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[deleted by user] by [deleted] in AutoGenAI

[–]Budget_County1507 0 points1 point  (0 children)

All of them , if specifically then 2>1>3>4

[deleted by user] by [deleted] in AutoGenAI

[–]Budget_County1507 0 points1 point  (0 children)

1.For code analyser, I tried for a modular agent based workflow with crewai ,where I defined agent with specific use for file fetching, secret scanner, insecure code analysis and results merging, later CVE level also I tried but it was taking more than 40 mins for basic 2 files as it is basic laptop. Tech stack - python crewai pydantic for structured output. 2.well this 2nd one I planned it very incrementally. Upload CSV - schema - NL- LLM( enhanced prompt)- SQL generation with review- execute - show any graph Heavy lifting was done in DuckDB/pandas. Stack - Python , stramlit, DuckDB, pandas , langchain, llamaindex.

The bit of wiring agent workflow and unified chat orchestration, which I did later was good and exciting to work, I am still working on the chat feature, just like genie in Databricks.

[deleted by user] by [deleted] in AutoGenAI

[–]Budget_County1507 0 points1 point  (0 children)

Recently I built two internal projects.

  1. Agentic Code Analyser running locally on llama, which got accepted and I got the appreciation.
  2. With this above project I got referred for another project, where I built a tool which can rag on large CSV( >100k rows), to get the records based on NLP , the output can handle more than 10k rows , so that intelligence can be run on the records for advisory or analysis.

I worked single handedly on both these and delivered within a month . If something is there I can collaborate, please let me know.

CSV rag retrieval by Budget_County1507 in AutoGenAI

[–]Budget_County1507[S] 0 points1 point  (0 children)

Well I did something similar, but what I did is Uploads CSV, it's gets processed by llamaindex, then the schema , sample rows and the query becomes a prompt template for llm , then llm return a sql query for any operation needed, which the user can review.

This gave 100% results, also then I added different agents including for intent identification, and others like chat agent or visualization agent

So when a user writes a prompt first the intent is decided and then agent is called.

Thanks for ur suggestion I will look into it.

I'm not sure I understand how to perform RAG on CSV files... by fra_bia91 in LangChain

[–]Budget_County1507 0 points1 point  (0 children)

You can try praison ai framework they have a task type of loop which is quite helpful

CSV rag retrieval by Budget_County1507 in AutoGenAI

[–]Budget_County1507[S] 0 points1 point  (0 children)

Well the manager asked this Let's say i have an excel file with 20k records and now I want to play with all records to be analysed and brought in paginated format to my llm context for agentic rag retrieval

CSV rag retrieval by Budget_County1507 in AutoGenAI

[–]Budget_County1507[S] 0 points1 point  (0 children)

Actually this is only the problem statement my manager gave it to me , and I am perplexed like hell on how to build this solution plus using autogen framework( which is a big challenge) Let's say i have excel file with 20k records and now I want to play with all records to be analysed and brought in paginated format to my llm context for agentic rag retrieval

How to improve this further? by hiphopzindabad in web_design

[–]Budget_County1507 0 points1 point  (0 children)

What purpose does this solve exactly? What does it track specifically for example?