diff --git a/llama_api/server/app_settings.py b/llama_api/server/app_settings.py
index d9cda2d..bd472da 100644
--- a/llama_api/server/app_settings.py
+++ b/llama_api/server/app_settings.py
@@ -155,6 +155,7 @@ def run(
     skip_pytorch_install: bool = False,
     skip_tensorflow_install: bool = False,
     skip_compile: bool = False,
+    api_key: Optional[str] = None,
 ) -> None:
     initialize_before_launch(
         git_and_disk_paths=Config.git_and_disk_paths,
@@ -169,6 +170,7 @@ def run(
     from uvicorn import Server as UvicornServer
 
     environ["MAX_WORKERS"] = str(max_workers)
+    environ["API_KEY"] = api_key or ""
 
     UvicornServer(
         config=UvicornConfig(
diff --git a/llama_api/utils/errors.py b/llama_api/utils/errors.py
index 2131101..f1580b3 100644
--- a/llama_api/utils/errors.py
+++ b/llama_api/utils/errors.py
@@ -1,3 +1,5 @@
+from functools import cached_property
+from os import environ
 from pathlib import Path
 from re import Match, Pattern, compile
 from typing import Callable, Coroutine, Dict, Optional, Tuple, Union
@@ -124,6 +126,17 @@ class RouteErrorHandler(APIRoute):
         ): ErrorResponseFormatters.model_not_found,
     }
 
+    api_key: Optional[str] = environ.get("API_KEY", None) or None
+
+    @cached_property
+    def authorization(self) -> Optional[str]:
+        """API key for authentication"""
+        if self.api_key is None:
+            return None
+        if not self.api_key.startswith("sk-"):
+            self.api_key = f"sk-{self.api_key}"
+        return f"Bearer {self.api_key}"
+
     def error_message_wrapper(
         self,
         error: Exception,
@@ -154,7 +167,7 @@ def error_message_wrapper(
         return 500, ErrorResponse(
             message=str(error),
             type="internal_server_error",
-            param=f"traceback:: {self.parse_trackback(error)}",
+            param=f"traceback:: {parse_trackback(error)}",
             code=type(error).__name__,
         )
 
@@ -167,6 +180,47 @@ async def custom_route_handler(self, request: Request) -> Response:
         """Defines custom route handler that catches exceptions and formats
         in OpenAI style error response"""
         try:
+            if self.authorization is not None:
+                # Check API key
+                authorization = request.headers.get(
+                    "Authorization",
+                    request.query_params.get("authorization", None),
+                )  # type: Optional[str]
+                if not authorization or not authorization.startswith(
+                    "Bearer "
+                ):
+                    error_response = ErrorResponse(
+                        message=(
+                            (
+                                "You didn't provide an API key. "
+                                "You need to provide your API key in "
+                                "an Authorization header using Bearer auth "
+                                "(i.e. Authorization: Bearer YOUR_KEY)."
+                            )
+                        ),
+                        type="invalid_request_error",
+                        param=None,
+                        code=None,
+                    )
+                    return JSONResponse(
+                        {"error": error_response},
+                        status_code=401,
+                    )
+                if authorization != self.authorization:
+                    api_key = authorization[len("Bearer ") :]  # noqa: E203
+                    error_response = ErrorResponse(
+                        message=(
+                            "Incorrect API key provided: "
+                            + mask_secret(api_key, 8, 4)
+                        ),
+                        type="invalid_request_error",
+                        param=None,
+                        code="invalid_api_key",
+                    )
+                    return JSONResponse(
+                        {"error": error_response},
+                        status_code=401,
+                    )
             return await super().get_route_handler()(request)
         except Exception as error:
             json_body = await request.json()
@@ -200,23 +254,36 @@ async def custom_route_handler(self, request: Request) -> Response:
                 status_code=status_code,
             )
 
