test: use default model in ollama and reduce code redundancy

Signed-off-by: Adrian Cole <[email protected]>

.github/workflows/ci.yaml

@@ -43,11 +43,7 @@ jobs:
     strategy:
       matrix:
         python-version:
-          # Only test the lastest python version.
-          - "3.12"
-        ollama-model:
-          # For quicker CI, use a smaller, tool-capable model than the default.
-          - "qwen2.5:0.5b"
+          - "3.12"  # Only test the latest python version.
 
     steps:
       - uses: actions/checkout@v4
@@ -75,11 +71,11 @@ jobs:
       # Tests use OpenAI which does not have a mechanism to pull models. Run a
       # simple prompt to (pull and) test the model first.
       - name: Test Ollama model
-        run: ollama run $OLLAMA_MODEL hello || cat ollama.log
+        run: |
+          OLLAMA_MODEL=$(uv run python -c "from src.exchange.providers.ollama import OLLAMA_MODEL; print(OLLAMA_MODEL)")
+          ollama run $OLLAMA_MODEL hello || cat ollama.log
         env:
           OLLAMA_MODEL: ${{ matrix.ollama-model }}
 
       - name: Run Ollama tests
         run: uv run pytest tests -m integration -k ollama
-        env:
-          OLLAMA_MODEL: ${{ matrix.ollama-model }}

tests/providers/openai/conftest.py

@@ -1,11 +1,19 @@
 import os
+from typing import Type, Tuple
+
 import pytest
 
-OPENAI_MODEL = "gpt-4o-mini"
+from exchange import Message
+from exchange.providers import Usage, Provider
+from exchange.providers.ollama import OLLAMA_MODEL
+
 OPENAI_API_KEY = "test_openai_api_key"
 OPENAI_ORG_ID = "test_openai_org_key"
 OPENAI_PROJECT_ID = "test_openai_project_id"
 
+OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", OLLAMA_MODEL)
+OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o-mini")
+
 
 @pytest.fixture
 def default_openai_api_key(monkeypatch):
@@ -50,3 +58,10 @@ 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 +1,21 @@
-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 exchange.providers.ollama import OllamaProvider
+from .conftest import complete, OLLAMA_MODEL
 
 
 @pytest.mark.vcr()
-def test_ollama_completion(default_openai_api_key):
-    reply_message, reply_usage = ollama_complete()
+def test_ollama_complete(default_openai_api_key):
+    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 +1,21 @@
-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
 
 
 @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()
+def test_openai_complete(default_openai_api_key):
+    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)