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Updated 2 years ago

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A community member encountered an error when trying to use the codeinterpreter tool, and the community members provided suggestions to resolve the issue. The suggestions included removing tools_spec from the import path and checking the source code. One community member mentioned that the notebook for the tool uses the proper import, and another community member asked about finding interesting data agent case studies and how to set up memory. The community members provided some resources for finding tool examples and agent demos, and confirmed that memory is automatically turned on when using chat.

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Hey team, I was trying to use the codeinterpreter tool, but got error:
ModuleNotFoundError: No module named 'llama_hub.tools.tool_spec'

Can you please help?
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16 comments
Remove tools_spec from the import path
Was that from a demo notebook ? 🫠
ahhh i see, let me try
yea... πŸ˜‚
I really wish we can have more quality examples
That one should not have slipped by. Sorry about that πŸ˜•
When in doubt, I always check the source code. That's probably just a "me" thing hahaha
haha, got cha, thanks so much for the prompt support Logan!
by the way - is there places where i can see interesting data agent case studis notebook?
so i can learn better about unique use cases can be built in data agents versus langchain
Hmmm, not really case studies yet. There is a folder of tool examples here
https://github.com/emptycrown/llama-hub/tree/main/llama_hub/tools/notebooks

As well as some agent demos here using llama index stuff
https://gpt-index.readthedocs.io/en/latest/core_modules/agent_modules/agents/modules.html
got it, thanks!
ContextRetrieverOpenAIAgent is pretty awesome
sorry one last question.. πŸ˜‚

How do i setup memory? is it automatically have memory turned on when i use chat? or do i need to do something special?
It automatically has memory! πŸ‘Œ
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