docs: del readme for now

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.