MultiAgents_DataAnalysis

A Python project implementing a multi‑agent data‑analysis pipeline that leverages an LLM for agent tasks, produces visualizations, and includes a written analysis report.

Table of Contents

• Overview
• Features
• Repository structure
• Requirements
• Installation
• Environment (OpenAI API key / .env)
• Configuration
• Usage
• Outputs
• Development notes
• Contributing
• License
• Contact

Overview

This repository coordinates multiple agents to analyze data and produce visualizations and a final analysis report. An OpenAI LLM is used by the agents; its credentials are provided via environment variables.

Features

• Multi-agent orchestration (agents.py)
• Central configuration for LLM usage (config.py)
• Utilities for data handling and plotting (utils.py)
• System message templates used by agents (system_messages.py)
• Exported analysis report (analysis_report.pdf)
• Saved visualizations (visualizations/)

Repository structure

• agents.py — agent implementations and orchestration
• main.py — entry point to run experiments / pipeline
• config.py — loads .env and defines llm_config (model, temperature, api_key, max_tokens)
• utils.py — helper functions (data loading, processing, plotting)
• system_messages.py — message templates used by agents
• visualizations/ — generated plots (output)
• analysis_report.pdf — final written report
• .gitignore
• .env.example (recommended)
• README.md

Requirements

• Python 3.8+
• Python packages likely used by the project: python-dotenv, pandas, numpy, matplotlib, seaborn, scikit-learn, requests (check imports)
• If a requirements.txt is not included, generate one from your environment or install packages manually: pip install python-dotenv pandas numpy matplotlib seaborn scikit-learn

Installation

1. Clone the repo: git clone https://github.com/ShreyanshWarde/MultiAgents_DataAnalysis-main2.git
2. Enter the project folder: cd MultiAgents_DataAnalysis-main2
3. Create and activate a virtual environment: python -m venv venv source venv/bin/activate # macOS / Linux venv\Scripts\activate # Windows
4. Install dependencies: pip install -r requirements.txt (If requirements.txt is not present, install the packages listed in Requirements.)

Environment (OpenAI API key / .env)

config.py calls load_dotenv() and reads the OPENAI_API_KEY environment variable. You must provide your OpenAI API key via environment variables or a .env file.

Recommended local setup (create a .env at repo root — DO NOT commit this file):

.env OPENAI_API_KEY=sk-REPLACE_WITH_YOUR_KEY

Alternative ways to provide the key:

• macOS / Linux: export OPENAI_API_KEY="sk-..."
• Windows PowerShell: $env:OPENAI_API_KEY="sk-..."
• CI / GitHub Actions: add OPENAI_API_KEY as a repository secret and reference it in the workflow.

Recommended committed helper files:

• .env.example (commit this file with placeholder value) Example .env.example: OPENAI_API_KEY=your_openai_api_key_here

• Ensure .env is listed in .gitignore: Add a line: .env

Security notes:

• Never commit your real API key.
• Use repository secrets in CI.

Configuration

• config.py contains llm_config:
  • model (default: "gpt-4")
  • temperature
  • api_key (read from OPENAI_API_KEY)
  • max_tokens
• Edit config.py or set environment variables to change behavior.

Usage

Run the main pipeline: python main.py

Check main.py for any CLI flags or additional parameters. Output files (visualizations, logs) are saved to the visualizations/ folder by default.

Outputs

• Visualizations: visualizations/
• Written report: analysis_report.pdf (included)

Development notes

• Ensure python-dotenv is installed (pip install python-dotenv) so load_dotenv() works.
• If you want, I can generate requirements.txt by scanning imports.
• Tests are not included — consider adding unit tests for utils and agent behavior.

Contributing

• Open issues or submit pull requests.
• Add a CONTRIBUTING.md if you want contribution guidelines.
• Add a LICENSE file to define reuse and distribution terms (MIT, Apache‑2.0, etc.).

License

No LICENSE file is included. Add one to declare a license.

Contact

Repository owner: https://github.com/ShreyanshWarde