diff --git a/docs/vectorizer-api-reference.md b/docs/vectorizer-api-reference.md
index 78ef54e1c..e01edcbe1 100644
--- a/docs/vectorizer-api-reference.md
+++ b/docs/vectorizer-api-reference.md
@@ -298,6 +298,7 @@ The function takes several parameters to customize the OpenAI embedding configur
 | dimensions   | int  | -                | ✔        | Define the number of dimensions for the embedding vectors. This should match the output dimensions of the chosen model.                                                                                                                                                                   |
 | chat_user    | text | -                | ✖        | The identifier for the user making the API call. This can be useful for tracking API usage or for OpenAI's monitoring purposes.                                                                                                                                                           |
 | api_key_name | text | `OPENAI_API_KEY` | ✖        | Set [the name of the environment variable that contains the OpenAI API key][openai-use-env-var]. This allows for flexible API key management without hardcoding keys in the database. On Timescale Cloud, you should set this to the name of the secret that contains the OpenAI API key. |
+| base_url     | text | -                | ✖        | Set the base_url of the OpenAI API. Note: no default configured here to allow configuration of the vectorizer worker through `OPENAI_BASE_URL` env var.                                                                                                                                   | 
 #### Returns
 
 A JSON configuration object that you can use in [ai.create_vectorizer](#create-vectorizers).
diff --git a/projects/extension/sql/idempotent/008-embedding.sql b/projects/extension/sql/idempotent/008-embedding.sql
index e03e21ed5..518e92eef 100644
--- a/projects/extension/sql/idempotent/008-embedding.sql
+++ b/projects/extension/sql/idempotent/008-embedding.sql
@@ -6,6 +6,7 @@ create or replace function ai.embedding_openai
 , dimensions pg_catalog.int4
 , chat_user pg_catalog.text default null
 , api_key_name pg_catalog.text default 'OPENAI_API_KEY'
+, base_url text default null
 ) returns pg_catalog.jsonb
 as $func$
     select json_object
@@ -15,6 +16,7 @@ as $func$
     , 'dimensions': dimensions
     , 'user': chat_user
     , 'api_key_name': api_key_name
+    , 'base_url': base_url
     absent on null
     )
 $func$ language sql immutable security invoker
diff --git a/projects/extension/sql/incremental/010-drop-embedding-openai-outdated-function.sql b/projects/extension/sql/incremental/010-drop-embedding-openai-outdated-function.sql
new file mode 100644
index 000000000..ddb39cb55
--- /dev/null
+++ b/projects/extension/sql/incremental/010-drop-embedding-openai-outdated-function.sql
@@ -0,0 +1,3 @@
+
+-- dropping in favour of the new signature (adding base_url param)
+drop function if exists ai.embedding_openai(text,integer,text,text);
\ No newline at end of file
diff --git a/projects/extension/tests/contents/output16.expected b/projects/extension/tests/contents/output16.expected
index ef557f1bc..bccda7779 100644
--- a/projects/extension/tests/contents/output16.expected
+++ b/projects/extension/tests/contents/output16.expected
@@ -21,7 +21,7 @@ CREATE EXTENSION
  function ai.disable_vectorizer_schedule(integer)
  function ai.drop_vectorizer(integer,boolean)
  function ai.embedding_ollama(text,integer,text,jsonb,text)
- function ai.embedding_openai(text,integer,text,text)
+ function ai.embedding_openai(text,integer,text,text,text)
  function ai.embedding_voyageai(text,integer,text,text)
  function ai.enable_vectorizer_schedule(integer)
  function ai.execute_vectorizer(integer)
diff --git a/projects/extension/tests/contents/output17.expected b/projects/extension/tests/contents/output17.expected
index 35c69d53b..bbb38a833 100644
--- a/projects/extension/tests/contents/output17.expected
+++ b/projects/extension/tests/contents/output17.expected
@@ -21,7 +21,7 @@ CREATE EXTENSION
  function ai.disable_vectorizer_schedule(integer)
  function ai.drop_vectorizer(integer,boolean)
  function ai.embedding_ollama(text,integer,text,jsonb,text)
- function ai.embedding_openai(text,integer,text,text)
+ function ai.embedding_openai(text,integer,text,text,text)
  function ai.embedding_voyageai(text,integer,text,text)
  function ai.enable_vectorizer_schedule(integer)
  function ai.execute_vectorizer(integer)
diff --git a/projects/extension/tests/privileges/function.expected b/projects/extension/tests/privileges/function.expected
index 3b19b8a8a..99b91dcfc 100644
--- a/projects/extension/tests/privileges/function.expected
+++ b/projects/extension/tests/privileges/function.expected
@@ -168,10 +168,10 @@
  f       | bob   | execute   | no      | ai     | embedding_ollama(model text, dimensions integer, base_url text, options jsonb, keep_alive text)
  f       | fred  | execute   | no      | ai     | embedding_ollama(model text, dimensions integer, base_url text, options jsonb, keep_alive text)
  f       | jill  | execute   | YES     | ai     | embedding_ollama(model text, dimensions integer, base_url text, options jsonb, keep_alive text)
- f       | alice | execute   | YES     | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text)
- f       | bob   | execute   | no      | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text)
- f       | fred  | execute   | no      | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text)
- f       | jill  | execute   | YES     | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text)
+ f       | alice | execute   | YES     | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text, base_url text)
+ f       | bob   | execute   | no      | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text, base_url text)
+ f       | fred  | execute   | no      | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text, base_url text)
+ f       | jill  | execute   | YES     | ai     | embedding_openai(model text, dimensions integer, chat_user text, api_key_name text, base_url text)
  f       | alice | execute   | YES     | ai     | embedding_voyageai(model text, dimensions integer, input_type text, api_key_name text)
  f       | bob   | execute   | no      | ai     | embedding_voyageai(model text, dimensions integer, input_type text, api_key_name text)
  f       | fred  | execute   | no      | ai     | embedding_voyageai(model text, dimensions integer, input_type text, api_key_name text)
diff --git a/projects/pgai/pgai/vectorizer/embedders/ollama.py b/projects/pgai/pgai/vectorizer/embedders/ollama.py
index 877e66296..f57744c31 100644
--- a/projects/pgai/pgai/vectorizer/embedders/ollama.py
+++ b/projects/pgai/pgai/vectorizer/embedders/ollama.py
@@ -9,6 +9,7 @@
 from typing_extensions import TypedDict, override
 
