diff --git a/modules/config.py b/modules/config.py
index 29a16d6dc..e3c427d2c 100644
--- a/modules/config.py
+++ b/modules/config.py
@@ -2,13 +2,14 @@
 import json
 import math
 import numbers
+
 import args_manager
 import tempfile
 import modules.flags
 import modules.sdxl_styles
 
 from modules.model_loader import load_file_from_url
-from modules.extra_utils import makedirs_with_log, get_files_from_folder
+from modules.extra_utils import makedirs_with_log, get_files_from_folder, try_eval_env_var
 from modules.flags import OutputFormat, Performance, MetadataScheme
 
 
@@ -200,7 +201,7 @@ def get_dir_or_set_default(key, default_value, as_array=False, make_directory=Fa
 path_outputs = get_path_output()
 
 
-def get_config_item_or_set_default(key, default_value, validator, disable_empty_as_none=False):
+def get_config_item_or_set_default(key, default_value, validator, disable_empty_as_none=False, expected_type=None):
     global config_dict, visited_keys
 
     if key not in visited_keys:
@@ -208,6 +209,7 @@ def get_config_item_or_set_default(key, default_value, validator, disable_empty_
     
     v = os.getenv(key)
     if v is not None:
+        v = try_eval_env_var(v, expected_type)
         print(f"Environment: {key} = {v}")
         config_dict[key] = v
 
