Weaviate • Vector Database
Weaviate • Vector Database
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Chat With Your Data
We've updated Verba, our open-source Retrieval Augmented Generation (RAG) app, to the next version. Run models fully free and open with our Ollama and SentenceTransformer integration, completely fine-tune your RAG system, and see how easy it is to chat with your data in minutes. Edward will take you through all the new updates, show you how to set it up locally and help you get started using advanced RAG on your own data in just a couple of minutes.
GitHub: github.com/weaviate/verba
Demo: verba.weaviate.io
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Переглядів: 373

Відео

MIPRO and DSPy with Krista Opsahl-Ong! - Weaviate Podcast #103
Переглядів 1,3 тис.14 днів тому
Hey everyone! Thank you so much for watching the 103rd Weaviate Podcast with Krista Opsahl-Ong from Stanford University. Krista is the lead author of MIPRO, short for Multi-prompt Instruction Proposal Optimizer, and one of the leading developers and scientists behind DSPy! This was such a fun discussion beginning with the motivation of Automated Prompt Engineering, Multi-Layer Language Programs...
Implementing RAG using Generative Search in Weaviate
Переглядів 30021 день тому
In this video, we utilize Weaviates generative search capabilities to implement RAG in our Next.js application. We also do some prompt engineering to define how we want our LLM to interact with the data we send it from Weaviate The code for this project can be found here: github.com/weaviate-tutorials/next-vector-search Find out more about generative search and RAG in Weaviate here: weaviate.io...
Semantic Search Queries with Next.js Server Actions
Переглядів 14321 день тому
In this video, we build a search component in Next.js that users can use to input queries and trigger searches. We then use server actions in Next.js to make semantic search queries to our Weaviate database. The code for this project can be found here: github.com/weaviate-tutorials/next-vector-search Learn more about semantic search in Weaviate here: weaviate.io/developers/weaviate/search/simil...
Retrieving data from Weaviate
Переглядів 11421 день тому
In this video, we retrieve data from Weaviate using raw retrieval and semantic search. We explore various filters and adjustments we can make to our data retrieval like filters and limits. The code for this project can be found here: github.com/weaviate-tutorials/next-vector-search Learn more about Retrieval Augmented Generation with these resources: - Weaviate Javascript Client Page: weaviate....
Importing Data into Weaviate
Переглядів 12921 день тому
In this video, we bulk import a JSON file of Wikipedia data with 10k objects into Weaviate Importing created Embeddings for each object and storing them alongside each other. The code for this project can be found here: github.com/weaviate-tutorials/next-vector-search Learn more about Retrieval Augmented Generation with these resources: - Weaviate Javascript Client Page: weaviate.io/developers/...
Creating a Collection in Weaviate
Переглядів 10521 день тому
In this video, we create a collection in our Weaviate database using the Weaviate Typescript client. We set our vectoriser to use the Cohere multilingual model to generate embeddings and our generative search to use OpenAI’s GPT-4 model. The code for this project can be found here: github.com/weaviate-tutorials/next-vector-search Find out more about Cohere and other models we support on our int...
Installing the Weaviate Typescript client
Переглядів 11721 день тому
In this video, we install and set up the Weaviate Typescript client for our Next.js project. To get the Admin keys and cluster URL for your .env file, go to console.weaviate.cloud/cluster-details/ You can find the Weaviate Client page here: weaviate.io/developers/weaviate/client-libraries/typescript/typescript-v3 The code for this project can be found here: github.com/weaviate-tutorials/next-ve...
Setting up your Next.js project
Переглядів 12921 день тому
In this lesson, we set up our Next.js project from an existing template. You can access the template here: github.com/malgamves/next-vector-search-base-course The code for this project can be found here: github.com/weaviate-tutorials/next-vector-search Learn more about Retrieval Augmented Generation with these resources: - Weaviate Javascript Client Page: weaviate.io/developers/weaviate/client-...
Setting up a Weaviate Cluster on Weaviate Cloud
