diff --git a/README.md b/README.md
index 0495b59..65e3135 100644
--- a/README.md
+++ b/README.md
@@ -26,13 +26,13 @@ ___
 
 ## Supported Models
 
-| LLM Family  | Hosting             | Supported LLMs                          |
-|-------------|---------------------|-----------------------------------------|
-| GPT(s)      | OpenAI endpoint     | `gpt-3.5-turbo`, `gpt-4`, `gpt-4-turbo` |
-| Google LLMs | VertexAI deployment | `text-bison@001`, `gemini-pro`          |
-| Llama2      | Azure deployment    | `llama2-7b`, `llama2-13b`, `llama2-70b` |
-| Mistral     | Azure deployment    | `Mistral-7b`, `Mixtral-7bx8`            |
-| Gemma       | GCP deployment      | `gemma`                                 |
+| LLM Family  | Hosting             | Supported LLMs                                                   |
+|-------------|---------------------|------------------------------------------------------------------|
+| GPT(s)      | OpenAI endpoint     | `gpt-3.5-turbo`, `gpt-4`, `gpt-4-turbo`, `gpt4-o`, `gpt4-o mini` |
+| Google LLMs | VertexAI deployment | `text-bison@001`, `gemini-pro`, `gemini-flash`                   |
+| Llama2      | Azure deployment    | `llama2-7b`, `llama2-13b`, `llama2-70b`                          |
+| Mistral     | Azure deployment    | `Mistral-7b`, `Mixtral-7bx8`                                     |
+| Gemma       | GCP deployment      | `gemma`                                                          |
 
 * Do you already have a subscription to a Cloud Provider for any the models above? Configure
 the model using your credentials and start querying!
diff --git a/allms/defaults/vertex_ai.py b/allms/defaults/vertex_ai.py
index 12fd2c4..5d03a75 100644
--- a/allms/defaults/vertex_ai.py
+++ b/allms/defaults/vertex_ai.py
@@ -10,7 +10,7 @@ class PalmModelDefaults:
 
 
 class GeminiModelDefaults:
-    GCP_MODEL_NAME = "gemini-pro"
+    GCP_MODEL_NAME = "gemini-1.5-flash-001"
     MODEL_TOTAL_MAX_TOKENS = 30720
     MAX_OUTPUT_TOKENS = 2048
     TEMPERATURE = 0.0
diff --git a/allms/domain/configuration.py b/allms/domain/configuration.py
index 20b8037..55ab712 100644
--- a/allms/domain/configuration.py
+++ b/allms/domain/configuration.py
@@ -1,5 +1,7 @@
 from dataclasses import dataclass
-from typing import Optional
+from typing import Dict, Optional
+
+from langchain_google_vertexai import HarmBlockThreshold, HarmCategory
 
 from allms.defaults.vertex_ai import GeminiModelDefaults, PalmModelDefaults
 
@@ -10,7 +12,8 @@ class AzureOpenAIConfiguration:
     deployment: str
     model_name: str
     api_version: str
-    api_key: str
+    api_key: Optional[str] = None
+    azure_ad_token: Optional[str] = None
 
 
 @dataclass
@@ -26,6 +29,7 @@ class VertexAIConfiguration:
     cloud_location: str
     palm_model_name: Optional[str] = PalmModelDefaults.GCP_MODEL_NAME
     gemini_model_name: Optional[str] = GeminiModelDefaults.GCP_MODEL_NAME
+    gemini_safety_settings: Optional[Dict[HarmCategory, HarmBlockThreshold]] = None
 
 
 class VertexAIModelGardenConfiguration(VertexAIConfiguration):
diff --git a/allms/models/__init__.py b/allms/models/__init__.py
index 9780f1b..fccf062 100644
--- a/allms/models/__init__.py
+++ b/allms/models/__init__.py
@@ -1,5 +1,6 @@
-from typing import Type
+from typing import Dict, Type
 
+from allms.domain.configuration import HarmBlockThreshold, HarmCategory
 from allms.domain.enumerables import AvailableModels
 from allms.models.abstract import AbstractModel
 from allms.models.azure_llama2 import AzureLlama2Model
@@ -16,11 +17,13 @@
     "VertexAIPalmModel",
     "VertexAIGeminiModel",
     "VertexAIGemmaModel",
+    "HarmCategory",
+    "HarmBlockThreshold",
     "get_available_models"
 ]
 
