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How to Build an AI Chatbot: RAG with LangChain & Streamlit. LLM chatbot tutorial for beginners
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How to build an LLM chatbot using Retrieval Augmented Generation (RAG), LangChain & Streamlit - Full tutorial end-end.
With this video, you will be able your own chatbot using the RAG framework. This video also provides langchain tutorial.
You will understand.
- what is langchain
- what is Retrieval Augmented Generation (RAG)
- what are embeddings
- what are vector databases
- How to deploy on streamlit using python
Takeaways :
- Document Genie is a chatbot built using the RAG Framework and Generative AI Model Gemini Pro.
- The app processes PDF documents, creates searchable vector stores, and generates accurate answers to user queries.
- RAG Framework helps avoid hallucination in language models by combining them with external knowledge databases.
- Retrieval augmented generation involves retrieval, augmentation, and generation to enhance the capabilities of language models.
- Embeddings and vector databases play a crucial role in converting text into numerical representations and finding relevant information.
langchain tutorial, streamlit tutorial, generative ai, langchain agents, python streamlit, langchain ai, python web app, machine learning, learn streamlit, how to use streamlit, openai
Chapters :
00:00 Introduction to Document Genie
02:00 How the App Works
03:00 Understanding Rack Framework
04:26 Retrieval Augmented Generation
05:24 Embeddings and Vector Databases
06:21 Code Overview
07:20 Setting up Streamlit Page
16:23 Deploying the App on Streamlit Community Cloud
16:53 Conclusion
#langchain #streamlit #python #generativeai #geminiapi #ai #ragframework
👨 WHO AM I -
I'm Sri Laxmi an AI product Manager who lives in San Francisco, CA. On this channel, we will learn how to build generative AI applications and use AI tools that can help us launch the projects that inspire us and, consequentially, lead the lives we've always dreamed about.
Sneak peek of upcoming projects:
- *Text Summarization:* Harness the power of Langchain and OpenAI to distill essential information from extensive texts, making comprehension faster and more efficient.
- *Llama 2 Chat:* Dive into conversational AI with a chatbot built on Meta's open-source Llama 2 LLM, designed for dynamic and engaging interactions.
- *Social Media Toolkit:* Elevate your online presence with a Hashtag and Caption Generator, utilizing the Cohere API for creative and impactful social media content.
If that sounds interesting, consider subscribing! See you in the next video 😀
Linkedin -
/ sri-laxmi
With this video, you will be able your own chatbot using the RAG framework. This video also provides langchain tutorial.
You will understand.
- what is langchain
- what is Retrieval Augmented Generation (RAG)
- what are embeddings
- what are vector databases
- How to deploy on streamlit using python
Takeaways :
- Document Genie is a chatbot built using the RAG Framework and Generative AI Model Gemini Pro.
- The app processes PDF documents, creates searchable vector stores, and generates accurate answers to user queries.
- RAG Framework helps avoid hallucination in language models by combining them with external knowledge databases.
- Retrieval augmented generation involves retrieval, augmentation, and generation to enhance the capabilities of language models.
- Embeddings and vector databases play a crucial role in converting text into numerical representations and finding relevant information.
langchain tutorial, streamlit tutorial, generative ai, langchain agents, python streamlit, langchain ai, python web app, machine learning, learn streamlit, how to use streamlit, openai
Chapters :
00:00 Introduction to Document Genie
02:00 How the App Works
03:00 Understanding Rack Framework
04:26 Retrieval Augmented Generation
05:24 Embeddings and Vector Databases
06:21 Code Overview
07:20 Setting up Streamlit Page
16:23 Deploying the App on Streamlit Community Cloud
16:53 Conclusion
#langchain #streamlit #python #generativeai #geminiapi #ai #ragframework
👨 WHO AM I -
I'm Sri Laxmi an AI product Manager who lives in San Francisco, CA. On this channel, we will learn how to build generative AI applications and use AI tools that can help us launch the projects that inspire us and, consequentially, lead the lives we've always dreamed about.
Sneak peek of upcoming projects:
- *Text Summarization:* Harness the power of Langchain and OpenAI to distill essential information from extensive texts, making comprehension faster and more efficient.
- *Llama 2 Chat:* Dive into conversational AI with a chatbot built on Meta's open-source Llama 2 LLM, designed for dynamic and engaging interactions.
- *Social Media Toolkit:* Elevate your online presence with a Hashtag and Caption Generator, utilizing the Cohere API for creative and impactful social media content.
If that sounds interesting, consider subscribing! See you in the next video 😀
Linkedin -
/ sri-laxmi
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