moving text art; adding sensitive value redaction + sorting

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ repos:
     hooks:
       - id: isort
 -   repo: https://github.com/PyCQA/flake8
-    rev: 7.2.0
+    rev: 7.3.0
     hooks:
     - id: flake8
 -   repo: https://github.com/pylint-dev/pylint
@@ -27,7 +27,7 @@ repos:
     hooks:
     - id: pylint
 -   repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.16.0
+    rev: v1.16.1
     hooks:
     - id: mypy
       additional_dependencies:
@@ -36,7 +36,7 @@ repos:
             'pydantic>=2.5.3',
         ]
 -   repo: https://github.com/PyCQA/bandit
-    rev: 1.8.3
+    rev: 1.8.5
     hooks:
     -   id: bandit
         args: [

src/axolotl/cli/cloud/__init__.py

@@ -7,7 +7,6 @@ from typing import Union
 
 import yaml
 
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.cloud.modal_ import ModalCloud
 from axolotl.utils.dict import DictDefault
 
@@ -24,7 +23,6 @@ def do_cli_preprocess(
     cloud_config: Union[Path, str],
     config: Union[Path, str],
 ) -> None:
-    print_axolotl_text_art()
     cloud_cfg = load_cloud_cfg(cloud_config)
     cloud = ModalCloud(cloud_cfg)
     with open(config, "r", encoding="utf-8") as file:
@@ -39,7 +37,6 @@ def do_cli_train(
     cwd=None,
     **kwargs,
 ) -> None:
-    print_axolotl_text_art()
     cloud_cfg = load_cloud_cfg(cloud_config)
     cloud = ModalCloud(cloud_cfg)
     with open(config, "r", encoding="utf-8") as file:
@@ -54,7 +51,6 @@ def do_cli_lm_eval(
     cloud_config: Union[Path, str],
     config: Union[Path, str],
 ) -> None:
-    print_axolotl_text_art()
     cloud_cfg = load_cloud_cfg(cloud_config)
     cloud = ModalCloud(cloud_cfg)
     with open(config, "r", encoding="utf-8") as file:

src/axolotl/cli/config.py

@@ -13,6 +13,7 @@ import torch
 import yaml
 from transformers.utils import is_torch_bf16_gpu_available
 
+from axolotl.cli.redaction import redact_sensitive_info
 from axolotl.integrations.base import PluginManager
 from axolotl.utils.comet_ import setup_comet_env_vars
 from axolotl.utils.config import (
@@ -233,6 +234,10 @@ def load_cfg(
     setup_comet_env_vars(cfg)
     plugin_set_cfg(cfg)
 
-    LOG.info(f"cfg:\n{json.dumps(cfg, indent=2, default=str)}")
+    redacted_cfg = redact_sensitive_info(cfg)
+    LOG.info(
+        "config:\n%s",
+        json.dumps(redacted_cfg, indent=2, default=str, sort_keys=True),
+    )
 
     return cfg

src/axolotl/cli/evaluate.py

@@ -9,7 +9,6 @@ from dotenv import load_dotenv
 from transformers.hf_argparser import HfArgumentParser
 
 from axolotl.cli.args import TrainerCliArgs
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.checks import check_accelerate_default_config, check_user_token
 from axolotl.cli.config import load_cfg
 from axolotl.common.datasets import load_datasets, load_preference_datasets
@@ -35,7 +34,6 @@ def do_evaluate(cfg: DictDefault, cli_args: TrainerCliArgs) -> None:
     patch_optimized_env()
 
     # pylint: disable=duplicate-code
-    print_axolotl_text_art()
     check_accelerate_default_config()
     if int(os.getenv("LOCAL_RANK", "0")) == 0:
         check_user_token()

src/axolotl/cli/inference.py

@@ -13,7 +13,6 @@ from dotenv import load_dotenv
 from transformers import GenerationConfig, TextIteratorStreamer, TextStreamer
 
 from axolotl.cli.args import InferenceCliArgs
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.config import load_cfg
 from axolotl.cli.utils import load_model_and_tokenizer
 from axolotl.utils.chat_templates import (
@@ -255,7 +254,6 @@ def do_cli(
         kwargs: Additional keyword arguments to override config file values.
     """
     # pylint: disable=duplicate-code
-    print_axolotl_text_art()
     parsed_cfg = load_cfg(config, inference=True, rl=None, **kwargs)
     parsed_cfg.sample_packing = False
     parser = transformers.HfArgumentParser(InferenceCliArgs)

