Langchain Agents Tutorial
The core idea of agents is to use an LLM to choose a sequence of actions to take. In chains, a sequence of actions is hardcoded (in code). In agents, a language model is used as a reasoning engine to determine which actions to take and in which order.
In this video I have explained the concept of Langchain Agents from scratch with code in 5 minutes.
Chapters:
00:00 - Introduction.
00:09 - 3 major components of an Agent
00:18 - Working of Langchain Agent
01:53 - Let's code our first Langchain Agent
03:44 - Let's run our first AI Agent!
05:18 - Thanks You!
Checkout my other videos:
1. Coding a privateGPT using LANGCHAIN, HuggingFace Embeddings and FREE LLM: • Coding a privateGPT using LANGCHAIN, Huggi...
2. Coding chatbot to talk with QURAN using ChatGPT and Langchain: • Langchain + ChatGPT - Coding chatbot to ta...
3. Build Semantic-Search with Elastic search and BERT vector embeddings : • Build Semantic-Search with Elastic search ...
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