Step-by-Step Guide to Building a RAG LLM App with LLamA2 and LLaMAindex

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Күн бұрын

In this video we will be creating an advanced RAG LLM app with Meta Llama2 and Llamaindex. We will be using Huggingface API for using the LLama2 model.
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Пікірлер: 127

@Pasha_Vamkon 2 ай бұрын

Thank you so much for this video!!! Very helpful!! I've managed to get a bit of understanding of LLM and to do my lab task!!!

@aravindsai2843 5 ай бұрын

Much awaited series, thank you krish Sir♥

@GerardoBarcia 5 ай бұрын

It would be amazing if you show us how to put all of this into production through an API! Thanks for your wonderful work! You Rock!!

@timothylenaerts1123 4 ай бұрын

vLLM is easy enough to use, they provide a docker image, run that bad boy with whatever model you want and use their openAI endpoint then you can just use that in langchain or Llama index

@chanishagarwal9103 3 ай бұрын

Thanks you krish for all your hard work. keep making such amazing videos.

@sandeepmahale1941 7 күн бұрын

Krish, thank you for creating easy to understand videos

@lixiasong3459 4 ай бұрын

Thank you, Sir, you are amazing!

@atifsaeedkhan9207 3 ай бұрын

U r really a good instructor. ❤

@rubyrana7786 3 ай бұрын

Indeed great video. Please try to include the reason for using different approaches of doing any process like in earlier videos the model was loaded differently and here differently. A simple explanation of the reason behind using a specific approach can be useful for the beginners. As the approach changes when we move forward in more complex applications and different use cases.

@MamadouMoussaBangoura Ай бұрын

thank you the cours i see in this rag topic , very good , i 'm french speaker but i understand your cours

@akshatapalsule2940 5 ай бұрын

Thankyou so much Krish, it was worth the wait :)

@nunoalexandre6408 5 ай бұрын

Love it

@smartwork7098 2 ай бұрын

Thanks man, it works well. (After correcting some changes made in llama and huggingface)

@ahmadmasood3939 Ай бұрын

I am facing problem while importing huggingfacellm. can you tell me what you did?

@krvedhavakrishna7710 Ай бұрын

@@ahmadmasood3939 while accessing tokens, in the create new token option, chnage token mode to write

@koushikvenuganan3999 13 күн бұрын

hi, btw im also facing the same issues while importing llama and huggingface . Can u help me to fix the issues ?

@ivanrowland142 4 ай бұрын

Love this. When is the next instalment?

@MLAlgoTrader Ай бұрын

You are amazing.

@y6bt2501 5 ай бұрын

Please make a video on RAG with CSV or database with local open source llm and with memory

@user-fp3tm1jp2f 3 ай бұрын

Lets Goooooo

@miteshgarg9420 4 ай бұрын

Hey Krish, amazing video again. Can you please help to create a similar solution for custom text 2 sql

@amritsubramanian8384 Ай бұрын

gr8 video

@dillikaextrovert 4 ай бұрын

Hello Krish The list of accessories you have mentioned, is not having right links for Amazon. Can you please give me the link for the writing pad which you use ?

@hassubalti7814 5 ай бұрын

sir greet method to teach us as well as gaining good grip on english. please make video about token used in llama 2 model used

@charmilagiri4602 5 ай бұрын

Sir Instead of using LLamA2 model from huggingface, Can we try the quantized llama model? If we use the quantized llama model will the output accuracy varies?

@GaneshEswar 3 ай бұрын

waiting for next video, please upload it ...

@DoomsdayDatabase 3 ай бұрын

Hi krish sir! they have updated the service_context to settings.llm and i am not able to understand how to implement it into this code. Please help! Thanks!

@yashghugardare519 5 ай бұрын

Sir..instead of RAG with pdf..make a video on Rag with videos.. which will process videos and be able to answer questions based on the video

@stevefisher35 4 ай бұрын

Thanks for the detailed run through, very useful . One question I have is on the two PDF documents you have. Are these available anywhere, just for testing purposes?

@sravan160 4 ай бұрын

i have some doubts in implementing the code.,can u help?

@eswararya196 2 ай бұрын

Yeah ask me?

@atifsaeedkhan9207 3 ай бұрын

Is it possible to use local llms instead huggingface directly? I have ollama nd lmstudio installed.

