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Introducing `Personalized Agentic RAG` - where the LLM remembers key details about the user and automatically chooses the tool for RAG. We'll build: 👏 ChatGPT like memory ⚙️ Function calling 🧙 Multi-Agent orchestration code:

Ashpreet Bedi

19,986 subscribers

45,035 просмотров • 2 лет назад •via X (Twitter)

Образование Наука и технологии

Anya Rossi• Live Now

Private livecam show

Комментарии: 9

Фото профиля Joel Burigo

Joel Burigo2 лет назад

Nice work

Фото профиля Ashpreet Bedi

Ashpreet Bedi2 лет назад

thank you

Фото профиля Shashank Shekhar

Shashank Shekhar2 лет назад

What do you use for illustrations - these are incredibly clean and beautiful looking!

Фото профиля Ryan Lisse

Ryan Lisse2 лет назад

@memdotai mem it

Фото профиля Mem

Mem2 лет назад

@ashpreetbedi Saved! Here's the compiled thread:

Фото профиля Nasrin Tohidi

Nasrin Tohidi2 лет назад

Brilliant! That's exactly what I needed!

Фото профиля Power Of AI

Power Of AI2 лет назад

That is awesome👍🏻

Фото профиля Mamba S6

Mamba S62 лет назад

Is it possible to run this with ollama as well? Thanks ahead :)

Фото профиля Koma

Koma2 лет назад

what is video recorder he was use?

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Lets build `Auto-RAG` where we let the LLM pull the data it needs from different sources. 🔎 The user asks a question. 🤔 LLM decides whether to search its knowledge, memory, internet or make an API call. ✍️ LLM answers with the context. Code:

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297,129 просмотров • 2 лет назад

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