LangChain Crash Course - All You Need to Know to Build Powerful Apps with LLMs

Welcome to the LangChain Crash Course! In this video, you will discover how to leverage large language models to develop powerful applications. We will guide you through all the essential features of this cutting-edge framework, providing you with a comprehensive understanding of its capabilities. By the end of this crash course, you'll be equipped with the knowledge and skills to build your own advanced applications using the LangChain framework.

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Links: 
LangChain: https://python.langchain.com/en/latest/index.html
LangChain Github: https://github.com/hwchase17/langchain
Google Colab: https://colab.research.google.com/drive/1w1WezGG66o4aSYNB0aOy4zut0tabB_3I?usp=sharing


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#langchain #largelanguagemodel #openai #gpt4

LangChain Crash Course - All You Need to Know to Build Powerful Apps with LLMs

Welcome to this tutorial video where we'll discuss the process of loading multiple PDF files in LangChain for information retrieval using OpenAI models like ChatGPT. Our step-by-step guide will explain how to convert PDF files into embeddings based on the chosen large language model. Let's get started!
Welcome to this tutorial where you'll learn how to extract valuable information from your PDFs using LangChain and OpenAI Text Embeddings. We'll guide you step-by-step through the process of setting up LangChain to communicate with your PDF files, allowing you to retrieve information efficiently and effectively. By the end of this tutorial, you'll have the skills necessary to use advanced language processing technology and improve your data analysis.

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LINKS:
Google Colab: https://colab.research.google.com/drive/1mIO99-4QWgIKvjgAFj0vvEbQi5xgNCPk?usp=sharing
LangChain: https://docs.langchain.com/docs/
VectorstoreIndexCreator vectorstore: https://tinyurl.com/3yz455m3

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#LangChain #InformationRetrieval #PDF #OpenAITextEmbeddings #DataAnalysis #LanguageProcessingTechnology #AI #MachineLearning #NaturalLanguageProcessing #NLP #Tutorial

Working with MULTIPLE PDF Files in LangChain: ChatGPT for your Data

If you're looking to harness the power of large language models for your data, this is the video for you. In this tutorial, you'll discover how to utilize LangChain to extract valuable information from your PDFs, utilizing OpenAI Text Embeddings. Step-by-step, we'll guide you through setting up LangChain to communicate with your PDF files, enabling you to conduct efficient and effective information retrieval. By the end of this video, you'll have the skills you need to leverage advanced language processing technology and elevate your data analysis.

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Links: 
Google Colab Notebook: https://colab.research.google.com/drive/181BSOH6KF_1o2lFG8DQ6eJd2MZyiSBNt?usp=sharing
LangChain Documentation: https://python.langchain.com/en/latest/index.html
OpenAI API: https://platform.openai.com/account/billing/overview
GPT4All Technical Report: https://s3.amazonaws.com/static.nomic.ai/gpt4all/2023_GPT4All_Technical_Report.pdf

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#LargeLanguageModel #LangChain #InformationRetrieval #PDF #OpenAITextEmbeddings #StepbyStep #DataAnalysis #LanguageProcessingTechnology #AI #MachineLearning #NaturalLanguageProcessing #NLP #Tutorial #HowTo

ChatGPT for YOUR OWN PDF files with LangChain

In this video, I will show you how to interact with your data using LangChain without the need for OpenAI apis, for absolutely free. We will be making use of huggingface hub embeddings for transforming our documents in to vector representation (embeddings). For Large Language Models, we will again using open-sourced models instead of Openai models (text-davinci-033, chatgpt etc.). All the step will be performed with FREE & open source tools with LangChain. 

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Links: 
Google Notebook: https://colab.research.google.com/drive/1NaEyuFWCkDtkufHIsWQhfgPLHybXeYA1?usp=sharing
LangChain: https://python.langchain.com/en/latest/index.html

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All Interesting Videos:
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Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Talk to YOUR DATA without OpenAI APIs: LangChain

"Build a ChatGPT-Powered PDF Assistant with Langchain and Streamlit | Step-by-Step Tutorial"

In this comprehensive tutorial, you'll embark on a project-based journey where we leverage Langchain and Streamlit to develop an interactive ChatGPT for your PDF documents. With the power of an LLM (Large Language Model) such as OpenAI's ChatGPT, we'll create an application that enables you to ask questions about PDFs and receive accurate answers.