@RanjitSingh-rq1qx 5 ай бұрын

Sir everything fine, but you have missed just one thing in this project, that why you have implemented or build prompt and why you have not used that prompt, why you have gone with default prompt ? And remaining part was so good with good explanation ❤️

@krishnaik06 5 ай бұрын

More examples i will come up with...this basic to intermediate RAG system

@tarekferradji 3 ай бұрын

Can I combine the LORA fint tuning for example and a RAG FOR THIS llm, can this work give me very interesting performances?

@rubyrana7786 3 ай бұрын

Why did we use a separate Embedding model here while in the earlier video of this playlist we directly used VectorStoreIndex on the documents. So why did we follow different approaches while creating similar Applications? Is it because of the different Model or it is just a different approach and can be done either way ?

@nikhilanand9022 2 ай бұрын

I had one doubt is Vector Store Index use any embedding model behind it for creating the Index or how it create the embedding the vector store index

@PuneetSharma-fb7oz Ай бұрын

@@nikhilanand9022 By default, VectorStoreIndex use OpenAI Embeddings if no other embeddings are explicitly specified.

@user-hj9ck9rp4c 4 ай бұрын

I am getting the error of VectorStorIndex from LLama_index

@ByYouTube2 4 ай бұрын

use- from llama_index.core import VectorStoreIndex,SimpleDirectoryReader,ServiceContext

@vinayaktiwari4463 4 ай бұрын

Hi Krish , which vector store have you utilised here? there was no mention of such in the code

@VivekGuptaMusic 4 ай бұрын

not saving the embeddings in any vector store directly using it

@chinnibngrm272 4 ай бұрын

Sir as I am a student.. I am not having gpu in my machine... I am not able to do projects with this open source llms n also with open ai... Can u please help us to solve the resource errors by using other models

@rajarams3722 11 күн бұрын

Sorry Krish...you started the playlist saying you would explain the difference in llamaindex vs langchain and why we should use either and when...but this play list with three videos does not deal with that, instead explains some hands on....Thanks for your work, but I think the assurances are not met..The play list has not been updated since Jan 24 ?

@MK5491 4 ай бұрын

@krishnaik06 Sir Thank you for this knowledgeable video, My question is which Evalution model we should use to show the accuracy in terms of answer and context retrieval. If possible, will you please create one video on evaluation method for RAG application.

@akashchavan3353 4 ай бұрын

@krishnaik06 sir I also want this thing, can you please create one video on evolution method. Thanks

@anant9421 4 ай бұрын

@krishnaik06 yes please can you please create a video on evaluation method for RAG application

@chinnibngrm272 4 ай бұрын

I am getting Runtimeerror: CUDA Error.... While running index= VectorStoreIndex.from_documents (docs, service_context=service_context) Sir please provide a solution to run with cpu....

@yuvrajthakur5728 5 ай бұрын

Hey Krish, why you left PWskills masters in data science course. I joined this because of you. But I am seeing there new tutors. I joined this course because of you only.

@MatkoZaja 2 ай бұрын

Is there a way to ensure that once PDFs are processed, they do not need to be reprocessed every time the script runs, but rather that a cached database can be stored? Does anyone have code for this?

@nostalgia18rishi 3 күн бұрын

I can't login using hugging face cli on colab. I have pasted the token from hugging face and control enter. The cell on my collab keeps running.

@fadhilayosof5927 5 ай бұрын

can you make a video to create flowchart by LLM

@shehrozkhan9563 3 ай бұрын

Can we add in conversation history to this app?

@ridj41 3 ай бұрын

where to get the data from, like you have done in this case? \

@Narutome30 5 ай бұрын

Y is he using google colab rather than vs code And also please answer this question -> can we use vs code to run seamless m4t meta model

@vivekshindeVivekShinde 5 ай бұрын

I have lots of pdf documents data and want to create a custom chatbot based on it. Then which one will be better: Langchain or Llamaindex?

@RanjitSingh-rq1qx 5 ай бұрын

Llamaindex for indexing purpose, and langchain used for response of query with Prompt by the langchain LLM, and used Gemini pro as a LLM model. Will be great combination of all these technologies ❤

@vivekshindeVivekShinde 5 ай бұрын

@@RanjitSingh-rq1qx Thanks for suggestions. I am looking for Open Source. So while Indexing in the Llamaindex, it doesn't use OpenAI api or something right?

