[@rohitkrsingh]

please take it to the next level. RAG and openAI both would be great for better results. Awesome work.

[@NeuralHackswithVasanth]

Cool sure

[@kishoretvk]

thanks for yet another good video.
langchain agents,
vllm setup, speculative decoding are few other good topics to cover, they make this app for next level upgrades

[@NeuralHackswithVasanth]

All great suggestions ☺️

[@henkhbit5748]

I have some additional question: how to add memory during the chat conversation?

[@karthikeyakuncham6929]

I think it handles only a single user number, what if the bot is about to handle multiple users?

[@tintintintin576]

Thank you so much for this!! Brilliant tutorial!

[@NeuralHackswithVasanth]

Glad 😊

[@vivekvyas3009]

While using whatsapp chatbot if the user uses different ksywords to reach to his desired results for eg if he uses 6 keywords in a flow in thst case will meta consider this as 6 chats or only one chat and will meta charge us for 6 chats or one chat? Please guide

[@NeuralHackswithVasanth]

I am not able to understand your query can you please simplify it

[@henkhbit5748]

Great video 👏👏

[@NeuralHackswithVasanth]

Thanks

[@henkhbit5748]

Thanks for the video. I thought ollma is not suited for multiuser out of the box? A similar video Using gradio or streamlit with local LLM would be Nice…

[@NeuralHackswithVasanth]

WhatsApp Chatbot using Streamlit? Which kind of video?

[@henkhbit5748]

@@NeuralHackswithVasanthlocal llm, rag, fastapi and streamlit with streaming (calling fastapi api)