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💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

Link to the code: https://pastebin.com/mcHG4cY4

Learn how to harness the power of Langchain, an open-source Python (and Javascript) framework, to create intelligent applications. Discover Langchain's capabilities in training GPT models on your data and generating personalized LLMs. Explore text embeddings and their integration with Langchain using OpenAI's API.

In this tutorial, we'll guide you through building a fully functional Streamlit application. Train GPT on PDF documents and fine-tune it to your specific use case. Experience the seamless user interface as you upload PDFs, ask questions, and receive prompt answers from the LLM.

Unleash Langchain's versatility in chatbots, document analysis, and more. Automate tasks and improve efficiency using Langchain with Streamlit.

Take your natural language processing skills to the next level. Start building powerful applications with Langchain today!


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Langchain: PDF Chat App (GUI) | ChatGPT for Your PDF FILES | Step-by-Step Tutorial

LangFlow is a user interface (UI) specifically built for LangChain, utilizing react-flow technology. Its purpose is to offer a seamless platform for effortless experimentation and prototyping of flows. Users can enjoy the convenience of drag-and-drop components and a chat box feature to enhance their experience.

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LINKS:
LangFlow: https://github.com/logspace-ai/langflow
Chat with websites: https://youtu.be/RBnuhhmD21U
LangChain Crash Course: https://youtu.be/5-fc4Tlgmro
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All Interesting Videos:
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Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

⛓️ LangFlow: Build Chatbots without Writing Code - LangChain

In this video, I will walk you through my own project that I am calling localGPT. This uses Instructor-Embeddings along with Vicuna-7B to enable you to chat with your files offline without the internet. It's under development and I will be adding more features on a regular basis. 

Github:  https://github.com/PromtEngineer/localGPT

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  


If you like the repo, don't forget to give it a ⭐

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💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

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LINKS:  
https://github.com/PromtEngineer/localGPT
Create a GUI Chatbot: https://youtu.be/RIWbalZ7sTo

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Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

LocalGPT: OFFLINE CHAT FOR YOUR FILES [Installation & Code Walkthrough]

To try everything Brilliant has to offer—free—for a full 30 days, visit https://brilliant.org/PromptEngineering/ . The first 200 of you will get 20% off Brilliant’s annual premium subscription.

In this video, we will be building a chatbot GUI using Streamlit. The chatbot will be powered by the Open Assistant model via its API. We will be building both the front and back end for the ChatAPP.  We will use Langchain for combining everything together. The goal is to show how can you integrate Open Assistant via its API in your OWN Applications. 

This video was sponsored by Brilliant

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LINKS:
OpenAssistant Model: https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
Github Repo: https://github.com/PromtEngineer/Chat-App-OpenAssistant-API
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Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Custom GUI App for Open-Assistant API - Tutorial | Step by step Guide

Flowise is a user interface (UI) specifically built for LangChain, utilizing react-flow technology. Its purpose is to offer a seamless platform for effortless experimentation and prototyping of flows. Users can enjoy the convenience of drag-and-drop components and a chat box feature to enhance their experience.

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LINKS:
Flowise Github: https://github.com/FlowiseAI/Flowise
Chat with websites: https://youtu.be/RBnuhhmD21U
LangChain Crash Course: https://youtu.be/5-fc4Tlgmro
Chat with PDF video: https://youtu.be/TLf90ipMzfE
LocalGPT: https://youtu.be/MlyoObdIHyo
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Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Flowise: No Code ChatBot Building Platform: LangChain

LangChain offers a significant advantage by enabling the development of Chat Agents capable of managing their memory. In this video, we explore different langchain memory types and provide guidance on integrating them into a LangChain Conversation chain.

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LINKS:
LangChain Memory: https://python.langchain.com/en/latest/modules/memory.html
Google Notebook: https://colab.research.google.com/drive/1ifv99QApTYQ-SJUDTSg7PjffN30tz5bQ?usp=sharing
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Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

#langchain #openai #chatgpttutorial

LangChain: Giving Memory to LLMs

In this video, we will discuss some of the best practices when it comes to prompt engineering for Large Language models. Our focus will be ChatGPT from OpenAI but these principles will apply to all other LLMs. 