-    def parse_trackback(self, exception: Exception) -> str:
-        """Parses traceback information from the exception"""
-        if (
-            exception.__traceback__ is not None
-            and exception.__traceback__.tb_next is not None
-        ):
-            # Get previous traceback from the exception
-            traceback = exception.__traceback__.tb_next
 
-            # Get filename, function name, and line number
-            try:
-                co_filename = Path(traceback.tb_frame.f_code.co_filename).name
-            except Exception:
-                co_filename = "UNKNOWN"
-            co_name = traceback.tb_frame.f_code.co_name
-            lineno = traceback.tb_lineno
-            return f"Error in {co_filename} at line {lineno} in {co_name}"
+def parse_trackback(exception: Exception) -> str:
+    """Parses traceback information from the exception"""
+    if (
+        exception.__traceback__ is not None
+        and exception.__traceback__.tb_next is not None
+    ):
+        # Get previous traceback from the exception
+        traceback = exception.__traceback__.tb_next
 
-        # If traceback is not available, return UNKNOWN
-        return "UNKNOWN"
+        # Get filename, function name, and line number
+        try:
+            co_filename = Path(traceback.tb_frame.f_code.co_filename).name
+        except Exception:
+            co_filename = "UNKNOWN"
+        co_name = traceback.tb_frame.f_code.co_name
+        lineno = traceback.tb_lineno
+        return f"Error in {co_filename} at line {lineno} in {co_name}"
+
+    # If traceback is not available, return UNKNOWN
+    return "UNKNOWN"
+
+
+def mask_secret(api_key: str, n_start: int, n_end: int) -> str:
+    length = len(api_key)
+    if length <= n_start + n_end:
+        return api_key
+    else:
+        return (
+            api_key[:n_start]
+            + "*" * (length - n_start - n_end)
+            + api_key[-n_end:]
+        )
diff --git a/main.py b/main.py
index 3939e19..74a0f1e 100644
--- a/main.py
+++ b/main.py
@@ -19,7 +19,6 @@
         help="Maximum number of process workers to run; default is 1",
     )
     parser.add_argument(
-        "-i",
         "--install-pkgs",
         action="store_true",
         help="Install all required packages before running the server",
@@ -43,9 +42,11 @@
         help="Skip installing tensorflow, if `install-pkgs` is set",
     )
     parser.add_argument(
-        "--skip-compile",
-        action="store_true",
-        help="Skip compiling the shared library of LLaMA C++ code",
+        "-k",
+        "--api-key",
+        type=str,
+        default=None,
+        help="API key to use for the server",
     )
 
     args = parser.parse_args()
@@ -56,5 +57,5 @@
         force_cuda=args.force_cuda,
         skip_pytorch_install=args.skip_torch_install,
         skip_tensorflow_install=args.skip_tf_install,
-        skip_compile=args.skip_compile,
+        api_key=args.api_key,
     )
diff --git a/poetry.lock b/poetry.lock
index 22f6c60..6e0f091 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -362,28 +362,28 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [[package]]
 name = "cmake"
-version = "3.27.0"
+version = "3.27.1"
 description = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
 optional = false
 python-versions = "*"
 files = [
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-    {file = "cmake-3.27.0-py2.py3-none-manylinux2010_i686.manylinux_2_12_i686.whl", hash = "sha256:199bfaefb752e82d8067aeee5d6a6e0414fe0d60e9a3fd08e95d537a97e0db16"},
-    {file = "cmake-3.27.0-py2.py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:8745eff805f36762d3e8e904698b853cb4a9da8b4b07d1c12bcd1e1a6c4a1709"},
-    {file = "cmake-3.27.0-py2.py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:58a3f39d3d1bc897f05e531bfa676246a2b25d424c6a47e4b6bbc193fb560db7"},
-    {file = "cmake-3.27.0-py2.py3-none-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:b470ccd3f86cf19a63f6b221c9cceebcc58e32d3787d0d5f9f43d1d91a095090"},
-    {file = "cmake-3.27.0-py2.py3-none-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:35a8d397ce883e93b5e6561e2803ce9470df52283862264093c1078530f98189"},
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+    {file = "cmake-3.27.1.tar.gz", hash = "sha256:7ee6af09b2b575a491483b72927ee7e4beb59e7fb86e6d905a7027607a3f367e"},
 ]
 