 from ..embeddings import (
+    BaseURLMixin,
     BatchApiCaller,
     Embedder,
     EmbeddingResponse,
@@ -58,7 +59,7 @@ class OllamaOptions(TypedDict, total=False):
     stop: Sequence[str]
 
 
-class Ollama(BaseModel, Embedder):
+class Ollama(BaseModel, BaseURLMixin, Embedder):
     """
     Embedder that uses Ollama to embed documents into vector representations.
 
@@ -66,14 +67,12 @@ class Ollama(BaseModel, Embedder):
         implementation (Literal["ollama"]): The literal identifier for this
             implementation.
         model (str): The name of the Ollama model used for embeddings.
-        base_url (str): The base url used to access the Ollama API.
         options (dict): Additional ollama-specific runtime options
         keep_alive (str): How long to keep the model loaded after the request
     """
 
     implementation: Literal["ollama"]
     model: str
-    base_url: str | None = None
     options: OllamaOptions | None = None
     keep_alive: str | None = None  # this is only `str` because of the SQL API
 
diff --git a/projects/pgai/pgai/vectorizer/embedders/openai.py b/projects/pgai/pgai/vectorizer/embedders/openai.py
index 7c4e9aa5c..ec5383ed0 100644
--- a/projects/pgai/pgai/vectorizer/embedders/openai.py
+++ b/projects/pgai/pgai/vectorizer/embedders/openai.py
@@ -11,6 +11,7 @@
 
 from ..embeddings import (
     ApiKeyMixin,
+    BaseURLMixin,
     BatchApiCaller,
     ChunkEmbeddingError,
     Embedder,
@@ -29,7 +30,7 @@
 )
 
 
-class OpenAI(ApiKeyMixin, BaseModel, Embedder):
+class OpenAI(ApiKeyMixin, BaseURLMixin, BaseModel, Embedder):
     """
     Embedder that uses OpenAI's API to embed documents into vector representations.
 
