diff --git a/.github/workflows/test-integrations-data-processing.yml b/.github/workflows/test-integrations-data-processing.yml
index ddac93d1e5..c40d45845d 100644
--- a/.github/workflows/test-integrations-data-processing.yml
+++ b/.github/workflows/test-integrations-data-processing.yml
@@ -25,7 +25,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.5","3.7","3.8","3.11","3.12"]
+        python-version: ["3.5","3.7","3.8","3.9","3.11","3.12"]
         # python3.6 reached EOL and is no longer being supported on
         # new versions of hosted runners on Github Actions
         # ubuntu-20.04 is the last version that supported python3.6
@@ -58,6 +58,10 @@ jobs:
         run: |
           set -x # print commands that are executed
           ./scripts/runtox.sh "py${{ matrix.python-version }}-huey-latest" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
+      - name: Test openai latest
+        run: |
+          set -x # print commands that are executed
+          ./scripts/runtox.sh "py${{ matrix.python-version }}-openai-latest" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
       - name: Test rq latest
         run: |
           set -x # print commands that are executed
@@ -110,6 +114,10 @@ jobs:
         run: |
           set -x # print commands that are executed
           ./scripts/runtox.sh --exclude-latest "py${{ matrix.python-version }}-huey" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
+      - name: Test openai pinned
+        run: |
+          set -x # print commands that are executed
+          ./scripts/runtox.sh --exclude-latest "py${{ matrix.python-version }}-openai" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
       - name: Test rq pinned
         run: |
           set -x # print commands that are executed
@@ -151,6 +159,10 @@ jobs:
         run: |
           set -x # print commands that are executed
           ./scripts/runtox.sh --exclude-latest "py2.7-huey" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
+      - name: Test openai py27
+        run: |
+          set -x # print commands that are executed
+          ./scripts/runtox.sh --exclude-latest "py2.7-openai" --cov=tests --cov=sentry_sdk --cov-report= --cov-branch
       - name: Test rq py27
         run: |
           set -x # print commands that are executed
diff --git a/mypy.ini b/mypy.ini
index fef90c867e..c1444d61e5 100644
--- a/mypy.ini
+++ b/mypy.ini
@@ -67,6 +67,8 @@ ignore_missing_imports = True
 ignore_missing_imports = True
 [mypy-huey.*]
 ignore_missing_imports = True
+[mypy-openai.*]
+ignore_missing_imports = True
 [mypy-arq.*]
 ignore_missing_imports = True
 [mypy-grpc.*]
diff --git a/scripts/split-tox-gh-actions/split-tox-gh-actions.py b/scripts/split-tox-gh-actions/split-tox-gh-actions.py
index f8beffc219..13b81283ca 100755
--- a/scripts/split-tox-gh-actions/split-tox-gh-actions.py
+++ b/scripts/split-tox-gh-actions/split-tox-gh-actions.py
@@ -70,6 +70,7 @@
         "beam",
         "celery",
         "huey",
+        "openai",
         "rq",
     ],
     "Databases": [
diff --git a/sentry_sdk/consts.py b/sentry_sdk/consts.py
index 2b58aecc24..e4edfddef1 100644
--- a/sentry_sdk/consts.py
+++ b/sentry_sdk/consts.py
@@ -219,6 +219,8 @@ class OP:
     MIDDLEWARE_STARLITE = "middleware.starlite"
     MIDDLEWARE_STARLITE_RECEIVE = "middleware.starlite.receive"
     MIDDLEWARE_STARLITE_SEND = "middleware.starlite.send"
+    OPENAI_CHAT_COMPLETIONS_CREATE = "ai.chat_completions.create.openai"
+    OPENAI_EMBEDDINGS_CREATE = "ai.embeddings.create.openai"
     QUEUE_SUBMIT_ARQ = "queue.submit.arq"
     QUEUE_TASK_ARQ = "queue.task.arq"
     QUEUE_SUBMIT_CELERY = "queue.submit.celery"
diff --git a/sentry_sdk/integrations/__init__.py b/sentry_sdk/integrations/__init__.py
index 21f7188ff1..c9737ae589 100644
--- a/sentry_sdk/integrations/__init__.py
+++ b/sentry_sdk/integrations/__init__.py
@@ -78,6 +78,7 @@ def iter_default_integrations(with_auto_enabling_integrations):
     "sentry_sdk.integrations.fastapi.FastApiIntegration",
     "sentry_sdk.integrations.flask.FlaskIntegration",
