Step-by-step tutorials on building voice and chat AI agents using OpenAI Agents SDK, Realtime API, function calling, multi-agent orchestration, and production deployment patterns.
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Learn LangGraph's graph-based approach to building stateful, multi-step AI workflows — including nodes, edges, conditional routing, state management, and human-in-the-loop patterns.
Set up LangSmith for tracing LangChain runs, analyzing run trees, building evaluation datasets, running automated evaluations, and collecting feedback on LLM outputs.
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.
