diff --git a/libs/vertexai/langchain_google_vertexai/_anthropic_utils.py b/libs/vertexai/langchain_google_vertexai/_anthropic_utils.py
new file mode 100644
index 000000000..6ca2f12c8
--- /dev/null
+++ b/libs/vertexai/langchain_google_vertexai/_anthropic_utils.py
@@ -0,0 +1,93 @@
+import re
+from typing import Dict, List, Optional, Tuple, Union
+
+from langchain_core.messages import BaseMessage
+
+_message_type_lookups = {"human": "user", "ai": "assistant"}
+
+
+def _format_image(image_url: str) -> Dict:
+    """Formats a message image to a dict for anthropic api."""
+    regex = r"^data:(?P<media_type>image/.+);base64,(?P<data>.+)$"
+    match = re.match(regex, image_url)
+    if match is None:
+        raise ValueError(
+            "Anthropic only supports base64-encoded images currently."
+            " Example: data:image/png;base64,'/9j/4AAQSk'..."
+        )
+    return {
+        "type": "base64",
+        "media_type": match.group("media_type"),
+        "data": match.group("data"),
+    }
+
+
+def _format_messages_anthropic(
+    messages: List[BaseMessage],
+) -> Tuple[Optional[str], List[Dict]]:
+    """Formats messages for anthropic."""
+    system_message: Optional[str] = None
+    formatted_messages: List[Dict] = []
+
+    for i, message in enumerate(messages):
+        if message.type == "system":
+            if i != 0:
+                raise ValueError("System message must be at beginning of message list.")
+            if not isinstance(message.content, str):
+                raise ValueError(
+                    "System message must be a string, "
+                    f"instead was: {type(message.content)}"
+                )
+            system_message = message.content
+            continue
+
+        role = _message_type_lookups[message.type]
+        content: Union[str, List[Dict]]
+
+        if not isinstance(message.content, str):
+            # parse as dict
+            assert isinstance(
+                message.content, list
+            ), "Anthropic message content must be str or list of dicts"
+
+            # populate content
+            content = []
+            for item in message.content:
+                if isinstance(item, str):
+                    content.append(
+                        {
+                            "type": "text",
+                            "text": item,
+                        }
+                    )
+                elif isinstance(item, dict):
+                    if "type" not in item:
+                        raise ValueError("Dict content item must have a type key")
+                    elif item["type"] == "image_url":
+                        # convert format
+                        source = _format_image(item["image_url"]["url"])
+                        content.append(
+                            {
+                                "type": "image",
+                                "source": source,
+                            }
+                        )
+                    elif item["type"] == "tool_use":
+                        item.pop("text", None)
+                        content.append(item)
+                    else:
+                        content.append(item)
+                else:
+                    raise ValueError(
+                        f"Content items must be str or dict, instead was: {type(item)}"
+                    )
+        else:
+            content = message.content
+
+        formatted_messages.append(
+            {
+                "role": role,
+                "content": content,
+            }
+        )
+    return system_message, formatted_messages
diff --git a/libs/vertexai/langchain_google_vertexai/model_garden.py b/libs/vertexai/langchain_google_vertexai/model_garden.py
index 6469fb425..982d24164 100644
--- a/libs/vertexai/langchain_google_vertexai/model_garden.py
+++ b/libs/vertexai/langchain_google_vertexai/model_garden.py
@@ -1,16 +1,34 @@
 from __future__ import annotations
 
 import asyncio
-from typing import Any, List, Optional
+from typing import Any, AsyncIterator, Dict, Iterator, List, Optional
 
 from langchain_core.callbacks.manager import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
+from langchain_core.language_models.chat_models import (
+    BaseChatModel,
+    agenerate_from_stream,
+    generate_from_stream,
+)
 from langchain_core.language_models.llms import BaseLLM
-from langchain_core.outputs import Generation, LLMResult
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    BaseMessage,
+)
+from langchain_core.outputs import (
+    ChatGeneration,
+    ChatGenerationChunk,
+    ChatResult,
+    Generation,
+    LLMResult,
+)
+from langchain_core.pydantic_v1 import root_validator
 