 
-def get_available_models() -> dict[str, Type[AbstractModel]]:
+def get_available_models() -> Dict[str, Type[AbstractModel]]:
     return {
         AvailableModels.AZURE_OPENAI_MODEL: AzureOpenAIModel,
         AvailableModels.AZURE_LLAMA2_MODEL: AzureLlama2Model,
diff --git a/allms/models/abstract.py b/allms/models/abstract.py
index 81da398..23f9ae2 100644
--- a/allms/models/abstract.py
+++ b/allms/models/abstract.py
@@ -33,6 +33,7 @@
 from allms.domain.input_data import InputData
 from allms.domain.prompt_dto import SummaryOutputClass, KeywordsOutputClass
 from allms.domain.response import ResponseData
+from allms.models.vertexai_base import GCPInvalidRequestError
 from allms.utils.long_text_processing_utils import get_max_allowed_number_of_tokens
 from allms.utils.response_parsing_utils import ResponseParser
 
@@ -168,7 +169,7 @@ async def _build_chat_prompts(
             self,
             prompt_template_args: dict,
             system_prompt: SystemMessagePromptTemplate
-    ) -> list[SystemMessagePromptTemplate | HumanMessagePromptTemplate]:
+    ) -> typing.List[typing.Union[SystemMessagePromptTemplate, HumanMessagePromptTemplate]]:
         human_message = HumanMessagePromptTemplate(prompt=PromptTemplate(**prompt_template_args))
         if not system_prompt:
             return [human_message]
@@ -261,7 +262,7 @@ async def _predict_example(
                 model_response = None
                 error_message = f"{IODataConstants.ERROR_MESSAGE_STR}: {invalid_request_error}"
 
-        except (InvalidArgument, ValueError, TimeoutError, openai.APIError) as other_error:
+        except (InvalidArgument, ValueError, TimeoutError, openai.APIError, GCPInvalidRequestError) as other_error:
             model_response = None
             logger.info(f"Error for id {input_data.id} has occurred. Message: {other_error} ")
             error_message = f"{type(other_error).__name__}: {other_error}"
@@ -331,7 +332,7 @@ def _validate_system_prompt(self, system_prompt: typing.Optional[str] = None) ->
                 raise ValueError(input_exception_message.get_system_prompt_contains_input_variables())
 
     @staticmethod
-    def _extract_input_variables_from_prompt(prompt: str) -> set[str]:
+    def _extract_input_variables_from_prompt(prompt: str) -> typing.Set[str]:
         input_variables_pattern = r'(?<!\{)\{([^{}]+)\}(?!\})'
         input_variables_set = set(re.findall(input_variables_pattern, prompt))
         return input_variables_set
diff --git a/allms/models/azure_openai.py b/allms/models/azure_openai.py
index 2007b02..645fb41 100644
--- a/allms/models/azure_openai.py
+++ b/allms/models/azure_openai.py
@@ -40,6 +40,7 @@ def _create_llm(self) -> AzureChatOpenAI:
             model_name=self._config.model_name,
             base_url=self._config.base_url,
             api_key=self._config.api_key,
+            azure_ad_token=self._config.azure_ad_token,
             temperature=self._temperature,
             max_tokens=self._max_output_tokens,
             request_timeout=self._request_timeout_s
diff --git a/allms/models/vertexai_base.py b/allms/models/vertexai_base.py
index 62a495b..cec3501 100644
--- a/allms/models/vertexai_base.py
+++ b/allms/models/vertexai_base.py
@@ -9,6 +9,10 @@
 from allms.constants.vertex_ai import VertexModelConstants
 
 
+class GCPInvalidRequestError(Exception):
+    pass
+
+
 class CustomVertexAI(VertexAI):
     async def _agenerate(
         self,
@@ -31,6 +35,9 @@ def was_response_blocked(generation: Generation) -> bool:
             **kwargs
         )
 