     "sentry_sdk.integrations.httpx.HttpxIntegration",
+    "sentry_sdk.integrations.openai.OpenAIIntegration",
     "sentry_sdk.integrations.pyramid.PyramidIntegration",
     "sentry_sdk.integrations.redis.RedisIntegration",
     "sentry_sdk.integrations.rq.RqIntegration",
diff --git a/sentry_sdk/integrations/openai.py b/sentry_sdk/integrations/openai.py
new file mode 100644
index 0000000000..5c05a43916
--- /dev/null
+++ b/sentry_sdk/integrations/openai.py
@@ -0,0 +1,279 @@
+from sentry_sdk import consts
+from sentry_sdk._types import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from typing import Any, Iterable, List, Optional, Callable, Iterator
+    from sentry_sdk.tracing import Span
+
+import sentry_sdk
+from sentry_sdk._functools import wraps
+from sentry_sdk.hub import Hub, _should_send_default_pii
+from sentry_sdk.integrations import DidNotEnable, Integration
+from sentry_sdk.utils import logger, capture_internal_exceptions, event_from_exception
+
+try:
+    from openai.resources.chat.completions import Completions
+    from openai.resources import Embeddings
+
+    if TYPE_CHECKING:
+        from openai.types.chat import ChatCompletionMessageParam, ChatCompletionChunk
+except ImportError:
+    raise DidNotEnable("OpenAI not installed")
+
+try:
+    import tiktoken  # type: ignore
+
+    enc = tiktoken.get_encoding("cl100k_base")
+
+    def count_tokens(s):
+        # type: (str) -> int
+        return len(enc.encode_ordinary(s))
+
+    logger.debug("[OpenAI] using tiktoken to count tokens")
+except ImportError:
+    logger.info(
+        "The Sentry Python SDK requires 'tiktoken' in order to measure token usage from some OpenAI APIs"
+        "Please install 'tiktoken' if you aren't receiving token usage in Sentry."
+        "See https://docs.sentry.io/platforms/python/integrations/openai/ for more information."
+    )
+
+    def count_tokens(s):
+        # type: (str) -> int
+        return 0
+
+
+COMPLETION_TOKENS_USED = "ai.completion_tоkens.used"
+PROMPT_TOKENS_USED = "ai.prompt_tоkens.used"
+TOTAL_TOKENS_USED = "ai.total_tоkens.used"
+
+
+class OpenAIIntegration(Integration):
+    identifier = "openai"
+
+    def __init__(self, include_prompts=True):
+        # type: (OpenAIIntegration, bool) -> None
+        self.include_prompts = include_prompts
+
+    @staticmethod
+    def setup_once():
+        # type: () -> None
+        Completions.create = _wrap_chat_completion_create(Completions.create)
+        Embeddings.create = _wrap_embeddings_create(Embeddings.create)
+
+
+def _capture_exception(hub, exc):
+    # type: (Hub, Any) -> None
+
+    if hub.client is not None:
+        event, hint = event_from_exception(
+            exc,
+            client_options=hub.client.options,
+            mechanism={"type": "openai", "handled": False},
+        )
+        hub.capture_event(event, hint=hint)
+
+
+def _calculate_chat_completion_usage(
+    messages, response, span, streaming_message_responses=None
+):
+    # type: (Iterable[ChatCompletionMessageParam], Any, Span, Optional[List[str]]) -> None
+    completion_tokens = 0
+    prompt_tokens = 0
+    total_tokens = 0
+    if hasattr(response, "usage"):
+        if hasattr(response.usage, "completion_tokens") and isinstance(
+            response.usage.completion_tokens, int
+        ):
+            completion_tokens = response.usage.completion_tokens
+        if hasattr(response.usage, "prompt_tokens") and isinstance(
+            response.usage.prompt_tokens, int
+        ):
+            prompt_tokens = response.usage.prompt_tokens
+        if hasattr(response.usage, "total_tokens") and isinstance(
+            response.usage.total_tokens, int
+        ):
+            total_tokens = response.usage.total_tokens
+
+    if prompt_tokens == 0:
+        for message in messages:
+            if "content" in message:
+                prompt_tokens += count_tokens(message["content"])
+
+    if completion_tokens == 0:
+        if streaming_message_responses is not None:
+            for message in streaming_message_responses:
+                completion_tokens += count_tokens(message)
