Metadata-Version: 2.4
Name: tonina
Version: 0.1.0
Summary: Multi-agent bioinformatics analysis system with comprehensive capabilities
License-Expression: GPL-3.0
Project-URL: Homepage, https://github.com/ToyokoLabs/tonina
Project-URL: Repository, https://github.com/ToyokoLabs/tonina
Requires-Python: >=3.12
Description-Content-Type: text/markdown
Requires-Dist: gffutils>=0.13
Requires-Dist: strands-agents[anthropic,gemini,ollama,openai]>=1.10.0
Requires-Dist: strands-agents-tools>=0.2.9
Requires-Dist: biopython>=1.85
Requires-Dist: python-dotenv>=1.0.0

# Tonina - Multi-Agent Bioinformatics Analysis System

Tonina is a comprehensive multi-agent bioinformatics analysis system that extends the capabilities of gffutilsAI to handle multiple types of biological data through specialized AI agents.

## Features

### Multi-Agent Architecture
- **GFF Agent**: Complete GFF file analysis (ported from gffutilsAI)
- **Sequence Agent**: FASTA sequence analysis and manipulation
- **Proteomics Agent**: Protein structure and functional analysis
- **Phylogenetics Agent**: Evolutionary analysis and tree operations
- **General Agent**: Cross-format utilities and file operations

### Intelligent Query Routing
Tonina automatically routes your queries to the appropriate specialized agent based on:
- File types (.gff, .fasta, .pdb, etc.)
- Query content and keywords
- Domain-specific terminology

### Multi-LLM Support
- **Local Models**: Ollama (llama3.1, codellama, etc.)
- **Cloud Models**: OpenAI GPT-4, Anthropic Claude, Google Gemini
- **Flexible Configuration**: Easy switching between providers

## Installation

```bash
# Clone the repository
git clone <repository-url>
cd tonina

# Install dependencies
pip install -e .

# Or using uv (recommended)
uv pip install -e .
```

## Configuration

1. Copy the example environment file:
```bash
cp .env.example .env
```

2. Edit `.env` with your API keys:
```bash
# For cloud models (optional)
OPENAI_API_KEY=your_key_here
ANTHROPIC_API_KEY=your_key_here
GOOGLE_API_KEY=your_key_here
```

## Usage

### Basic Commands

```bash
# Interactive mode with local model
tonina --model llama3.1 --server local

# Single query
tonina --query "What genes are in chromosome 1?" --model gpt-4o

# Batch processing
tonina --batch queries.txt --model claude-3-5-sonnet-latest

# Specific provider
tonina --anthropic --model claude-3-5-sonnet-latest
tonina --gemini --model gemini-2.0-flash-exp
tonina --openai --model gpt-4o
```

### Agent-Specific Examples

#### GFF Analysis
```bash
tonina "Find all genes in chromosome 1 between positions 1000-5000"
tonina "Calculate feature statistics for my GFF file"
tonina "Export all membrane proteins to CSV"
```

#### Sequence Analysis
```bash
tonina "Analyze this FASTA file for ORFs"
tonina "Calculate GC content for all sequences"
tonina "Find motifs in this protein sequence"
```

#### Multi-Agent Workflows
```bash
tonina "Extract genes from GFF, get their sequences, and analyze domains"
# This automatically coordinates: GFF Agent → Sequence Agent → Proteomics Agent
```

## Agent Capabilities

### GFF Agent (31 tools)
- Coordinate-based queries and region analysis
- Feature statistics and length distributions
- Attribute searches and GO function analysis
- Intergenic region identification
- Comprehensive export capabilities

### Sequence Agent (15+ tools)
- FASTA file parsing and validation
- Sequence composition analysis
- ORF finding and translation
- Motif searching and pattern matching
- Multiple sequence alignment

### Proteomics Agent (15+ tools)
- Protein structure analysis (PDB files)
- Domain prediction and annotation
- Functional classification
- Comparative protein analysis

### Phylogenetics Agent (10+ tools)
- Phylogenetic tree parsing
- Evolutionary distance calculations
- Species comparison
- Ortholog identification

### General Agent (10+ tools)
- Cross-format file operations
- Data integration workflows
- Format conversion utilities
- Batch processing tools

## Development

### Adding New Agents

1. Create agent directory: `src/tonina/agents/new_agent/`
2. Implement tools with `@tool` decorator
3. Create agent class extending `BaseAgent`
4. Register in `AgentManager`

### Adding New Tools

```python
from strands import tool

@tool
def my_analysis_tool(input_file: str, parameter: str) -> dict:
    \"\"\"Tool description for AI understanding\"\"\"
    # Implementation
    return {"result": "analysis_output"}
```

## License

GPL-3.0 License - see LICENSE file for details.

## Contributing

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Submit a pull request

## Support

For issues and questions, please use the GitHub issue tracker.
