How tufanbera/insightllm- works
InsightLLM is a Streamlit no-code analytics app: users upload CSV or Excel data, inspect an overview and visualizations, and request AI insights or answers in natural language. The app coordinates dataset loading and statistics, chart generation, and Gemini requests, then presents results. The README documents these capabilities; sampled source confirms the main module calls and Gemini integration, while some app lines are omitted, so uncertain UI wiring is not expanded.
Main entry points: app.py Streamlit App · llm_handler.py LLM Handler · data_processor.py Data Processor · visualizer.py Chart Generator
Components 7
User Application
- Streamlit App
app.py
Dataset Analysis
- Data Processor
utils/data_processor.py - Dataset Overview
utils/data_processor.py - Chart Generator
utils/visualizer.py
AI Analysis
- LLM Handler
utils/llm_handler.py
Other components
- Analyst
- Google Gemini
Connections 9
- Analyst → Streamlit App: uploads / asks
- Streamlit App → Data Processor: loads data
- Data Processor → Streamlit App: returns dataframe
- Streamlit App → Dataset Overview: requests statistics
- Streamlit App → Chart Generator: requests charts
- Streamlit App → LLM Handler: requests insights / answers
- LLM Handler → Google Gemini: sends prompts
- Google Gemini → LLM Handler: returns responses
- Streamlit App → Analyst: displays results