src/axolotl/cli/main.py

@@ -20,6 +20,7 @@ from axolotl.cli.args import (
     TrainerCliArgs,
     VllmServeCliArgs,
 )
+from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.sweeps import generate_sweep_configs
 from axolotl.cli.utils import (
     add_options_from_config,
@@ -40,6 +41,7 @@ LOG = get_logger(__name__)
 @click.version_option(version=axolotl.__version__, prog_name="axolotl")
 def cli():
     """Axolotl CLI - Train and fine-tune large language models"""
+    print_axolotl_text_art()
 
 
 @cli.command()

src/axolotl/cli/merge_lora.py

@@ -6,7 +6,6 @@ from typing import Union
 import fire
 from dotenv import load_dotenv
 
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.config import load_cfg
 from axolotl.cli.utils import load_model_and_tokenizer
 from axolotl.utils.dict import DictDefault
@@ -23,8 +22,6 @@ def do_merge_lora(*, cfg: DictDefault) -> None:
     Args:
         cfg: Dictionary mapping `axolotl` config keys to values.
     """
-    print_axolotl_text_art()
-
     model, tokenizer, processor = load_model_and_tokenizer(cfg=cfg)
     safe_serialization = cfg.save_safetensors is True
 

src/axolotl/cli/merge_sharded_fsdp_weights.py

@@ -22,7 +22,6 @@ from huggingface_hub import split_torch_state_dict_into_shards
 from safetensors.torch import save_file as safe_save_file
 from torch.distributed.checkpoint.format_utils import _EmptyStateDictLoadPlanner
 
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.config import load_cfg
 from axolotl.utils.logging import get_logger
 
@@ -194,7 +193,6 @@ def do_cli(config: Union[Path, str] = Path("examples/"), **kwargs):
         kwargs: Additional keyword arguments to override config file values.
     """
     # pylint: disable=duplicate-code
-    print_axolotl_text_art()
     parsed_cfg = load_cfg(config, **kwargs)
 
     fsdp_dir = Path(parsed_cfg.output_dir) / "pytorch_model_fsdp_0"

src/axolotl/cli/preprocess.py

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
 from transformers import AutoModelForCausalLM
 
 from axolotl.cli.args import PreprocessCliArgs
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.checks import check_accelerate_default_config, check_user_token
 from axolotl.cli.config import load_cfg
 from axolotl.common.const import DEFAULT_DATASET_PREPARED_PATH
@@ -33,7 +32,6 @@ def do_preprocess(cfg: DictDefault, cli_args: PreprocessCliArgs) -> None:
         cfg: Dictionary mapping `axolotl` config keys to values.
         cli_args: Preprocessing-specific CLI arguments.
     """
-    print_axolotl_text_art()
     check_accelerate_default_config()
     check_user_token()
 

src/axolotl/cli/quantize.py

@@ -7,7 +7,6 @@ from typing import Union
 
 from transformers import AutoModelForCausalLM
 
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.config import load_cfg
 from axolotl.loaders import load_tokenizer
 from axolotl.utils.logging import get_logger
@@ -27,7 +26,6 @@ def do_quantize(
         config (Union[Path, str]): The path to the config file
         cli_args (dict): Additional command-line arguments
     """
-    print_axolotl_text_art()
 
     cfg = load_cfg(config)
 

