Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Implement real-time streaming in LangChain applications with callback handlers for token-by-token output, custom event logging, cost tracking, and production monitoring hooks.
Learn how to install pgvector, create vector columns, build IVFFlat and HNSW indexes, and run similarity queries directly inside PostgreSQL without adding another database to your stack.
A hands-on guide to setting up Pinecone, creating serverless indexes, upserting embeddings, running similarity queries, and filtering results with metadata for production AI applications.
Learn to set up Weaviate, design schemas with vectorizer modules, import data, and run hybrid keyword-plus-vector searches using Weaviate's GraphQL API and Python client.
Learn when to use cosine similarity, Euclidean distance, or dot product for vector search, how normalization affects results, and practical guidance on choosing dimensions and metrics.
Build a production-grade pipeline for embedding and ingesting millions of documents into a vector database, covering chunking strategies, parallel processing, rate limiting, and progress tracking.
Learn three strategies for isolating tenant data in vector databases — namespaces, metadata filtering, and separate indexes — with tradeoffs for security, performance, and cost at scale.
Learn how to rigorously benchmark vector databases with proper methodology — measuring latency, throughput, and recall under realistic conditions to make informed infrastructure decisions.
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