Learn RAG From Scratch - Python AI Tutorial from a LangChain Engineer

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Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer. This Python course teaches you how to use RAG to combine your own custom data with the power of Large Language Models (LLMs).
💻 Code: github.com/langchain-ai/rag-f...
If you're completely new to LangChain and want to learn about some fundamentals, check out our guide for beginners: www.freecodecamp.org/news/beg...
✏️ Course created by Lance Martin, PhD.
Lance on X: / rlancemartin
⭐️ Course Contents ⭐️
⌨️ (0:00:00) Overview
⌨️ (0:05:53) Indexing
⌨️ (0:10:40) Retrieval
⌨️ (0:15:52) Generation
⌨️ (0:22:14) Query Translation (Multi-Query)
⌨️ (0:28:20) Query Translation (RAG Fusion)
⌨️ (0:33:57) Query Translation (Decomposition)
⌨️ (0:40:31) Query Translation (Step Back)
⌨️ (0:47:24) Query Translation (HyDE)
⌨️ (0:52:07) Routing
⌨️ (0:59:08) Query Construction
⌨️ (1:05:05) Indexing (Multi Representation)
⌨️ (1:11:39) Indexing (RAPTOR)
⌨️ (1:19:19) Indexing (ColBERT)
⌨️ (1:26:32) CRAG
⌨️ (1:44:09) Adaptive RAG
⌨️ (2:12:02) The future of RAG
🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama
--
Learn to code for free and get a developer job: www.freecodecamp.org
Read hundreds of articles on programming: freecodecamp.org/news

Опубликовано:

11 май 2024

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Комментарии : 63

@mr.daniish 25 дней назад

Lance is the man! Love his content

@faisalmushtaq2287 25 дней назад

I was waiting for this particular course. Thanks

@iqtech6065 23 дня назад

Assala mu alaikum brother

@sagarkeshave5357 25 дней назад

Include more of langchain, llms, industry level based tutorials

@jplkid14 12 дней назад

The complete happenstance of the phrase "do rag" sounding like "durag" coming from this video was awesome. Sorry, totally unrelated...but it made me chuckle.

@geekyprogrammer4831 25 дней назад

This man is amazing!

@ser1ification 24 дня назад

This is great! Thank you so much!

@mukilloganathan1442 24 дня назад

Always a fan of a lance video

@utk1000 14 дней назад

VERY WELL EXPLAINED. THANK YOU

@jasonmuscat534 6 дней назад

Lance thank you for sharing your deep insights on the subject of RAG and taking the time to share this with the community. Just a question, at 1:04:00 into the overall video concerning the subject of Query Construction. For the question: "videos that are focused on the topic of chat langchain that are published before 2024" Should the result have been?: latest_publish_date: 2024-01-01 as opposed to earliest_publish_date: 2024-01-01 This would be more inline with question: "videos on chat langchain published in 2023" where the results where: earliest_publish_date: 2023-01-01 latest_publish_date: 2024-01-01 Thank you

@yashtiwari3565 23 дня назад

Please let us know when the blog related to adaptive RAG will be uploaded, Lance mentioned that he will be uploading it in a day or so. Also I wanted to ask this question to general public, which one is better, State machines or Guardrails?? (In the context of creating complex flows using llms)

@janeslt 25 дней назад

Thank you!!!

@CodeKitchen 24 дня назад

Love the teaching style! at 9:00 you mention that you've walked through the code previously. Is there another video to go with this one or did I miss something?

@KOTAGIRISIVAKUMAR 19 дней назад

those are shorts videos and they combined them to form an long single video. when lance referring previous video means not another video.

@shraeychikker694 11 дней назад

I think this is the playlist from the videos are taken: ru-vid.com/group/PLfaIDFEXuae2LXbO1_PKyVJiQ23ZztA0x

@CodeKitchen 10 дней назад

@@shraeychikker694 Nice one - many thanks :)

@devloper_hs 9 дней назад

Awesome as always

@souhaildahmeni9961 3 дня назад

Thanks for the content !

@claudiodisalvo9925 19 дней назад

This is great content. Speaking of that 95% of private data I guess a lot of practitioner are finding it hard to convince business people to share their data with an LLM provider. And of course concerns are very much understandable. I guess people would feel more comfortable if a RAG application would be able to clearly define a partition of data that it can work on for the benefit of the tool, and a partition that can be either used as obfuscated or simply never shared, not even by chance.

