diff --git a/CHANGELOG.md b/CHANGELOG.md
index a644b13d2..189dd785d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -12,12 +12,15 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - `BaseTask.add_parent()` to add a parent task to a child task.
 - `BaseTask.add_parents()` to add multiple parent tasks to a child task.
 - `Structure.resolve_relationships()` to resolve asymmetrically defined parent/child relationships. In other words, if a parent declares a child, but the child does not declare the parent, the parent will automatically be added as a parent of the child when running this method. The method is invoked automatically by `Structure.before_run()`.
+- `CohereEmbeddingDriver` for using Cohere's embeddings API.
+- `CohereStructureConfig` for providing Structures with quick Cohere configuration.
 
 ### Changed
 - **BREAKING**: `Workflow` no longer modifies task relationships when adding tasks via `tasks` init param, `add_tasks()` or `add_task()`. Previously, adding a task would automatically add the previously added task as its parent. Existing code that relies on this behavior will need to be updated to explicitly add parent/child relationships using the API offered by `BaseTask`.
 - `Structure.before_run()` now automatically resolves asymmetrically defined parent/child relationships using the new `Structure.resolve_relationships()`.
 - Updated `HuggingFaceHubPromptDriver` to use `transformers`'s `apply_chat_template`.
 - Updated `HuggingFacePipelinePromptDriver` to use chat features of `transformers.TextGenerationPipeline`.
+- Updated `CoherePromptDriver` to use Cohere's latest SDK.
 
 ### Fixed
 - `Workflow.insert_task()` no longer inserts duplicate tasks when given multiple parent tasks.
diff --git a/docs/griptape-framework/drivers/embedding-drivers.md b/docs/griptape-framework/drivers/embedding-drivers.md
index 49dfde4a5..58182b03e 100644
--- a/docs/griptape-framework/drivers/embedding-drivers.md
+++ b/docs/griptape-framework/drivers/embedding-drivers.md
@@ -164,6 +164,29 @@ embeddings = driver.embed_string("Hello world!")
 print(embeddings[:3])
 ```
 
+### Cohere Embeddings
+
+The [CohereEmbeddingDriver](../../reference/griptape/drivers/embedding/cohere_embedding_driver.md) uses the [Cohere Embeddings API](https://docs.cohere.com/docs/embeddings).
+
+!!! info
+    This driver requires the `drivers-embedding-cohere` [extra](../index.md#extras).
+
+```python
+import os
+from griptape.drivers import CohereEmbeddingDriver
+
+embedding_driver=CohereEmbeddingDriver(
+    model="embed-english-v3.0",
+    api_key=os.environ["COHERE_API_KEY"],
+    input_type="search_document",
+)
+
+embeddings = embedding_driver.embed_string("Hello world!")
+
+# display the first 3 embeddings
+print(embeddings[:3])
+```
+
 ### Override Default Structure Embedding Driver
 Here is how you can override the Embedding Driver that is used by default in Structures. 
 
diff --git a/griptape/config/__init__.py b/griptape/config/__init__.py
index 7783b3886..541eb0db0 100644
--- a/griptape/config/__init__.py
+++ b/griptape/config/__init__.py
@@ -8,6 +8,7 @@
 from .amazon_bedrock_structure_config import AmazonBedrockStructureConfig
 from .anthropic_structure_config import AnthropicStructureConfig
 from .google_structure_config import GoogleStructureConfig
+from .cohere_structure_config import CohereStructureConfig
 
 
 __all__ = [
@@ -19,4 +20,5 @@
     "AmazonBedrockStructureConfig",
     "AnthropicStructureConfig",
     "GoogleStructureConfig",
+    "CohereStructureConfig",
 ]
diff --git a/griptape/config/cohere_structure_config.py b/griptape/config/cohere_structure_config.py
new file mode 100644
index 000000000..82f11b8f4
--- /dev/null
+++ b/griptape/config/cohere_structure_config.py
@@ -0,0 +1,37 @@
+from attrs import Factory, define, field
+
+from griptape.config import StructureConfig
+from griptape.drivers import (
+    BaseEmbeddingDriver,
+    BasePromptDriver,
+    CoherePromptDriver,
+    CohereEmbeddingDriver,
+    BaseVectorStoreDriver,
+    LocalVectorStoreDriver,
+)
+
+
+@define
+class CohereStructureConfig(StructureConfig):
+    api_key: str = field(metadata={"serializable": False}, kw_only=True)
+