-from langchain_google_vertexai._base import _BaseVertexAIModelGarden
+from langchain_google_vertexai._anthropic_utils import _format_messages_anthropic
+from langchain_google_vertexai._base import _BaseVertexAIModelGarden, _VertexAICommon
 
 
 class VertexAIModelGarden(_BaseVertexAIModelGarden, BaseLLM):
@@ -70,3 +88,137 @@ async def _agenerate(
             endpoint=self.endpoint_path, instances=instances
         )
         return self._parse_response(response)
+
+
+class ChatAnthropicVertex(_VertexAICommon, BaseChatModel):
+    async_client: Any = None  #: :meta private:
+    model_name: str = "claude-3-sonnet@20240229"
+    "Underlying model name."
+    max_output_tokens: int = 1024
+
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        from anthropic import AnthropicVertex, AsyncAnthropicVertex
+
+        values["client"] = AnthropicVertex(
+            project_id=values["project"],
+            region=values["location"],
+            max_retries=values["max_retries"],
+        )
+        values["async_client"] = AsyncAnthropicVertex(
+            project_id=values["project"],
+            region=values["location"],
+            max_retries=values["max_retries"],
+        )
+        return values
+
+    @property
+    def _default_params(self):
+        return {
+            "model": self.model_name,
+            "max_tokens": self.max_output_tokens,
+            "temperature": self.temperature,
+            "top_k": self.top_k,
+            "top_p": self.top_p,
+        }
+
+    def _format_params(
+        self,
+        *,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        **kwargs: Any,
+    ) -> Dict[str, Any]:
+        system_message, formatted_messages = _format_messages_anthropic(messages)
+        params = self._default_params
+        params.update(kwargs)
+        params.update(
+            {
+                "system": system_message,
+                "messages": formatted_messages,
+                "stop_sequences": stop,
+            }
+        )
+        return {k: v for k, v in params.items() if v is not None}
+
+    def _format_output(self, data: Any, **kwargs: Any) -> ChatResult:
+        data_dict = data.model_dump()
+        content = data_dict["content"]
+        llm_output = {
+            k: v for k, v in data_dict.items() if k not in ("content", "role", "type")
+        }
+        if len(content) == 1 and content[0]["type"] == "text":
+            msg = AIMessage(content=content[0]["text"])
+        else:
+            msg = AIMessage(content=content)
+        return ChatResult(
+            generations=[ChatGeneration(message=msg)],
+            llm_output=llm_output,
+        )
+
+    def _generate(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        params = self._format_params(messages=messages, stop=stop, **kwargs)
+        if self.streaming:
+            stream_iter = self._stream(
+                messages, stop=stop, run_manager=run_manager, **kwargs
+            )
+            return generate_from_stream(stream_iter)
+        data = self.client.messages.create(**params)
+        return self._format_output(data, **kwargs)
+
+    async def _agenerate(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        params = self._format_params(messages=messages, stop=stop, **kwargs)
+        if self.streaming:
+            stream_iter = self._astream(
+                messages, stop=stop, run_manager=run_manager, **kwargs
+            )
+            return await agenerate_from_stream(stream_iter)
+        data = await self.async_client.messages.create(**params)
+        return self._format_output(data, **kwargs)
+
+    @property
+    def _llm_type(self) -> str:
+        """Return type of chat model."""
+        return "anthropic-chat-vertexai"
+
+    def _stream(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> Iterator[ChatGenerationChunk]:
+        params = self._format_params(messages=messages, stop=stop, **kwargs)
+        with self.client.messages.stream(**params) as stream:
+            for text in stream.text_stream:
+                chunk = ChatGenerationChunk(message=AIMessageChunk(content=text))
+                if run_manager:
+                    run_manager.on_llm_new_token(text, chunk=chunk)
+                yield chunk
+
+    async def _astream(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> AsyncIterator[ChatGenerationChunk]:
+        params = self._format_params(messages=messages, stop=stop, **kwargs)
+        async with self.async_client.messages.stream(**params) as stream:
+            async for text in stream.text_stream:
+                chunk = ChatGenerationChunk(message=AIMessageChunk(content=text))
+                if run_manager:
+                    await run_manager.on_llm_new_token(text, chunk=chunk)
+                yield chunk
diff --git a/libs/vertexai/poetry.lock b/libs/vertexai/poetry.lock
index 48f8c3eae..9bd3331eb 100644
--- a/libs/vertexai/poetry.lock
+++ b/libs/vertexai/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
 [[package]]
 name = "aiohttp"
@@ -124,6 +124,30 @@ files = [
 [package.dependencies]
 typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
 