+        if not all(result.generations):
+            raise GCPInvalidRequestError("The response is empty. It may have been blocked due to content filtering.")
+
         return LLMResult(
             generations=(
                 chain(result.generations)
diff --git a/allms/models/vertexai_gemini.py b/allms/models/vertexai_gemini.py
index a19e395..af7089b 100644
--- a/allms/models/vertexai_gemini.py
+++ b/allms/models/vertexai_gemini.py
@@ -1,12 +1,20 @@
+import typing
 from asyncio import AbstractEventLoop
-from langchain_community.llms.vertexai import VertexAI
 from typing import Optional
 
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_google_vertexai import VertexAI
+from vertexai.preview import tokenization
+from vertexai.tokenization._tokenizers import Tokenizer
+
 from allms.defaults.general_defaults import GeneralDefaults
 from allms.defaults.vertex_ai import GeminiModelDefaults
 from allms.domain.configuration import VertexAIConfiguration
-from allms.models.vertexai_base import CustomVertexAI
+from allms.domain.input_data import InputData
 from allms.models.abstract import AbstractModel
+from allms.models.vertexai_base import CustomVertexAI
+
+BASE_GEMINI_MODEL_NAMES = ["gemini-1.0-pro", "gemini-1.5-pro", "gemini-1.5-flash"]
 
 
 class VertexAIGeminiModel(AbstractModel):
@@ -28,6 +36,8 @@ def __init__(
         self._verbose = verbose
         self._config = config
 
+        self._gcp_tokenizer = self._get_gcp_tokenizer(self._config.gemini_model_name)
+
         super().__init__(
             temperature=temperature,
             model_total_max_tokens=model_total_max_tokens,
@@ -44,7 +54,29 @@ def _create_llm(self) -> CustomVertexAI:
             temperature=self._temperature,
             top_p=self._top_p,
             top_k=self._top_k,
+            safety_settings=self._config.gemini_safety_settings,
             verbose=self._verbose,
             project=self._config.cloud_project,
             location=self._config.cloud_location
-        )
\ No newline at end of file
+        )
+
+    def _get_prompt_tokens_number(self, prompt: ChatPromptTemplate, input_data: InputData) -> int:
+        return self._gcp_tokenizer.count_tokens(
+            prompt.format_prompt(**input_data.input_mappings).to_string()
+        ).total_tokens
+
+    def _get_model_response_tokens_number(self, model_response: typing.Optional[str]) -> int:
+        if model_response:
+            return self._gcp_tokenizer.count_tokens(model_response).total_tokens
+        return 0
+
+    @staticmethod
+    def _get_gcp_tokenizer(model_name) -> Tokenizer:
+        try:
+            return tokenization.get_tokenizer_for_model(model_name)
+        except ValueError:
+            for base_model_name in BASE_GEMINI_MODEL_NAMES:
+                if model_name.startswith(base_model_name):
+                    return tokenization.get_tokenizer_for_model(base_model_name)
+            raise
+
diff --git a/allms/models/vertexai_gemma.py b/allms/models/vertexai_gemma.py
index eb725c4..7834d4a 100644
--- a/allms/models/vertexai_gemma.py
+++ b/allms/models/vertexai_gemma.py
@@ -1,6 +1,6 @@
 from asyncio import AbstractEventLoop
 
-from langchain_community.llms.vertexai import VertexAIModelGarden
+from langchain_google_vertexai import VertexAIModelGarden
 from typing import Optional
 
 from allms.defaults.general_defaults import GeneralDefaults
diff --git a/allms/models/vertexai_palm.py b/allms/models/vertexai_palm.py
index 9845068..674823a 100644
--- a/allms/models/vertexai_palm.py
+++ b/allms/models/vertexai_palm.py
@@ -1,5 +1,5 @@
 from asyncio import AbstractEventLoop
-from langchain_community.llms.vertexai import VertexAI
+from langchain_google_vertexai import VertexAI
 from typing import Optional
 
 from allms.defaults.general_defaults import GeneralDefaults
diff --git a/poetry.lock b/poetry.lock
index b0bbe6f..d6d4950 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -150,24 +150,25 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "3.7.1"
+version = "4.6.2.post1"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
-    {file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
-    {file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
+    {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"},
+    {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"},
 ]
 