#promptengineering #chatgpt #openai 

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LINKS:
GPT Best Practices: https://platform.openai.com/docs/guides/gpt-best-practices
Chat with DOCs: https://youtu.be/TLf90ipMzfE
Chat with websites: https://youtu.be/RBnuhhmD21U
PDF Chat UI: https://youtu.be/RIWbalZ7sTo
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All Interesting Videos:
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Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Prompt Engineering - Get the MOST OUT of ChatGPT/GPT-4

OpenAI just announced new updates to their LLMs including reduced pricing for ChatGPT and Embedding models as well as NEW ChatGPT model with a 16K context window. Now 32K Context window GPT-4 is also available (with a waitlist). These models can now make API calls. 

#openai #chatgpt #gpt4 
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LINKS:
OpenAI Announcement: https://openai.com/blog/function-calling-and-other-api-updates
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Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

ChatGPT 16K Token Context Window is INSANE!

In this video, I will show you how to install GPT-Engineer on your local machine. GPT-Engineer lets you build a powerful App with just one prompt using Agents. The Agents work like a human engineers by asking you clarifying questions regarding the implementation. 

We will Build Apps using GPT-Engineer including a Simple Website and a Snake Game. GPT-Engineer will implement the entire codebase from your single prompt.

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LINKS:
Github Repo: https://github.com/AntonOsika/gpt-engineer/tree/main
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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

GPT-ENGINEER: Build POWERFUL APPs with ONE PROMPT [Installation & Tutorial]

Aider is a command-line chat tool that allows you to write and edit code with OpenAI's GPT models. You can ask GPT to help you start a new project, or modify code in your existing git repo. Aider makes it easy to git commit, diff & undo changes proposed by GPT without copy/pasting. 

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☕ Buy me a Coffee: https://ko-fi.com/promptengineering
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📧 Business Contact: engineerprompt@gmail.com
💼Consulting: https://calendly.com/engineerprompt/consulting-call
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LINKS:
Aider: https://github.com/paul-gauthier/aider
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TimeStamps:
Introduction: [0:00]
Installation: [1:50]
Aider Basic Setup: [3:15]
Translation Project: [3:44]
Tips & Tricks: [12:15]

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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

AIDER: NEW GPT-Engineer | AI Coding Assistant | Installation & Tutorial

In this video I will show you how to use Caching techniques to reduce the cost on API calls as well as improve the response time for your LLM based Applications. We will be looking at InMemoryCache and SQLiteCache for caching the responses from OpenAI's API. Same approaches can be used with Open-Source Models. 

#chatgpt #largelanguagemodels #langchain #cache 

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🔗 :
Github Repo: https://tinyurl.com/2p8mcusm

Timestamps:
Intro: [0:00]
Why Cache? [0:17]
LLM Cache: [1:09]
Cache with OpenAI API: [1:35]
LangChain Cache: [3:40]
SQLiteCache: [8:42]
Other types of Cache: [10:40]
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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Slash API Costs: Mastering Caching for LLM Applications

In this video tutorial, I will show you how to chat with your documents and add memory to your chatbots. We will use both OpenAI's models as well as open-source localGPT models for creating the chatbot and adding memory to it. 

#largelanguagemodels #langchain #localGPT
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LINKS:
Github link: https://tinyurl.com/25bjk3cj
Memory in Langchain: https://youtu.be/dxO6pzlgJiY
Chat with PDF files: https://youtu.be/TLf90ipMzfE
LocalGPT: https://youtu.be/MlyoObdIHyo
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TimeStamps:
Intro: [0:00]
Adding Memory to RetreivalChain: [01:55]
Memory in OpenAI models: [2:51]
Running GUI: [06:21]
Adding Memory to LocalGPT [09:48]
Outro: [14:45]
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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

ChatBOT with Memory for Your Documents - OpenAI & LocalGPT

Private video

In this video, I will show you how to use the newly released Llama-2 by Meta as part of the LocalGPT. LocalGPT let's you chat with your own documents. We will also go over some of the new updates to the project. 

