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LangChain Tutorial (Python) #6: Self-Reasoning Agents with Tools

#openai #langchain Agents are one of the most important features of Langchain and extremely fun to use. We can give our agent an instruction, and it will use the power of LLM's and Tools to figure out the actions to take, the sequence of events and then use tools the achieve it's goals. ☕ Buy me a coffee: https://www.buymeacoffee.com/leonvanzyl 📑 Useful Links: Langchain Python docs: https://python.langchain.com/docs/get... Source Code: https://github.com/leonvanzyl/langcha... Langsmith: https://www.langchain.com/langsmith Tavily Search API: https://app.tavily.com/home 💬 Chat with Like-Minded Individuals on Discord:   / discord   🧠 I can build your chatbots for you! https://www.cognaitiv.ai 🕒 TIMESTAMPS: 00:00 - Intro 00:22 - Project setup 01:40 - Prompt Agent Scratchpad 02:59 - Agent Types 03:21 - Creating our agent 03:50 - Create agent executor 04:41 - Add Tavily Search Tool 05:08 - Tavily API Key 05:52 - Langsmith 06:53 - Adding chat history 09:28 - Add Retriever as Tool 11:38 - Create retriever tool

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