrieval
RAG-Ingest: A tool for converting PDFs to markdown and indexing them for enhanced Retrieval Augmented Generation (RAG) capabilities.
Contextual Retrieval solves this problem by prepending chunk-specific explanatory context to each chunk before embedding (“Contextual Embeddings”) and creating the BM25 index (“Contextual BM25”).
Chatbot based on Contextual RAG with Hybrid Search and Reranking with short conversation history awareness, fully OpenSource.
ContextualRetriever enhances document retrieval accuracy by leveraging Voyage AI models for embedding & reranking models, and the GEMINI model for context and retrieval generation.
A powerful toolkit for text chunking and semantic search using OpenSearch. This toolkit provides various text chunking strategies and embedding capabilities for efficient document retrieval.
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