 [package.extras]
@@ -413,34 +413,34 @@ files = [
 
 [[package]]
 name = "cryptography"
-version = "41.0.2"
+version = "41.0.3"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
@@ -880,13 +880,13 @@ testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs
 
 [[package]]
 name = "importlib-resources"
-version = "6.0.0"
+version = "6.0.1"
 description = "Read resources from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -970,13 +970,13 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "jsonschema"
-version = "4.18.4"
+version = "4.19.0"
 description = "An implementation of JSON Schema validation for Python"
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 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -1177,13 +1177,13 @@ files = [
 
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-version = "1.5.1"
+version = "1.5.2"
 description = "Project documentation with Markdown."
 optional = false
 python-versions = ">=3.7"
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 [package.dependencies]
@@ -1208,13 +1208,13 @@ min-versions = ["babel (==2.9.0)", "click (==7.0)", "colorama (==0.4)", "ghp-imp
 
 [[package]]
 name = "mkdocs-autorefs"
-version = "0.4.1"
+version = "0.5.0"
 description = "Automatically link across pages in MkDocs."
 optional = false
-python-versions = ">=3.7"
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 files = [
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 [package.dependencies]
@@ -1283,28 +1283,28 @@ python-legacy = ["mkdocstrings-python-legacy (>=0.2.1)"]
 
 [[package]]
 name = "mkdocstrings-python"
-version = "1.2.1"
+version = "1.3.0"
 description = "A Python handler for mkdocstrings."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
-griffe = ">=0.30"
+griffe = ">=0.30,<0.33"
 mkdocstrings = ">=0.20"
 
 [[package]]
 name = "more-itertools"
-version = "10.0.0"
+version = "10.1.0"
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 python-versions = ">=3.8"
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 ]
 
 [package.extras]
-all = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "flax (>=0.6.3)", "h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "isort (>=5.5.4)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "numpy (>=1.21.6)", "paddlepaddle (>=2.4.1)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)", "tensorflow (>=2.11.0)", "torch (>=1.10)"]
-dev = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "flax (>=0.6.3)", "h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "isort (>=5.5.4)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "numpy (>=1.21.6)", "paddlepaddle (>=2.4.1)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)", "tensorflow (>=2.11.0)", "torch (>=1.10)"]
+all = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "flax (>=0.6.3)", "h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "isort (>=5.5.4)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "numpy (>=1.21.6)", "paddlepaddle (>=2.4.1)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)", "tensorflow (==2.11.0)", "torch (>=1.10)"]
+dev = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "flax (>=0.6.3)", "h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "isort (>=5.5.4)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "numpy (>=1.21.6)", "paddlepaddle (>=2.4.1)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)", "tensorflow (==2.11.0)", "torch (>=1.10)"]
 jax = ["flax (>=0.6.3)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)"]
 numpy = ["numpy (>=1.21.6)"]
 paddlepaddle = ["paddlepaddle (>=2.4.1)"]
+pinned-tf = ["tensorflow (==2.11.0)"]
 quality = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "isort (>=5.5.4)"]
 tensorflow = ["tensorflow (>=2.11.0)"]
 testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "numpy (>=1.21.6)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "setuptools-rust (>=1.5.2)"]
@@ -2788,20 +2762,20 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.65.0"
+version = "4.66.0"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.65.0-py3-none-any.whl", hash = "sha256:c4f53a17fe37e132815abceec022631be8ffe1b9381c2e6e30aa70edc99e9671"},
-    {file = "tqdm-4.65.0.tar.gz", hash = "sha256:1871fb68a86b8fb3b59ca4cdd3dcccbc7e6d613eeed31f4c332531977b89beb5"},
+    {file = "tqdm-4.66.0-py3-none-any.whl", hash = "sha256:39d459c7140b7890174e69d4d68d6291bc774a55b4bc5d93c0b760798ac5a03e"},
+    {file = "tqdm-4.66.0.tar.gz", hash = "sha256:cc6e7e52202d894e66632c5c8a9330bd0e3ff35d2965c93ca832114a3d865362"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [package.extras]
-dev = ["py-make (>=0.1.0)", "twine", "wheel"]
+dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
 notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
@@ -2877,13 +2851,13 @@ vision = ["Pillow (<10.0.0)"]
 
