Build your own simple LLM application using LangChain in Python | Langchain Basic Concepts

Hi, thanks for watching our video about python project LangChain
Overview about why the LangChain library is so useful.

In this video we're going to look at the problem with Hugging Face Hub and how LangChain comes to the rescue. Also explore how we can use Langchain with GPT4.

LangChain is a Python framework for developing applications powered by language models. In this video we take a look at LangChain, see how it works, and what you can do with it!

In this video we’ll walk you through:
- GPT4
- LangChain
- Generative AI
- HuggingFaceHub
- Optimization Technique Deep Learning
- Multimodal
- Deep Learning
- ChatGPT
- palm-e Models
- VALLE
- GOOGLE LAMDA

OpenAI has officially announced GPT-4 the latest version of its incredibly popular large language model powering artificial intelligence (AI) chatbots. ChatGPT is an AI chatbot that utilizes the language models of GPT-3 and GPT-4 for interactive communication. In other words you can use chatgpt with gpt4. A Generative Pre-Trained Transformer (GPT) is a sophisticated neural network architecture used to train large language models (LLMs). It makes use of large amounts of publicly available Internet text to simulate human communication.

Main improvements:
* It's multimodal (what it is is in video)
* Longer context length
* Better performance
* More safer

chatgpt,
langchain,
gpt4,
google AI,
Google Lamda,
Google PALM,
artificial intelligence,
Machine learning,
transformer models,
deep learning

TIMESTAMPS
0:00 Intro
1:00 Langchain overview
2:00 Langchain Agent
2:35 Agent example
4:00 Build your own LLM with Lanchain


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LINKS/Sources USED:
Openai : https://www.youtube.com/watch?v=outcGtbnMuQ
PromptChaining: https://www.youtube.com/watch?v=p6MA8q19uo0
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