 [package.dependencies]
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
-test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (<0.22)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "astroid"
@@ -184,8 +185,8 @@ files = [
 lazy-object-proxy = ">=1.4.0"
 typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
 wrapt = [
-    {version = ">=1.11,<2", markers = "python_version < \"3.11\""},
     {version = ">=1.14,<2", markers = "python_version >= \"3.11\""},
+    {version = ">=1.11,<2", markers = "python_version < \"3.11\""},
 ]
 
 [[package]]
@@ -808,12 +809,12 @@ files = [
 google-auth = ">=2.14.1,<3.0.dev0"
 googleapis-common-protos = ">=1.56.2,<2.0.dev0"
 grpcio = [
-    {version = ">=1.33.2,<2.0dev", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
     {version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.33.2,<2.0dev", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
 ]
 grpcio-status = [
-    {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
     {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
 ]
 proto-plus = [
     {version = ">=1.22.3,<2.0.0dev", markers = "python_version < \"3.13\""},
@@ -1237,19 +1238,19 @@ protobuf = ["grpcio-tools (>=1.67.1)"]
 
 [[package]]
 name = "grpcio-status"
-version = "1.62.3"
+version = "1.67.1"
 description = "Status proto mapping for gRPC"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
-    {file = "grpcio-status-1.62.3.tar.gz", hash = "sha256:289bdd7b2459794a12cf95dc0cb727bd4a1742c37bd823f760236c937e53a485"},
-    {file = "grpcio_status-1.62.3-py3-none-any.whl", hash = "sha256:f9049b762ba8de6b1086789d8315846e094edac2c50beaf462338b301a8fd4b8"},
+    {file = "grpcio_status-1.67.1-py3-none-any.whl", hash = "sha256:16e6c085950bdacac97c779e6a502ea671232385e6e37f258884d6883392c2bd"},
+    {file = "grpcio_status-1.67.1.tar.gz", hash = "sha256:2bf38395e028ceeecfd8866b081f61628114b384da7d51ae064ddc8d766a5d11"},
 ]
 
 [package.dependencies]
 googleapis-common-protos = ">=1.5.5"
-grpcio = ">=1.62.3"
-protobuf = ">=4.21.6"
+grpcio = ">=1.67.1"
+protobuf = ">=5.26.1,<6.0dev"
 
 [[package]]
 name = "h11"
@@ -1834,6 +1835,9 @@ files = [
     {file = "markdown-3.7.tar.gz", hash = "sha256:2ae2471477cfd02dbbf038d5d9bc226d40def84b4fe2986e49b59b6b472bbed2"},
 ]
 
+[package.dependencies]
+importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""}
+
 [package.extras]
 docs = ["mdx-gh-links (>=0.2)", "mkdocs (>=1.5)", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-nature (>=0.6)", "mkdocs-section-index", "mkdocstrings[python]"]
 testing = ["coverage", "pyyaml"]
@@ -1999,6 +2003,7 @@ files = [
 click = ">=7.0"
 colorama = {version = ">=0.4", markers = "platform_system == \"Windows\""}
 ghp-import = ">=1.0"
+importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""}
 jinja2 = ">=2.11.1"
 markdown = ">=3.3.6"
 markupsafe = ">=2.0.1"
@@ -2026,6 +2031,7 @@ files = [
 ]
 
 [package.dependencies]
+importlib-metadata = {version = ">=4.3", markers = "python_version < \"3.10\""}
 mergedeep = ">=1.3.4"
 platformdirs = ">=2.2.0"
 pyyaml = ">=5.1"
@@ -2319,13 +2325,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "23.2"
+version = "24.1"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "packaging-23.2-py3-none-any.whl", hash = "sha256:8c491190033a9af7e1d931d0b5dacc2ef47509b34dd0de67ed209b5203fc88c7"},
-    {file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
+    {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"},
+    {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
 ]
 
 [[package]]
@@ -2510,22 +2516,22 @@ testing = ["google-api-core (>=1.31.5)"]
 