+        elif hasattr(response, "choices"):
+            for choice in response.choices:
+                if hasattr(choice, "message"):
+                    completion_tokens += count_tokens(choice.message)
+
+    if total_tokens == 0:
+        total_tokens = prompt_tokens + completion_tokens
+
+    if completion_tokens != 0:
+        span.set_data(COMPLETION_TOKENS_USED, completion_tokens)
+    if prompt_tokens != 0:
+        span.set_data(PROMPT_TOKENS_USED, prompt_tokens)
+    if total_tokens != 0:
+        span.set_data(TOTAL_TOKENS_USED, total_tokens)
+
+
+def _wrap_chat_completion_create(f):
+    # type: (Callable[..., Any]) -> Callable[..., Any]
+    @wraps(f)
+    def new_chat_completion(*args, **kwargs):
+        # type: (*Any, **Any) -> Any
+        hub = Hub.current
+        if not hub:
+            return f(*args, **kwargs)
+
+        integration = hub.get_integration(OpenAIIntegration)  # type: OpenAIIntegration
+        if not integration:
+            return f(*args, **kwargs)
+
+        if "messages" not in kwargs:
+            # invalid call (in all versions of openai), let it return error
+            return f(*args, **kwargs)
+
+        try:
+            iter(kwargs["messages"])
+        except TypeError:
+            # invalid call (in all versions), messages must be iterable
+            return f(*args, **kwargs)
+
+        kwargs["messages"] = list(kwargs["messages"])
+        messages = kwargs["messages"]
+        model = kwargs.get("model")
+        streaming = kwargs.get("stream")
+
+        span = sentry_sdk.start_span(
+            op=consts.OP.OPENAI_CHAT_COMPLETIONS_CREATE, description="Chat Completion"
+        )
+        span.__enter__()
+        try:
+            res = f(*args, **kwargs)
+        except Exception as e:
+            _capture_exception(Hub.current, e)
+            span.__exit__(None, None, None)
+            raise e from None
+
+        with capture_internal_exceptions():
+            if _should_send_default_pii() and integration.include_prompts:
+                span.set_data("ai.input_messages", messages)
+            span.set_data("ai.model_id", model)
+            span.set_data("ai.streaming", streaming)
+
+            if hasattr(res, "choices"):
+                if _should_send_default_pii() and integration.include_prompts:
+                    span.set_data(
+                        "ai.responses", list(map(lambda x: x.message, res.choices))
+                    )
+                _calculate_chat_completion_usage(messages, res, span)
+                span.__exit__(None, None, None)
+            elif hasattr(res, "_iterator"):
+                data_buf: list[list[str]] = []  # one for each choice
+
+                old_iterator = res._iterator  # type: Iterator[ChatCompletionChunk]
+
+                def new_iterator():
+                    # type: () -> Iterator[ChatCompletionChunk]
+                    with capture_internal_exceptions():
+                        for x in old_iterator:
+                            if hasattr(x, "choices"):
+                                choice_index = 0
+                                for choice in x.choices:
+                                    if hasattr(choice, "delta") and hasattr(
+                                        choice.delta, "content"
+                                    ):
+                                        content = choice.delta.content
+                                        if len(data_buf) <= choice_index:
+                                            data_buf.append([])
+                                        data_buf[choice_index].append(content or "")
+                                    choice_index += 1
+                            yield x
+                        if len(data_buf) > 0:
+                            all_responses = list(
+                                map(lambda chunk: "".join(chunk), data_buf)
+                            )
+                            if (
+                                _should_send_default_pii()
+                                and integration.include_prompts