+[[package]]
+name = "anthropic"
+version = "0.23.1"
+description = "The official Python library for the anthropic API"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "anthropic-0.23.1-py3-none-any.whl", hash = "sha256:6dc5779dae83a5834864f4a4af0166c972b70f4cb8fd2765e1558282cc6d6242"},
+    {file = "anthropic-0.23.1.tar.gz", hash = "sha256:9325103702cbc96bb09d1b58c36bde75c726f6a01029fb4d85f41ebba07e9066"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tokenizers = ">=0.13.0"
+typing-extensions = ">=4.7,<5"
+
+[package.extras]
+bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
+vertex = ["google-auth (>=2,<3)"]
+
 [[package]]
 name = "anyio"
 version = "4.3.0"
@@ -340,6 +364,28 @@ files = [
 marshmallow = ">=3.18.0,<4.0.0"
 typing-inspect = ">=0.4.0,<1"
 
+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+    {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
+[[package]]
+name = "docstring-parser"
+version = "0.16"
+description = "Parse Python docstrings in reST, Google and Numpydoc format"
+optional = false
+python-versions = ">=3.6,<4.0"
+files = [
+    {file = "docstring_parser-0.16-py3-none-any.whl", hash = "sha256:bf0a1387354d3691d102edef7ec124f219ef639982d096e26e3b60aeffa90637"},
+    {file = "docstring_parser-0.16.tar.gz", hash = "sha256:538beabd0af1e2db0146b6bd3caa526c35a34d61af9fd2887f3a8a27a739aa6e"},
+]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.2.0"
@@ -354,6 +400,22 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "filelock"
+version = "3.13.3"
+description = "A platform independent file lock."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "filelock-3.13.3-py3-none-any.whl", hash = "sha256:5ffa845303983e7a0b7ae17636509bc97997d58afeafa72fb141a17b152284cb"},
+    {file = "filelock-3.13.3.tar.gz", hash = "sha256:a79895a25bbefdf55d1a2a0a80968f7dbb28edcd6d4234a0afb3f37ecde4b546"},
+]
+
+[package.extras]
+docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
+typing = ["typing-extensions (>=4.8)"]
+
 [[package]]
 name = "freezegun"
 version = "1.4.0"
@@ -454,15 +516,50 @@ files = [
     {file = "frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b"},
 ]
 
+[[package]]
+name = "fsspec"
+version = "2024.3.1"
+description = "File-system specification"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fsspec-2024.3.1-py3-none-any.whl", hash = "sha256:918d18d41bf73f0e2b261824baeb1b124bcf771767e3a26425cd7dec3332f512"},
+    {file = "fsspec-2024.3.1.tar.gz", hash = "sha256:f39780e282d7d117ffb42bb96992f8a90795e4d0fb0f661a70ca39fe9c43ded9"},
+]
+
+[package.extras]
+abfs = ["adlfs"]
+adl = ["adlfs"]
+arrow = ["pyarrow (>=1)"]
+dask = ["dask", "distributed"]
+devel = ["pytest", "pytest-cov"]
+dropbox = ["dropbox", "dropboxdrivefs", "requests"]
+full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
+fuse = ["fusepy"]
+gcs = ["gcsfs"]
+git = ["pygit2"]
+github = ["requests"]
+gs = ["gcsfs"]
+gui = ["panel"]
+hdfs = ["pyarrow (>=1)"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
+libarchive = ["libarchive-c"]
+oci = ["ocifs"]
+s3 = ["s3fs"]
+sftp = ["paramiko"]
+smb = ["smbprotocol"]
+ssh = ["paramiko"]
+tqdm = ["tqdm"]
+
 [[package]]
 name = "google-api-core"
-version = "2.17.1"
+version = "2.18.0"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.17.1.tar.gz", hash = "sha256:9df18a1f87ee0df0bc4eea2770ebc4228392d8cc4066655b320e2cfccb15db95"},
-    {file = "google_api_core-2.17.1-py3-none-any.whl", hash = "sha256:610c5b90092c360736baccf17bd3efbcb30dd380e7a6dc28a71059edb8bd0d8e"},
+    {file = "google-api-core-2.18.0.tar.gz", hash = "sha256:62d97417bfc674d6cef251e5c4d639a9655e00c45528c4364fbfebb478ce72a9"},
+    {file = "google_api_core-2.18.0-py3-none-any.whl", hash = "sha256:5a63aa102e0049abe85b5b88cb9409234c1f70afcda21ce1e40b285b9629c1d6"},
 ]
 