Переглядів 15121 день тому
We set up a free sandbox cluster in Weaviate Cloud in this lesson! The code for this project can be found here: github.com/weaviate-tutorials/next-vector-search Sign up for Weaviate Cloud here: console.weaviate.cloud/ Learn more about Retrieval Augmented Generation with these resources: Weaviate Javascript Client Page: weaviate.io/developers/weaviate/client-libraries/typescript/typescript-v3 We...
An Introduction to RAG Apps with Weaviate and Next.js
Переглядів 33621 день тому
Welcome to our course on building RAG apps in Weaviate with Next.js. In this course, we’ll create a project from scratch with Next.js using the Weaviate Typescript client. This is great for anyone looking to go from zero to something with RAG and Vector embeddings. Find the rest of the video for this course in this playlist: ua-cam.com/play/PLTL2JUbrY6tUaE8TYCVYItnwvDknJyeFL.html The code for t...
AI-Native Development with Guy Podjarny and Bob van Luijt - Weaviate Podcast #102!
Переглядів 241Місяць тому
AI is completely transforming how we build software! But how exactly? What does it mean for a software application to be AI-Native versus AI-Enabled? How many other aspects of software development and creativity are impacted by AI? Guy Podjarny is a co-founder of Snyk, a remarkably successful Cybersecurity company. He is now back on the founder journey, diving into AI-Native Development with Te...
Chat with your code: RAG with Weaviate and LlamaIndex
Переглядів 336Місяць тому
Chat with your code: RAG with Weaviate and LlamaIndex
Scaling Pandas with Devin Petersohn - Weaviate Podcast #101!
Переглядів 281Місяць тому
Scaling Pandas with Devin Petersohn - Weaviate Podcast #101!
Generative UIs with Lucas Negritto and Bob van Luijt - Weaviate Podcast #100!
Переглядів 6442 місяці тому
Generative UIs with Lucas Negritto and Bob van Luijt - Weaviate Podcast #100!
Advanced AI Agents with RAG
Переглядів 6 тис.2 місяці тому
Advanced AI Agents with RAG
ACORN with Liana Patel and Abdel Rodriguez - Weaviate Podcast #99!
Переглядів 5912 місяці тому
ACORN with Liana Patel and Abdel Rodriguez - Weaviate Podcast #99!
Window Search Tree with Josh Engels - Weaviate Podcast #98!
Переглядів 3772 місяці тому
Window Search Tree with Josh Engels - Weaviate Podcast #98!
Vector Quantization: The Vector Clubhouse Episode 2
Переглядів 2272 місяці тому
Vector Quantization: The Vector Clubhouse Episode 2
AI Renaissance Berlin - AI Buzzwords
Переглядів 1773 місяці тому
AI Renaissance Berlin - AI Buzzwords
The Future of Search with Nils Reimers and Erika Cardenas - Weaviate Podcast #97!
Переглядів 1,2 тис.3 місяці тому
The Future of Search with Nils Reimers and Erika Cardenas - Weaviate Podcast #97!
Deep Learning with Letitia Parcalabescu - Weaviate Podcast #96!
Переглядів 4383 місяці тому
Deep Learning with Letitia Parcalabescu - Weaviate Podcast #96!
All Your Vector Embeddings Are Belong To You
Переглядів 7883 місяці тому
All Your Vector Embeddings Are Belong To You
Open Source RAG running LLMs locally with Ollama
Переглядів 26 тис.3 місяці тому
Open Source RAG running LLMs locally with Ollama
Guest Lecture: Vector Quantization Techniques with Etienne | Brown University CSCI
Переглядів 4643 місяці тому
Guest Lecture: Vector Quantization Techniques with Etienne | Brown University CSCI
DSPy End-to-End: Meetup in San Francisco
Переглядів 5 тис.4 місяці тому
DSPy End-to-End: Meetup in San Francisco
Google Cloud Marketplace with Dai Vu and Bob van Luijt - Weaviate Podcast #95!
Переглядів 3374 місяці тому
Google Cloud Marketplace with Dai Vu and Bob van Luijt - Weaviate Podcast #95!
ParlayANN with Magdalen Dobson Manohar - Weaviate Podcast #94!
Переглядів 3524 місяці тому
ParlayANN with Magdalen Dobson Manohar - Weaviate Podcast #94!
Zain and JP chat about: Vector embedding models for AI
Переглядів 1,2 тис.4 місяці тому
Zain and JP chat about: Vector embedding models for AI
RAGKit with Kyle Davis - Weaviate Podcast #93!
Переглядів 7415 місяців тому
RAGKit with Kyle Davis - Weaviate Podcast #93!

КОМЕНТАРІ

  • @arpita0608
    @arpita0608 День тому

    But again sharing private info to this company can be dangerous, so uploading documents is a doubt

  • @tristanbob
    @tristanbob 4 дні тому

    Great video about an awesome open source contribution. Thanks!

  • @beta5770
    @beta5770 4 дні тому

    Adding multimodal support would just make this amazing. Weaviate does come with the multimodal operators

  • @hannahb1426
    @hannahb1426 5 днів тому

    Great video !!!!