@RanjitSingh-rq1qx 5 ай бұрын

@@vivekshindeVivekShinde yes all are open source

@chinnibngrm272 4 ай бұрын

Guys can you please share the implementation of this by mixing llama index, Langchain, Gemini pro.... Please ... It will be very helpful 😊😊

@nikhilanand9022 2 ай бұрын

@@vivekshindeVivekShinde I think when we use the Vector Store index it use the openai embedding model api for creating the index can you please confirm once ?

@himanshudeswal9895 4 ай бұрын

Hi, can anyone tell me how to download these raw pdf’s for hands on please??

@Playstore-zc5xk 4 ай бұрын

How to convert this into end to end?

@abhinandansharma3983 3 ай бұрын

where i will get this dataset

@aritrasaha1854 Күн бұрын

how to do it if I have a csv file instead of a pdf

@PuneetSharma-fb7oz Ай бұрын

"ServiceContext" is now deprecated and replaced with "Settings" object. You may need to update this tutorial. Also, at 16:19 why did you used two different embeddings? HuggingFaceEmbeddings and LangChainEmbedding? Isn't just any one is enough?

@rajarams3722 11 күн бұрын

Yes, there are lots of gaps such as these in his recent videos..Seems like he is in a hurry to have his hands on every topic that emerges and he is losing direction..starting new playlist and leaving it to start new ones..

@achukisaini2797 5 ай бұрын

How to reduce hallucination? if answer is not in context then it is hallucinating .

@soulfuljourney22 5 ай бұрын

may be you can modify the prompt to answer for not in context situation

@IamMarcusTurner 4 ай бұрын

literally prompt the LLM if not in document tell the LLM to say it does not know.

@riteshsingh811 4 ай бұрын

If the content is present , still its hallucinating , there are certain advance RAG techniques like Window Sentence Retrieval and Auto Merging Retrieval that can help.It will help in improving the context. Just try read regarding it and implement. It will help u. Also tuning agent to not give answer when it doesn't know helps in case of unknown scenario.

@thomasmuller1521 3 ай бұрын

The libraries changed: from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, ServiceContext from llama_index.llms.huggingface import HuggingFaceLLM from llama_index.core.prompts.prompts import SimpleInputPrompt from langchain.embeddings.huggingface import HuggingFaceEmbeddings from langchain.embeddings import HuggingFaceEmbeddings from llama_index.embeddings.langchain import LangchainEmbedding import llama_index

@AmitojSingh-tf9ex 3 ай бұрын

bro this line is giving error from llama_index.embeddings.langchain import LangchainEmbedding how do i find correct one

@AmitojSingh-tf9ex 3 ай бұрын

how to make this thing running from langchain.embeddings.huggingface import HuggingFaceEmbeddings from langchain.embeddings import HuggingFaceEmbeddings from llama_index.embeddings import LangchainEmbedding embed_model=LangchainEmbedding( HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2"))

@khyathinkadam5524 2 ай бұрын

while running import torch llm = HuggingFaceLLM( context_window=4096, max_new_tokens=256, generate_kwargs={"temperature": 0.0, "do_sample": False}, system_prompt=system_prompt, query_wrapper_prompt=query_wrapper_prompt, tokenizer_name="meta-llama/Llama-2-7b-chat-hf", model_name="meta-llama/Llama-2-7b-chat-hf", device_map="auto", # uncomment this if using CUDA to reduce memory usage model_kwargs={"torch_dtype": torch.float16 , "load_in_8bit":True} ) in colob i m getting import error stating that i need to install accelarate but i already have in in my env

@nikhilanand9022 2 ай бұрын

I had one doubt is Vector Store Index use any embedding model behind it for creating the Index or how it create the embedding the vector store index

@goldy5553 4 ай бұрын

Library is pretty messed up, nothing is working everwhere there is a module import error and function is missing or deprecated. if you found this, don't worry guys we are on same page. Sir could you please check if there is a some issues or what they have done to library

@eswararya196 2 ай бұрын

If you are having moldule import error then use llama_index.core Instead of llama_index

@user-bb5nz6cf5j 4 ай бұрын

Sir , the llama index library is modifying everyday , and there are many import errors in the code , can you tell me the suitable version of llama-index to run the code

@ishratsyed2857 4 ай бұрын

I was having the same issue, I tried installing version 0.9.40 and it's working now

@sebastienmaillet9371 4 ай бұрын

@@ishratsyed2857 i tried to install llama_index version 0.9.40 but i got the following message: ImportError Traceback (most recent call last) in () ----> 1 from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext 2 from llama_index.llms import HuggingFaceLLM 3 from llama_index.prompts.prompts import SimpleInputPrompt ImportError: cannot import name 'VectorStoreIndex' from 'llama_index' (unknown location)

@sebastienmaillet9371 4 ай бұрын

do you know what i might be missing ?

