LangSmith + LangChain v1: Full AI Agent Tracing & Debugging Tutorial скачать в хорошем качестве

LangSmith + LangChain v1: Full AI Agent Tracing & Debugging Tutorial

In this video, we integrate LangSmith observability into our existing LangChain AI agent so you can clearly trace, debug, and monitor every step of your agent’s execution and reasoning process. You’ll learn: ✅ What LangSmith observability is and why it’s important ✅ How to enable tracing and logging in your LangChain application ✅ How to inspect execution traces, tool calls, prompts, and responses ✅ Why observability is essential when building production-ready AI agents Add the following configuration to your .env file: LANGSMITH_TRACING=true LANGSMITH_API_KEY=your_api_key_here LANGSMITH_PROJECT=your_project_name LANGSMITH_ENDPOINT=https://api.smith.langchain.com 🔗 LangSmith Observability Documentation: https://www.langchain.com/langsmith/observ... 🔗 LangSmith Dashboard (Create Free Account): https://smith.langchain.com/ 🔗 Useful Links 📌 Previous Videos (Recommended): 1️⃣ Setting Up Ollama Locally    • Run ChatGPT-Like AI Locally Using Ollama |...   2️⃣ Creating an Agent & Connecting it with Ollama (Local Setup)    • Build Your First AI Agent with LangChain V...   3️⃣ Build an AI Agent with LangChain v1 (Groq, OpenAI, Anthropic, Gemini & More!)    • Build an AI Agent with LangChain v1 (Groq,...   This tutorial builds on the earlier videos in this playlist where we covered: • Installing and configuring Ollama • Connecting LangChain with local and cloud LLM providers • Creating and integrating tools into our AI agent If you found this video helpful: 👍 Like the video 📌 Subscribe for more AI agent tutorials 💬 Comment “DEBUG” if you’d like to see advanced observability, testing, and evaluation videos next #LangSmith #LangChain #AIAgent #DebugAI #Observability #Ollama #Python #LocalLLM