docs: README

README.md

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+---
+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.
+
+## Features
+
+- **Dataset Curation**: Generate and curate image datasets
+- **Single Image Analysis**: Benchmark different AI models on individual images
+- **Agentic Analysis**: Multi-step AI reasoning and analysis
+- **Multiple AI Providers**: Support for OpenAI, Anthropic, and Google AI
+
+## Quick Start
+
+### 1. Setup Environment
+
+```bash
+cd simple_G_ai_bot
+```
+
+Create a `.env` file in the project root:
+
+```bash
+# .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
+```
+
+### 2. Install Dependencies
+
+```bash
+uv sync
+```
+
+### 3. Usage Examples
+
+#### Dataset Curation
+Generate 50 urban outdoor samples:
+```bash
+python main.py --mode data --samples 50 --urban --no-indoor
+```
+
+#### Single Image Analysis
+Benchmark GPT-4o on 5 samples:
+```bash
+python main.py --mode benchmark --models gpt-4o --samples 5
+```
+
+#### Agentic Analysis
+Run multi-step analysis with Gemini:
+```bash
+python main.py --mode agent --model gemini-2.5-pro --steps 10 --samples 5
+```
+
+## Configuration
+
+### Environment Variables
+
+| Variable | Description | Required |
+|----------|-------------|----------|
+| `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)
+
+## Supported Models
+
+- **OpenAI**: GPT-4o, GPT-4, GPT-3.5-turbo
+- **Anthropic**: Claude-3-opus, Claude-3-sonnet, Claude-3-haiku
+- **Google**: Gemini-2.5-pro, Gemini-pro, Gemini-pro-vision
+
+## Requirements
+
+- Python 3.8+
+- UV package manager
+- Valid API keys for desired AI providers
+
+## Installation
+
+1. Clone the repository
+2. Navigate to project directory: `cd simple_G_ai_bot`
+3. Create `.env` file with your API keys
+4. Install dependencies: `uv sync`
+5. Run the bot with desired mode and options
+
+## Examples
+
+### Basic Dataset Generation
+```bash
+python main.py --mode data --samples 20
+```
+
+### Urban Scene Analysis
+```bash
+python main.py --mode data --samples 30 --urban --no-indoor
+```
+
+### Model Comparison
+```bash
+python main.py --mode benchmark --models gpt-4o --samples 10
+python main.py --mode benchmark --models claude-3-opus --samples 10
+```
+
+### Advanced Agentic Workflow
+```bash
+python main.py --mode agent --model gemini-2.5-pro --steps 15 --samples 3
+```
+
+## Security Note
+
+⚠️ **Important**: Never commit your `.env` file to version control. Add `.env` to your `.gitignore` file to keep your API keys secure.
+
+## License
+
+MIT License - see LICENSE file for details.