If you like the repo, don't forget to give it a ⭐

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

#localGPT #Llama-2 #langchain 
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☕ Buy me a Coffee: https://ko-fi.com/promptengineering
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💼Consulting: https://calendly.com/engineerprompt/consulting-call
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LINKS:
LocalGPT Github: https://github.com/PromtEngineer/localGPT
LocalGPT Video: https://youtu.be/MlyoObdIHyo
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Timestamps:
Intro: [0:00]
Setup of LocalGPT: [01:20]
Updates to ingest.py: [05:10]
Updates to run_localGPT.py: [08:31]
Support for GGML, GPTQ & HF models: [09:20]
Adding Llama-2: [12:30]
Running Llama-2 in localGPT: [17:00]
Show Sources: [18:45]
How to Improve Answers: [19:25]
Updates: API & GUI: [20:40]
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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Llama-2 with LocalGPT: Chat with YOUR Documents

In this video, we will cover how to add memory to the localGPT project. We will also cover how to add Custom Prompt Templates to selected LLM. In this video, we will use Llama-2 as an example LLM for talking to your Documents. 

#localGPT #langchain #llama 

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☕ Buy me a Coffee: https://ko-fi.com/promptengineering
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💼Consulting: https://calendly.com/engineerprompt/consulting-call
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LINKS:
LocalGPT Github: https://github.com/PromtEngineer/localGPT
LocalGPT Video: https://youtu.be/MlyoObdIHyo
LocalGPT & Llama-2: https://youtu.be/lbFmceo4D5E
Adding Memories to LLMs: https://youtu.be/dxO6pzlgJiY
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Timestamp:
intro: [0:00]
Adding history to memory: [0:50]
LocalGPT setup: [1:40]
Ingest your Documents: [3:58]
Running localGPT: [6:40]
Adding memory to Llama-2: [8:40]
Custom Prompt Template: [9:40]
localGPT API: [13:20]
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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

LocalGPT & Llama-2: Adding Chat History & Custom Prompt Templates

In this video, I will show you how to use the localGPT API. With localGPT API, you can build Applications with localGPT to talk to your documents from anywhere you want. In this example application, we will be using Llama-2 LLM. 

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  


#llama #localgpt #llm 
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☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Support my work on Patreon: Patreon.com/PromptEngineering
🦾 Discord: https://discord.com/invite/t4eYQRUcXB
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LINKS:
LocalGPT Github: https://github.com/PromtEngineer/localGPT
LocalGPT Video: https://youtu.be/MlyoObdIHyo
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Timestamps:
Intro: [00:00]
Setting up localGPT Repo: [01:33]
Llama-2 and other LLMs: [03:18]
Running the API: [04:25]
Running the GUI with API: [05:00]
The GUI Tutorial: [06:15]
What exactly is happening: [08:37]
Add more docs to the Vector Store: [09:05]
Code Walkthrough: [10:30]
Outro: [14:25]
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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

LocalGPT API: Build Powerful Doc Chat Apps

The Idea of SmartGPT was presented by AI Explained, SmartGPT is a framework that includes self-reflection or critique from the LLM on its generated responses to think step by step and evaluate its answers before showing them to the user. This technique has shown to improve the performance of LLMs significantly on benchmarks such as MMLU. 

We will look at how to use the SmartGPT framework in Langchain to power your own LLM Apps. 


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☕ Buy me a Coffee: https://ko-fi.com/promptengineering
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LINKS: https://python.langchain.com/docs/use_cases/more/self_check/smart_llm
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All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

SmartGPT: Make ChatGPT Smarter

Learn how to chat with your code base using the power of Large Language Models and Langchain. In this video we will use CODE-Llama to talk to the GitHub repo of LangChain. 