@@ -252,41 +254,49 @@ def init_temp_path(path: str | None, default_path: str) -> str:
     key='temp_path',
     default_value=default_temp_path,
     validator=lambda x: isinstance(x, str),
+    expected_type=str
 ), default_temp_path)
 temp_path_cleanup_on_launch = get_config_item_or_set_default(
     key='temp_path_cleanup_on_launch',
     default_value=True,
-    validator=lambda x: isinstance(x, bool)
+    validator=lambda x: isinstance(x, bool),
+    expected_type=bool
 )
 default_base_model_name = default_model = get_config_item_or_set_default(
     key='default_model',
     default_value='model.safetensors',
-    validator=lambda x: isinstance(x, str)
+    validator=lambda x: isinstance(x, str),
+    expected_type=str
 )
 previous_default_models = get_config_item_or_set_default(
     key='previous_default_models',
     default_value=[],
-    validator=lambda x: isinstance(x, list) and all(isinstance(k, str) for k in x)
+    validator=lambda x: isinstance(x, list) and all(isinstance(k, str) for k in x),
+    expected_type=list
 )
 default_refiner_model_name = default_refiner = get_config_item_or_set_default(
     key='default_refiner',
     default_value='None',
-    validator=lambda x: isinstance(x, str)
+    validator=lambda x: isinstance(x, str),
+    expected_type=str
 )
 default_refiner_switch = get_config_item_or_set_default(
     key='default_refiner_switch',
     default_value=0.8,
-    validator=lambda x: isinstance(x, numbers.Number) and 0 <= x <= 1
+    validator=lambda x: isinstance(x, numbers.Number) and 0 <= x <= 1,
+    expected_type=numbers.Number
 )
 default_loras_min_weight = get_config_item_or_set_default(
     key='default_loras_min_weight',
     default_value=-2,
-    validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10
+    validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10,
+    expected_type=numbers.Number
 )
 default_loras_max_weight = get_config_item_or_set_default(
     key='default_loras_max_weight',
     default_value=2,
-    validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10
+    validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10,
+    expected_type=numbers.Number
 )
 default_loras = get_config_item_or_set_default(
     key='default_loras',
@@ -320,38 +330,45 @@ def init_temp_path(path: str | None, default_path: str) -> str:
     validator=lambda x: isinstance(x, list) and all(
         len(y) == 3 and isinstance(y[0], bool) and isinstance(y[1], str) and isinstance(y[2], numbers.Number)
         or len(y) == 2 and isinstance(y[0], str) and isinstance(y[1], numbers.Number)
-        for y in x)
+        for y in x),
+    expected_type=list
 )
 default_loras = [(y[0], y[1], y[2]) if len(y) == 3 else (True, y[0], y[1]) for y in default_loras]
 default_max_lora_number = get_config_item_or_set_default(
     key='default_max_lora_number',
     default_value=len(default_loras) if isinstance(default_loras, list) and len(default_loras) > 0 else 5,
-    validator=lambda x: isinstance(x, int) and x >= 1
+    validator=lambda x: isinstance(x, int) and x >= 1,
+    expected_type=int
 )
 default_cfg_scale = get_config_item_or_set_default(
     key='default_cfg_scale',
     default_value=7.0,
-    validator=lambda x: isinstance(x, numbers.Number)
+    validator=lambda x: isinstance(x, numbers.Number),
+    expected_type=numbers.Number
 )
 default_sample_sharpness = get_config_item_or_set_default(
     key='default_sample_sharpness',
     default_value=2.0,
-    validator=lambda x: isinstance(x, numbers.Number)
+    validator=lambda x: isinstance(x, numbers.Number),
+    expected_type=numbers.Number
 )
 default_sampler = get_config_item_or_set_default(
     key='default_sampler',
     default_value='dpmpp_2m_sde_gpu',
-    validator=lambda x: x in modules.flags.sampler_list
+    validator=lambda x: x in modules.flags.sampler_list,
+    expected_type=str
 )
 default_scheduler = get_config_item_or_set_default(
     key='default_scheduler',
     default_value='karras',
-    validator=lambda x: x in modules.flags.scheduler_list
+    validator=lambda x: x in modules.flags.scheduler_list,
+    expected_type=str
 )
 default_vae = get_config_item_or_set_default(
     key='default_vae',
     default_value=modules.flags.default_vae,
-    validator=lambda x: isinstance(x, str)
+    validator=lambda x: isinstance(x, str),
+    expected_type=str
 )
 default_styles = get_config_item_or_set_default(
     key='default_styles',
@@ -360,121 +377,144 @@ def init_temp_path(path: str | None, default_path: str) -> str:
         "Fooocus Enhance",
         "Fooocus Sharp"
     ],
-    validator=lambda x: isinstance(x, list) and all(y in modules.sdxl_styles.legal_style_names for y in x)
+    validator=lambda x: isinstance(x, list) and all(y in modules.sdxl_styles.legal_style_names for y in x),
+    expected_type=list
 )
 default_prompt_negative = get_config_item_or_set_default(
     key='default_prompt_negative',
     default_value='',
     validator=lambda x: isinstance(x, str),
-    disable_empty_as_none=True
+    disable_empty_as_none=True,
+    expected_type=str
 )
 default_prompt = get_config_item_or_set_default(
     key='default_prompt',
     default_value='',
     validator=lambda x: isinstance(x, str),
-    disable_empty_as_none=True
+    disable_empty_as_none=True,
+    expected_type=str
 )
 default_performance = get_config_item_or_set_default(
     key='default_performance',
     default_value=Performance.SPEED.value,
-    validator=lambda x: x in Performance.list()
+    validator=lambda x: x in Performance.list(),
+    expected_type=str
 )
 default_advanced_checkbox = get_config_item_or_set_default(
     key='default_advanced_checkbox',
     default_value=False,
-    validator=lambda x: isinstance(x, bool)
+    validator=lambda x: isinstance(x, bool),
+    expected_type=bool
 )
 default_max_image_number = get_config_item_or_set_default(
     key='default_max_image_number',
     default_value=32,
-    validator=lambda x: isinstance(x, int) and x >= 1
+    validator=lambda x: isinstance(x, int) and x >= 1,
+    expected_type=int
 )
 default_output_format = get_config_item_or_set_default(
     key='default_output_format',
     default_value='png',
-    validator=lambda x: x in OutputFormat.list()
+    validator=lambda x: x in OutputFormat.list(),
+    expected_type=str
 )
 default_image_number = get_config_item_or_set_default(
     key='default_image_number',
     default_value=2,
-    validator=lambda x: isinstance(x, int) and 1 <= x <= default_max_image_number
+    validator=lambda x: isinstance(x, int) and 1 <= x <= default_max_image_number,
+    expected_type=int
 )
 checkpoint_downloads = get_config_item_or_set_default(
     key='checkpoint_downloads',
     default_value={},
-    validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items())
+    validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items()),
+    expected_type=dict
 )
 lora_downloads = get_config_item_or_set_default(
     key='lora_downloads',
     default_value={},
-    validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items())
+    validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items()),
+    expected_type=dict
 )
 embeddings_downloads = get_config_item_or_set_default(
     key='embeddings_downloads',
     default_value={},
-    validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items())
+    validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items()),
+    expected_type=dict
 )
 available_aspect_ratios = get_config_item_or_set_default(
     key='available_aspect_ratios',
     default_value=modules.flags.sdxl_aspect_ratios,
-    validator=lambda x: isinstance(x, list) and all('*' in v for v in x) and len(x) > 1
+    validator=lambda x: isinstance(x, list) and all('*' in v for v in x) and len(x) > 1,
+    expected_type=list
 )
 default_aspect_ratio = get_config_item_or_set_default(
     key='default_aspect_ratio',
     default_value='1152*896' if '1152*896' in available_aspect_ratios else available_aspect_ratios[0],
-    validator=lambda x: x in available_aspect_ratios
+    validator=lambda x: x in available_aspect_ratios,
+    expected_type=str
 )
 default_inpaint_engine_version = get_config_item_or_set_default(
     key='default_inpaint_engine_version',
     default_value='v2.6',
-    validator=lambda x: x in modules.flags.inpaint_engine_versions
+    validator=lambda x: x in modules.flags.inpaint_engine_versions,
+    expected_type=str
 )
 default_cfg_tsnr = get_config_item_or_set_default(
     key='default_cfg_tsnr',
     default_value=7.0,
-    validator=lambda x: isinstance(x, numbers.Number)
+    validator=lambda x: isinstance(x, numbers.Number),
+    expected_type=numbers.Number
 )
 default_clip_skip = get_config_item_or_set_default(
     key='default_clip_skip',
     default_value=2,
-    validator=lambda x: isinstance(x, int) and 1 <= x <= modules.flags.clip_skip_max
+    validator=lambda x: isinstance(x, int) and 1 <= x <= modules.flags.clip_skip_max,
+    expected_type=int
 )
 default_overwrite_step = get_config_item_or_set_default(
     key='default_overwrite_step',
     default_value=-1,
-    validator=lambda x: isinstance(x, int)
+    validator=lambda x: isinstance(x, int),
+    expected_type=int
 )
 default_overwrite_switch = get_config_item_or_set_default(
     key='default_overwrite_switch',
     default_value=-1,
-    validator=lambda x: isinstance(x, int)
+    validator=lambda x: isinstance(x, int),
+    expected_type=int
 )
 example_inpaint_prompts = get_config_item_or_set_default(
     key='example_inpaint_prompts',
     default_value=[
         'highly detailed face', 'detailed girl face', 'detailed man face', 'detailed hand', 'beautiful eyes'
     ],
-    validator=lambda x: isinstance(x, list) and all(isinstance(v, str) for v in x)
+    validator=lambda x: isinstance(x, list) and all(isinstance(v, str) for v in x),
+    expected_type=list
 )
 default_black_out_nsfw = get_config_item_or_set_default(
     key='default_black_out_nsfw',
     default_value=False,
-    validator=lambda x: isinstance(x, bool)
+    validator=lambda x: isinstance(x, bool),
+    expected_type=bool
 )
 default_save_metadata_to_images = get_config_item_or_set_default(
     key='default_save_metadata_to_images',
     default_value=False,
-    validator=lambda x: isinstance(x, bool)
+    validator=lambda x: isinstance(x, bool),
+    expected_type=bool
 )
 default_metadata_scheme = get_config_item_or_set_default(
     key='default_metadata_scheme',
     default_value=MetadataScheme.FOOOCUS.value,
-    validator=lambda x: x in [y[1] for y in modules.flags.metadata_scheme if y[1] == x]
+    validator=lambda x: x in [y[1] for y in modules.flags.metadata_scheme if y[1] == x],
+    expected_type=str
 )
 metadata_created_by = get_config_item_or_set_default(
     key='metadata_created_by',
     default_value='',
-    validator=lambda x: isinstance(x, str)
+    validator=lambda x: isinstance(x, str),
+    expected_type=str
 )
 