+    prompt_driver: BasePromptDriver = field(
+        default=Factory(lambda self: CoherePromptDriver(model="command-r", api_key=self.api_key), takes_self=True),
+        metadata={"serializable": True},
+        kw_only=True,
+    )
+    embedding_driver: BaseEmbeddingDriver = field(
+        default=Factory(
+            lambda self: CohereEmbeddingDriver(
+                model="embed-english-v3.0", api_key=self.api_key, input_type="search_document"
+            ),
+            takes_self=True,
+        ),
+        metadata={"serializable": True},
+        kw_only=True,
+    )
+    vector_store_driver: BaseVectorStoreDriver = field(
+        default=Factory(lambda self: LocalVectorStoreDriver(embedding_driver=self.embedding_driver), takes_self=True),
+        kw_only=True,
+        metadata={"serializable": True},
+    )
diff --git a/griptape/drivers/__init__.py b/griptape/drivers/__init__.py
index f44602f8b..3050989fe 100644
--- a/griptape/drivers/__init__.py
+++ b/griptape/drivers/__init__.py
@@ -29,6 +29,7 @@
 from .embedding.huggingface_hub_embedding_driver import HuggingFaceHubEmbeddingDriver
 from .embedding.google_embedding_driver import GoogleEmbeddingDriver
 from .embedding.dummy_embedding_driver import DummyEmbeddingDriver
+from .embedding.cohere_embedding_driver import CohereEmbeddingDriver
 
 from .embedding_model.base_embedding_model_driver import BaseEmbeddingModelDriver
 from .embedding_model.sagemaker_huggingface_embedding_model_driver import SageMakerHuggingFaceEmbeddingModelDriver
@@ -143,6 +144,7 @@
     "GoogleEmbeddingDriver",
     "DummyEmbeddingDriver",
     "BaseEmbeddingModelDriver",
+    "CohereEmbeddingDriver",
     "SageMakerHuggingFaceEmbeddingModelDriver",
     "SageMakerTensorFlowHubEmbeddingModelDriver",
     "BaseVectorStoreDriver",
diff --git a/griptape/drivers/embedding/cohere_embedding_driver.py b/griptape/drivers/embedding/cohere_embedding_driver.py
new file mode 100644
index 000000000..5e8bdf4dd
--- /dev/null
+++ b/griptape/drivers/embedding/cohere_embedding_driver.py
@@ -0,0 +1,43 @@
+from __future__ import annotations
+from typing import TYPE_CHECKING
+from attrs import define, field, Factory
+from griptape.drivers import BaseEmbeddingDriver
+from griptape.tokenizers import CohereTokenizer
+from griptape.utils import import_optional_dependency
+
+if TYPE_CHECKING:
+    from cohere import Client
+
+
+@define
+class CohereEmbeddingDriver(BaseEmbeddingDriver):
+    """
+    Attributes:
+        api_key: Cohere API key.
+        model: 	Cohere model name.
+        client: Custom `cohere.Client`.
+        tokenizer: Custom `CohereTokenizer`.
+        input_type: Cohere embedding input type.
+    """
+
+    DEFAULT_MODEL = "models/embedding-001"
+
+    api_key: str = field(kw_only=True, metadata={"serializable": False})
+    client: Client = field(
+        default=Factory(lambda self: import_optional_dependency("cohere").Client(self.api_key), takes_self=True),
+        kw_only=True,
+    )
+    tokenizer: CohereTokenizer = field(
+        default=Factory(lambda self: CohereTokenizer(model=self.model, client=self.client), takes_self=True),
+        kw_only=True,
+    )
+
+    input_type: str = field(kw_only=True, metadata={"serializable": True})
+
+    def try_embed_chunk(self, chunk: str) -> list[float]:
+        result = self.client.embed(texts=[chunk], model=self.model, input_type=self.input_type)
+
+        if isinstance(result.embeddings, list):
+            return result.embeddings[0]
+        else:
+            raise ValueError("Non-float embeddings are not supported.")
diff --git a/griptape/drivers/prompt/cohere_prompt_driver.py b/griptape/drivers/prompt/cohere_prompt_driver.py
index 2f85c49bf..7a2f39cd6 100644
--- a/griptape/drivers/prompt/cohere_prompt_driver.py
+++ b/griptape/drivers/prompt/cohere_prompt_driver.py
@@ -1,5 +1,5 @@
 from __future__ import annotations
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 from collections.abc import Iterator
 from attrs import define, field, Factory
 from griptape.artifacts import TextArtifact
@@ -21,7 +21,7 @@ class CoherePromptDriver(BasePromptDriver):
         tokenizer: Custom `CohereTokenizer`.
