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AI Developer Accelerator
9.9k members • Free
2 contributions to AI Developer Accelerator
Jul 25 •
Do I Need RAG ?
Hi Here is another one, I got couple csv files customers.csv, support.csv, activities.csv.. they are huge files with > 50k records each. Currently they are uploaded to Sql db and using MCP to pull the data. The flow is 1. user query goes to LLM via agent (using Google ADK) 2. LLM converts that to Sql 3. Sql is executed to pull relevant data from the DB 4. Agent returns the result back to the user via LLM All working well. Wondering how can I leverage RAG here and what would be the benefit ? Is RAG primarily for unstructured data ? Thanks
0 likes • Jul 25
@Paul Miller so far tried agentic AI using Google ADK. Pulling data from local sql DB. Seems like its working fine. Also using Gemini LLM. Wondering what would be the benefit incorporating this data (csv) into RAG..
0 likes • Jul 26
@Paul Miller I think that is a great point. We do have customer commentary, activity commentary etc in the data that needs analysis and putting it in RAG may be a good idea
Jul 24 •
Leveraging AI to process log files
Hi, first time here and just getting started with GenAI and agentic AI. Wondering how can I leverage AI to process log files. Identify patterns, issues etc. Challenge here is the volume of log data and I don't want to break the bank or wait endlessly for the response.. thanks
0 likes • Jul 24
Thanks yep that is helpful. That will get me started for sure. I am also thinking the challenging part would be to identify the kind of lines to pull as patterns could occur anywhere and anytime. Selective extraction might obscure the issue ..But thanks for the idea though.
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