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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 views • 2 years ago •via X (Twitter)

Education Science & Technology

Anya Rossi• Live Now

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9 Comments

Joel Burigo2 years ago

Nice work

Ashpreet Bedi2 years ago

thank you

Shashank Shekhar2 years ago

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

Ryan Lisse2 years ago

@memdotai mem it

Mem2 years ago

@ashpreetbedi Saved! Here's the compiled thread:

Nasrin Tohidi2 years ago

Brilliant! That's exactly what I needed!

Power Of AI2 years ago

That is awesome👍🏻

Mamba S62 years ago

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

Koma2 years ago

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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