     """
 
-    api_key: str = field(kw_only=True, metadata={"serializable": True})
+    api_key: str = field(kw_only=True, metadata={"serializable": False})
     model: str = field(kw_only=True, metadata={"serializable": True})
     client: Client = field(
         default=Factory(lambda self: import_optional_dependency("cohere").Client(self.api_key), takes_self=True),
@@ -33,33 +33,37 @@ class CoherePromptDriver(BasePromptDriver):
     )
 
     def try_run(self, prompt_stack: PromptStack) -> TextArtifact:
-        result = self.client.generate(**self._base_params(prompt_stack))
+        result = self.client.chat(**self._base_params(prompt_stack))
 
-        if result.generations:
-            if len(result.generations) == 1:
-                generation = result.generations[0]
-
-                return TextArtifact(value=generation.text.strip())
-            else:
-                raise Exception("completion with more than one choice is not supported yet")
-        else:
-            raise Exception("model response is empty")
+        return TextArtifact(value=result.text)
 
     def try_stream(self, prompt_stack: PromptStack) -> Iterator[TextArtifact]:
-        result = self.client.generate(
-            **self._base_params(prompt_stack),
-            stream=True,  # pyright: ignore[reportCallIssue]
-        )
+        result = self.client.chat_stream(**self._base_params(prompt_stack))
 
-        for chunk in result:
-            yield TextArtifact(value=chunk.text)
+        for event in result:
+            if event.event_type == "text-generation":
+                yield TextArtifact(value=event.text)
 
     def _base_params(self, prompt_stack: PromptStack) -> dict:
-        prompt = self.prompt_stack_to_string(prompt_stack)
+        user_message = prompt_stack.inputs[-1].content
+        history_messages = [self.__to_cohere_message(input) for input in prompt_stack.inputs[:-1]]
+
         return {
-            "prompt": self.prompt_stack_to_string(prompt_stack),
-            "model": self.model,
+            "message": user_message,
+            "chat_history": history_messages,
             "temperature": self.temperature,
-            "end_sequences": self.tokenizer.stop_sequences,
-            "max_tokens": self.max_output_tokens(prompt),
+            "stop_sequences": self.tokenizer.stop_sequences,
         }
+
+    def __to_cohere_message(self, input: PromptStack.Input) -> dict[str, Any]:
+        return {"role": self.__to_cohere_role(input.role), "text": input.content}
+
+    def __to_cohere_role(self, role: str) -> str:
+        if role == PromptStack.SYSTEM_ROLE:
+            return "SYSTEM"
+        if role == PromptStack.USER_ROLE:
+            return "USER"
+        elif role == PromptStack.ASSISTANT_ROLE:
+            return "CHATBOT"
+        else:
+            return "USER"
diff --git a/griptape/schemas/base_schema.py b/griptape/schemas/base_schema.py
index 79ae5e51f..2dd454b53 100644
--- a/griptape/schemas/base_schema.py
+++ b/griptape/schemas/base_schema.py
@@ -110,6 +110,7 @@ def _resolve_types(cls, attrs_cls: type) -> None:
         from typing import Any
 
         boto3 = import_optional_dependency("boto3") if is_dependency_installed("boto3") else Any
+        Client = import_optional_dependency("cohere").Client if is_dependency_installed("cohere") else Any
 
         attrs.resolve_types(
             attrs_cls,
@@ -122,6 +123,7 @@ def _resolve_types(cls, attrs_cls: type) -> None:
                 "BaseTokenizer": BaseTokenizer,
                 "BasePromptModelDriver": BasePromptModelDriver,
                 "boto3": boto3,
+                "Client": Client,
             },
         )
 
diff --git a/griptape/tokenizers/cohere_tokenizer.py b/griptape/tokenizers/cohere_tokenizer.py
index 0a3c6a236..e6845d9ca 100644
--- a/griptape/tokenizers/cohere_tokenizer.py
+++ b/griptape/tokenizers/cohere_tokenizer.py
@@ -9,8 +9,8 @@
 
 @define()
 class CohereTokenizer(BaseTokenizer):
-    MODEL_PREFIXES_TO_MAX_INPUT_TOKENS = {"command": 4096}
-    MODEL_PREFIXES_TO_MAX_OUTPUT_TOKENS = {"command": 4096}
+    MODEL_PREFIXES_TO_MAX_INPUT_TOKENS = {"command-r": 128000, "command": 4096, "embed": 512}
+    MODEL_PREFIXES_TO_MAX_OUTPUT_TOKENS = {"command": 4096, "embed": 512}
 