 [[package]]
 name = "trove-classifiers"
-version = "2023.7.6"
+version = "2023.8.7"
 description = "Canonical source for classifiers on PyPI (pypi.org)."
 optional = false
 python-versions = "*"
 files = [
-    {file = "trove-classifiers-2023.7.6.tar.gz", hash = "sha256:8a8e168b51d20fed607043831d37632bb50919d1c80a64e0f1393744691a8b22"},
-    {file = "trove_classifiers-2023.7.6-py3-none-any.whl", hash = "sha256:b420d5aa048ee7c456233a49203f7d58d1736af4a6cde637657d78c13ab7969b"},
+    {file = "trove-classifiers-2023.8.7.tar.gz", hash = "sha256:c9f2a0a85d545e5362e967e4f069f56fddfd91215e22ffa48c66fb283521319a"},
+    {file = "trove_classifiers-2023.8.7-py3-none-any.whl", hash = "sha256:a676626a31286130d56de2ea1232484df97c567eb429d56cfcb0637e681ecf09"},
 ]
 
 [[package]]
@@ -2937,13 +2911,13 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.23.1"
+version = "0.23.2"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "uvicorn-0.23.1-py3-none-any.whl", hash = "sha256:1d55d46b83ee4ce82b4e82f621f2050adb3eb7b5481c13f9af1744951cae2f1f"},
-    {file = "uvicorn-0.23.1.tar.gz", hash = "sha256:da9b0c8443b2d7ee9db00a345f1eee6db7317432c9d4400f5049cc8d358383be"},
+    {file = "uvicorn-0.23.2-py3-none-any.whl", hash = "sha256:1f9be6558f01239d4fdf22ef8126c39cb1ad0addf76c40e760549d2c2f43ab53"},
+    {file = "uvicorn-0.23.2.tar.gz", hash = "sha256:4d3cc12d7727ba72b64d12d3cc7743124074c0a69f7b201512fc50c3e3f1569a"},
 ]
 
 [package.dependencies]
@@ -3290,4 +3264,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<3.12"
-content-hash = "aa1a41ec0841ea5edb99dec7e07806ec94342aa67c3d26e3061f1f101c34cf7b"
+content-hash = "09b071c03e16e84be7d44b7cfc1670a2035ac8f96c5894cfd11726355a9fe3b4"
diff --git a/readme.md b/readme.md
index 31acf57..7a3eadd 100644
--- a/readme.md
+++ b/readme.md
@@ -18,74 +18,74 @@ You can use this server to run the models in your own application, or use it as
 
 ## Before you start
 
-1. **Python 3.8 / 3.9 / 3.10 / 3.11** is required to run the server. You can download it from [this link](https://www.python.org/downloads/)
+1. **Python 3.8 / 3.9 / 3.10 / 3.11** is required to run the server. You can download it from https://www.python.org/downloads/
 
+2. **llama.cpp**: To use llama.cpp, and if you are **Windows** user, download [CMake](https://cmake.org/download/) to compile library.
 