+                            ):
+                                span.set_data("ai.responses", all_responses)
+                            _calculate_chat_completion_usage(
+                                messages, res, span, all_responses
+                            )
+                    span.__exit__(None, None, None)
+
+                res._iterator = new_iterator()
+            else:
+                span.set_data("unknown_response", True)
+                span.__exit__(None, None, None)
+            return res
+
+    return new_chat_completion
+
+
+def _wrap_embeddings_create(f):
+    # type: (Callable[..., Any]) -> Callable[..., Any]
+
+    @wraps(f)
+    def new_embeddings_create(*args, **kwargs):
+        # type: (*Any, **Any) -> Any
+
+        hub = Hub.current
+        if not hub:
+            return f(*args, **kwargs)
+
+        integration = hub.get_integration(OpenAIIntegration)  # type: OpenAIIntegration
+        if not integration:
+            return f(*args, **kwargs)
+
+        with sentry_sdk.start_span(
+            op=consts.OP.OPENAI_EMBEDDINGS_CREATE,
+            description="OpenAI Embedding Creation",
+        ) as span:
+            if "input" in kwargs and (
+                _should_send_default_pii() and integration.include_prompts
+            ):
+                if isinstance(kwargs["input"], str):
+                    span.set_data("ai.input_messages", [kwargs["input"]])
+                elif (
+                    isinstance(kwargs["input"], list)
+                    and len(kwargs["input"]) > 0
+                    and isinstance(kwargs["input"][0], str)
+                ):
+                    span.set_data("ai.input_messages", kwargs["input"])
+            if "model" in kwargs:
+                span.set_data("ai.model_id", kwargs["model"])
+            try:
+                response = f(*args, **kwargs)
+            except Exception as e:
+                _capture_exception(Hub.current, e)
+                raise e from None
+
+            prompt_tokens = 0
+            total_tokens = 0
+            if hasattr(response, "usage"):
+                if hasattr(response.usage, "prompt_tokens") and isinstance(
+                    response.usage.prompt_tokens, int
+                ):
+                    prompt_tokens = response.usage.prompt_tokens
+                if hasattr(response.usage, "total_tokens") and isinstance(
+                    response.usage.total_tokens, int
+                ):
+                    total_tokens = response.usage.total_tokens
+
+            if prompt_tokens == 0:
+                prompt_tokens = count_tokens(kwargs["input"] or "")
+
+            if total_tokens == 0:
+                total_tokens = prompt_tokens
+
+            span.set_data(PROMPT_TOKENS_USED, prompt_tokens)
+            span.set_data(TOTAL_TOKENS_USED, total_tokens)
+
+            return response
+
+    return new_embeddings_create
diff --git a/setup.py b/setup.py
index 0af275d6af..0299bf91fb 100644
--- a/setup.py
+++ b/setup.py
@@ -60,6 +60,7 @@ def get_file_text(file_name):
         "httpx": ["httpx>=0.16.0"],
         "huey": ["huey>=2"],
         "loguru": ["loguru>=0.5"],
+        "openai": ["openai>=1.0.0", "tiktoken>=0.3.0"],
         "opentelemetry": ["opentelemetry-distro>=0.35b0"],
         "opentelemetry-experimental": [
             "opentelemetry-distro~=0.40b0",
diff --git a/tests/integrations/openai/__init__.py b/tests/integrations/openai/__init__.py
new file mode 100644
index 0000000000..d6cc3d5505
--- /dev/null
+++ b/tests/integrations/openai/__init__.py
@@ -0,0 +1,3 @@
+import pytest
+
+pytest.importorskip("openai")
diff --git a/tests/integrations/openai/test_openai.py b/tests/integrations/openai/test_openai.py
new file mode 100644
index 0000000000..ecdedd2694
--- /dev/null
+++ b/tests/integrations/openai/test_openai.py
@@ -0,0 +1,231 @@
+import pytest
+from openai import OpenAI, Stream, OpenAIError
+from openai.types import CompletionUsage, CreateEmbeddingResponse, Embedding
+from openai.types.chat import ChatCompletion, ChatCompletionMessage, ChatCompletionChunk