 [[package]]
 name = "protobuf"
-version = "4.25.5"
+version = "5.28.3"
 description = ""
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "protobuf-4.25.5-cp310-abi3-win32.whl", hash = "sha256:5e61fd921603f58d2f5acb2806a929b4675f8874ff5f330b7d6f7e2e784bbcd8"},
-    {file = "protobuf-4.25.5-cp310-abi3-win_amd64.whl", hash = "sha256:4be0571adcbe712b282a330c6e89eae24281344429ae95c6d85e79e84780f5ea"},
-    {file = "protobuf-4.25.5-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:b2fde3d805354df675ea4c7c6338c1aecd254dfc9925e88c6d31a2bcb97eb173"},
-    {file = "protobuf-4.25.5-cp37-abi3-manylinux2014_aarch64.whl", hash = "sha256:919ad92d9b0310070f8356c24b855c98df2b8bd207ebc1c0c6fcc9ab1e007f3d"},
-    {file = "protobuf-4.25.5-cp37-abi3-manylinux2014_x86_64.whl", hash = "sha256:fe14e16c22be926d3abfcb500e60cab068baf10b542b8c858fa27e098123e331"},
-    {file = "protobuf-4.25.5-cp38-cp38-win32.whl", hash = "sha256:98d8d8aa50de6a2747efd9cceba361c9034050ecce3e09136f90de37ddba66e1"},
-    {file = "protobuf-4.25.5-cp38-cp38-win_amd64.whl", hash = "sha256:b0234dd5a03049e4ddd94b93400b67803c823cfc405689688f59b34e0742381a"},
-    {file = "protobuf-4.25.5-cp39-cp39-win32.whl", hash = "sha256:abe32aad8561aa7cc94fc7ba4fdef646e576983edb94a73381b03c53728a626f"},
-    {file = "protobuf-4.25.5-cp39-cp39-win_amd64.whl", hash = "sha256:7a183f592dc80aa7c8da7ad9e55091c4ffc9497b3054452d629bb85fa27c2a45"},
-    {file = "protobuf-4.25.5-py3-none-any.whl", hash = "sha256:0aebecb809cae990f8129ada5ca273d9d670b76d9bfc9b1809f0a9c02b7dbf41"},
-    {file = "protobuf-4.25.5.tar.gz", hash = "sha256:7f8249476b4a9473645db7f8ab42b02fe1488cbe5fb72fddd445e0665afd8584"},
+    {file = "protobuf-5.28.3-cp310-abi3-win32.whl", hash = "sha256:0c4eec6f987338617072592b97943fdbe30d019c56126493111cf24344c1cc24"},
+    {file = "protobuf-5.28.3-cp310-abi3-win_amd64.whl", hash = "sha256:91fba8f445723fcf400fdbe9ca796b19d3b1242cd873907979b9ed71e4afe868"},
+    {file = "protobuf-5.28.3-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:a3f6857551e53ce35e60b403b8a27b0295f7d6eb63d10484f12bc6879c715687"},
+    {file = "protobuf-5.28.3-cp38-abi3-manylinux2014_aarch64.whl", hash = "sha256:3fa2de6b8b29d12c61911505d893afe7320ce7ccba4df913e2971461fa36d584"},
+    {file = "protobuf-5.28.3-cp38-abi3-manylinux2014_x86_64.whl", hash = "sha256:712319fbdddb46f21abb66cd33cb9e491a5763b2febd8f228251add221981135"},
+    {file = "protobuf-5.28.3-cp38-cp38-win32.whl", hash = "sha256:3e6101d095dfd119513cde7259aa703d16c6bbdfae2554dfe5cfdbe94e32d548"},
+    {file = "protobuf-5.28.3-cp38-cp38-win_amd64.whl", hash = "sha256:27b246b3723692bf1068d5734ddaf2fccc2cdd6e0c9b47fe099244d80200593b"},
+    {file = "protobuf-5.28.3-cp39-cp39-win32.whl", hash = "sha256:135658402f71bbd49500322c0f736145731b16fc79dc8f367ab544a17eab4535"},
+    {file = "protobuf-5.28.3-cp39-cp39-win_amd64.whl", hash = "sha256:70585a70fc2dd4818c51287ceef5bdba6387f88a578c86d47bb34669b5552c36"},
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 ]
 
