Add runpod sls handler (#2530) [skip ci]

* Add runpod sls handler

* remove LICENSE and fix README

* chore: lint

* use axolotl cloud image as base and various fixes

* fix: trim allowed cuda versions

* restore dockerfile

* chore: update title

* use axolotl cloud image

---------

Co-authored-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: NanoCode012 <nano@axolotl.ai>

.runpod/src/utils.py

@@ -0,0 +1,89 @@
+"""
+Runpod launcher utils
+"""
+
+import os
+
+import yaml
+
+
+def get_output_dir(run_id):
+    path = f"fine-tuning/{run_id}"
+    return path
+
+
+def make_valid_config(input_args):
+    """
+    Creates and saves updated config file, returns the path to the new config
+    :param input_args: dict of input args
+    :return: str, path to the updated config file
+    """
+    # Load default config
+    with open("config/config.yaml", "r", encoding="utf-8") as fin:
+        all_args = yaml.safe_load(fin)
+
+    if not input_args:
+        print("No args provided, using defaults")
+    else:
+        all_args.update(input_args)
+
+    # Create updated config path
+    updated_config_path = "config/updated_config.yaml"
+
+    # Save updated config to new file
+    with open(updated_config_path, "w", encoding="utf-8") as f:
+        yaml.dump(all_args, f)
+
+    return updated_config_path
+
+
+def set_config_env_vars(args: dict):
+    """
+    Convert API arguments into environment variables.
+    Handles nested dictionaries, lists, and special values.
+
+    Args:
+        args (dict): The arguments dictionary from the API request
+    """
+
+    def process_value(value):
+        """Convert Python values to string format for environment variables"""
+        if value is None:
+            return ""
+        if isinstance(value, bool):
+            return str(value).lower()
+        if isinstance(value, (list, dict)):
+            return str(value)
+        return str(value)
+
+    def set_env_vars(data, prefix=""):
+        """Recursively set environment variables from nested dictionary"""
+        for key, value in data.items():
+            env_key = prefix + key.upper()
+
+            # Handle special cases
+            if isinstance(value, dict):
+                # For nested dictionaries (like special_tokens)
+                set_env_vars(value, f"{env_key}_")
+            elif isinstance(value, list):
+                # Handle list of dictionaries (like datasets)
+                if value and isinstance(value[0], dict):
+                    for i, item in enumerate(value):
+                        set_env_vars(item, f"{env_key}_{i}_")
+                else:
+                    # For simple lists (like lora_target_modules)
+                    os.environ[env_key] = process_value(value)
+            else:
+                # Handle all other cases
+                os.environ[env_key] = process_value(value)
+
+    # Clear any existing related environment variables
+    # This prevents old values from persisting
+    for key in list(os.environ.keys()):
+        if key.startswith(
+            ("BASE_MODEL", "MODEL_TYPE", "TOKENIZER_TYPE", "DATASET", "LORA_", "WANDB_")
+        ):
+            del os.environ[key]
+
+    # Set new environment variables
+    set_env_vars(args)