@@ -60,7 +61,9 @@ def _openai_user(self) -> str | openai.NotGiven:
 
     @cached_property
     def _embedder(self) -> resources.AsyncEmbeddings:
-        return openai.AsyncOpenAI(api_key=self._api_key, max_retries=3).embeddings
+        return openai.AsyncOpenAI(
+            base_url=self.base_url, api_key=self._api_key, max_retries=3
+        ).embeddings
 
     @override
     def _max_chunks_per_batch(self) -> int:
diff --git a/projects/pgai/pgai/vectorizer/embeddings.py b/projects/pgai/pgai/vectorizer/embeddings.py
index a40f91f02..89ae384df 100644
--- a/projects/pgai/pgai/vectorizer/embeddings.py
+++ b/projects/pgai/pgai/vectorizer/embeddings.py
@@ -165,6 +165,17 @@ async def setup(self) -> None:  # noqa: B027 empty on purpose
         """
 
 
+class BaseURLMixin:
+    """
+    A mixin class that provides functionality for managing base URLs.
+
+    Attributes:
+        base_url (str | None): The base URL for the API.
+    """
+
+    base_url: str | None = None
+
+
 class ApiKeyMixin:
     """
     A mixin class that provides functionality for managing API keys.
diff --git a/projects/pgai/pyproject.toml b/projects/pgai/pyproject.toml
index 2851c44f3..455e8d24a 100644
--- a/projects/pgai/pyproject.toml
+++ b/projects/pgai/pyproject.toml
@@ -118,4 +118,5 @@ dev-dependencies = [
     "testcontainers==4.8.1",
     "build==1.2.2.post1",
     "twine==5.1.1",
+    "mitmproxy>=11.0.2",
 ]
diff --git a/projects/pgai/tests/vectorizer/cassettes/openai-character_text_splitter-chunk_value-items=1-batch_size=1-custom_base_url=False.yaml b/projects/pgai/tests/vectorizer/cassettes/openai-character_text_splitter-chunk_value-items=1-batch_size=1-custom_base_url=False.yaml
new file mode 100644
index 000000000..7b83e73da
--- /dev/null
+++ b/projects/pgai/tests/vectorizer/cassettes/openai-character_text_splitter-chunk_value-items=1-batch_size=1-custom_base_url=False.yaml
@@ -0,0 +1,231 @@
+interactions:
+- request:
+    body: '{"input": [[2252, 62, 16]], "model": "text-embedding-ada-002", "encoding_format":
+      "float"}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate
+      connection:
+      - keep-alive
+      content-length:
+      - '90'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - AsyncOpenAI/Python 1.53.0
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - async:asyncio
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.53.0
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.10.15
+    method: POST
+    uri: https://api.openai.com/v1/embeddings
+  response:
+    body:
+      string: !!binary |
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diff --git a/projects/pgai/tests/vectorizer/conftest.py b/projects/pgai/tests/vectorizer/conftest.py
index 23b593535..6459f8e56 100644
--- a/projects/pgai/tests/vectorizer/conftest.py
+++ b/projects/pgai/tests/vectorizer/conftest.py
@@ -1,12 +1,18 @@
+import asyncio
 import os
+import threading
 from collections.abc import Callable, Generator, Mapping
 from pathlib import Path
 from typing import Any
+from urllib.parse import urlparse
 
 import pytest
 import tiktoken
 import vcr  # type:ignore
 from dotenv import load_dotenv
+from mitmproxy import options
+from mitmproxy.http import HTTPFlow
+from mitmproxy.tools.dump import DumpMaster
 from testcontainers.core.image import DockerImage  # type:ignore
 from testcontainers.postgres import PostgresContainer  # type:ignore
 
@@ -113,3 +119,49 @@ def postgres_container(
     load_openai_key: bool = params.get("load_openai_key", True)  # type: ignore
 
