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”).
ContextualRetriever enhances document retrieval accuracy by leveraging Voyage AI models for embedding & reranking models, and the GEMINI model for context and retrieval generation.
Chatbot based on Contextual RAG with Hybrid Search and Reranking with short conversation history awareness, fully OpenSource.
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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