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LangChain Series for Beginners – Prompts, Structured Outputs & Chatbots
Toolkits Explained — Organizing Multiple AI Tools Efficiently | Video 28 | LangChain Series

Toolkits Explained — Organizing Multiple AI Tools Efficiently | Video 28 | LangChain Series

LangChain Series for Beginners – Prompts, Structured Outputs & Chatbots

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32 درس
07:26 RunnableSequence Explained — Building Multi-Step AI Pipelines | Video 18 | LangChain Series
06:14 I built an agent that improves/critiques my other agent output | Python + LangGraph + Groq Tutorial
49:49 Full-Stack AI Engineer: Master LangChain + LangGraph in One Video
17:52 InjectedTool Explained — Building Multi-Step Agentic Workflows | Video 31 | LangChain Series
07:08 Enforced Tool Execution — Building Fully Functional AI Agents | Video 30 |
05:41 Tool Binding Explained — Connecting AI Models to Functional Tools | Video 29 | LangChain Series
05:39 Toolkits Explained — Organizing Multiple AI Tools Efficiently | Video 28 | LangChain Series
05:00 StructuredTool Explained — Building Smarter, Safer AI Tools | Video 27 | LangChain Series
05:23 Tools in LangChain — Turning LLMs into Actionable AI Agents | Video 26 | LangChain Series
16:20 Build a YouTube Q&A RAG AI with FAISS, Embeddings & Gemini 2.5 Flash | Video 25 | LangChain Series
07:22 Chroma Vector Store Retriever — Powering Semantic Search in AI | Video 24 | LangChain Series
05:41 Retrievers Explained — The Memory Engine Behind LangChain AI | Video 23 | LangChain Series
12:32 Vector Stores Explained — Giving AI Memory with Chroma | Video 22 | LangChain Series
16:21 Text Splitters Explained — Chunking Documents the Smart Way | Video 21 | LangChain Series
18:08 Document Loaders Explained — Import Real-World Data into LangChain | Video 20 | LangChain Series
07:04 RunnableParallel Explained — Run Multiple AI Tasks Simultaneously | Video 19 | LangChain Series
01:40 LangChain Series Introduction | Video 1 | Build AI Agents, Chatbots & LLM Apps Step-by-Step
14:17 Building a RAG Pipeline: Retrieval-Augmented Generation Explained | Video 17 | LangChain Series
12:49 Understanding Embeddings: The Heart of Intelligent AI Retrieval | Video 16 | LangChain Series
13:08 LLMChain Explained: The Building Block of AI Workflows | Video 15 | LangChain Series
13:08 Parallel Chains: Run Multiple AI Workflows Simultaneously | Video 14 | LangChain Series
13:08 Conditional Chains: Build Dynamic & Flexible AI Workflows | Video 13 | LangChain Series
07:26 Sequential Chains: Build Multi-Step AI Workflows | Video 12 | LangChain Series
09:34 PydanticOutputParser for Validated & Structured AI Responses | Video 11 | LangChain Series
11:02 StructuredOutputParser & OutputFixingParser Explained | Video 10 | LangChain Series
14:46 PromptTemplate, StrOutputParser & Chaining for Multi-Step AI Workflows | Video 9 | LangChain Series
09:00 Strict Structured Outputs with Pydantic for Review Analysis | Video 8 | LangChain Series
08:31 Advanced Structured Outputs: Multi-Field Review Extraction | Video 7 | LangChain Series
08:33 Structured Outputs with TypedDict | Video 6 | LangChain Series
07:47 MessagesPlaceholder Explained in ChatPromptTemplate | Video 5 | LangChain Series
05:01 ChatPromptTemplate Explained: Build Reusable AI Prompts | Video 4 | LangChain Series
09:15 Chat History & Message Types for Context Aware Chatbots | Video 3 | LangChain Series