  • @dan_taninecz_geopol
    @dan_taninecz_geopol 5 днів тому

    Can it use external vector databases?

  • @dan_taninecz_geopol
    @dan_taninecz_geopol 5 днів тому

    Does this get around the issue of inaccuracies in the function call or in the translation from natural to structured language?

  • @CharlySUASISA
    @CharlySUASISA 5 днів тому

    verba serve for api access ?

  • @m.c.4458
    @m.c.4458 6 днів тому

    I have been making my own local rag. for my professon. Just using prompt engineering :P I know how hard this is to achieve.

  • @dodmedium
    @dodmedium 11 днів тому

    this video contains no info.... not clear why we needed a separate video for this

  • @thannon72
    @thannon72 18 днів тому

    Friendly advice - you need to introduce your topics before speaking about them. This industry is just getting going, and already strange terminology and acronyms are appearing. You are both talking about very basic concepts, but for some reason speaking in another language that makes it impossible to follow. The only reason that anything is confusing is because people assume listeners know what they know.

  • @istvandarvas3372
    @istvandarvas3372 18 днів тому

    Guys! This was awesome! Thanks!

  • @joser100
    @joser100 18 днів тому

    my brain just broke-down on minute 25... I love the in-depth view, pity i was not to level... Luckily we got back to my level soon after... Very good interview...

  • @ConnorShorten
    @ConnorShorten 18 днів тому

    Thank you so much for joining the podcast Krista! It was awesome getting to discuss all these things with you! Go MIPRO and Go DSPy!!

  • @beckbeckend7297
    @beckbeckend7297 29 днів тому

    So there is no direct access to the embeddings storage, i.e. not in the same runtime, only fetching them via API. Which is basically clones vectors in the memory of a server(s) where Weaviate is located. Would be more useful to be able to work directly with the embeddings inside persistence layer. Performing clustering algorithms, launching different regressions algorithms etc. The only benefit i see, is the removal of the round-trip of the data stored in the vector database. I.e. app <-> vector database. As all of the module logic can be implemented in the app, no need to develop module for that.

  • @harrykang9055
    @harrykang9055 Місяць тому

    Is there anywhere I can find this great power point?

  • @stephenkiilu8579
    @stephenkiilu8579 Місяць тому

    Excellent! I found the video very useful

  • @mklobucaric
    @mklobucaric Місяць тому

    Thanks, great video.

  • @rickyS-D76
    @rickyS-D76 Місяць тому

    Another great video by Zain. It will be great of you can share the slides or links used in the slides. Thanks in advance.

  • @BanditZA
    @BanditZA Місяць тому

    Bros head is about to fall off

  • @jagrat12354
    @jagrat12354 Місяць тому

    I wonder if it can read data from a sql database directly ?

  • @anubisai
    @anubisai Місяць тому

    Think it's pronounced Gleaner as in you glean info from other info. Thank for the video.

  • @darkmatter9583
    @darkmatter9583 Місяць тому

    can you share code please?

  • @snehotoshbanerjee1938
    @snehotoshbanerjee1938 Місяць тому

    Great discussion!!

  • @divyaraj-rana
    @divyaraj-rana Місяць тому

    Really amazing innovation by Weaviate team! Their workshops speaks about their groundbreaking applications and making it open-source.

  • @user-xi2hx1wo1p
    @user-xi2hx1wo1p Місяць тому

    is there an implementation for this out there ?

  • @culeforever5408
    @culeforever5408 2 місяці тому

    great video

  • @MudroZvon
    @MudroZvon 2 місяці тому

    I used RAG in my life coach UA-camr AI character in Telegram. Prepared a lot of AI processed data of him, with fine-grained segments. The most amazing AI experience for me yet - JulienHimselfBot

  • @ChristopherG-k4n
    @ChristopherG-k4n 2 місяці тому

    In the description

  • @iva1389
    @iva1389 2 місяці тому

    super exciting episode

  • @VincentFulco
    @VincentFulco 2 місяці тому

    Congrats Everyone. Well done indeed. Kudos!

  • @NERDDISCO
    @NERDDISCO 2 місяці тому

    I love this video! Thank you very much!!!

  • @connor-shorten
    @connor-shorten 2 місяці тому

    Thank you so much for joining Lucas! Odapt!! Super interesting example of an AI-native application, really loved the discussion of native multimodality as well!

  • @GeorgeFoxRules
    @GeorgeFoxRules 2 місяці тому

    This is gotta be one of the weirdest videos I’ve ever seen on UA-cam. The content is so awesome and great but the camera creates some kind of a surreal image. It’s like hyper realism or something. The image quality is so immersive. It’s almost distracting so weird.

