Cohere AI's LLM for Semantic Search in Python

Learn how to implement semantic search using Cohere AI's large language model (LLM) and Pinecone vector database in Python. Explore the process of generating language embeddings with Cohere's Embed API endpoint and indexing them in Pinecone for fast and scalable vector search. Discover the power of combining these services to build applications for semantic search, question-answering, and advanced sentiment analysis. Follow along as the video guides you through architecture overview, code setup, API key configuration, data embedding, vector index creation, and query testing. Gain insights into leveraging state-of-the-art NLP models and vector search techniques for processing large text datasets efficiently.