Would love to see how to use a complex scraper tool i created in python with an agent, can you create anything and use it as a tool for agent like another script you made that has a flask api?
Hey Mervin, I really like your explanations of these tools. Good job on that. One quick question, what is the minimum requirement of the operating system to run ollama locally.
Memory requirements 7b models generally require at least 8GB of RAM 13b models generally require at least 16GB of RAM 70b models generally require at least 64GB of RAM
Llamaindex is jist data and rag right so this is custom agents not crew or anything in combination with rag is that right or does Lindex have its own own agents now?
I liked crewAI .. not a hands on yet person with ai coding(code reader now 🤪), but the systematic way of setting up crew ai(similar to here) appealed to me
Mervin, this is good stuff, I am using PC not Mac. when I run the code , it comes back UI.py not found. where can I find this or do I have to create it?
If you already know llama index this is a easy path towards ai agents. Llama index has its own advantage in regards to simplifying handling data. But if you are beginner to the whole ai and you want to learn ai agents , try CrewAI or PraisonAI
Thanks!
Thank you
How do LlamaIndex agents compare to Langchain agents? Especially I'm curious about a comparison between the ReAct agents
Thank my man. I always on the lookout for your latest posts
Mervin, thanks a lot, I'm looking forward for more about lamaindex with the new Mistral and more komplex tools.
Can llama be accessed programmatically from a custom app via local network connection?
Would love to see how to use a complex scraper tool i created in python with an agent, can you create anything and use it as a tool for agent like another script you made that has a flask api?
How does it make decision what tool to use?
Ps: Lama Index seems to be so simple in comparison to other stuff you‘ve showed us.
Hey Mervin, I really like your explanations of these tools. Good job on that. One quick question, what is the minimum requirement of the operating system to run ollama locally.
Memory requirements
7b models generally require at least 8GB of RAM
13b models generally require at least 16GB of RAM
70b models generally require at least 64GB of RAM
@@MervinPraison thank you
cool vid
I am guessing this needs pemdas or bodmas rules .. agent with rules? If you say 3x3-5x5, it would need rules incorporation, rt?
Llamaindex is jist data and rag right so this is custom agents not crew or anything in combination with rag is that right or does Lindex have its own own agents now?
So Mervin, this is a good vid. But are there many roads to Rome? You showcased crewAI b4. How does that differ from llamaindex agents?
If you already know llama index , then this path is easy to get in to ai agents .
For beginners you can try CrewAI or PraisonAI
I liked crewAI .. not a hands on yet person with ai coding(code reader now 🤪), but the systematic way of setting up crew ai(similar to here) appealed to me
Mervin, this is good stuff, I am using PC not Mac. when I run the code , it comes back UI.py not found. where can I find this or do I have to create it?
Use a conda virtual environment. Then it doesn't matter if you're windows, Linux, mac
Mervin, please don‘t let us do it. Please show us another enhanced example!! ❤❤
Why did you say that?😅 I love small examples that could be used as a template and easily recollected.
@@farexBaby-ur8ns , yeah, and I love additional extended examples to find better into it. Not only but also… 🤩
How does it compare against crewai or langgraph?
If you already know llama index this is a easy path towards ai agents.
Llama index has its own advantage in regards to simplifying handling data.
But if you are beginner to the whole ai and you want to learn ai agents , try CrewAI or PraisonAI
This example is too simple - even I could follow and do it 😂
hai mervin teach a video on integrating with website and productionizing