@santhoshmanoharan8969 4 ай бұрын

@@sebastienmaillet9371 I have tried the same code from my local anaconda environment, I'm getting error with the importing packages but it is working fine when I use Google Colab, can anyone explain why?

@ShreyasR-vr1es 2 ай бұрын

Trying using the import like this instead: from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, ServiceContext from llama_index.llms.huggingface import HuggingFaceLLM from llama_index.core.prompts.prompts import SimpleInputPrompt This should work for you!

@blakdronzer 19 күн бұрын

there is an issue downloading the model LLAMA2 / LLAMA3 - as it requires to be authenticated / accepted by their team. Even after getting it authenticated / accepted - when we try download the code by your pattern / huggingface_clt - it still says - access denied to the config file - and hence cannot download any model locally - so if you could practically share insights or build a new video that pertains to the latest situation, will be awesome

@rajarams3722 11 күн бұрын

Please try in google colab..I tried in my local laptop and many things failed.

@blakdronzer 4 күн бұрын

Well i discovered lately that this models are available only for pro accounta. Since I subscribed to one monther, it is working fine now. Strange... Marking it open but available only for subscribers

@harshab2743 2 ай бұрын

i am getting an error while importing vectorstoreIndex from llamaIndex saying that llamaIndex doesn't exist. can someone help

@ShreyasR-vr1es 2 ай бұрын

@aiwithuday Ай бұрын

@@ShreyasR-vr1es also pip install llama-index-llms-huggingface

@sumanmaity3162 2 ай бұрын

Hello Krish, I'm getting a basic error as below. Can you please help? ImportError Traceback (most recent call last) in () ----> 1 from llama_index import VectorStoreIndex,SimpleDirectoryReader,ServiceContext 2 from llama_index.llms import HuggingFaceLLM 3 from llama_index.prompts.prompts import SimpleInputPrompt ImportError: cannot import name 'VectorStoreIndex' from 'llama_index' (unknown location)

@ShreyasR-vr1es 2 ай бұрын

@sumanmaity3162 2 ай бұрын

@@ShreyasR-vr1es Thank you, other 2 worked but I'm getting error in below ModuleNotFoundError Traceback (most recent call last) in () ----> 1 from llama_index.llms.huggingface import HuggingFaceLLM ModuleNotFoundError: No module named 'llama_index.llms.huggingface'

@sumanmaity3162 2 ай бұрын

Please ignore, it worked, had some installation issues. Thank you so much.

@darshitshah8668 Ай бұрын

@@sumanmaity3162 I am facing same error, how did it get resolved for you?

@sumanmaity3162 Ай бұрын

@@darshitshah8668 Please reinstall, it should work

@KumR 5 ай бұрын

Hey Krish. Video is cool. But can you tell us how we will know what are the different things we will need to import . You may have done lot of research. Kindly point us to the source of truth.

@Arkantosi 2 ай бұрын

Old tutorial. Most of the imports no longer work due to deprications.

@HammieLicious 21 күн бұрын

SimpleInputPrompt is broken. still shows the concept tho

@shreyavalte3077 5 ай бұрын

I have a very big question

@yetanotheremail 5 ай бұрын

Han please ask

@minimal2224 4 ай бұрын

Lol the suspense is killing me

@Lemonboi-lmn21 3 ай бұрын

any updates ?

@user-gk7ox3of4b 3 ай бұрын

i need those pdfs

@khyathinkadam5524 2 ай бұрын

@AnandYadav-gv1xw 2 ай бұрын

from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext ImportError: cannot import name 'VectorStoreIndex' from 'llama_index' (unknown location)

@Sohammhatre10 2 ай бұрын

Simple directory reader too

@ShreyasR-vr1es 2 ай бұрын

@sayanghosh6996 2 ай бұрын

06:00 !pip install -q llama-index llama-index-llms-huggingface from llama_index.core import VectorStoreIndex,SimpleDirectoryReader,ServiceContext from llama_index.llms.huggingface import HuggingFaceLLM from llama_index.core.prompts.prompts import SimpleInputPrompt

@yourealive1 2 ай бұрын

thank you so much