 [[package]]
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 colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
 dill = [
-    {version = ">=0.2", markers = "python_version < \"3.11\""},
     {version = ">=0.3.6", markers = "python_version >= \"3.11\""},
+    {version = ">=0.2", markers = "python_version < \"3.11\""},
 ]
 isort = ">=4.2.5,<6"
 mccabe = ">=0.6,<0.8"
 platformdirs = ">=2.2.0"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 tomlkit = ">=0.10.1"
+typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
 spelling = ["pyenchant (>=3.2,<4.0)"]
@@ -3283,6 +3290,68 @@ files = [
 cryptography = ">=2.0"
 jeepney = ">=0.6"
 
+[[package]]
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+python-versions = "*"
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+
 [[package]]
 name = "shapely"
 version = "2.0.6"
@@ -3452,13 +3521,13 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "tenacity"
-version = "8.5.0"
+version = "9.0.0"
 description = "Retry code until it succeeds"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -3519,111 +3588,123 @@ blobfile = ["blobfile (>=2)"]
 
 [[package]]
 name = "tokenizers"
-version = "0.20.1"
+version = "0.20.2"
 description = ""
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 python-versions = ">=3.7"
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+    {file = "tokenizers-0.20.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efbef80ef87459fffe3c615ba393b185ebe1e3069083b7619549d3d22dd08ba2"},
+    {file = "tokenizers-0.20.2-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:0e0d0b6814a2285323fe669d2da5614fdb999b4b5d963d964f6fc8092065447d"},
+    {file = "tokenizers-0.20.2-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:efaa29e985e2a9eff6a8fb2d454ba23dfd82324f04a76e8e193673261fc54ffe"},
+    {file = "tokenizers-0.20.2.tar.gz", hash = "sha256:05c95c59b200c2fcf9b2da2d17df9236fb7a6df4136cfb251dfaa8803c0127fd"},
 ]
 
 [package.dependencies]
@@ -4048,5 +4129,5 @@ type = ["pytest-mypy"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.10"
-content-hash = "6569c8073ba22003a725acafbcb290754931b196f826be4c83ba6305b0231642"
+python-versions = ">=3.9.0,<4.0"
+content-hash = "892d85f4d206759b5b071de06e529adf3e371fe60b4c8aeb9d08aa51afdf59e0"
diff --git a/pyproject.toml b/pyproject.toml
index cc8ff2f..713ef59 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,13 +1,13 @@
 [tool.poetry]
 name = "allms"
-version = "1.0.4"
+version = "1.0.11"
 description = ""
 authors = ["Allegro Opensource <opensource@allegro.com>"]
 readme = "README.md"
 packages = [{include = "allms"}]
 
 [tool.poetry.dependencies]
-python = "^3.10"
+python = ">=3.9.0,<4.0"
 fsspec = "^2023.6.0"
 google-cloud-aiplatform = "1.70.0"
 pydash = "^7.0.6"
@@ -20,6 +20,7 @@ pytest-mock = "^3.14.0"
 respx = "^0.21.1"
 langchain-community = "^0.3.5"
 langchain-google-vertexai = "^2.0.7"
+sentencepiece = "^0.2.0"
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.0"
diff --git a/tests/conftest.py b/tests/conftest.py
index 160ec67..8f75c5d 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,5 +1,6 @@
 import asyncio
 import typing
+from contextlib import ExitStack
 from dataclasses import dataclass
 from unittest.mock import patch
 
@@ -35,13 +36,13 @@ def __init__(self, *args, **kwargs):
 def models():
     event_loop = asyncio.new_event_loop()
 
-    with (
-        patch("allms.models.vertexai_palm.CustomVertexAI", ModelWithoutAsyncRequestsMock),
-        patch("allms.models.vertexai_gemini.CustomVertexAI", ModelWithoutAsyncRequestsMock),
-        patch("allms.models.vertexai_gemma.VertexAIModelGardenWrapper", ModelWithoutAsyncRequestsMock),
-        patch("allms.models.azure_llama2.AzureMLOnlineEndpointAsync", ModelWithoutAsyncRequestsMock),
-        patch("allms.models.azure_mistral.AzureMLOnlineEndpointAsync", ModelWithoutAsyncRequestsMock)
-    ):
+    with ExitStack() as stack:
+        stack.enter_context(patch("allms.models.vertexai_palm.CustomVertexAI", ModelWithoutAsyncRequestsMock))
+        stack.enter_context(patch("allms.models.vertexai_gemini.CustomVertexAI", ModelWithoutAsyncRequestsMock))
+        stack.enter_context(patch("allms.models.vertexai_gemma.VertexAIModelGardenWrapper", ModelWithoutAsyncRequestsMock))
+        stack.enter_context(patch("allms.models.azure_llama2.AzureMLOnlineEndpointAsync", ModelWithoutAsyncRequestsMock))
+        stack.enter_context(patch("allms.models.azure_mistral.AzureMLOnlineEndpointAsync", ModelWithoutAsyncRequestsMock))
+
         return {
                 "azure_open_ai": AzureOpenAIModel(
                     config=AzureOpenAIConfiguration(
diff --git a/tests/test_end_to_end.py b/tests/test_end_to_end.py
index 0983ece..0294205 100644
--- a/tests/test_end_to_end.py
+++ b/tests/test_end_to_end.py
@@ -1,5 +1,6 @@
 import re
 
