README.md

metadata

title: Omniscient
emoji: 👁️‍🗨️
colorFrom: indigo
colorTo: purple
sdk: streamlit
python_version: 3.11
sdk_version: 1.35.0
app_file: app.py
pinned: false

🧠 Omniscient

"The all-knowing AI that sees everything, knows everything"

A versatile AI bot for image analysis and dataset curation with support for multiple AI models

🎮 Try it Live on HuggingFace! (Actively WIP)

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✨ Features

🗃️ Dataset Curation Generate and curate high-quality image datasets with intelligent filtering and categorization. 🔍 Image Analysis with multiple angle Benchmark different AI models on individual images with detailed performance metrics.

🤖 Agentic Analysis Multi-step AI reasoning and analysis with advanced decision-making capabilities. 🌐 Multiple AI Providers Seamless integration with OpenAI, Anthropic, and Google AI platforms.

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🚀 Quick Start

📋 Step 1: Setup Environment

cd simple_G_ai_bot

Create a .env file in the project root:

# 🔐 .env
OPENAI_API_KEY=your_openai_api_key_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here
GOOGLE_API_KEY=your_google_api_key_here

📦 Step 2: Install Dependencies

uv sync

🎯 Step 3: Usage Examples

🏗️ Dataset Curation

Generate 50 urban outdoor samples:

python main.py --mode data --samples 50 --urban --no-indoor

⚡ Single Image Analysis

Benchmark GPT-4o on 5 samples:

python main.py --mode benchmark --models gpt-4o --samples 5

🧠 Agentic Analysis

Run multi-step analysis with Gemini:

python main.py --mode agent --model gemini-2.5-pro --steps 10 --samples 5

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⚙️ Configuration

🔑 Environment Variables

Variable	Description	Status
OPENAI_API_KEY	OpenAI API key for GPT models	🔶 Optional
ANTHROPIC_API_KEY	Anthropic API key for Claude models	🔶 Optional
GOOGLE_API_KEY	Google AI API key for Gemini models	🔶 Optional

🛠️ Command Line Options

🌟 Common Options

• --mode → Operation mode (data, benchmark, agent)
• --samples → Number of samples to process (default: 10)

🏙️ Data Mode Options

• --urban → Focus on urban environments
• --no-indoor → Exclude indoor scenes

📊 Benchmark Mode Options

• --models → AI model to use (e.g., gpt-4o, claude-3, gemini-pro)

🤖 Agent Mode Options

• --model → AI model for agentic analysis
• --steps → Number of reasoning steps (default: 5)

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🎯 Supported Models

Provider	Models	Status
🔵 OpenAI	GPT-4o, GPT-4, GPT-3.5-turbo	✅ Active
🟣 Anthropic	Claude-3-opus, Claude-3-sonnet, Claude-3-haiku	✅ Active
🔴 Google	Gemini-2.5-pro, Gemini-pro, Gemini-pro-vision	✅ Active

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📋 Requirements

Prerequisites:

• 🐍 Python 3.8+
• 📦 UV package manager
• 🔑 Valid API keys for desired AI providers

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🔧 Installation

1️⃣ Clone the repository git clone <repository-url> 2️⃣ Navigate to project directory cd simple_G_ai_bot

3️⃣ Create .env file with your API keys touch .env # Add your API keys 4️⃣ Install dependencies uv sync

5️⃣ Run the bot with desired mode and options! 🎉

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💡 Examples

🏗️ Basic Dataset Generation

python main.py --mode data --samples 20

🌆 Urban Scene Analysis

python main.py --mode data --samples 30 --urban --no-indoor

⚔️ Model Comparison

# GPT-4o Analysis
python main.py --mode benchmark --models gpt-4o --samples 10

# Claude-3 Analysis  
python main.py --mode benchmark --models claude-3-opus --samples 10

🧠 Advanced Agentic Workflow

python main.py --mode agent --model gemini-2.5-pro --steps 15 --samples 3

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🔐 Security Note

⚠️ Important: Never commit your .env file to version control. Add .env to your .gitignore file to keep your API keys secure.

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📜 License

MIT License - see LICENSE file for details.

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⭐ Star this repo if you find it useful!