 [package.dependencies]
@@ -476,6 +573,7 @@ grpcio-status = [
     {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 = ">=1.22.3,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0.dev0"
 requests = ">=2.18.0,<3.0.0.dev0"
 
@@ -486,31 +584,31 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.122.0"
+version = "2.125.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-python-client-2.122.0.tar.gz", hash = "sha256:77447bf2d6b6ea9e686fd66fc2f12ee7a63e3889b7427676429ebf09fcb5dcf9"},
-    {file = "google_api_python_client-2.122.0-py2.py3-none-any.whl", hash = "sha256:a5953e60394b77b98bcc7ff7c4971ed784b3b693e9a569c176eaccb1549330f2"},
+    {file = "google-api-python-client-2.125.0.tar.gz", hash = "sha256:51a0385cff65ec135106e8be60ee7112557396dde5f44113ae23912baddda143"},
+    {file = "google_api_python_client-2.125.0-py2.py3-none-any.whl", hash = "sha256:0a62b60fbd61b61a455f15d925264b3301099b67cafd2d33cf8bf151f1fca4f4"},
 ]
 
 [package.dependencies]
 google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0.dev0"
-google-auth = ">=1.19.0,<3.0.0.dev0"
-google-auth-httplib2 = ">=0.1.0"
-httplib2 = ">=0.15.0,<1.dev0"
+google-auth = ">=1.32.0,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0.dev0"
+google-auth-httplib2 = ">=0.2.0,<1.0.0"
+httplib2 = ">=0.19.0,<1.dev0"
 uritemplate = ">=3.0.1,<5"
 
 [[package]]
 name = "google-auth"
-version = "2.28.2"
+version = "2.29.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.28.2.tar.gz", hash = "sha256:80b8b4969aa9ed5938c7828308f20f035bc79f9d8fb8120bf9dc8db20b41ba30"},
-    {file = "google_auth-2.28.2-py2.py3-none-any.whl", hash = "sha256:9fd67bbcd40f16d9d42f950228e9cf02a2ded4ae49198b27432d0cded5a74c38"},
+    {file = "google-auth-2.29.0.tar.gz", hash = "sha256:672dff332d073227550ffc7457868ac4218d6c500b155fe6cc17d2b13602c360"},
+    {file = "google_auth-2.29.0-py2.py3-none-any.whl", hash = "sha256:d452ad095688cd52bae0ad6fafe027f6a6d6f560e810fec20914e17a09526415"},
 ]
 
 [package.dependencies]
@@ -542,24 +640,26 @@ httplib2 = ">=0.19.0"
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.44.0"
+version = "1.46.0"
 description = "Vertex AI API client library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "google-cloud-aiplatform-1.44.0.tar.gz", hash = "sha256:65876e8080ed3c4b3ec79c9a4090faab558fc369e3e4e75fa7a43d9813680cb2"},
-    {file = "google_cloud_aiplatform-1.44.0-py2.py3-none-any.whl", hash = "sha256:3670d961ce8c3da3d4bc3451b0e73221a461ebc7805ca16a51df99cbfd3785b0"},
+    {file = "google-cloud-aiplatform-1.46.0.tar.gz", hash = "sha256:9eeefcd34dbad2a1ade830d025154189d257e8dcfea45771dcac6e34a2783782"},
+    {file = "google_cloud_aiplatform-1.46.0-py2.py3-none-any.whl", hash = "sha256:a30a64f8bcefa0646340cf57abca192bb9ca9c456a47b842651a9564bba0534a"},
 ]
 
 [package.dependencies]
+docstring-parser = "<1"
 google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.8.dev0,<3.0.0dev", extras = ["grpc"]}
 google-auth = ">=2.14.1,<3.0.0dev"
-google-cloud-bigquery = ">=1.15.0,<4.0.0dev"
+google-cloud-bigquery = ">=1.15.0,<3.20.0 || >3.20.0,<4.0.0dev"
 google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
 google-cloud-storage = ">=1.32.0,<3.0.0dev"
 packaging = ">=14.3"
 proto-plus = ">=1.22.0,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
+pydantic = "<3"
 shapely = "<3.0.0dev"
 
