CLI Implementation with Click

.github/workflows/tests-nightly.yml

@@ -60,7 +60,8 @@ jobs:
 
       - name: Run tests
         run: |
-          pytest --ignore=tests/e2e/ tests/
+          pytest -n8 --dist loadfile --ignore=tests/e2e/ --ignore=tests/patched/ tests/
+          pytest tests/patched/
 
       - name: cleanup pip cache
         run: |

.github/workflows/tests.yml

@@ -79,7 +79,8 @@ jobs:
 
       - name: Run tests
         run: |
-          pytest -n8 --ignore=tests/e2e/ tests/
+          pytest -n8 --dist loadfile --ignore=tests/e2e/ --ignore=tests/patched/ tests/
+          pytest tests/patched/
 
       - name: cleanup pip cache
         run: |
@@ -123,7 +124,8 @@ jobs:
 
       - name: Run tests
         run: |
-          pytest -n8 --ignore=tests/e2e/ tests/
+          pytest -n8 --dist loadfile --ignore=tests/e2e/ --ignore=tests/patched/ tests/
+          pytest tests/patched/
 
       - name: cleanup pip cache
         run: |

README.md

@@ -135,6 +135,46 @@ accelerate launch -m axolotl.cli.inference examples/openllama-3b/lora.yml \
 accelerate launch -m axolotl.cli.train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/openllama-3b/lora.yml
 ```
 
+### Axolotl CLI
+
+If you've installed this package using `pip` from source, we now support a new, more
+streamlined CLI using [click](https://click.palletsprojects.com/en/stable/). Rewriting
+the above commands:
+
+```bash
+# preprocess datasets - optional but recommended
+CUDA_VISIBLE_DEVICES="0" axolotl preprocess examples/openllama-3b/lora.yml
+
+# finetune lora
+axolotl train examples/openllama-3b/lora.yml
+
+# inference
+axolotl inference examples/openllama-3b/lora.yml \
+    --lora-model-dir="./outputs/lora-out"
+
+# gradio
+axolotl inference examples/openllama-3b/lora.yml \
+    --lora-model-dir="./outputs/lora-out" --gradio
+
+# remote yaml files - the yaml config can be hosted on a public URL
+# Note: the yaml config must directly link to the **raw** yaml
+axolotl train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/openllama-3b/lora.yml
+```
+
+We've also added a new command for fetching `examples` and `deepspeed_configs` to your
+local machine. This will come in handy when installing `axolotl` from PyPI.
+
+```bash
+# Fetch example YAML files (stores in "examples/" folder)
+axolotl fetch examples
+
+# Fetch deepspeed config files (stores in "deepspeed_configs/" folder)
+axolotl fetch deepspeed_configs
+
+# Optionally, specify a destination folder
+axolotl fetch examples --dest path/to/folder
+```
+
 ## Badge ❤🏷️
 
 Building something cool with Axolotl? Consider adding a badge to your model card.
@@ -206,7 +246,6 @@ Thanks to all of our contributors to date. Help drive open source AI progress fo
 ❌: not supported
 ❓: untested
 
-
 ## Advanced Setup
 
 ### Environment

cicd/cicd.sh

@@ -1,6 +1,7 @@
 #!/bin/bash
 set -e
 
-pytest -v --durations=10 -n8 --ignore=tests/e2e/ /workspace/axolotl/tests/
-pytest -v --durations=10 -n1 --dist loadfile -v /workspace/axolotl/tests/e2e/patched/ /workspace/axolotl/tests/e2e/integrations/
+pytest -v --durations=10 -n8 --ignore=tests/e2e/ --ignore=tests/patched/ /workspace/axolotl/tests/
+pytest -v --durations=10 -n1 --dist loadfile /workspace/axolotl/tests/patched/
+pytest -v --durations=10 -n1 --dist loadfile /workspace/axolotl/tests/e2e/patched/ /workspace/axolotl/tests/e2e/integrations/
 pytest -v --durations=10 --ignore=tests/e2e/patched/ --ignore=tests/e2e/multigpu/ --ignore=tests/e2e/integrations/ /workspace/axolotl/tests/e2e/

outputs

@@ -0,0 +1 @@
+/workspace/data/axolotl-artifacts

setup.py

@@ -103,6 +103,11 @@ def parse_requirements():
     packages=find_packages("src"),
     install_requires=install_requires,
     dependency_links=dependency_links,
+    entry_points={
+        "console_scripts": [
+            "axolotl=axolotl.cli.main:main",
+        ],
+    },
     extras_require={
         "flash-attn": [
             "flash-attn==2.7.0.post2",

src/axolotl/cli/__init__.py

@@ -380,7 +380,7 @@ def choose_config(path: Path):
 
     if len(yaml_files) == 1:
         print(f"Using default YAML file '{yaml_files[0]}'")
-        return yaml_files[0]
+        return str(yaml_files[0])
 
     print("Choose a YAML file:")
     for idx, file in enumerate(yaml_files):