     client: Client = field(kw_only=True)
 
diff --git a/poetry.lock b/poetry.lock
index c89d577b4..65e767cc5 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -955,13 +955,13 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [[package]]
 name = "cohere"
-version = "5.5.0"
+version = "5.5.4"
 description = ""
 optional = true
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "cohere-5.5.0-py3-none-any.whl", hash = "sha256:7792e8898c95f2cb955b2d9f23b8602f73f3b698d59f1a1b4896c53809671da0"},
-    {file = "cohere-5.5.0.tar.gz", hash = "sha256:00b492ebf8921e83cb2371f2ee36ddf301422daae3024343a87d4316f02b711b"},
+    {file = "cohere-5.5.4-py3-none-any.whl", hash = "sha256:8b692dcb5e86b554e5884168a7d2454951ce102fbd983e9053ec933e06bf02fa"},
+    {file = "cohere-5.5.4.tar.gz", hash = "sha256:14acb2ccf272e958f79f9241ae972fd82e96b9b8ee9e6922a5687370761203ec"},
 ]
 
 [package.dependencies]
@@ -971,7 +971,7 @@ httpx = ">=0.21.2"
 httpx-sse = ">=0.4.0,<0.5.0"
 pydantic = ">=1.9.2"
 requests = ">=2.0.0,<3.0.0"
-tokenizers = ">=0.19,<0.20"
+tokenizers = ">=0.15,<0.16"
 types-requests = ">=2.0.0,<3.0.0"
 typing_extensions = ">=4.0.0"
 
@@ -5263,120 +5263,130 @@ files = [
 
 [[package]]
 name = "tokenizers"
-version = "0.19.1"
+version = "0.15.2"
 description = ""
 optional = true
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
-huggingface-hub = ">=0.16.4,<1.0"
+huggingface_hub = ">=0.16.4,<1.0"
 
 [package.extras]
 dev = ["tokenizers[testing]"]
-docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
-testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
+docs = ["setuptools_rust", "sphinx", "sphinx_rtd_theme"]
+testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests"]
 
 [[package]]
 name = "tomli"
@@ -5515,39 +5525,41 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformers"
-version = "4.41.2"
+version = "4.39.3"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = true
 python-versions = ">=3.8.0"
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 ]
 
 [package.dependencies]
 filelock = "*"
-huggingface-hub = ">=0.23.0,<1.0"
+huggingface-hub = ">=0.19.3,<1.0"
 numpy = ">=1.17"
 packaging = ">=20.0"
 pyyaml = ">=5.1"
 regex = "!=2019.12.17"
 requests = "*"
 safetensors = ">=0.4.1"
-tokenizers = ">=0.19,<0.20"
+tokenizers = ">=0.14,<0.19"
 tqdm = ">=4.27"
 
 [package.extras]
 accelerate = ["accelerate (>=0.21.0)"]
 agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
-all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision"]
+all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.14,<0.19)", "torch", "torchaudio", "torchvision"]
 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 codecarbon = ["codecarbon (==1.2.0)"]
 deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
-deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
-dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
-dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"]
-dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
-flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
+deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm", "tokenizers (>=0.14,<0.19)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
+dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.14,<0.19)", "urllib3 (<2.0.0)"]
+dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm", "tokenizers (>=0.14,<0.19)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
+docs = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "hf-doc-builder", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.14,<0.19)", "torch", "torchaudio", "torchvision"]
+docs-specific = ["hf-doc-builder"]
+flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)"]
 flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 ftfy = ["ftfy"]
 integrations = ["optuna", "ray[tune] (>=2.7.0)", "sigopt"]
@@ -5557,7 +5569,7 @@ natten = ["natten (>=0.14.6,<0.15.0)"]
 onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
 onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
 optuna = ["optuna"]
-quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.1.5)", "urllib3 (<2.0.0)"]
+quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "ruff (==0.1.5)", "urllib3 (<2.0.0)"]
