feat: allow users to configure a base_url for the vectorizer OpenAI e…

…mbedder

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

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:

projects/pgai/pgai/vectorizer/embeddings.py

@@ -165,6 +165,26 @@ 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
+
+    def set_base_url(self, base_url: str | None):
+        """
+        Sets the base URL from the provided secrets.
+
+        Args:
+            base_url (str | None): The base URL to be set.
+        """
+        self.base_url = base_url
+
+
 class ApiKeyMixin:
     """
     A mixin class that provides functionality for managing API keys.

projects/pgai/tests/vectorizer/cassettes/openai-character_text_splitter-chunk_value-items=1-batch_size=1.yaml

@@ -229,4 +229,234 @@ interactions:
     status:
       code: 200
       message: OK
+- 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:
+      - '62'
+      content-type:
+      - application/json
+      host:
+      - example.com:8000
+      user-agent:
+      - AsyncOpenAI/Python 1.42.0
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - async:asyncio
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.42.0
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.12.4
+    method: POST
+    uri: http://example.com:8000/embeddings
+  response:
+    body:
+      string: !!binary |
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 version: 1

projects/pgai/tests/vectorizer/test_vectorizer_cli.py

@@ -117,11 +117,17 @@ def source_table(
     return table_name
 
 
+@pytest.fixture
+def openai_custom_base_url(request: pytest.FixtureRequest) -> str | None:
+    return request.param if hasattr(request, "param") else None
+
+
 @pytest.fixture
 def configured_openai_vectorizer_id(
     source_table: str,
     cli_db: tuple[TestDatabase, Connection],
     test_params: tuple[int, int, int, str, str],
+    openai_custom_base_url: str | None,
 ) -> int:
     """Creates and configures a vectorizer for testing"""
     _, concurrency, batch_size, chunking, formatting = test_params
@@ -136,6 +142,10 @@ def configured_openai_vectorizer_id(
                     'text-embedding-ada-002',
                     1536,
                     api_key_name => 'OPENAI_API_KEY'
+                    {
+                        f", base_url => '{openai_custom_base_url}'"
+                        if openai_custom_base_url is not None else ""
+                    }
                 ),
                 chunking => ai.{chunking},
                 formatting => ai.{formatting},
@@ -235,23 +245,41 @@ def test_params(request: pytest.FixtureRequest) -> tuple[int, int, int, str, str
 
 class TestWithOpenAiVectorizer:
     @pytest.mark.parametrize(
-        "test_params",
+        "test_params,openai_custom_base_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
+                "http://example.com: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_custom_base_url"],
     )
     def test_process_vectorizer(
         self,