🔥Join the AI Engineer Bootcamp: Hey there.. The second edition of the AI Engineering Cohort is starting soon. - Learn with step-by-step lessons and exercises - Join a community of like-minded and amazing people - I'll be there to personally answer all your questions 🤓 - The spots are limited since I'll be directly interacting with you You can join the waitlist now 👉 course.alejandro-ao.com/ Cheers!
@LookNumber93 ай бұрын
Yes. More on LlamaIndex please. I so appreciate your clear and thoughtful tutorials. Beautifully done!
@alejandro_ao3 ай бұрын
i appreciate it! absolutely 💪
@eric-theodore-cartman61512 ай бұрын
Yes please make a whole series, especially the application based on usecases. @@alejandro_ao
@adil385Ай бұрын
Been looking at this for a few weeks and this is the perfect start for anyone wanting to understand RAG and llama index. Fantastic video :)
@changed2173 ай бұрын
Thank you so much man, just yesterday I was struggling with the same thing, there is no recent content on llamaindex, everything is outdated. This is a live-saver, please continue this series.
@alejandro_ao3 ай бұрын
you can count on that
@davidtindell9503 ай бұрын
Works Very Well and very low cost (in pennies per PDF). Further savings by 'Persisting the Index' ... Thank You Yet Again! I own you a whole pot of coffee ! 😄
@IdPreferNot13 ай бұрын
LLamaindex looks like a survivor. Would love to see some of the advanced new features in your coming tutorials.
@alejandro_ao3 ай бұрын
totally agree. i am sure they will be shaping the AI app sphere for a long time
@tlyoon3 ай бұрын
Am considering using llamaindex for my ai application project after viewing your wonderfully done video, which is straightforward, simple and absolutely understandable. I am expecting a follow-up video by you on how to deploy llamaindex online for a realistic entrepreneur setting.
@janwillemaltink22163 ай бұрын
always eager to start building things after watching one of your videos. You really have a talent for explaining things super clear and easy .
@megamind4523 ай бұрын
I was searching about llamaindex yesterday on your KZbin channel
@alejandro_ao3 ай бұрын
we're in sync 😎
@ai-touch93 ай бұрын
the moment you say good morning, I feel like I woke up on a flight with pilot announcement, Good stuff btw.
@Muzeemkhankamaal6 күн бұрын
Really nice and to the point tutorial.. Thank you.
@alejandro_ao3 күн бұрын
thank **you**
@rochedavid16433 ай бұрын
Merci beaucoup pour ce contenu de qualité (comme toutes tes vidéos), vivement la suite ! (j'espère que tu aborderas la création de RAG basé sur des agents)
@somerset0062 ай бұрын
Thanks for the up-to-date video on Llama Index! It would have been helpful to explicitly mention the deltas from half a few months back.
@user-wr4yl7tx3w3 ай бұрын
i like to learn llamaindex but i wonder if i will just be spreading myself too thin by trying to master both langchain and llamaindex. do you have any advice?
@nyceyesАй бұрын
Their documentation is lacking, so thank you for this. Question: In your code editor, I noticed the hover-over text: "start coding or generate with AI". What code generator service and/or plugin are you using, if you don't mind me asking? 😊 (E.g. GitHub Copilot, etc). Thank you. Edit: Ah, it's probably whatever CoLab offers. I was too focused on the LlamaIndex talk to notice the IDE was CoLab. LoL
@iacondiego2 ай бұрын
Good video, I have seen few videos that explain this topic well, greetings from Chile
@RakshithML-vo1tr2 ай бұрын
Bro literally you are doing such a useful thing please do more videos its very helpful lots of love from student community ❤️
@BrandonFoltz3 ай бұрын
Excellent as usual! And useful as usual. Thanks and stay cool. 😎
@alejandro_ao3 ай бұрын
thank you brandon! always a pleasure to see you around!
@gazorbpazorbianАй бұрын
Great video! Keep em coming! Quick question. When you load documents can it get the documents recursively inside data? Like if there are more folders inside folders? Is there any limit to loading documents? Any aditional advice on the loading documents? What if a document has many pages and it has a footer and a header with repetitive content? Could that affect negatively the retrieval?
@AlexCasimirF3 ай бұрын
Love your videos!!! Great content here again. One question: in 30:20 where the index gets created locally, what do the subfolders look like? "image_vector_store", "graph_store"... - does this mean the dataloaders would also split a PDF in plain text, graphs, images and then store the respectivbe embeddings in separate folders? Tried it on my own PDFs but could not make much sense of the index files unfortunately...
@sunitjoshi35733 ай бұрын
Nice & articulate. Thanks for putting this out.
@alejandro_ao2 ай бұрын
I appreciate it :) expect many more to come
@PauloRogeriopauloaraxa3 ай бұрын
Excelente explicação como sempre. Parabéns.👏👏👏
@akshaymenon50883 ай бұрын
Can this setup be implemented within a protected infrastructure? I have sensitive data that I don't want to leave my network
@ziggyybr3 ай бұрын
It helped me a lot! Thanks for the video
@alejandro_ao3 ай бұрын
no worries!
@haiderkhalilpk3 ай бұрын
Very precise and much much useful!
@alejandro_ao3 ай бұрын
hey there, thanks! glad to see you around!
@rmjjanssen26453 ай бұрын
Great video. So if I understand correctly, the code example only shows the parsing into documents. So no nodes, embedding/vectorising and persistent storage in a vector DB? Any observations on weak/ strengths in comparison with langchain? The parts upto vector db and the parts from user upto vector DB
@Pingu_astrocat213 ай бұрын
Alejandro Thank you for the clear introduction to LlamaIndex. Instead of using OpenAI API , how can we use a model from hugging face?