"🚀 Dive into Advanced Source Code Analysis with LLMs! | How GitHub Co-Pilot & Others Transform Coding 🧠 | Step-by-Step Guide on QA Pipeline & Innovative Splitting Strategies! 🔍 #CodeAnalysis #LLMmagic"

CONNECT:

☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Support my work on Patreon: Patreon.com/PromptEngineering
🦾 Discord: https://discord.com/invite/t4eYQRUcXB
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📧 Business Contact: engineerprompt@gmail.com
💼Consulting: https://calendly.com/engineerprompt/consulting-call

LINKS:
Code link: https://python.langchain.com/docs/use_cases/code_understanding

Timestamps:
00:00 Intro
01:22 Setup - LangChain
01:51 Doc loader and Text Splitter
03:03 Retriever and Vector Store
03:57 Code Llama with LlamaCpp
04:40 Where to Download Code-Llama From? 
05:55 Setting up LlamaCpp
06:55 Running Code-llama
08:00 RAG with Code-llama
09:17 Wrong way of using Code-llama
10:40 Correct Template for Code-llama
12:43 GPU speed to expect with Llama-Cpp

CODE-LLAMA For Talking to Code Base and Documentation

In this video, we will look at all the exciting updates to the LocalGPT project that lets you chat with your documents. The new updates include support for GGUF format model with llama cpp, better prompt template for restricting answering using Llama-2 template and a lot more!

If you like the repo, don't forget to give it a ⭐
💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  


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☕ Buy me a Coffee: https://ko-fi.com/promptengineering
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🦾 Discord: https://discord.com/invite/t4eYQRUcXB
▶️️ Subscribe: https://www.youtube.com/@engineerprompt?sub_confirmation=1
📧 Business Contact: engineerprompt@gmail.com
💼Consulting: https://calendly.com/engineerprompt/consulting-call
💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
LINKS:
Github Link: https://github.com/PromtEngineer/localGPT
LocalGPT- Detailed walkthrough: https://youtu.be/MlyoObdIHyo
LocalGPT with Llama2: https://youtu.be/lbFmceo4D5E
LocalGPT with Memory: https://youtu.be/KBrT0czrtAs

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Timestamps:
[00:00] Intro
[00:54] LlamaCpp with GPU
[04:54] GPU VRAM Required for LLMs
[06:33] Which LLMs are supported
[07:00] Adding Documents to Vector Store
[08:08] Chatting with Documents
[11:25] Limit Answers to the given context
[14:18] Where are the models downloaded. 
[15:23] Define Context Window
[16:00] Change N_GPU_layers
[16:22] Change the Embedding model
[16:50] Change the LLM


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

LocalGPT Updates - Tips & Tricks

Learn how to use the newly released Gemini Pro API with LangChain for building chatbots, multimodal applications and RAG pipeline. 

Want to Follow:
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Join this channel to get access to perks:
https://www.youtube.com/channel/UCDq7SjbgRKty5TgGafW8Clg/join

LINKS:
Google Colab: https://tinyurl.com/28bw3ntv
Gemini Pro API: https://youtu.be/64Ldwi9YU4I
Chat with your Documents: https://youtu.be/RIWbalZ7sTo
LocalGPT: https://youtu.be/lbFmceo4D5E


TIMESTAMPS: 
[00:00] Gemini Pro API with Langchain
[00:44] Setting Up the Environment
[02:06] Interacting with Gemini Pro API
[03:50] Using Gemini Pro API with Langchain Framework
[05:00] Working with Images 
[06:20] Creating Multimodal Systems with Gemini Pro API
[07:58] Creating a Chat with Document System
[08:39] In-Context Information Retrieval Approach
[12:56] RAC Pipeline Approach
[16:32] Conclusion


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

GEMINI Pro with LangChain | Chat, MultiModal and Chat with your Documents

Learn how to serve multiple users with localgpt API. Users will be able to chat with the common knowledge base hosted on a single server. 

🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

LINKS:
LocalGPT API Tutorial: http://tinyurl.com/bxs6n49p
LocalGPT Repo: https://github.com/PromtEngineer/localGPT

TIMESTAMPS:
[00:00] Introduction to localGPT API
[02:04] Step-by-Step Guide to Setting Up Local GPT
[02:20] Using a Pre-Configured VM for Local GPT
[05:32] Ingesting Documents and Creating a Knowledge Base
[06:35] Starting the API Server and Serving Multiple Clients
[06:56] Using the Local GPT UI and Making API Calls


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

LocalGPT API: Serve Multiple Users At the Same time

Learn how to build an RAG pipeline with the world's fastest LLM API via Groq API. We will build an RAG application that will enable you to chat with a website and will wrap everything in a Streamlit App. 


🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

Signup for Advanced RAG:
https://tally.so/r/3y9bb0

LINKS:
Getting Started with Groq: https://youtu.be/S53BanCP14c
How to chunk: https://youtu.be/n0uPzvGTFI0
Code: https://github.com/PromtEngineer/YoutTube-Tutorial.git

TIMESTAMPS:
[00:00] Introduction
[00:39] Setting Up: Installing Packages and Importing Libraries
[01:32] Designing the RAC Pipeline: From Data to Response
[02075] Implementing the RAC Pipeline with Groq API
[06:00] RAG with Streamlit and Groq API
[10:07] Streamlit App in Action: Real-Time Responses


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Chat with Documents is Now Crazy Fast thanks to Groq API and Streamlit

In this video we will learn how to use the Groq API with localgpt to buiild a RAG pipline. This will enable you to chat with your documents using the Fast LPU inference that Groq has to offer. 

🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

LINKS:
LocalGPT: https://tinyurl.com/26sk3puj
Groq: https://youtu.be/S53BanCP14c

Signup for Advanced RAG:
https://tally.so/r/3y9bb0


TIMESTAMPS:
[00:00] Groq with LocalGPT
[00:29] Sneak Peek: Upcoming UI for Local GPT
[01:20] Setting Up the Environment
[06:55] Setting up Groq API in localgpt
[05:35] Comparing Performance: Grok API vs. Hugging Face Models



All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Ultra Fast LocalGPT inference with Groq API

How to define the chunk size when building a Retrieval Augmented Generation (RAG) application? In this video learn how to define it properly. 

🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

LINKS:
How chunking works: https://huggingface.co/spaces/m-ric/chunk_visualizer

Signup for Advanced RAG:
https://tally.so/r/3y9bb0


TIMESTAMPS:
[00:00] Introduction
[01:46] Embedding Models and Chunk Size Optimization
[04:20] Practical Demonstration: Tokenization and Chunk Distribution
[06:55] Exploring Different Splitting Mechanisms


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

How to Set the Chunk Size in Document Splitter | RAG | LangChain

ColBERT is a fast and accurate retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds. This can be used as a potential alternative to Dense Embeddings in Retrieval Augmented Generation. In this video we explore using ColBERTv2 with RAGatouille and compare it with OpenAI Embedding models. 


🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

Signup for Advanced RAG:
https://tally.so/r/3y9bb0

LINKS:
Find the Notebook here: https://github.com/PromtEngineer/YoutTube-Tutorial
ColBERTv2 with RAGatouille Video: https://youtu.be/xTzUn3G9YA0
ColBERTv2 Paper: https://arxiv.org/pdf/2112.01488.pdf
ColBERT Github: https://github.com/stanford-futuredata/ColBERT
RAGatouille: https://github.com/bclavie/RAGatouille?tab=readme-ov-file

TIMESTAMPS:
[00:00] Introduction
[00:29] Use ColBERT in LangChain
[08:46] Use ColBERT in LlamaIndex


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Advanced RAG with ColBERT in LangChain and LlamaIndex

In this video, I'll show you how to create a fully functional chat system using your own documents with just 10 lines of Python code. We'll dive into Retrieval Augmented Generation (RAG) without relying on frameworks like LangChain, LamaIndex, or vector stores such as Chroma. 

💻 RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag

LINKS: 
Colab: https://tinyurl.com/cnufkeky
Ben's X account: https://x.com/bclavie
Ragatouille/ColBERT video: https://youtu.be/kEgeegk9iqo


Let's Connect: 
🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

Signup for Newsletter, localgpt:
https://tally.so/r/3y9bb0


00:00 Introduction to Building a Chat System without Frameworks
00:26 Understanding Retrieval Augmented Generation (RAG)
02:12 Setting Up the Python Environment
03:39 Data Preparation and Chunking
05:12 Embedding the Chunks
06:31 Retrieving Relevant Chunks
08:53 Generating Responses with LLM
09:50 Advanced Techniques and Recommendations
11:15 Conclusion and Further Learning


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

RAG from Scratch in 10 lines Python without Frameworks (LangChain, LlamaIndex, Chroma etc.)