 [package.extras]
@@ -575,6 +675,7 @@ prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<0.103.1)", "httpx (>=0.23.
 preview = ["cloudpickle (<3.0)", "google-cloud-logging (<4.0)"]
 private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
 ray = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)"]
+ray-testing = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pytest-xdist", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "ray[train] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "scikit-learn", "tensorflow", "torch (>=2.0.0,<2.1.0)", "xgboost", "xgboost-ray"]
 tensorboard = ["tensorflow (>=2.3.0,<2.15.0)"]
 testing = ["bigframes", "cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.103.1)", "google-api-core (>=2.11,<3.0.0)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "ipython", "kfp (>=2.6.0,<3.0.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyfakefs", "pytest-asyncio", "pytest-xdist", "pyyaml (==5.3.1)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (==2.13.0)", "tensorflow (>=2.3.0,<2.15.0)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost", "xgboost-ray"]
 vizier = ["google-vizier (>=0.1.6)"]
@@ -582,13 +683,13 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.19.0"
+version = "3.20.1"
 description = "Google BigQuery API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-bigquery-3.19.0.tar.gz", hash = "sha256:8e311dae49768e1501fcdc5e916bff4b7e169471e5707919f4a6f78a02b3b5a6"},
-    {file = "google_cloud_bigquery-3.19.0-py2.py3-none-any.whl", hash = "sha256:c6b8850247a4b132066e49f6e45f850c22824482838688d744a4398eea1120ed"},
+    {file = "google-cloud-bigquery-3.20.1.tar.gz", hash = "sha256:318aa3abab5f1900ee24f63ba8bd02b9cdafaa942d738b4dc14a4ef2cc2d925f"},
+    {file = "google_cloud_bigquery-3.20.1-py2.py3-none-any.whl", hash = "sha256:d3e62fe61138c658b8853c402e2d8fb9346c84e602e21e3a26584be10fc5b0a4"},
 ]
 
 [package.dependencies]
@@ -672,13 +773,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.15.0"
+version = "2.16.0"
 description = "Google Cloud Storage API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-storage-2.15.0.tar.gz", hash = "sha256:7560a3c48a03d66c553dc55215d35883c680fe0ab44c23aa4832800ccc855c74"},
-    {file = "google_cloud_storage-2.15.0-py2.py3-none-any.whl", hash = "sha256:5d9237f88b648e1d724a0f20b5cde65996a37fe51d75d17660b1404097327dd2"},
+    {file = "google-cloud-storage-2.16.0.tar.gz", hash = "sha256:dda485fa503710a828d01246bd16ce9db0823dc51bbca742ce96a6817d58669f"},
+    {file = "google_cloud_storage-2.16.0-py2.py3-none-any.whl", hash = "sha256:91a06b96fb79cf9cdfb4e759f178ce11ea885c79938f89590344d079305f5852"},
 ]
 
 [package.dependencies]
@@ -977,6 +1078,38 @@ googleapis-common-protos = ">=1.5.5"
 grpcio = ">=1.62.1"
 protobuf = ">=4.21.6"
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "1.0.5"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+    {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
+
 [[package]]
 name = "httplib2"
 version = "0.22.0"
@@ -991,6 +1124,64 @@ files = [
 [package.dependencies]
 pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
 