+from openai.types.chat.chat_completion import Choice
+from openai.types.chat.chat_completion_chunk import ChoiceDelta, Choice as DeltaChoice
+from openai.types.create_embedding_response import Usage as EmbeddingTokenUsage
+
+from sentry_sdk import start_transaction
+from sentry_sdk.integrations.openai import (
+    OpenAIIntegration,
+    COMPLETION_TOKENS_USED,
+    PROMPT_TOKENS_USED,
+    TOTAL_TOKENS_USED,
+)
+
+from unittest import mock  # python 3.3 and above
+
+
+EXAMPLE_CHAT_COMPLETION = ChatCompletion(
+    id="chat-id",
+    choices=[
+        Choice(
+            index=0,
+            finish_reason="stop",
+            message=ChatCompletionMessage(
+                role="assistant", content="the model response"
+            ),
+        )
+    ],
+    created=10000000,
+    model="model-id",
+    object="chat.completion",
+    usage=CompletionUsage(
+        completion_tokens=10,
+        prompt_tokens=20,
+        total_tokens=30,
+    ),
+)
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [(True, True), (True, False), (False, True), (False, False)],
+)
+def test_nonstreaming_chat_completion(
+    sentry_init, capture_events, send_default_pii, include_prompts
+):
+    sentry_init(
+        integrations=[OpenAIIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    client = OpenAI(api_key="z")
+    client.chat.completions._post = mock.Mock(return_value=EXAMPLE_CHAT_COMPLETION)
+
+    with start_transaction(name="openai tx"):
+        response = (
+            client.chat.completions.create(
+                model="some-model", messages=[{"role": "system", "content": "hello"}]
+            )
+            .choices[0]
+            .message.content
+        )
+
+    assert response == "the model response"
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "ai.chat_completions.create.openai"
+
+    if send_default_pii and include_prompts:
+        assert "hello" in span["data"]["ai.input_messages"][0]["content"]
+        assert "the model response" in span["data"]["ai.responses"][0]
+    else:
+        assert "ai.input_messages" not in span["data"]
+        assert "ai.responses" not in span["data"]
+
+    assert span["data"][COMPLETION_TOKENS_USED] == 10
+    assert span["data"][PROMPT_TOKENS_USED] == 20
+    assert span["data"][TOTAL_TOKENS_USED] == 30
+
+
+# noinspection PyTypeChecker
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [(True, True), (True, False), (False, True), (False, False)],
+)
+def test_streaming_chat_completion(
+    sentry_init, capture_events, send_default_pii, include_prompts
+):
+    sentry_init(
+        integrations=[OpenAIIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    client = OpenAI(api_key="z")
+    returned_stream = Stream(cast_to=None, response=None, client=None)
+    returned_stream._iterator = [
+        ChatCompletionChunk(
+            id="1",
+            choices=[
+                DeltaChoice(
+                    index=0, delta=ChoiceDelta(content="hel"), finish_reason=None
+                )
+            ],
+            created=100000,
+            model="model-id",
+            object="chat.completion.chunk",
+        ),
+        ChatCompletionChunk(
+            id="1",
+            choices=[
+                DeltaChoice(
+                    index=1, delta=ChoiceDelta(content="lo "), finish_reason=None
+                )
+            ],
+            created=100000,
+            model="model-id",
+            object="chat.completion.chunk",
+        ),
+        ChatCompletionChunk(
+            id="1",
+            choices=[
+                DeltaChoice(
+                    index=2, delta=ChoiceDelta(content="world"), finish_reason="stop"
+                )
+            ],
+            created=100000,
+            model="model-id",
+            object="chat.completion.chunk",
+        ),
+    ]
+
+    client.chat.completions._post = mock.Mock(return_value=returned_stream)
+    with start_transaction(name="openai tx"):
+        response_stream = client.chat.completions.create(
