Metadata-Version: 2.4
Name: apherisfold-cli
Version: 0.1.10
Summary: Prototype ApherisFold CLI for Hub-backed customer demos.
Author: Apheris
License-Expression: MIT
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: jsonschema<5,>=4
Requires-Dist: rich>=13
Requires-Dist: truststore<1,>=0.10
Requires-Dist: typer<1,>=0.12
Provides-Extra: dev
Requires-Dist: pytest<9,>=8; extra == "dev"
Requires-Dist: ruff<1,>=0.9; extra == "dev"
Dynamic: license-file

# ApherisFold CLI

Command-line interface for submitting and managing prediction, benchmark, and fine-tuning workflows on an Apheris Hub instance.

## Requirements

- Python 3.10 or later
- Access to an Apheris Hub instance

## Installation

### conda

Recommended if you already use conda for scientific Python work. A dedicated environment avoids dependency conflicts.

#### Linux / macOS

```bash
conda create -n apherisfold python=3.11 -y
conda activate apherisfold
pip install apherisfold-cli
```

#### Windows (Anaconda Prompt or PowerShell)

```powershell
conda create -n apherisfold python=3.11 -y
conda activate apherisfold
pip install apherisfold-cli
```

Activate the environment at the start of each session with `conda activate apherisfold`.

### venv (standard Python)

#### Linux / macOS (venv)

```bash
python3 -m venv ~/.venvs/apherisfold
source ~/.venvs/apherisfold/bin/activate
pip install apherisfold-cli
```

#### Windows (PowerShell, venv)

```powershell
python -m venv $env:USERPROFILE\.venvs\apherisfold
& $env:USERPROFILE\.venvs\apherisfold\Scripts\Activate.ps1
pip install apherisfold-cli
```

Activate the environment at the start of each session with the `activate` command above.

### Verify

```bash
apherisfold --version
apherisfold --help
```

### Upgrade

```bash
pip install --upgrade apherisfold-cli
```

## Quick start

```bash
# Log in with your ApherisFold Hub URL
apherisfold login --url https://hub.example.com

# See available models and weights
apherisfold weights list

# Submit a prediction
apherisfold workflow predict run \
  --model openfold3 \
  --weight 3.0.0 \
  --input ./request.json

# By default, local artifacts are written under ./.apherisfold/runs/<workflow>/<id>
# relative to the directory where you run the command. Use --output to choose another directory.

# List submitted jobs
apherisfold workflow predict list

# Inspect a job
apherisfold workflow predict get --id job_NUlyMsnWq
```

## Workflows

| Workflow             | Entry point                                   |
| -------------------- | --------------------------------------------- |
| Structure prediction | `apherisfold workflow predict run`            |
| Benchmarking         | `apherisfold workflow benchmark run`          |
| Fine-tuning          | `apherisfold workflow fine-tune prepare`      |

### Affinity prediction

When using weights that support affinity prediction, the CLI selects the ligand chain automatically if there is only one. For queries with multiple ligand chains, specify which one to score with `--affinity-ligand`:

```bash
apherisfold workflow predict run \
  --model openfold3 \
  --weight 3.0.0 \
  --input ./request.json \
  --affinity-ligand B
```

Use `--help` on any subcommand for the full option reference and examples:

```bash
apherisfold workflow predict run --help
apherisfold workflow benchmark run --help
apherisfold workflow fine-tune prepare --help
```

## Support

Contact [support@apheris.com](mailto:support@apheris.com) for access and deployment assistance.