 ray = ["ray[tune] (>=2.7.0)"]
 retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
 sagemaker = ["sagemaker (>=2.31.0)"]
@@ -5566,16 +5578,16 @@ serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
 sigopt = ["sigopt"]
 sklearn = ["scikit-learn"]
 speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
-testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
-tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
-tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
+testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "tensorboard", "timeout-decorator"]
+tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
+tf-cpu = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 timm = ["timm"]
-tokenizers = ["tokenizers (>=0.19,<0.20)"]
+tokenizers = ["tokenizers (>=0.14,<0.19)"]
 torch = ["accelerate (>=0.21.0)", "torch"]
 torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
 torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
-torchhub = ["filelock", "huggingface-hub (>=0.23.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
+torchhub = ["filelock", "huggingface-hub (>=0.19.3,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.14,<0.19)", "torch", "tqdm (>=4.27)"]
 video = ["av (==9.2.0)", "decord (==0.6.0)"]
 vision = ["Pillow (>=10.0.1,<=15.0)"]
 
@@ -6047,6 +6059,7 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 all = ["anthropic", "beautifulsoup4", "boto3", "cohere", "elevenlabs", "filetype", "google-generativeai", "mail-parser", "markdownify", "marqo", "opensearch-py", "pandas", "pgvector", "pillow", "pinecone-client", "playwright", "psycopg2-binary", "pusher", "pymongo", "pypdf", "redis", "snowflake-sqlalchemy", "sqlalchemy-redshift", "torch", "trafilatura", "transformers", "voyageai"]
 drivers-embedding-amazon-bedrock = ["boto3"]
 drivers-embedding-amazon-sagemaker = ["boto3"]
+drivers-embedding-cohere = ["cohere"]
 drivers-embedding-google = ["google-generativeai"]
 drivers-embedding-huggingface = ["huggingface-hub", "transformers"]
 drivers-embedding-voyageai = ["voyageai"]
@@ -6083,4 +6096,4 @@ loaders-pdf = ["pypdf"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "658965f94fd55e2ff1ee9e3579854d247344ce9da8b2f8f8a08826a515fb2aff"
+content-hash = "7d073f2b3d8b7e16b3315c7c59925884fadda9c0b0c179b191a748de669f2e0c"
diff --git a/pyproject.toml b/pyproject.toml
index c82cb8e26..b750051e0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -31,9 +31,9 @@ dateparser = "^1.1.8"
 requests = "^2"
 
 # drivers
-cohere = { version = ">=4", optional = true }
+cohere = { version = "^5.5.4", optional = true }
 anthropic = { version = "^0.20.0", optional = true }
-transformers = { version = "^4.41.2", optional = true }
+transformers = { version = "^4.39.3", optional = true }
 huggingface-hub = { version = ">=0.13", optional = true }
 boto3 = { version = "^1.28.2", optional = true }
 sqlalchemy-redshift = { version = "*", optional = true }
@@ -91,6 +91,7 @@ drivers-embedding-amazon-sagemaker = ["boto3"]
 drivers-embedding-huggingface = ["huggingface-hub", "transformers"]
 drivers-embedding-voyageai = ["voyageai"]
 drivers-embedding-google = ["google-generativeai"]
+drivers-embedding-cohere = ["cohere"]
 
 drivers-web-scraper-trafilatura = ["trafilatura"]
 drivers-web-scraper-markdownify = ["playwright", "beautifulsoup4", "markdownify"]
diff --git a/tests/unit/config/test_cohere_structure_config.py b/tests/unit/config/test_cohere_structure_config.py
new file mode 100644
index 000000000..1dc585421
--- /dev/null
+++ b/tests/unit/config/test_cohere_structure_config.py
@@ -0,0 +1,38 @@
+from pytest import fixture
+from griptape.config import CohereStructureConfig
+
+
+class TestCohereStructureConfig:
+    @fixture
+    def config(self):
+        return CohereStructureConfig(api_key="api_key")
+
+    def test_to_dict(self, config):
+        assert config.to_dict() == {
+            "type": "CohereStructureConfig",
+            "image_generation_driver": {"type": "DummyImageGenerationDriver"},
+            "image_query_driver": {"type": "DummyImageQueryDriver"},
+            "conversation_memory_driver": None,
+            "text_to_speech_driver": {"type": "DummyTextToSpeechDriver"},
+            "audio_transcription_driver": {"type": "DummyAudioTranscriptionDriver"},