+[[package]]
+name = "httpx"
+version = "0.27.0"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpx-0.27.0-py3-none-any.whl", hash = "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5"},
+    {file = "httpx-0.27.0.tar.gz", hash = "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5"},
+]
+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+
+[[package]]
+name = "huggingface-hub"
+version = "0.22.2"
+description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "huggingface_hub-0.22.2-py3-none-any.whl", hash = "sha256:3429e25f38ccb834d310804a3b711e7e4953db5a9e420cc147a5e194ca90fd17"},
+    {file = "huggingface_hub-0.22.2.tar.gz", hash = "sha256:32e9a9a6843c92f253ff9ca16b9985def4d80a93fb357af5353f770ef74a81be"},
+]
+
+[package.dependencies]
+filelock = "*"
+fsspec = ">=2023.5.0"
+packaging = ">=20.9"
+pyyaml = ">=5.1"
+requests = "*"
+tqdm = ">=4.42.1"
+typing-extensions = ">=3.7.4.3"
+
+[package.extras]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+cli = ["InquirerPy (==0.3.4)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
+hf-transfer = ["hf-transfer (>=0.1.4)"]
+inference = ["aiohttp", "minijinja (>=1.0)"]
+quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
+tensorflow = ["graphviz", "pydot", "tensorflow"]
+tensorflow-testing = ["keras (<3.0)", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+torch = ["safetensors", "torch"]
+typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
+
 [[package]]
 name = "idna"
 version = "3.6"
@@ -1040,13 +1231,13 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "0.1.12"
+version = "0.1.14"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = ">=3.8.1,<4.0"
+python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain-0.1.12-py3-none-any.whl", hash = "sha256:b4dd1760e2d035daefad08af60a209b96b729ee45492d34e3e127e553a471034"},
-    {file = "langchain-0.1.12.tar.gz", hash = "sha256:5f612761ba548b81748ed8dc70535e8de0531445415028a82de3fd8255bfa8a3"},
+    {file = "langchain-0.1.14-py3-none-any.whl", hash = "sha256:94f9b5df2421faaf762d4f43b9d65c270c2f701934580d281e4c6226deef7234"},
+    {file = "langchain-0.1.14.tar.gz", hash = "sha256:124c6244cf3957616b98f2df07dc2992fc40dff6ed1a62d8ee8a40f1e0260a40"},
 ]
 
 [package.dependencies]
@@ -1054,8 +1245,8 @@ aiohttp = ">=3.8.3,<4.0.0"
 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
 dataclasses-json = ">=0.5.7,<0.7"
 jsonpatch = ">=1.33,<2.0"
-langchain-community = ">=0.0.28,<0.1"
-langchain-core = ">=0.1.31,<0.2.0"
+langchain-community = ">=0.0.30,<0.1"
+langchain-core = ">=0.1.37,<0.2.0"
 langchain-text-splitters = ">=0.0.1,<0.1"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = ">=1,<2"
@@ -1069,31 +1260,31 @@ tenacity = ">=8.1.0,<9.0.0"
 azure = ["azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-textanalytics (>=5.3.0,<6.0.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-core (>=1.26.4,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "azure-search-documents (==11.4.0b8)", "openai (<2)"]
 clarifai = ["clarifai (>=9.1.0)"]
 cli = ["typer (>=0.9.0,<0.10.0)"]
-cohere = ["cohere (>=4,<5)"]
+cohere = ["cohere (>=4,<6)"]
 docarray = ["docarray[hnswlib] (>=0.32.0,<0.33.0)"]
 embeddings = ["sentence-transformers (>=2,<3)"]
-extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cohere (>=4,<5)", "couchbase (>=4.1.9,<5.0.0)", "dashvector (>=1.0.1,<2.0.0)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "langchain-openai (>=0.0.2,<0.1)", "lxml (>=4.9.2,<5.0.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "upstash-redis (>=0.15.0,<0.16.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
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 javascript = ["esprima (>=4.0.1,<5.0.0)"]
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+llms = ["clarifai (>=9.1.0)", "cohere (>=4,<6)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (<2)", "openlm (>=0.0.5,<0.0.6)", "torch (>=1,<3)", "transformers (>=4,<5)"]
 openai = ["openai (<2)", "tiktoken (>=0.3.2,<0.6.0)"]
 qdrant = ["qdrant-client (>=1.3.1,<2.0.0)"]
 text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
 
 [[package]]
 name = "langchain-community"
-version = "0.0.28"
+version = "0.0.31"
 description = "Community contributed LangChain integrations."
 optional = false
-python-versions = ">=3.8.1,<4.0"
+python-versions = "<4.0,>=3.8.1"
 files = [
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 numpy = ">=1,<2"
 PyYAML = ">=5.3"
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 [package.dependencies]
-numpy = ">=1.13.3"
+numpy = ">=1.19.3"
 
 [[package]]
 name = "numpy"
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 [package.dependencies]
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 doc = ["reno", "sphinx", "tornado (>=4.5)"]
 
