hello devs, a bit lost with how to use Supabase VectorStore, i need to process the document once in the Upload, and then use the vector store to answer the questions. most of the examples didn't explain how can be done.
before i was creating table embeddings, and save the embedded document inside it and use sql similarity search inside Supabase.

I am a bit confused here, i have a client who wants to chat or ask his data, this data will be scientific papers, so before llamaindex i was using long road using Openai, embeddings, save to Supabase, then query, so here i am a bit confused how to start, i need a bit advanced example if there is any please.

hellos devs, i want to use the OpenWeatherMapToolSpec tool in llama-index-integrations how i can import it to use it?

from llama_index.core.readers import SimpleDirectoryReader
it's working for me

devs, i need to feed a system prompt to my ReAct agent, do i use it like in the.
ReAct Agent - A Simple Intro with Calculator Tools
agent.update_prompts({"agent_worker:system_prompt": react_system_prompt}) ?

i am getting error: TypeError: FunctionTool.from_defaults() missing 1 required positional argument: 'fn'
my methods are Async functions so they need to be await

pick_func = FunctionTool.from_defaults(async_fn=flight_service.create_pickup_flight_alert)
any idea why the error is up?

hello devs, i get lost a bit looking to use LLava model , i searched the docs and the import i found in the example it doesn't work or maybe you changed the name of the Classes, i need to use LLava to read the input images

do i need always to write doc string for the function need to be called by LLM?

Hello devs, i need to know if i can pass a function that is callback function for an event, inside FunctionTool.from_defaults(fn=callback_function)

def callback_function(request:Request): resp = request.json() print(resp)

so i need to trigger the agent when i receive the event... is it possible???

@Logan M do you think it's time to bump Pydantic up and start rid off the Deprecations messages from pydantic?
example:The schema method is deprecated; use model_json_schema instead. Deprecated in Pydantic V2.0 to be removed in V3.0.

guys i need some guide here:
i didn't understand this "The output is a valid Pydantic object that we can then use to call functions/APIs" in:
https://docs.llamaindex.ai/en/stable/examples/output_parsing/openai_pydantic_program/

i already returning the valid pydantic model from OpenAIPydanticProgram.from_defaults but i get lost where to use it, i wanna feed the generated dict to another agent so it can call a functions.

i am getting this error whiel using UnstracturedReader()
Error: Resource averaged_perceptron_tagger not found. Please use the NLTK Downloader to obtain the resource:
i installed nltk package but still have same error

devs i need some suggestions in my use case here:
i saving docs that have users info in Supabase bucket, i need to load it to be used by llm agent to extract the needed data , like in the example here : https://docs.llamaindex.ai/en/stable/examples/usecases/email_data_extraction/
so i need the best practice, do i need to just create temp dir and download it? or convert the needed data to Vectors and save it then retrieve it by llm.
i am a bit Lost tbh. 😟

guys what is the roles for git branching names? example: mad/fix-bug

ok i am having issue using openai assistant using llamaindex: i got this error:
ImportError: cannot import name 'MessageContentText' from 'openai.types.beta.threads' (/llm-test/pythonProject/.venv/lib/python3.12/site-packages/openai/types/beta/threads/__init__.py). Did you mean: 'MessageContentDelta'?
I think we need to open issue and change or update the import then open PR