src/axolotl/cli/redaction.py

@@ -0,0 +1,96 @@
+"""Utils for redaction of sensitive information in config."""
+
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+# NOTE: Borrowed from the telemetry logic. Should be unified with it once merged.
+WHITELIST_PATH = str(Path(__file__).parent / "redaction_whitelist.yaml")
+
+with open(WHITELIST_PATH, encoding="utf-8") as f:
+    WHITELIST = yaml.safe_load(f)
+
+    # Send org strings to lowercase since model names are case insensitive
+    WHITELIST["organizations"] = {org.lower() for org in WHITELIST["organizations"]}
+
+
+# NOTE: Need to keep these up to date with any config schema changes.
+FIELDS_TO_REDACT = {
+    "base_model",
+    "tokenizer_config",
+    "base_model_config",
+    "pretraining_dataset",  # NOTE: this field may be a string or a dictionary.
+    "resume_from_checkpoint",
+    "hub_model_id",
+}
+PREFIXES_TO_REDACT = {"wandb_", "comet_", "mlflow_", "gradio_"}
+PATH_INDICATORS = {"path", "dir"}
+
+
+def is_whitelisted(value: str) -> bool:
+    """
+    Check if model / dataset / etc. org is in whitelist.
+
+    This logic is borrowed from the telemetry logic. Should be unified with it once
+    merged.
+
+    Args:
+        value: Value for one of `FIELDS_WITH_ORGS` ("base_model", etc.).
+
+    Returns:
+        Boolean indicating whitelist membership.
+    """
+    # NOTE: This membership-checking logic can be improved.
+    # What happens when a local model path matches a whitelisted org?
+    parts = value.split("/")
+    if len(parts) < 2:
+        return False
+    org = parts[0]
+    whitelisted = org.lower() in WHITELIST["organizations"]
+
+    return whitelisted
+
+
+def redact_sensitive_info(properties: dict[str, Any]) -> dict[str, Any]:
+    """
+    Redact properties to remove any paths, API keys, etc., so as to avoid collecting
+    private or personally identifiable information (PII).
+
+    This logic is borrowed from the telemetry logic. It can be unified with it once
+    merged.
+
+    Args:
+        properties: Dictionary of properties to redact.
+
+    Returns:
+        Properties dictionary with redaction applied.
+    """
+    if not properties:
+        return {}
+
+    def redact_value(value: Any, key: str = "") -> Any:
+        """Recursively sanitize values, redacting those with path-like keys"""
+        if isinstance(key, str) and isinstance(value, str):
+            # Other redaction special cases
+            if (
+                key in FIELDS_TO_REDACT
+                or any(prefix in key for prefix in PREFIXES_TO_REDACT)
+                or any(indicator in key.lower() for indicator in PATH_INDICATORS)
+            ):
+                # Fields with whitelisted orgs don't need to be redacted
+                if not is_whitelisted(value):
+                    return "[REDACTED]"
+
+        # Handle nested values
+        if isinstance(value, dict):
+            return {k: redact_value(v, k) for k, v in value.items()}
+        if isinstance(value, list):
+            return [redact_value(item) for item in value]
+
+        return value
+
+    # Create new dict with redacted values
+    redacted = {k: redact_value(v, k) for k, v in properties.items()}
+
+    return redacted

src/axolotl/cli/redaction_whitelist.yaml

@@ -0,0 +1,17 @@
+organizations:
+  - "axolotl-ai-co"
+  - "meta-llama"
+  - "huggingface"
+  - "nvidia"
+  - "facebook"
+  - "google"
+  - "microsoft"
+  - "deepseek-ai"
+  - "HuggingFaceTB"
+  - "mistralai"
+  - "Qwen"
+  - "unsloth"
+  - "NousResearch"
+  - "allenai"
+  - "amd"
+  - "tiiuae"

src/axolotl/cli/train.py

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
 from transformers.hf_argparser import HfArgumentParser
 
 from axolotl.cli.args import TrainerCliArgs
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.cli.checks import check_accelerate_default_config, check_user_token
 from axolotl.cli.config import load_cfg
 from axolotl.common.datasets import load_datasets, load_preference_datasets
@@ -35,7 +34,6 @@ def do_train(cfg: DictDefault, cli_args: TrainerCliArgs):
     # Enable expandable segments for cuda allocation to improve VRAM usage
     patch_optimized_env()
 
-    print_axolotl_text_art()
     check_accelerate_default_config()
     if int(os.getenv("LOCAL_RANK", "0")) == 0:
         check_user_token()

src/axolotl/train.py

@@ -23,7 +23,6 @@ from transformers import PreTrainedModel, PreTrainedTokenizer, ProcessorMixin
 from transformers.integrations.deepspeed import is_deepspeed_zero3_enabled
 from transformers.trainer import Trainer
 
-from axolotl.cli.art import print_axolotl_text_art
 from axolotl.common.datasets import TrainDatasetMeta
 from axolotl.contribs.lgpl import (  # pylint: disable = no-name-in-module
     fix_untrained_tokens,
@@ -545,8 +544,6 @@ def train(
     Returns:
         Tuple of (model, tokenizer) after training
     """
-    print_axolotl_text_art()
-
     # Setup model, tokenizer, (causal or RLHF) trainer, etc.
     (
         trainer,