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Local LLM in KNIME - Financial Ratio Analysis MIR Use Case

Dataset:

Corporate Credit Rating with Financial Ratios

Using a Local LLM with your KNIME Dataflow

Agenda:

  1. When is a local LLM beneficial

  2. GPT4ALL intro and setup

  3. KNIME GenAI nodes intro and setup

  4. Use case - Generating financial analysis reports with AI

Prerequisites:

  1. Familiarity with KNIME

  2. KNIME AI Extension installed

  3. Some familiarity with LLMs and prompt engineering

Company Financial Ratios
CSV Reader
Ticker AscDate desc
Sorter
REPLACE WITHYOUR MODEL PATH
Local GPT4All LLM Selector
Retain MostRecent Records
Duplicate Row Filter
Provide instructions to the LLM and return the generated analysis
LLM Prompter
Randomly selectone company
Row Sampler
Full sector names
Table Creator
Unpivot
Replace sectorwith full names
Value Lookup
Remove the '_' in column names
String Replacer
Convert response to a JSON data type
String to JSON
Parse response
JSON Path
Create column Names: value pairs
String Manipulation
Group data intoone blob of text
GroupBy
Unpivot
Create column Names: value pairs
String Manipulation
Column Auto Type Cast
Combine response piecesto create a readable report
GroupBy

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: TosinAdekanye
Created at: 2025-10-17
On NodePit since: 2025-11-13
Last update: 2025-11-13
Created with KNIME version: v5.8.0

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