-3. **ExLlama**: If you are **Windows** user and you want to use ExLlama, follow the instruction of this [repository](https://github.com/turboderp/exllama#windows-prerequisites). Maybe this requires to install both [MSVC 2022](https://visualstudio.microsoft.com/downloads/) and [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive).
+3. **ExLlama**: To use ExLlama, install the prerequisites of this [repository](https://github.com/turboderp/exllama). Maybe **Windows** user needs to install both [MSVC 2022](https://visualstudio.microsoft.com/downloads/) and [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive).
 
-## How can I get the models?
+## How to download the models
 
-   #### 1. **Automatic download** (_Recommended_)
-   > ![image](contents/auto-download-model.png)
-
-   - Just set **model_path** of your own model defintion in `model_definitions.py` as actual **huggingface repository** and run the server. The server will automatically download the model from HuggingFace.co, when the model is requested for the first time.
-   
-   #### 2. **Manual download**
-   > ![image](contents/example-models.png)
-
-   - You can download the models manually if you want. I prefer to use the [following link](https://huggingface.co/TheBloke) to download the models
+You can download the models from HuggingFace. I prefer to use the following link to download the models: https://huggingface.co/TheBloke
 
+1. **LLama.cpp** models: Download the **bin** file from the GGML model page. Choose quantization method you prefer. The bin file name will be the **model_path**.
 
+     *Available quantizations: q4_0, q4_1, q5_0, q5_1, q8_0, q2_K, q3_K_S, q3_K_M, q3_K_L, q4_K_S, q4_K_M, q5_K_S, q6_K*
 
-1. For **LLama.cpp** models: Download the **bin** file from the GGML model page. Choose quantization method you prefer. The bin file name will be the **model_path**.
+2. **Exllama** models: Download three files from the GPTQ model page: **config.json / tokenizer.model / xxx.safetensors** and put them in a folder. The folder name will be the **model_path**.
 
-   The LLama.cpp GGML model must be put here as a **bin** file, in `models/ggml/`.
+## Where to put the models
 
-   For example, if you downloaded a q4_0 quantized model from [this link](https://huggingface.co/TheBloke/robin-7B-v2-GGML),
-   The path of the model has to be **robin-7b.ggmlv3.q4_0.bin**.
+> **Note:** The models are not included in this repository. You have to download them from HuggingFace.
 
-     *Available quantizations: q4_0, q4_1, q5_0, q5_1, q8_0, q2_K, q3_K_S, q3_K_M, q3_K_L, q4_K_S, q4_K_M, q5_K_S, q6_K*
 
-2. For **Exllama** models: Download three files from the GPTQ model page: **config.json / tokenizer.model / \*.safetensors** and put them in a folder. The folder name will be the **model_path**.
+### 1. Llama.cpp
+The LLama.cpp GGML model must be put here as a **bin** file, in `models/ggml/`.
 
-   The Exllama GPTQ model must be put here as a **folder**, in `models/gptq/`.
+For example, if you downloaded a q4_0 quantized model from "https://huggingface.co/TheBloke/robin-7B-v2-GGML",
+The path of the model has to be **robin-7b.ggmlv3.q4_0.bin**.
 
-   For example, if you downloaded 3 files from [this link](https://huggingface.co/TheBloke/orca_mini_7B-GPTQ/tree/main),
+### 2. Exllama
+The Exllama GPTQ model must be put here as a **folder**, in `models/gptq/`.
 
-   - orca-mini-7b-GPTQ-4bit-128g.no-act.order.safetensors
-   - tokenizer.model
-   - config.json
+For example, if you downloaded 3 files from "https://huggingface.co/TheBloke/orca_mini_7B-GPTQ/tree/main":
 
-   then you need to put them in a folder.
-   The path of the model has to be the folder name. Let's say, **orca_mini_7b**, which contains the 3 files.
+- orca-mini-7b-GPTQ-4bit-128g.no-act.order.safetensors
+- tokenizer.model
+- config.json
 
+Then you need to put them in a folder.
+The path of the model has to be the folder name. Let's say, **orca_mini_7b**, which contains the 3 files.
 
