Wow CSV file reading agent, this is so cool, does this mean that agent can also be programmed to generate SQL and access data from a database and do additional analysis?
As far as I know, the only sql parser in crewai tools is PGSearchTool, which is specifically made for PostgreSQL database tables; yep, it can search and generate sql queries, I think they call it Retrieve and Generate RAG. I haven't tested it yet, but if enough viewers ask for it, I may make sth out of it :)
Thanks for your comment. You are right! I checked the top 3 manually in the CSV file and it looks different. With Mistral I get more accurate results. However, LLAMA3 produced a good synthesis of the career path. The video is basically meant as a tutorial (how to do), but the choice of LLM makes a difference. Thanks for watching :)
Is your dataset a CSV file? This video tutorial is a standard way of calling a CSV file within the CrewAI framework, if you don't get accurate results, change the model, e.g., to Mistral or Qwen2, or dbrx (from Databricks) on a sample dataset where you already know the results; any of the model's which produce accurate results, use that one on your target dataset. If you are doing a more serious data anlytics work, keep in mind that most of these LLMs are primarily language models (designed to predict the next word, not necessarily the 'correct' data), so in this case, using the traditional methods in Pandas, for example for data wrangling, or machine learning models from Scikit-learn will give you the most accurate results. If you insist on agentic method, then try asking one of those LLM agents to access Pandas or Scikit-learn and do the work for you. I haven't tried this honestly, so I don't know how it would turn out. But please keep me updated if this works for you. Hope this information helps :0