    • @thunkin-ai
      @thunkin-ai 2 місяці тому

      they're just using front lighting and a short camera focal length thing... relax...

    • @thunkin-ai
      @thunkin-ai 2 місяці тому

      actually... looks like a technique where the background is blurred... but the person is in sharp focus...

    • @thunkin-ai
      @thunkin-ai 2 місяці тому

      might be green screen

    • @philipvollet
      @philipvollet 2 місяці тому

      @@thunkin-ai@thunken Nope, no green screen, all in person, at the AI Campus in Berlin. It's the cam and blurring setup, but this is by intent

    • @thunkin-ai
      @thunkin-ai 2 місяці тому

      @@philipvollet it’s nice.

  • @syedabilgrami6603
    @syedabilgrami6603 2 місяці тому

    feels like I am watching bunch of robots talking

  • @PixelProRanger-cv5ii
    @PixelProRanger-cv5ii 2 місяці тому

    Is this a generated video?

  • @restrollar8548
    @restrollar8548 2 місяці тому

    Like the tech, but the health use case is really clunky and very simple. Medical data is messy and you would obviously be asking patients most of these questions, not an LLM!

  • @ocin3055
    @ocin3055 2 місяці тому

    Verba ist wirklich ein super Tool, bin sehr begeistert! Integriert ihr auch GraphRAG (von Microsoft) in das Tool?

  • @MrAnkitnakra
    @MrAnkitnakra 2 місяці тому

    Very helpful , I am able to set up on local host , however not able to ingest data, trying to upload a PDF

  • @etiennedilocker9729
    @etiennedilocker9729 2 місяці тому

    Love this! Thanks for the shoutout. I love that the signal processing example for quantization is now named after me, but I have to say I didn't come up with it, either. The Wikipedia article for quantization actually mentions the Analog-Digital-Converter example. I think I probably got it from there 🙃

  • @HAMLTN
    @HAMLTN 2 місяці тому

    I Have an idea that you could implement.

  • @ConnorShorten
    @ConnorShorten 2 місяці тому

    Thank you so much for joining the podcast both! I loved learning about ACORN to improve Vector Search with Filtering. The whole journey of learning about ACORN has also really helped my understanding of HNSW more broadly. Super exciting as always to see more research in Approximate Nearest Neighbor Search!

  • @drtristanbehrens
    @drtristanbehrens 2 місяці тому

    Richtig nice!

  • @kevon217
    @kevon217 2 місяці тому

    Always look forward to Connor’s hyped introductions. Great discussion. Nils sentence transformer work got me into this space in the first place. Looking forward to further advancements in multi-attribute embeddings. Would love more podcasts on sota embeddings and new directions. Been meaning to try out newer approaches like nv-embed and gritlm. Have you explored these?

  • @AdamLichty
    @AdamLichty 2 місяці тому

    Is the console only available for cloud instances? Or is there a way to have a local console or something for local docker instances?

  • @connor-shorten
    @connor-shorten 2 місяці тому

    Thank you so much for joining Josh! Learned so much from this conversation! Window Search Tree!

  • @dshorten1766
    @dshorten1766 2 місяці тому

    Another great podcast!

  • @KOTAGIRISIVAKUMAR
    @KOTAGIRISIVAKUMAR 3 місяці тому

    can anyone help me with the alternatives to the verba?

  • @Hits-Sandbox
    @Hits-Sandbox 3 місяці тому

    Wow, Victoria, is a natural in front of the Camera, perfect presentation and body language movement just right for the level of presentation required. It almost looks like she went to school for acting, NLP and Micro Expression presentation for marketing.

  • @saulyarhi675
    @saulyarhi675 3 місяці тому

    This is beautiful. I'm working with 5 classmates (electromechanical and software engineering college) on a proyect, we developed a tiny robot able to chat with patients as a co therapist, using a raspberry pi and a LLM. But the hallucinations are way too dangerous here, so i suggested to my team we start implementing RAG. Generating and "validating" the psychology database is really, really, really time consuming, it's hard, tricky and it takes a long time to have good quality examples, but we are pretty sure it's gonna be 100% worth it. I just had knowledge of Ollama and i would love to try out Verba in our prototype, so people in need can start getting attention and we can right away start recollecting data from the final model already deployed. I would love to collaborate with you guys, I'm such an enthusiast of opensource communities and corporations, and I loved the concept you evoke so much. <3