Step by step no-code RAG application using Langflow.
HTML-код
- Опубликовано: 21 апр 2024
- Source code of this example:
github.com/svpino/llm/tree/ma...
Lanflow's GitHub Repository: bit.ly/3JcNXeC
Astra Vectorstore database: dtsx.io/4aw3x17
I teach a live, interactive program that'll help you build production-ready Machine Learning systems from the ground up. Check it out here:
www.ml.school
To keep up with my content:
• Twitter/X: / svpino
• LinkedIn: / svpino 
Наука
What I liked about this is that you start with intent and end with a result, while meticulously going through specifics, even if it is high level.
That’s the goal!
I am a software engineer with looooong experience, but I am super confused about AI and inner workings. I might just start this was to see how things operate at the top and turn this into code on the other side. Make more videos about langflow, very nice content. Thank you!
$10 per step...? This is what makes all the incoming finetunes of Lllama3 70B a game changer... that price will drop to
Very good and clear explanation! Thanks a lot for sharing the valuable information!
TY for the thoroughness in your explanation!
From learning one day to using what I learnt to quickly develop a POC is super cool. Thanks Santiago!
Wow man. This is awesome!! El fantastico. Cant wait to have more tutorials, with fully local options this time. 🎉
Great content Santiago! Well done and structured! Thanks!
This is a truly excellent tutorial. It's the first time I've worked with this framework, and the video covers every detail with perfect clarity.
I made some variations, using Ollama with llama3 and Chroma as a vector store, and everything went smoothly thanks to your clear explanations.
Fantastic work!
Awesome!
Awesome! Thx for sharing Langflow. The visual approach is my wqy to go. Exactly what I was looking for. And boom, it appeared in my timeline. 😎
And yet another great post Santiago. This is awesome!
Perfect , this really opens my mind about the possibilites we can have . keep it up , these type of videos really help
Awesome session .... I coded along and LangFlow is pretty cool.
Exactly what I was looking for! thank you!
Really cool, thanks for sharing!
Great video, that's exactly what I'm looking for. Thank you so much for sharing！
Esto es oro Santiago, muchas gracias!
This is awesome, great content, perfect explanations, so helpful, 1000 thanks Santiago for sharing! 🙏
Always great contents! Really clear and concise demo of langchain. Maybe you can make a video of how to allow the user to dynamically chose a website to ask questions about
Great tutorial. I'd LOVE to see someone (anyone!) demo how to use OpenAI custom agents via API...not just the vanilla core model(s) API.
Awesome, appreciate you're sharing it 👍does Langflow support other inputs from text, for example images, tables, etc. does it have OCR komponent supported too ?
Thank you so much for the great video.
Great tutorial...
Really good!
Holy crap this project looks SO MUCH BETTER than Flowise, from top to bottom.
Hi! Thanks for the tutorial. How do you recommend to calculate costs to run the application in production?
Amazing 🤯🤯🤯, Thank you Santiago
Thank You Santiago
Thank you for sharing your insights on "Step by step no-code RAG application using Langflow."
Question:
Regarding your use of chunking by 1000 and embedding with a size of 1536 for OpenAI, my question is: If I were to increase the chunking size to something larger, such as 2000, would that present any issues? Would it increase or decrease the performance of the model?
I'm curious to understand the tradeoffs and implications of using a larger chunking size. Does it have an impact on things like model accuracy, training time, or memory usage? I'd appreciate your insights on how the chunking size can affect the overall performance and effectiveness of the machine learning system.
Thank you again for your valuable contributions. I look forward to hearing your thoughts on this follow-up question.
Excelent!!
Nice, thanks
Great video @svpino, as always. However, I found that the python code using sample.json doesn't provide accurate results always as we get from the 'Run' using the browser. Even the same question that works well on browser gets a totally unrelated result on Python code when run with the json. Do you suggest anything on this?
Excellent man! How i can use SQL database for the RAG instead of the URL to provide the context?
Thanks man
in langflow , can we have "RAG + Tool usage" , at the same time.?
how can you set it up with Ollama?
It seems to me that your interface looks different from mine. I don't have a core component but several other menus which I don't see in yours. What have I done wrong? Great tutorial, Man.
Make sure you run the prerelease version
My input components missing , why is that ?
Does this took work offline? Meaning it doesn't effect our data privacy please?
how to use the keys from .env to run the python code if i import your flow json without embedded keys
Use the python-dotenv library.
👌👏👏👏👏👏👏👏👏
I need an app where I can transcribe and summarize videos, audio files and from sites like RUclips similar to an app like Eightify or Summarify.
the URL i am working with requires login, how would it be handled in this case?
Can’t do it like this. You need to find a way to authenticate and get access to the information.
Try agents .. crewai
ok, now how do you verify the security of the app? how do you make sure it isn't stealing your customers data?
Use it for POC only .. for production that different
something has changed since the video, it's taken over 6 hours and the install is still running Downloading wcwidth-0.2.9-py2.py3-none-any.whl (102 kB)
|████████████████████████████████| 102 kB 4.2 MB/s