Insight Flow 📊

A "Chat with your Data" engine emphasizing transparency and strict sourcing.

📖 The "Why"

I built Insight Flow to solve a specific problem: trusting LLM analysis. Standard chatbots often hallucinate when analyzing private data. This engine is designed to be a strict analyst.

It uses a RAG (Retrieval-Augmented Generation) pipeline to ingest local CSVs, but with a twist: it forces transparency. Every answer includes a "Source Dropdown" showing the exact raw data rows the model used. If the data isn't there, the system prompt forces it to say "I don't know" rather than guessing.

Core Tech: Python 3.12, Streamlit, LangChain, ChromaDB (Vectors), OpenAI.

🚀 Quick Start

This repo uses a Makefile to handle the messy Python venv setup and execution.

1. Prerequisites (Don't skip this)

ChromaDB requires C++ compilers for its vector indexing. If you get a chroma-hnswlib error during install, you likely need this:

• Ubuntu/Debian: sudo apt-get install python3-dev build-essential
• MacOS: xcode-select --install

2. Install & Run

# Clone & Enter
git clone [https://github.com/OneBuffaloLabs/insight-flow.git](https://github.com/OneBuffaloLabs/insight-flow.git)
cd insight-flow

# Setup Env (Needs your API Key)
echo "OPENAI_API_KEY=sk-your-key-here" > .env

# Auto-install (creates venv, installs dependencies)
make install

# Launch UI (Localhost:3000)
make run

⚡ What makes this different?

Most RAG tutorials just dump text into a database. Insight Flow adds a "Senior Analyst" layer:

• Transparency First: The UI renders the raw source documents in an expander for every single answer. You can verify the math yourself.
• Anti-Hallucination: The system prompt is tuned to reject questions outside the dataset's scope.
• Analyst Controls: A sidebar slider adjusts the "Temperature." Keep it at 0.0 for strict data reporting, or bump it up if you want the model to brainstorm trends.

📂 Project Structure

• app.py: The frontend. Handles the Streamlit session state, file uploads, and chat bubbles.
• src/rag_engine.py: The brain. Manages the ChromaDB vector store, embedding generation, and LangChain retrieval logic.
• Makefile: Shortcuts for dev workflows (make clean, make lint, etc).
• requirements.txt: Pinned production dependencies.

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Built by Andrew Elbaneh @ One Buffalo Labs. License MIT