@@ -391,7 +391,7 @@ def choose_config(path: Path):
         try:
             choice = int(input("Enter the number of your choice: "))
             if 1 <= choice <= len(yaml_files):
-                chosen_file = yaml_files[choice - 1]
+                chosen_file = str(yaml_files[choice - 1])
             else:
                 print("Invalid choice. Please choose a number from the list.")
         except ValueError:

src/axolotl/cli/inference.py

@@ -2,6 +2,7 @@
 CLI to run inference on a trained model
 """
 from pathlib import Path
+from typing import Union
 
 import fire
 import transformers
@@ -16,7 +17,7 @@
 from axolotl.common.cli import TrainerCliArgs
 
 
-def do_cli(config: Path = Path("examples/"), gradio=False, **kwargs):
+def do_cli(config: Union[Path, str] = Path("examples/"), gradio=False, **kwargs):
     # pylint: disable=duplicate-code
     print_axolotl_text_art()
     parsed_cfg = load_cfg(config, inference=True, **kwargs)

src/axolotl/cli/main.py

@@ -0,0 +1,231 @@
+"""CLI definition for various axolotl commands."""
+# pylint: disable=redefined-outer-name
+import subprocess  # nosec B404
+from typing import Optional
+
+import click
+
+from axolotl.cli.utils import (
+    add_options_from_config,
+    add_options_from_dataclass,
+    build_command,
+    fetch_from_github,
+)
+from axolotl.common.cli import PreprocessCliArgs, TrainerCliArgs
+from axolotl.utils.config.models.input.v0_4_1 import AxolotlInputConfig
+
+
+@click.group()
+def cli():
+    """Axolotl CLI - Train and fine-tune large language models"""
+
+
+@cli.command()
+@click.argument("config", type=click.Path(exists=True, path_type=str))
+@add_options_from_dataclass(PreprocessCliArgs)
+@add_options_from_config(AxolotlInputConfig)
+def preprocess(config: str, **kwargs):
+    """Preprocess datasets before training."""
+    kwargs = {k: v for k, v in kwargs.items() if v is not None}
+
+    from axolotl.cli.preprocess import do_cli
+
+    do_cli(config=config, **kwargs)
+
+
+@cli.command()
+@click.argument("config", type=click.Path(exists=True, path_type=str))
+@click.option(
+    "--accelerate/--no-accelerate",
+    default=True,
+    help="Use accelerate launch for multi-GPU training",
+)
+@add_options_from_dataclass(TrainerCliArgs)
+@add_options_from_config(AxolotlInputConfig)
+def train(config: str, accelerate: bool, **kwargs):
+    """Train or fine-tune a model."""
+    kwargs = {k: v for k, v in kwargs.items() if v is not None}
+
+    if accelerate:
+        base_cmd = ["accelerate", "launch", "-m", "axolotl.cli.train"]
+        if config:
+            base_cmd.append(config)
+        cmd = build_command(base_cmd, kwargs)
+        subprocess.run(cmd, check=True)  # nosec B603
+    else:
+        from axolotl.cli.train import do_cli
+
+        do_cli(config=config, **kwargs)
+
+
+@cli.command()
+@click.argument("config", type=click.Path(exists=True, path_type=str))
+@click.option(
+    "--accelerate/--no-accelerate",
+    default=True,
+    help="Use accelerate launch for multi-GPU inference",
+)
+@click.option(
+    "--lora-model-dir",
+    type=click.Path(exists=True, path_type=str),
+    help="Directory containing LoRA model",
+)
+@click.option(
+    "--base-model",
+    type=click.Path(exists=True, path_type=str),
+    help="Path to base model for non-LoRA models",
+)
+@click.option("--gradio", is_flag=True, help="Launch Gradio interface")
+@click.option("--load-in-8bit", is_flag=True, help="Load model in 8-bit mode")
+@add_options_from_dataclass(TrainerCliArgs)
+@add_options_from_config(AxolotlInputConfig)
+def inference(
+    config: str,
+    accelerate: bool,
+    lora_model_dir: Optional[str] = None,
+    base_model: Optional[str] = None,
+    **kwargs,
+):
+    """Run inference with a trained model."""
+    kwargs = {k: v for k, v in kwargs.items() if v is not None}
+    del kwargs["inference"]  # interferes with inference.do_cli
+
+    if lora_model_dir:
+        kwargs["lora_model_dir"] = lora_model_dir
+    if base_model:
+        kwargs["output_dir"] = base_model
+
+    if accelerate:
+        base_cmd = ["accelerate", "launch", "-m", "axolotl.cli.inference"]
+        if config:
+            base_cmd.append(config)
+        cmd = build_command(base_cmd, kwargs)