+            model="some-model", messages=[{"role": "system", "content": "hello"}]
+        )
+        response_string = "".join(
+            map(lambda x: x.choices[0].delta.content, response_stream)
+        )
+    assert response_string == "hello world"
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "ai.chat_completions.create.openai"
+
+    if send_default_pii and include_prompts:
+        assert "hello" in span["data"]["ai.input_messages"][0]["content"]
+        assert "hello world" in span["data"]["ai.responses"][0]
+    else:
+        assert "ai.input_messages" not in span["data"]
+        assert "ai.responses" not in span["data"]
+
+    try:
+        import tiktoken  # type: ignore # noqa # pylint: disable=unused-import
+
+        assert span["data"][COMPLETION_TOKENS_USED] == 2
+        assert span["data"][PROMPT_TOKENS_USED] == 1
+        assert span["data"][TOTAL_TOKENS_USED] == 3
+    except ImportError:
+        pass  # if tiktoken is not installed, we can't guarantee token usage will be calculated properly
+
+
+def test_bad_chat_completion(sentry_init, capture_events):
+    sentry_init(integrations=[OpenAIIntegration()], traces_sample_rate=1.0)
+    events = capture_events()
+
+    client = OpenAI(api_key="z")
+    client.chat.completions._post = mock.Mock(
+        side_effect=OpenAIError("API rate limit reached")
+    )
+    with pytest.raises(OpenAIError):
+        client.chat.completions.create(
+            model="some-model", messages=[{"role": "system", "content": "hello"}]
+        )
+
+    (event,) = events
+    assert event["level"] == "error"
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [(True, True), (True, False), (False, True), (False, False)],
+)
+def test_embeddings_create(
+    sentry_init, capture_events, send_default_pii, include_prompts
+):
+    sentry_init(
+        integrations=[OpenAIIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+
+    client = OpenAI(api_key="z")
+
+    returned_embedding = CreateEmbeddingResponse(
+        data=[Embedding(object="embedding", index=0, embedding=[1.0, 2.0, 3.0])],
+        model="some-model",
+        object="list",
+        usage=EmbeddingTokenUsage(
+            prompt_tokens=20,
+            total_tokens=30,
+        ),
+    )
+
+    client.embeddings._post = mock.Mock(return_value=returned_embedding)
+    with start_transaction(name="openai tx"):
+        response = client.embeddings.create(
+            input="hello", model="text-embedding-3-large"
+        )
+
+    assert len(response.data[0].embedding) == 3
+
+    tx = events[0]
+    assert tx["type"] == "transaction"
+    span = tx["spans"][0]
+    assert span["op"] == "ai.embeddings.create.openai"
+    if send_default_pii and include_prompts:
+        assert "hello" in span["data"]["ai.input_messages"][0]
+    else:
+        assert "ai.input_messages" not in span["data"]
+
+    assert span["data"][PROMPT_TOKENS_USED] == 20
+    assert span["data"][TOTAL_TOKENS_USED] == 30
diff --git a/tox.ini b/tox.ini
index a23251f186..1e7ba06a00 100644
--- a/tox.ini
+++ b/tox.ini
@@ -146,6 +146,11 @@ envlist =
     {py3.5,py3.11,py3.12}-loguru-v{0.5}
     {py3.5,py3.11,py3.12}-loguru-latest
 
+    # OpenAI
+    {py3.9,py3.11,py3.12}-openai-v1
+    {py3.9,py3.11,py3.12}-openai-latest
+    {py3.9,py3.11,py3.12}-openai-notiktoken
+
     # OpenTelemetry (OTel)
     {py3.7,py3.9,py3.11,py3.12}-opentelemetry
 
@@ -439,6 +444,13 @@ deps =
     loguru-v0.5: loguru~=0.5.0
     loguru-latest: loguru
 
+    # OpenAI
+    openai-v1: openai~=1.0.0
+    openai-v1: tiktoken~=0.6.0
+    openai-latest: openai
+    openai-latest: tiktoken~=0.6.0
+    openai-notiktoken: openai
+
     # OpenTelemetry (OTel)
     opentelemetry: opentelemetry-distro
 
@@ -597,6 +609,7 @@ setenv =
     httpx: TESTPATH=tests/integrations/httpx
     huey: TESTPATH=tests/integrations/huey
     loguru: TESTPATH=tests/integrations/loguru
+    openai: TESTPATH=tests/integrations/openai
     opentelemetry: TESTPATH=tests/integrations/opentelemetry
     pure_eval: TESTPATH=tests/integrations/pure_eval
     pymongo: TESTPATH=tests/integrations/pymongo