+![image](contents/example-models.png)
 
 ## Where to define the models
-Define llama.cpp & exllama models in `model_definitions.py`. You can define all necessary parameters to load the models there. Refer to the example in the file. For detailed options, refer to the `llama_api/schemas/models.py` file.
+Define llama.cpp & exllama models in `model_definitions.py`. You can define all necessary parameters to load the models there. Refer to the example in the file.
 
 ## How to run server
 
-All required packages will be **installed automatically** with this command.
+All required packages will be installed automatically with this command.
 
 ```bash
 python -m main --install-pkgs
 ```
 
-If you already have all required packages installed, you can **skip the installation** with this command.
+If you already have all required packages installed, you can skip the installation with this command.
 ```bash
 python -m main
 ```
-**Options**:
+Options:
 ```b
   -h, --help            show this help message and exit
-  --port PORT           Port to run the server on; default is 8000
-  --max-workers MAX_WORKERS
+  -p PORT, --port PORT  Port to run the server on; default is 8000
+  -w MAX_WORKERS, --max-workers MAX_WORKERS
                         Maximum number of process workers to run; default is 1
   --install-pkgs        Install all required packages before running the server
-  --force-cuda          Force CUDA version of pytorch to be used when installing pytorch. e.g. torch==2.0.1+cu118
+  --force-cuda          Force CUDA version of pytorch to be usedwhen installing pytorch. e.g. torch==2.0.1+cu118
   --skip-torch-install  Skip installing pytorch, if `install-pkgs` is set
   --skip-tf-install     Skip installing tensorflow, if `install-pkgs` is set
+  -k API_KEY, --api-key API_KEY
+                        API key to use for the server
 ```
 
 ## Usage: Text Completion
diff --git a/requirements.txt b/requirements.txt
index 2c76573..75b8ca9 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -11,7 +11,7 @@ click==8.1.6 ; python_full_version >= "3.8.1" and python_version < "3.12"
 cmake==3.27.0 ; python_full_version >= "3.8.1" and python_version < "3.12"
 colorama==0.4.6 ; python_full_version >= "3.8.1" and python_version < "3.12" and (os_name == "nt" or platform_system == "Windows")
 crashtest==0.4.1 ; python_full_version >= "3.8.1" and python_version < "3.12"
-cryptography==41.0.2 ; python_full_version >= "3.8.1" and python_version < "3.12" and sys_platform == "linux"
+cryptography==41.0.3 ; python_full_version >= "3.8.1" and python_version < "3.12" and sys_platform == "linux"
 diskcache==5.6.1 ; python_full_version >= "3.8.1" and python_version < "3.12"
 distlib==0.3.7 ; python_full_version >= "3.8.1" and python_version < "3.12"
 dulwich==0.21.5 ; python_full_version >= "3.8.1" and python_version < "3.12"
@@ -80,7 +80,7 @@ transformers==4.31.0 ; python_full_version >= "3.8.1" and python_version < "3.12
 trove-classifiers==2023.7.6 ; python_full_version >= "3.8.1" and python_version < "3.12"
 typing-extensions==4.7.1 ; python_full_version >= "3.8.1" and python_version < "3.12"
 urllib3==1.26.16 ; python_full_version >= "3.8.1" and python_version < "3.12"
-uvicorn[standard]==0.23.1 ; python_full_version >= "3.8.1" and python_version < "3.12"
+uvicorn[standard]==0.23.2 ; python_full_version >= "3.8.1" and python_version < "3.12"
 uvloop==0.17.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_full_version >= "3.8.1" and python_version < "3.12"
 virtualenv==20.24.2 ; python_full_version >= "3.8.1" and python_version < "3.12"
 watchfiles==0.19.0 ; python_full_version >= "3.8.1" and python_version < "3.12"