+import pytest
 import httpx
 import respx
 from httpx import Response
@@ -9,7 +10,7 @@
 from allms.constants.input_data import IODataConstants
 from allms.domain.configuration import VertexAIConfiguration
 from allms.domain.prompt_dto import KeywordsOutputClass
-from allms.models.vertexai_gemini import VertexAIGeminiModel
+from allms.models import VertexAIGeminiModel, HarmBlockThreshold, HarmCategory
 from allms.utils import io_utils
 from tests.conftest import AzureOpenAIEnv
 
@@ -156,7 +157,7 @@ def test_gemini_version_is_passed_to_model(self):
         model_config = VertexAIConfiguration(
             cloud_project="dummy-project-id",
             cloud_location="us-central1",
-            gemini_model_name="gemini-model-name"
+            gemini_model_name="gemini-1.0-pro-001"
         )
 
         # WHEN
@@ -181,3 +182,58 @@ def test_model_times_out(
             # THEN
             assert responses[0].response is None
             assert "Request timed out" in responses[0].error
+    def test_gemini_specific_args_are_passed_to_model(self):
+        gemini_model_name = "gemini-1.5-pro-001"
+        gemini_safety_settings = {
+            HarmCategory.HARM_CATEGORY_UNSPECIFIED: HarmBlockThreshold.BLOCK_NONE,
+            HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
+            HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_ONLY_HIGH,
+            HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
+            HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
+        }
+        model_config = VertexAIConfiguration(
+            cloud_project="dummy-project-id",
+            cloud_location="us-central1",
+            gemini_model_name=gemini_model_name,
+            gemini_safety_settings=gemini_safety_settings
+        )
+        # WHEN
+        gemini_model = VertexAIGeminiModel(config=model_config)
+
+        # THEN
+        assert gemini_model._llm.model_name == gemini_model_name
+        assert gemini_model._llm.safety_settings == gemini_safety_settings
+
+    @pytest.mark.parametrize(
+        "model_name", [
+            "gemini-1.0-pro", "gemini-1.5-pro", "gemini-1.5-flash","gemini-1.0-pro-001", "gemini-1.0-pro-002",
+            "gemini-1.5-pro-001", "gemini-1.5-flash-001", "gemini-1.5-pro-preview-0514"
+        ]
+    )
+    def test_correct_gemini_model_name_work(self, model_name):
+        # GIVEN
+        model_config = VertexAIConfiguration(
+            cloud_project="dummy-project-id",
+            cloud_location="us-central1",
+            gemini_model_name=model_name,
+        )
+
+        # WHEN & THEN
+        VertexAIGeminiModel(config=model_config)
+
+    @pytest.mark.parametrize(
+        "model_name", [
+            "gemini-2.0-pro", "geminis-1.5-pro", "gemini-flash", "gemini-1.5-preview-pro", "gpt4"
+        ]
+    )
+    def test_incorrect_gemini_model_name_fail(self, model_name):
+        # GIVEN
+        model_config = VertexAIConfiguration(
+            cloud_project="dummy-project-id",
+            cloud_location="us-central1",
+            gemini_model_name=model_name,
+        )
+
+        # WHEN & THEN
+        with pytest.raises(ValueError, match=f"Model {model_name} is not supported."):
+            VertexAIGeminiModel(config=model_config)
diff --git a/tests/test_model_behavior_for_different_input_data.py b/tests/test_model_behavior_for_different_input_data.py
index 9e4d1cf..fa464e2 100644
--- a/tests/test_model_behavior_for_different_input_data.py
+++ b/tests/test_model_behavior_for_different_input_data.py
@@ -78,7 +78,7 @@ def test_exception_when_input_data_is_missing_and_prompt_contains_input_key(self
                 model.generate(prompt, None)
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_exception_when_num_prompt_tokens_larger_than_model_total_max_tokens(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         chain_run_mock.return_value = "{}"
@@ -97,7 +97,7 @@ def test_exception_when_num_prompt_tokens_larger_than_model_total_max_tokens(sel
             assert "Value Error has occurred: Prompt is too long" in response.error
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_whether_curly_brackets_are_not_breaking_the_prompt(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         chain_run_mock.return_value = "{}"
@@ -115,7 +115,7 @@ def test_whether_curly_brackets_are_not_breaking_the_prompt(self, tokens_mock, c
             assert response.response is not None
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_warning_when_num_prompt_tokens_plus_max_output_tokens_larger_than_model_total_max_tokens(
             self,
             tokens_mock,
diff --git a/tests/test_output_parser.py b/tests/test_output_parser.py
index 17e1724..5b270b8 100644
--- a/tests/test_output_parser.py
+++ b/tests/test_output_parser.py
@@ -9,7 +9,7 @@
 