@Kalmaos 17 дней назад

Maybe the solution would be running the model locally?

@juanpablopenaloza5093 10 дней назад

NVDIA CHATRTX might just do the job

@cristian_palau 7 дней назад

Great video! What software is used to create these nice diagrams ?

@izzatullobaltabayev8619 13 дней назад

Thank you !

@FranciscoJPolo 24 дня назад

Great!!

@cyborg69420 3 дня назад

I recommend this vid to everyone.

@karimelfa1394 25 дней назад

thank you

@afrazhussain3778 25 дней назад

great content

@ChristianBernhardt-tp1tn 4 дня назад

i have an question. In the rag-fusion part in the fusion_rank function: why u using the index (rank) to upgrade your scores ? Isnt it better to use the variable "previous_score" ?? the variable rank is just an index, wich descripes in witch order you read in the chunks. btw ty for the video you are an livesaver

@tubege 11 дней назад

Question:. Is it possible to do RAG across different vector stores that use different embedding strategies?

@ivant_true 23 дня назад

Thanks

@Yomi4D 11 дней назад

Amazing.

@teddysalas3590 21 день назад

is it possible i can do rag and combine data with huggingface models?

@GeandersonLenz 15 дней назад

What the name of this screen recorder used by Lance?

@utkarshkapil 25 дней назад

GOLD

@iuseh 19 дней назад

llama 3 in 15T tokens, chart would be different if you released video 3 days later :)

@VipinAp-iy9tt 18 дней назад

How to add coverstional memory to it?

@iCeTainment 25 дней назад

❤❤❤

@willcheng8257 25 дней назад

Like first and then watch

@andyhall7032 24 дня назад

And there was me thinking "how can it take over 2 hours to talk about applying RAG status to your project plans"

@nawaz_haider 24 дня назад

Udemy created 50 accounts to dislike this video

@vishwanathnb128 22 дня назад

😂😂😂

@zaidnadeem4918 22 дня назад

I will create 50 accounts to like your comment 😂

@Thomas_Leo 24 дня назад

Amazing videos but how does this translate into careers or jobs? What positions are employers looking for? Would they even hire anyone without experience? How do you even get started? I'm aware this channel mostly focuses on the coding and hands-on experience but I wish there was an actual channel focused on employment. I'm pretty sure there are channels out there and if anyone has recommendations, I'll be grateful.

@samtx 23 дня назад

look on linkedin jobs title descriptions keywords if any with llm ai

@vcool 16 дней назад

Start working on some AI projects first, on your own, in your spare time. Show some results. Once you have two to show, getting a job should be easier. You don't actually need this langchain thing. As for how you get started, if you've already used GPT-4, etc., thinking about larger workflows that chain inputs and outputs in creative ways to solve problems. Also think about when you need to use embeddings for distance computation. You can use the LLM+embedding APIs directly or via an SDK, optionally sometimes with a local vector database. You don't need to go fancy.

@samtx 16 дней назад

@@vcool what results? What you done

@Andrew-Tsegaye 25 дней назад

LLM Agents plzzz... ❤

@sanjaybhatikar 13 дней назад

Thanks for the excellent video! If your goal is to democratize gen AI to as diverse an audience as possible, I suggest you stop using OpenAI in these tutorials. In many parts of the world, having a credit card is not an option and OpenAI quickly backs you into that corner. Use, promote and support open-sources alternatives instead. Thank you.

@Josholsan 22 дня назад

Hello, at 27:13 why is he using itemgetter to pass the question? What's the difference between doing that and setting a RunnablePassthrough() in there?

@flaviobrienza6081 22 дня назад

No difference, just that with RunnablePassThrough() you don't need a dictionary in the invoke

@roberth8737 24 дня назад

This is the way...

@vcool 13 дней назад

Does this video have everyone brainwashed? If you know basic programming, you don't need langchain at all. I don't like unnecessary abstractions.

@Haz2288 12 дней назад

Yeah but the building blocks are useful. Do you write your own sorting functions?

@bradyanderson2250 9 дней назад

@vcool would you mind expanding on what the alternative is to langchain? Genuinely curious on learning, not attacking

@vcool 16 дней назад

This seems like it's going to pigeonhole me and tie my hands into a small dogmatic set of patterns, when what I need is broader freedom that I can accomplish without it.