test: reduce code redundancy in openai based tests

src/exchange/providers/ollama.py

@@ -37,7 +37,10 @@ def from_env(cls: Type["OllamaProvider"]) -> "OllamaProvider":
             base_url=url,
             timeout=httpx.Timeout(60 * 10),
         )
-        # from_env is expected to fail if provider is not available
-        # so we run a quick test that the endpoint is running
-        client.get("")
+        # from_env is expected to fail if required ENV variables are not
+        # available. Since this provider can run with defaults, we substitute
+        # a health check to verify the endpoint is running.
+        client.get("/")
+        # The OpenAI API is defined after "v1/", so we need to join it here.
+        client.base_url = client.base_url.join("v1/")
         return cls(client)

src/exchange/providers/openai.py

@@ -43,7 +43,7 @@ def from_env(cls: Type["OpenAiProvider"]) -> "OpenAiProvider":
                 "Failed to get OPENAI_API_KEY from the environment, see https://platform.openai.com/docs/api-reference/api-keys"
             )
         client = httpx.Client(
-            base_url=url,
+            base_url=url + "v1/",
             auth=("Bearer", key),
             timeout=httpx.Timeout(60 * 10),
         )
@@ -93,5 +93,9 @@ def complete(
 
     @retry_procedure
     def _post(self, payload: dict) -> dict:
-        response = self.client.post("v1/chat/completions", json=payload)
+        # Note: While OpenAI and Ollama mount the API under "v1", this is
+        # conventional and not a strict requirement. For example, Azure OpenAI
+        # mounts the API under the deployment name, and "v1" is not in the URL.
+        # See https://github.com/openai/openai-openapi/blob/master/openapi.yaml
+        response = self.client.post("chat/completions", json=payload)
         return raise_for_status(response).json()

tests/providers/openai/conftest.py

@@ -1,22 +1,25 @@
 import os
+from typing import Type, Tuple
+
 import pytest
 
-OPENAI_MODEL = "gpt-4o-mini"
+from exchange import Message
+from exchange.providers import Usage, Provider
+
 OPENAI_API_KEY = "test_openai_api_key"
 OPENAI_ORG_ID = "test_openai_org_key"
 OPENAI_PROJECT_ID = "test_openai_project_id"
 
 
 @pytest.fixture
-def default_openai_api_key(monkeypatch):
+def default_openai_env(monkeypatch):
     """
-    This fixture avoids the error OpenAiProvider.from_env() raises when the
-    OPENAI_API_KEY is not set in the environment.
+    This fixture prevents OpenAIProvider.from_env() from erring on missing
+    environment variables.
 
     When running VCR tests for the first time or after deleting a cassette
-    recording, a real OPENAI_API_KEY must be passed as an environment variable,
-    so real responses can be fetched. Subsequent runs use the recorded data, so
-    don't need a real key.
+    recording, set required environment variables, so that real requests don't
+    fail. Subsequent runs use the recorded data, so don't them.
     """
     if "OPENAI_API_KEY" not in os.environ:
         monkeypatch.setenv("OPENAI_API_KEY", OPENAI_API_KEY)
@@ -50,3 +53,10 @@ def scrub_response_headers(response):
     response["headers"]["openai-organization"] = OPENAI_ORG_ID
     response["headers"]["Set-Cookie"] = "test_set_cookie"
     return response
+
+
+def complete(provider_cls: Type[Provider], model: str) -> Tuple[Message, Usage]:
+    provider = provider_cls.from_env()
+    system = "You are a helpful assistant."
+    messages = [Message.user("Hello")]
+    return provider.complete(model=model, system=system, messages=messages, tools=None)

tests/providers/openai/test_ollama.py

@@ -1,33 +1,25 @@
-from typing import Tuple
-
 import os
+
 import pytest
 
 from exchange import Text
-from exchange.message import Message
-from exchange.providers.base import Usage
 from exchange.providers.ollama import OllamaProvider, OLLAMA_MODEL
+from .conftest import complete
+
+OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", OLLAMA_MODEL)
 
 
 @pytest.mark.vcr()
-def test_ollama_completion(default_openai_api_key):
-    reply_message, reply_usage = ollama_complete()
+def test_ollama_complete():
+    reply_message, reply_usage = complete(OllamaProvider, OLLAMA_MODEL)
 
     assert reply_message.content == [Text(text="Hello! I'm here to help. How can I assist you today? Let's chat. 😊")]
     assert reply_usage.total_tokens == 33
 