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+dev = ["tokenizers[testing]"]
+docs = ["setuptools_rust", "sphinx", "sphinx_rtd_theme"]
+testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests"]
+
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+
+[package.extras]
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+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
 [[package]]
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 [[package]]
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+version = "2.31.0.20240403"
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 [package.dependencies]
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 [[package]]
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+version = "4.11.0"
 description = "Backported and Experimental Type Hints for Python 3.8+"
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 ]
 
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@@ -2378,4 +2714,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "e1f5b1b60ca14f9ad4f9a839db8850fbe5f8c263ef0b4657e997546cdd1fce93"
+content-hash = "20e7de8ceb50b733e0e89b0149543792358daa55ea17e144bdd84d164921004a"
diff --git a/libs/vertexai/pyproject.toml b/libs/vertexai/pyproject.toml
index ec5da944d..857809451 100644
--- a/libs/vertexai/pyproject.toml
+++ b/libs/vertexai/pyproject.toml
@@ -18,6 +18,12 @@ google-cloud-storage = "^2.14.0"
 types-requests = "^2.31.0"
 types-protobuf = "^4.24.0.4"
 
+[tool.poetry.group.anthropic]
+optional = true
+
+[tool.poetry.group.anthropic.dependencies]
+anthropic = {extras = ["vertexai"], version = ">=0.23.0,<1"}
+
 [tool.poetry.group.test]
 optional = true
 
diff --git a/libs/vertexai/tests/integration_tests/test_model_garden.py b/libs/vertexai/tests/integration_tests/test_model_garden.py
index 5500692e1..618d98974 100644
--- a/libs/vertexai/tests/integration_tests/test_model_garden.py
+++ b/libs/vertexai/tests/integration_tests/test_model_garden.py
@@ -2,9 +2,18 @@
 from typing import Optional
 
 import pytest
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    HumanMessage,
+    SystemMessage,
+)
 from langchain_core.outputs import LLMResult
 
-from langchain_google_vertexai import VertexAIModelGarden
+from langchain_google_vertexai.model_garden import (
+    ChatAnthropicVertex,
+    VertexAIModelGarden,
+)
 
 
 @pytest.mark.skip("CI testing not set up")
@@ -87,3 +96,63 @@ async def test_model_garden_agenerate(
     output = await llm.agenerate(["What is the meaning of life?", "How much is 2+2"])
     assert isinstance(output, LLMResult)
     assert len(output.generations) == 2
+
+
+def test_anthropic() -> None:
+    project = os.environ["PROJECT"]
+    location = "us-central1"
+    model = ChatAnthropicVertex(
+        project=project,
+        location=location,
+    )
+    raw_context = (
+        "My name is Peter. You are my personal assistant. My favorite movies "
+        "are Lord of the Rings and Hobbit."
+    )
+    question = (
+        "Hello, could you recommend a good movie for me to watch this evening, please?"
+    )
+    context = SystemMessage(content=raw_context)
+    message = HumanMessage(content=question)
+    response = model.invoke([context, message])
+    assert isinstance(response, AIMessage)
+    assert isinstance(response.content, str)
+    assert response.response_metadata["model"] == "claude-3-sonnet-20240229"
+
+
+def test_anthropic_stream() -> None:
+    project = os.environ["PROJECT"]
+    location = "us-central1"
+    model = ChatAnthropicVertex(
+        project=project,
+        location=location,
+    )
+    question = (
+        "Hello, could you recommend a good movie for me to watch this evening, please?"
+    )
+    message = HumanMessage(content=question)
+    sync_response = model.stream([message])
+    for chunk in sync_response:
+        assert isinstance(chunk, AIMessageChunk)
+
+
+async def test_anthropic_async() -> None:
+    project = os.environ["PROJECT"]
+    location = "us-central1"
+    model = ChatAnthropicVertex(
+        project=project,
+        location=location,
+    )
+    raw_context = (
+        "My name is Peter. You are my personal assistant. My favorite movies "
+        "are Lord of the Rings and Hobbit."
+    )
+    question = (
+        "Hello, could you recommend a good movie for me to watch this evening, please?"
+    )
+    context = SystemMessage(content=raw_context)
+    message = HumanMessage(content=question)
+    response = await model.ainvoke([context, message])
+    assert isinstance(response, AIMessage)
+    assert isinstance(response.content, str)
+    assert response.response_metadata["model"] == "claude-3-sonnet-20240229"