+        subprocess.run(cmd, check=True)  # nosec B603
+    else:
+        from axolotl.cli.inference import do_cli
+
+        do_cli(config=config, **kwargs)
+
+
+@cli.command()
+@click.argument("config", type=click.Path(exists=True, path_type=str))
+@click.option(
+    "--accelerate/--no-accelerate",
+    default=False,
+    help="Use accelerate launch for multi-GPU operations",
+)
+@click.option(
+    "--model-dir",
+    type=click.Path(exists=True, path_type=str),
+    help="Directory containing model weights to shard",
+)
+@click.option(
+    "--save-dir",
+    type=click.Path(path_type=str),
+    help="Directory to save sharded weights",
+)
+@add_options_from_dataclass(TrainerCliArgs)
+@add_options_from_config(AxolotlInputConfig)
+def shard(config: str, accelerate: bool, **kwargs):
+    """Shard model weights."""
+    kwargs = {k: v for k, v in kwargs.items() if v is not None}
+
+    if accelerate:
+        base_cmd = ["accelerate", "launch", "-m", "axolotl.cli.shard"]
+        if config:
+            base_cmd.append(config)
+        cmd = build_command(base_cmd, kwargs)
+        subprocess.run(cmd, check=True)  # nosec B603
+    else:
+        from axolotl.cli.shard import do_cli
+
+        do_cli(config=config, **kwargs)
+
+
+@cli.command()
+@click.argument("config", type=click.Path(exists=True, path_type=str))
+@click.option(
+    "--accelerate/--no-accelerate",
+    default=True,
+    help="Use accelerate launch for weight merging",
+)
+@click.option(
+    "--model-dir",
+    type=click.Path(exists=True, path_type=str),
+    help="Directory containing sharded weights",
+)
+@click.option(
+    "--save-path", type=click.Path(path_type=str), help="Path to save merged weights"
+)
+@add_options_from_dataclass(TrainerCliArgs)
+@add_options_from_config(AxolotlInputConfig)
+def merge_sharded_fsdp_weights(config: str, accelerate: bool, **kwargs):
+    """Merge sharded FSDP model weights."""
+    kwargs = {k: v for k, v in kwargs.items() if v is not None}
+
+    if accelerate:
+        base_cmd = [
+            "accelerate",
+            "launch",
+            "-m",
+            "axolotl.cli.merge_sharded_fsdp_weights",
+        ]
+        if config:
+            base_cmd.append(config)
+        cmd = build_command(base_cmd, kwargs)
+        subprocess.run(cmd, check=True)  # nosec B603
+    else:
+        from axolotl.cli.merge_sharded_fsdp_weights import do_cli
+
+        do_cli(config=config, **kwargs)
+
+
+@cli.command()
+@click.argument("config", type=click.Path(exists=True, path_type=str))
+@click.option(
+    "--lora-model-dir",
+    type=click.Path(exists=True, path_type=str),
+    help="Directory containing the LoRA model to merge",
+)
+@click.option(
+    "--output-dir",
+    type=click.Path(path_type=str),
+    help="Directory to save the merged model",
+)
+def merge_lora(
+    config: str,
+    lora_model_dir: Optional[str] = None,
+    output_dir: Optional[str] = None,
+):
+    """Merge a trained LoRA into a base model"""
+    kwargs = {}
+    if lora_model_dir:
+        kwargs["lora_model_dir"] = lora_model_dir
+    if output_dir:
+        kwargs["output_dir"] = output_dir
+
+    from axolotl.cli.merge_lora import do_cli
+
+    do_cli(config=config, **kwargs)
+
+
+@cli.command()
+@click.argument("directory", type=click.Choice(["examples", "deepspeed_configs"]))
+@click.option("--dest", help="Destination directory")
+def fetch(directory: str, dest: Optional[str]):
+    """
+    Fetch example configs or other resources.
+
+    Available directories:
+    - examples: Example configuration files
+    - deepspeed_configs: DeepSpeed configuration files
+    """
+    fetch_from_github(f"{directory}/", dest)
+
+
+def main():
+    cli()
+
+
+if __name__ == "__main__":
+    main()

src/axolotl/cli/merge_lora.py

@@ -2,6 +2,7 @@
 CLI to run merge a trained LoRA into a base model
 """
 from pathlib import Path
+from typing import Union
 
 import fire
 import transformers
@@ -11,7 +12,7 @@
 from axolotl.common.cli import TrainerCliArgs
 
 
-def do_cli(config: Path = Path("examples/"), **kwargs):
+def do_cli(config: Union[Path, str] = Path("examples/"), **kwargs):
     # pylint: disable=duplicate-code
     print_axolotl_text_art()
     parser = transformers.HfArgumentParser((TrainerCliArgs))