 
 @pytest.mark.integration
-def test_ollama_completion_integration():
-    reply = ollama_complete()
+def test_ollama_complete_integration():
+    reply = complete(OllamaProvider, OLLAMA_MODEL)
 
     assert reply[0].content is not None
     print("Completion content from OpenAI:", reply[0].content)
-
-
-def ollama_complete() -> Tuple[Message, Usage]:
-    provider = OllamaProvider.from_env()
-    model = os.getenv("OLLAMA_MODEL", OLLAMA_MODEL)
-    system = "You are a helpful assistant."
-    messages = [Message.user("Hello")]
-    return provider.complete(model=model, system=system, messages=messages, tools=None)

tests/providers/openai/test_openai.py

@@ -1,39 +1,25 @@
-from typing import Tuple
-
 import os
+
 import pytest
 
 from exchange import Text
-from exchange.message import Message
-from exchange.providers.base import Usage
 from exchange.providers.openai import OpenAiProvider
-from .conftest import OPENAI_MODEL, OPENAI_API_KEY
+from .conftest import complete
 
+OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o-mini")
 
-@pytest.mark.vcr()
-def test_openai_completion(monkeypatch):
-    # When running VCR tests the first time, it needs OPENAI_API_KEY to call
-    # the real service. Afterward, it is not needed as VCR mocks the service.
-    if "OPENAI_API_KEY" not in os.environ:
-        monkeypatch.setenv("OPENAI_API_KEY", OPENAI_API_KEY)
 
-    reply_message, reply_usage = openai_complete()
+@pytest.mark.vcr()
+def test_openai_complete(default_openai_env):
+    reply_message, reply_usage = complete(OpenAiProvider, OPENAI_MODEL)
 
     assert reply_message.content == [Text(text="Hello! How can I assist you today?")]
     assert reply_usage.total_tokens == 27
 
 
 @pytest.mark.integration
-def test_openai_completion_integration():
-    reply = openai_complete()
+def test_openai_complete_integration():
+    reply = complete(OpenAiProvider, OPENAI_MODEL)
 
     assert reply[0].content is not None
-    print("Completion content from OpenAI:", reply[0].content)
-
-
-def openai_complete() -> Tuple[Message, Usage]:
-    provider = OpenAiProvider.from_env()
-    model = OPENAI_MODEL
-    system = "You are a helpful assistant."
-    messages = [Message.user("Hello")]
-    return provider.complete(model=model, system=system, messages=messages, tools=None)
+    print("Complete content from OpenAI:", reply[0].content)

tests/test_integration.py

@@ -12,13 +12,13 @@
 cases = [
     # Set seed and temperature for more determinism, to avoid flakes
     (get_provider("ollama"), os.getenv("OLLAMA_MODEL", OLLAMA_MODEL), dict(seed=3, temperature=0.1)),
-    (get_provider("openai"), "gpt-4o-mini", dict()),
+    (get_provider("openai"), os.getenv("OPENAI_MODEL", "gpt-4o-mini"), dict()),
     (get_provider("databricks"), "databricks-meta-llama-3-70b-instruct", dict()),
     (get_provider("bedrock"), "anthropic.claude-3-5-sonnet-20240620-v1:0", dict()),
 ]
 
 
-@pytest.mark.integration  # skipped in CI/CD
+@pytest.mark.integration
 @pytest.mark.parametrize("provider,model,kwargs", cases)
 def test_simple(provider, model, kwargs):
     provider = provider.from_env()
@@ -39,7 +39,7 @@ def test_simple(provider, model, kwargs):
     assert "gandalf" in response.text.lower()
 
 
-@pytest.mark.integration  # skipped in CI/CD
+@pytest.mark.integration
 @pytest.mark.parametrize("provider,model,kwargs", cases)
 def test_tools(provider, model, kwargs, tmp_path):
     provider = provider.from_env()

tests/test_integration_vision.py

@@ -1,3 +1,5 @@
+import os
+
 import pytest
 from exchange.content import ToolResult, ToolUse
 from exchange.exchange import Exchange
@@ -6,7 +8,7 @@
 from exchange.providers import get_provider
 
 cases = [
-    (get_provider("openai"), "gpt-4o-mini"),
+    (get_provider("openai"), os.getenv("OPENAI_MODEL", "gpt-4o-mini")),
 ]