     return postgres_container_manager(load_openai_key=load_openai_key)  # type: ignore
+
+
+class ReverseProxyAddon:
+    def __init__(self, target_url: str):
+        self.target = urlparse(target_url)
+
+    def request(self, flow: HTTPFlow):
+        flow.request.host = str(self.target.hostname)
+        flow.request.path = self.target.path + flow.request.path
+        flow.request.scheme = "https"
+        flow.request.port = 443
+
+
+def run_reverse_proxy(
+    target_host: str, listen_port: int = 8000, listen_host: str = "localhost"
+):
+    async def start_proxy():
+        opts = options.Options(listen_host=listen_host, listen_port=listen_port)
+        master = DumpMaster(opts)
+        master.addons.add(ReverseProxyAddon(target_host))  # type:ignore
+
+        try:
+            await master.run()
+        finally:
+            master.shutdown()
+
+    # mitmproxy relies on asyncio for its event loop
+    def run_event_loop():
+        asyncio.run(start_proxy())
+
+    proxy_thread = threading.Thread(target=run_event_loop, daemon=True)
+    proxy_thread.start()
+
+
+@pytest.fixture(scope="function")
+def openai_proxy_url(request: pytest.FixtureRequest):
+    if not hasattr(request, "param") or request.param is None:
+        # a valid url is required in order to start the openai proxy fixture
+        return None
+
+    port = request.param
+    run_reverse_proxy("https://api.openai.com/v1", port)
+
+    proxy_url = f"http://localhost:{port}"
+    print(f"OpenAI API proxy running on {proxy_url}")
+    return f"http://localhost:{port}"
diff --git a/projects/pgai/tests/vectorizer/test_vectorizer_cli.py b/projects/pgai/tests/vectorizer/test_vectorizer_cli.py
index 04f97154c..440103ac1 100644
--- a/projects/pgai/tests/vectorizer/test_vectorizer_cli.py
+++ b/projects/pgai/tests/vectorizer/test_vectorizer_cli.py
@@ -122,6 +122,7 @@ def configured_openai_vectorizer_id(
     source_table: str,
     cli_db: tuple[TestDatabase, Connection],
     test_params: tuple[int, int, int, str, str],
+    openai_proxy_url: str | None,
 ) -> int:
     """Creates and configures a vectorizer for testing"""
     _, concurrency, batch_size, chunking, formatting = test_params
@@ -136,6 +137,10 @@ def configured_openai_vectorizer_id(
                     'text-embedding-ada-002',
                     1536,
                     api_key_name => 'OPENAI_API_KEY'
+                    {
+                        f", base_url => '{openai_proxy_url}'"
+                        if openai_proxy_url is not None else ""
+                    }
                 ),
                 chunking => ai.{chunking},
                 formatting => ai.{formatting},
@@ -235,23 +240,41 @@ def test_params(request: pytest.FixtureRequest) -> tuple[int, int, int, str, str
 
 class TestWithOpenAiVectorizer:
     @pytest.mark.parametrize(
-        "test_params",
+        "test_params,openai_proxy_url",
         [
             (
-                1,
-                1,
-                1,
-                "chunking_character_text_splitter('content')",
-                "formatting_python_template('$chunk')",
+                (
+                    1,
+                    1,
+                    1,
+                    "chunking_character_text_splitter('content')",
+                    "formatting_python_template('$chunk')",
+                ),
+                None,  # No base_url is set. Use default (https://api.openai.com/v1)
             ),
             (
-                4,
-                2,
-                2,
-                "chunking_character_text_splitter('content')",
-                "formatting_python_template('$chunk')",
+                (
+                    1,
+                    1,
+                    1,
+                    "chunking_character_text_splitter('content')",
+                    "formatting_python_template('$chunk')",
+                ),
+                # Same test as before but with a custom base_url
+                8000,
+            ),
+            (
+                (
+                    4,
+                    2,
+                    2,
+                    "chunking_character_text_splitter('content')",
+                    "formatting_python_template('$chunk')",
+                ),
+                None,  # No base_url is set. Use default (https://api.openai.com/v1)
             ),
         ],
+        indirect=["openai_proxy_url"],
     )
     def test_process_vectorizer(
         self,
@@ -260,6 +283,7 @@ def test_process_vectorizer(
         configured_openai_vectorizer_id: int,
         vcr_: Any,
         test_params: tuple[int, int, int, str, str],
+        openai_proxy_url: str | None,
     ):
         """Test successful processing of vectorizer tasks"""
         num_items, concurrency, batch_size, _, _ = test_params
@@ -280,9 +304,11 @@ def test_process_vectorizer(
         # When running the worker with cassette matching original test params
         cassette = (
             f"openai-character_text_splitter-chunk_value-"
-            f"items={num_items}-batch_size={batch_size}.yaml"
+            f"items={num_items}-batch_size={batch_size}-"
+            f"custom_base_url={openai_proxy_url is not None}.yaml"
         )
         logging.getLogger("vcr").setLevel(logging.DEBUG)
+
         with vcr_.use_cassette(cassette):
             result = CliRunner().invoke(
                 vectorizer_worker,
diff --git a/projects/pgai/uv.lock b/projects/pgai/uv.lock
index d9a17daf4..87f2b1751 100644
--- a/projects/pgai/uv.lock
+++ b/projects/pgai/uv.lock
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 ]
 
+[[package]]
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+version = "1.2.0"
+source = { registry = "https://pypi.org/simple" }
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+
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 version = "1.3.1"
@@ -134,13 +162,25 @@ dependencies = [
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     { name = "sniffio" },
-    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
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