# Dummy vs Real Evo2 Implementation
This document explains the dummy implementation system used for testing without requiring full Evo2 model dependencies.
The project supports two modes of operation:
1. **Real Mode**: Uses the actual Evo2 models (requires `evo2` package installation and model weights)
2. **Dummy Mode**: Uses a lightweight mock implementation that mimics the Evo2 interface
## Environment Variable
Set the `EVO2_MCP_USE_DUMMY` environment variable:
```bash
# Linux/macOS
export EVO2_MCP_USE_DUMMY=true
# Windows (cmd)
set EVO2_MCP_USE_DUMMY=true
# Windows (PowerShell)
$env:EVO2_MCP_USE_DUMMY="true"
```
Accepted values: `true`, `1`, `yes` (case-insensitive)
### In Tests
```bash
# Run tests with dummy implementation
EVO2_MCP_USE_DUMMY=true pytest
# Run real model integration tests (requires evo2 package)
pytest -m real_evo2
```
## Dummy Implementation Details
The dummy implementation (`src/evo2_mcp/dummy_evo2.py`) provides:
- **DummyEvo2**: Main model class
- `forward()`: Returns random logits and embeddings with correct shapes
- `score_sequences()`: Returns plausible log probability scores
- `generate()`: Generates random DNA sequences
- **DummyTokenizer**: Character-level DNA tokenizer
- Maps A→0, C→1, G→2, T→3, N→4
### Return Value Characteristics
- **Scores**: Random values between -2.0 and -1.0 (mean) or scaled by sequence length (sum)
- **Embeddings**: Random tensors with dimension 256
- **Generated sequences**: Random DNA strings (A, C, G, T) with length up to `n_tokens`
- **Deterministic**: Uses fixed random seed (42) for reproducibility
## GitHub Actions
The CI/CD pipeline automatically uses dummy mode by setting `EVO2_MCP_USE_DUMMY=true` in the test workflow. This:
- Speeds up test execution significantly
- Eliminates need for model weight downloads
- Reduces compute requirements
- Ensures tests pass without external dependencies
## When to Use Each Mode
### Use Dummy Mode For:
- Unit tests
- CI/CD pipelines
- Development without model access
- Fast iteration cycles
- Testing tool interfaces and validation logic
### Use Real Mode For:
- Integration tests with actual model behavior
- Validating model outputs
- Performance benchmarking
- Production deployments
## Implementation Details
The switch is implemented in `src/evo2_mcp/model.py`:
```python
USE_DUMMY_EVO2 = os.getenv("EVO2_MCP_USE_DUMMY", "false").lower() in ("true", "1", "yes")
def _create_model(checkpoint: str) -> Any:
if USE_DUMMY_EVO2:
from evo2_mcp.dummy_evo2 import DummyEvo2
return DummyEvo2(checkpoint)
from evo2 import Evo2
return Evo2(checkpoint)
```
This ensures a single, centralized switch point for all model instantiation.