RAG from Scratch without any Frameworks

In this video, I explain how Agentic RAG improves information retrieval in RAG pipelines, making responses more accurate by refining queries and analyzing retrievals. I walk through implementing this using tools like Transformers agents, and compare it with traditional RAG. Watch to learn how to create detailed and accurate responses with Agentic RAG!

LINKS:
Colabl: https://tinyurl.com/k5vsuj2v

💻 RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag

Let's Connect: 
🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

Signup for Newsletter, localgpt:
https://tally.so/r/3y9bb0


TIMESTAMP: 
00:00 Introduction to Retrieval Augmented Generation (RAG)
00:18 Challenges in Traditional RAG
01:02 Introducing Agentic RAG
02:35 Implementing Agentic RAG with Transformers Agents
03:07 Setting Up the Environment
07:13 Building the Retrieval Tool
10:39 Creating the Agentic Loop
13:52 Comparing Agentic RAG with Standard RAG
15:40 Conclusion and Future Content


All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

Agentic RAG: Make Chatting with Docs Smarter

In this video, I review the new ColPali paper which suggests using vision models for document retrieval, offering both impressive results and explainability. We'll explore the current challenges with RAG systems, the new approach, the groundbreaking results, and even demo this model. Tune in to see how this innovative method outperforms existing methods and can transform your retrieval processes.


LINKS:
Paper: https://arxiv.org/pdf/2407.01449
Vespa Blog: https://blog.vespa.ai/retrieval-with-vision-language-models-colpali/
Try here: https://huggingface.co/spaces/manu/ColPali-demo
ColBERT VIDEOS:
https://youtu.be/kEgeegk9iqo
https://youtu.be/xTzUn3G9YA0

💻 RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag

Let's Connect: 
🦾 Discord: https://discord.com/invite/t4eYQRUcXB
☕ Buy me a Coffee: https://ko-fi.com/promptengineering
|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
Become Member: http://tinyurl.com/y5h28s6h

💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).  

Signup for Newsletter, localgpt:
https://tally.so/r/3y9bb0


00:00 Introduction to ColPali: A New Approach to Document Retrieval
00:40 Challenges with Existing RAG Systems
02:02 Proposed Solution: Vision Models for Retrieval
02:34 Benchmarking and Performance
05:09 Detailed Architecture of ColPali
08:34 Retrieval Process Explained
13:28 Practical Implementation and Testing
17:05 Conclusion and Future Directions

All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z

ColPali: Vision Language Models for Efficient Document Retrieval

<p>In this video, I review the new ColPali paper which suggests using vision models for document retrieval, offering both impressive results and explainability. We'll explore the current challenges with RAG systems, the new approach, the groundbreaking results, and even demo this model. Tune in to see how this innovative method outperforms existing methods and can transform your retrieval processes. LINKS: Paper: https://arxiv.org/pdf/2407.01449 Vespa Blog: https://blog.vespa.ai/retrieval-with-vision-language-models-colpali/ Try here: https://huggingface.co/spaces/manu/ColPali-demo ColBERT VIDEOS: https://youtu.be/kEgeegk9iqo https://youtu.be/xTzUn3G9YA0 💻 RAG Beyond Basics Course: https://prompt-s-site.thinkific.com/courses/rag Let's Connect: 🦾 Discord: https://discord.com/invite/t4eYQRUcXB ☕ Buy me a Coffee: https://ko-fi.com/promptengineering |🔴 Patreon: https://www.patreon.com/PromptEngineering 💼Consulting: https://calendly.com/engineerprompt/consulting-call 📧 Business Contact: engineerprompt@gmail.com Become Member: http://tinyurl.com/y5h28s6h 💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off). Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 00:00 Introduction to ColPali: A New Approach to Document Retrieval 00:40 Challenges with Existing RAG Systems 02:02 Proposed Solution: Vision Models for Retrieval 02:34 Benchmarking and Performance 05:09 Detailed Architecture of ColPali 08:34 Retrieval Process Explained 13:28 Practical Implementation and Testing 17:05 Conclusion and Future Directions All Interesting Videos: Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z</p>

Langchain

Chapters

Course Chapters