@alejandro_ao3 ай бұрын
definitely, coming up!
@Pingu_astrocat213 ай бұрын
@@alejandro_ao thank you! waiting :)
@CaptainBri-ro4lp2 ай бұрын
Great tutorial!!
@Jay-wx6jt3 ай бұрын
Their recent documents are really really good
@alejandro_ao3 ай бұрын
they are awesome indeed
@samuelsztabholz24193 ай бұрын
Très bonne présentation. Merci
@alejandro_ao3 ай бұрын
je t'en prie !
@GP-qs6cq3 ай бұрын
can i setup llamIndex on my own server? i dont want to use api or don't want to send data to other's server
@sarveshsawant7232Ай бұрын
This is perfect
@alejandro_ao17 күн бұрын
you are
@encianhoratiu53012 ай бұрын
Can you make a video where you discuss how you can test a RAG?
@J.jocker3 ай бұрын
what 's the different between (llamaindex for chatbot creation) and (langchain +streamlit ...for pdf bot(the video you did last time) which of them is more suitable if I want to create a chatbot for a company
@alejandro_ao3 ай бұрын
there is a bit of overlap between the two. but you really can't go wrong with either of them. they are both very reliable and have a great community. it seems to me that llamaindex is focusing a lot more on the data ingestion side and langchain is going more for them overall orchestration of the components. at least for now. the good news is that you can use both :) most of the paradigms are compatible, so you can take advantage of the strengths of each one. in the meantime, i recommend you focus on one of the two and then start implementing features from the other one as needed. you will soon get the core concepts and be able to choose which one is better suited fr a specific project 👍
@_wallykhalid2 ай бұрын
Really interested to see a fully open source version of this with hugginface embeddings and models.
@alejandro_ao2 ай бұрын
coming up!! sorry been super busy with the cohort 😅
@KumR3 ай бұрын
Hey AO.. Looks like the default LLM is being used which is Da Vinci. Can we upgrade to GPT4o?
@alejandro_ao3 ай бұрын
hello there, absolutely. for this particular example, you can just add the model param to the query engine: ```python from llama_index.core import VectorStoreIndex, SimpleDirectoryReader from llama_index.llms.openai import OpenAI documents = SimpleDirectoryReader("data").load_data() index = VectorStoreIndex.from_documents(documents) query_engine = index.as_query_engine(llm=OpenAI(model="gpt-4o-mini")) response = query_engine.query("What is the bootcamp about?") print(response) ``` btw, i am pretty sure that the default model that llamaindex uses with openai is gpt-3.5-turbo. look: github.com/run-llama/llama_index/blob/41643a65bc89cfdb3eb0c11b4f8cb256b02aa21c/llama-index-integrations/llms/llama-index-llms-openai/llama_index/llms/openai/base.py#L78
@trealwilliams15632 ай бұрын
Thank You✊🏾💎
@alejandro_ao2 ай бұрын
😌 no problem
@VR-fh4im2 ай бұрын
You should become a professor it will benefit thousands of students in your country. Well taught.
@alejandro_ao2 ай бұрын
i hope to do that one day! thank you, it means a lot!
@jacobsmith78773 ай бұрын
Looking forward to Agentic RAG system build with function calling and etc
@yaseenal-wesabi59643 ай бұрын
Should we pay for the openai api key? And How
@AMR24423 ай бұрын
I’m waiting for the local install video.
@CaiqueBikeBJJ2 ай бұрын
Do you already have a video how to use Llama-Index with local llama3 instead of ChatGPT? Thanks!
@alejandro_ao2 ай бұрын
Not yet, but coming up next week!
@limjuroy70782 ай бұрын
Interesting~
@acharafranklyn51673 ай бұрын
Welldone boss i almost thought you stole it from Krish Naik but your adding the lamaparse made the difference
@alejandro_ao3 ай бұрын
thanks mate! i'm pretty sure both of us took it from the official docs, tbh 😅 but yeah, i wanted to give a more wholesome presentation of all their offer, not only the open-source part :)
@alejandro_ao3 ай бұрын
i feel like this shirt makes it look like i'm at the beach
@SamiUllah-xv8ft3 ай бұрын
it looks cool
@alejandro_ao3 ай бұрын
😎
@sylap3 ай бұрын
looking great bro!
@sam-uw3gf3 ай бұрын
can do langchain tutotrial with open source I was searching and got none in case any please give me the link
@SonGoku-pc7jl3 ай бұрын
thanks
@alejandro_ao3 ай бұрын
thank *you*!
@GabrielVilladiegoOchoa-nt1xc3 ай бұрын
Excelente
@alejandro_ao3 ай бұрын
hola amigo 🙌
@TriconDigitalАй бұрын
hoping for video #2
@alejandro_ao17 күн бұрын
finally here, sorry lots of work!!
@Rits1804-l4r2 ай бұрын
brother please make a video on RAG (by using the llama index), I have done it already if you need I can send you, so you can save your time for research, Please explain it in your language , please use open source model instead open ai
@adityahpatel3 ай бұрын
It is vague at this point - 12:50 "nodes are interconnected creating a network of knowledge". This is very old technique. Obviously embeddings of chunks semantically close to each other will fall in the same area in embedding space. So they are interconnected..How is this any different from chroma db or ANY xyz other vector database in the world? What is different here!
@romanemul12 ай бұрын
LlamaIndex is a commercial product, with pricing based on usage... Ok bye. Thanks for a video anyway.