 class TestOutputModelParserForDifferentModelOutputs:
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_output_parser_returns_desired_format(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         text_output = "This is the model output"
@@ -27,7 +27,7 @@ def test_output_parser_returns_desired_format(self, tokens_mock, chain_run_mock,
             assert model_response[0].response.summary == text_output
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_output_parser_returns_error_when_model_output_returns_different_field(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         text_output = "This is the model output"
@@ -45,7 +45,7 @@ def test_output_parser_returns_error_when_model_output_returns_different_field(s
             assert model_response[0].response is None
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     @pytest.mark.parametrize("json_response", [
         ("{\"summary\": \"This is the model output\"}"),
         ("Sure! Here's the JSON you wanted: {\"summary\": \"This is the model output\"} Have a nice day!"),
@@ -66,7 +66,7 @@ def test_output_parser_extracts_json_from_response(self, tokens_mock, chain_run_
             assert model_response[0].response == SummaryOutputClass(summary="This is the model output")
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_output_parser_returns_error_when_json_is_garbled(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         chain_run_mock.return_value = "Sure! Here's the JSON you wanted: {\"summary: \"text\"}"
@@ -82,7 +82,7 @@ def test_output_parser_returns_error_when_json_is_garbled(self, tokens_mock, cha
             assert model_response[0].response is None
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_output_parser_returns_parsed_class_when_model_output_returns_too_many_fields(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         text_output = "This is the model output"
@@ -100,7 +100,7 @@ def test_output_parser_returns_parsed_class_when_model_output_returns_too_many_f
             assert model_response[0].response.summary == text_output
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_model_returns_output_as_python_list_correctly(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         text_output = ["1", "2", "3"]
@@ -118,7 +118,7 @@ def test_model_returns_output_as_python_list_correctly(self, tokens_mock, chain_
             assert model_response[0].response.keywords == list(map(str, text_output))
 
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     def test_model_output_when_input_data_is_empty(self, tokens_mock, chain_run_mock, models):
         # GIVEN
         expected_model_response = "2+2 is 4"
diff --git a/tests/test_utf_characters_data.py b/tests/test_utf_characters_data.py
index f7606f7..b8981bb 100644
--- a/tests/test_utf_characters_data.py
+++ b/tests/test_utf_characters_data.py
@@ -6,7 +6,7 @@
 
 class TestModelBehaviorForSpecialCharacters:
     @patch("langchain.chains.base.Chain.arun")
-    @patch("langchain_community.llms.vertexai.VertexAI.get_num_tokens")
+    @patch("langchain_google_vertexai.llms.VertexAI.get_num_tokens")
     @pytest.mark.parametrize("input_character", list(html.entities.entitydefs.values()))
     def test_model_is_not_broken_by_special_characters(self, tokens_mock, arun_mock, input_character, models):
         # GIVEN