 example_inpaint_prompts = [[x] for x in example_inpaint_prompts]
diff --git a/modules/extra_utils.py b/modules/extra_utils.py
index 9906c8202..c2dfa8104 100644
--- a/modules/extra_utils.py
+++ b/modules/extra_utils.py
@@ -1,4 +1,6 @@
 import os
+from ast import literal_eval
+
 
 def makedirs_with_log(path):
     try:
@@ -24,3 +26,16 @@ def get_files_from_folder(folder_path, extensions=None, name_filter=None):
                 filenames.append(path)
 
     return filenames
+
+
+def try_eval_env_var(value: str, expected_type=None):
+    try:
+        value_eval = value
+        if expected_type is bool:
+            value_eval = value.title()
+        value_eval = literal_eval(value_eval)
+        if expected_type is not None and not isinstance(value_eval, expected_type):
+            return value
+        return value_eval
+    except:
+        return value
diff --git a/tests/test_extra_utils.py b/tests/test_extra_utils.py
new file mode 100644
index 000000000..a849aa16d
--- /dev/null
+++ b/tests/test_extra_utils.py
@@ -0,0 +1,74 @@
+import numbers
+import os
+import unittest
+
+import modules.flags
+from modules import extra_utils
+
+
+class TestUtils(unittest.TestCase):
+    def test_try_eval_env_var(self):
+        test_cases = [
+            {
+                "input": ("foo", str),
+                "output": "foo"
+            },
+            {
+                "input": ("1", int),
+                "output": 1
+            },
+            {
+                "input": ("1.0", float),
+                "output": 1.0
+            },
+            {
+                "input": ("1", numbers.Number),
+                "output": 1
+            },
+            {
+                "input": ("1.0", numbers.Number),
+                "output": 1.0
+            },
+            {
+                "input": ("true", bool),
+                "output": True
+            },
+            {
+                "input": ("True", bool),
+                "output": True
+            },
+            {
+                "input": ("false", bool),
+                "output": False
+            },
+            {
+                "input": ("False", bool),
+                "output": False
+            },
+            {
+                "input": ("True", str),
+                "output": "True"
+            },
+            {
+                "input": ("False", str),
+                "output": "False"
+            },
+            {
+                "input": ("['a', 'b', 'c']", list),
+                "output": ['a', 'b', 'c']
+            },
+            {
+                "input": ("{'a':1}", dict),
+                "output": {'a': 1}
+            },
+            {
+                "input": ("('foo', 1)", tuple),
+                "output": ('foo', 1)
+            }
+        ]
+
+        for test in test_cases:
+            value, expected_type = test["input"]
+            expected = test["output"]
+            actual = extra_utils.try_eval_env_var(value, expected_type)
+            self.assertEqual(expected, actual)