🤖 AutoSight – Automated AI Data Analysis Pipeline on Google Cloud

AutoSight is a multi-agent AI system that automates the entire data analytics pipeline — from dataset ingestion to AI-powered insights — using Google Cloud Platform (GCP).

With just a CSV URL, AutoSight:

• 📥 Crawls and uploads the dataset to Google Cloud Storage
• 📊 Cleans and analyzes trends using pandas and seaborn
• 🧠 Generates summaries using Gemini or GPT-like models
• 🗃️ Loads data into BigQuery for structured querying
• 📈 Displays all results in a modern Streamlit dashboard

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🚀 Features

• 🌐 Web-based CSV ingestion from any public URL
• 📈 Trend analysis + visual plots
• 🤖 Natural language summaries with LLMs
• ☁️ Cloud-native: Cloud Storage + BigQuery
• 🖥️ Streamlit-powered live dashboard
• 💡 Modular agent architecture for easy extensibility

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🛠️ Tech Stack

Layer	Technology
💻 Backend	Python 3.12
☁️ Cloud	Google Cloud Storage, BigQuery, Vertex AI
🤖 AI	Gemini Pro (or OpenAI GPT)
📊 Visualization	matplotlib, seaborn, Streamlit
🧱 Architecture	Multi-Agent System

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📁 Folder Structure

AutoSight/
├── main.py                      # Orchestrates entire pipeline
├── dashboard.py                 # Streamlit frontend
├── requirements.txt             # Python dependencies
├── README.md                    # This file
│
├── agents/
│   ├── data\_crawler\_agent/
│   │   └── agent.py             # Downloads CSV to GCS
│   ├── analyzer\_agent/
│   │   └── agent.py             # Analyzes data + generates summary
│   └── bigquery\_writer\_agent/
│       └── agent.py             # Loads dataset into BigQuery

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⚙️ Setup Guide

1. Clone the repository

git clone https://github.com/your-username/AutoSight.git
cd AutoSight

2. Create a virtual environment

python3 -m venv venv
source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Configure GCP

1. Enable these APIs:

   • Vertex AI
   • Cloud Storage
   • BigQuery

2. Create a service account with roles:

   • Storage Admin
   • BigQuery Data Editor
   • Vertex AI User

3. Download its credentials file as:

   autosight-agent-key.json
   

5. Run the pipeline

python main.py

The script will:

• Download and store the dataset in GCS
• Analyze and generate a plot + summary
• Load structured data into BigQuery
• Launch the interactive dashboard automatically

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📊 Example Dataset

Default dataset:

Air Travel (1958–1960)

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🧠 Future Enhancements

• Upload custom CSVs via dashboard
• Deploy Streamlit app to GCP App Engine
• Add forecasting and clustering agents
• Multi-dataset support + scheduling

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🙅‍♂️ .gitignore

Create a .gitignore with the following:

autosight-agent-key.json
output.png
summary.txt
__pycache__/
*.pyc
venv/
.env

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💬 Contact

Built by Shaun Danny

📧 shaundanny2007@gmail.com 💼 LinkedIn

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🏁 Acknowledgements

Inspired by Google Cloud Multi-Agent Hackathon and the original InsightAgents project.

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Would you like me to create and export this `README.md` file for you directly so you can drop it into your GitHub repo?