Hi all, I am relatively new to CrewAI and had a question about efficiently creating agents/tasks to allow me to handle a problem. If you could provide any advice/point me to appropriate documentation/examples for my question below, it would be greatly appreciated!
Essentially, I want to run a series of prompts in which I ask a question about a piece of information, using the text of a file for the LLM to base it’s answers on. If I was doing this using an LLM’s API, I would simply provide the document as a system prompt and user prompt the LLM for each piece of information. However, I would like to use CrewAI to orchestrate this process and take advantage of output format enforcement, async execution and other features.
My question is:
- Given my problem overview, how would I create a crew that would efficiently execute it (especially without reproviding the file as a user prompt to every LLM call). It makes sense for me to have an agent that takes a piece of information/text and has the context of the document and outputs a well-formatted answer about the information. What’s confusing to me is how to have a task/agent that takes in as context all of the pieces of information and the document and delegates it to the specialized agent to repeat a task many times for each individual piece of information