+            "prompt_driver": {
+                "type": "CoherePromptDriver",
+                "temperature": 0.1,
+                "max_tokens": None,
+                "stream": False,
+                "model": "command-r",
+            },
+            "embedding_driver": {
+                "type": "CohereEmbeddingDriver",
+                "model": "embed-english-v3.0",
+                "input_type": "search_document",
+            },
+            "vector_store_driver": {
+                "type": "LocalVectorStoreDriver",
+                "embedding_driver": {
+                    "type": "CohereEmbeddingDriver",
+                    "model": "embed-english-v3.0",
+                    "input_type": "search_document",
+                },
+            },
+        }
diff --git a/tests/unit/drivers/embedding/test_cohere_embedding_driver.py b/tests/unit/drivers/embedding/test_cohere_embedding_driver.py
new file mode 100644
index 000000000..af6a5576d
--- /dev/null
+++ b/tests/unit/drivers/embedding/test_cohere_embedding_driver.py
@@ -0,0 +1,21 @@
+from unittest.mock import Mock
+import pytest
+from griptape.drivers import CohereEmbeddingDriver
+
+
+class TestCohereEmbeddingDriver:
+    @pytest.fixture(autouse=True)
+    def mock_client(self, mocker):
+        mock_client = mocker.patch("cohere.Client").return_value
+
+        mock_client.embed.return_value = Mock(embeddings=[[0, 1, 0]])
+
+        return mock_client
+
+    def test_init(self):
+        assert CohereEmbeddingDriver(model="embed-english-v3.0", api_key="bar", input_type="search_document")
+
+    def test_try_embed_chunk(self):
+        assert CohereEmbeddingDriver(
+            model="embed-english-v3.0", api_key="bar", input_type="search_document"
+        ).try_embed_chunk("foobar") == [0, 1, 0]
diff --git a/tests/unit/drivers/prompt/test_cohere_prompt_driver.py b/tests/unit/drivers/prompt/test_cohere_prompt_driver.py
index 907e27325..b3ceb11a4 100644
--- a/tests/unit/drivers/prompt/test_cohere_prompt_driver.py
+++ b/tests/unit/drivers/prompt/test_cohere_prompt_driver.py
@@ -8,16 +8,16 @@ class TestCoherePromptDriver:
     @pytest.fixture
     def mock_client(self, mocker):
         mock_client = mocker.patch("cohere.Client").return_value
-        mock_client.generate.return_value.generations = [Mock()]
-        mock_client.generate.return_value.generations[0].text = "model-output"
+        mock_client.chat.return_value = Mock(text="model-output")
+
         return mock_client
 
     @pytest.fixture
     def mock_stream_client(self, mocker):
         mock_client = mocker.patch("cohere.Client").return_value
-        mock_chunk = Mock()
-        mock_chunk.text = "model-output"
-        mock_client.generate.return_value = iter([mock_chunk])
+        mock_chunk = Mock(text="model-output", event_type="text-generation")
+        mock_client.chat_stream.return_value = iter([mock_chunk])
+
         return mock_client
 
     @pytest.fixture(autouse=True)
@@ -55,16 +55,3 @@ def test_try_stream_run(self, mock_stream_client, prompt_stack):  # pyright: ign
 
         # Then
         assert text_artifact.value == "model-output"
-
-    @pytest.mark.parametrize("choices", [[], [1, 2]])
-    def test_try_run_throws_when_multiple_choices_returned(self, choices, mock_client, prompt_stack):
-        # Given
-        driver = CoherePromptDriver(model="command", api_key="api-key")
-        mock_client.generate.return_value.generations = choices
-
-        # When
-        with pytest.raises(Exception) as e:
-            driver.try_run(prompt_stack)
-
-        # Then
-        e.value.args[0] == "Completion with more than one choice is not supported yet."
diff --git a/tests/unit/tokenizers/test_cohere_tokenizer.py b/tests/unit/tokenizers/test_cohere_tokenizer.py
index ca724cee6..9ca23f4f0 100644
--- a/tests/unit/tokenizers/test_cohere_tokenizer.py
+++ b/tests/unit/tokenizers/test_cohere_tokenizer.py
@@ -7,6 +7,7 @@ class TestCohereTokenizer:
     @pytest.fixture(autouse=True)
     def mock_client(self, mocker):
         mock_client = mocker.patch("cohere.Client").return_value.tokenize.return_value.tokens = ["foo", "bar"]
+
         return mock_client
 
     @pytest.fixture