add test for text output

examples/team_recommender/tests/example_0_text_output/test_good_fit_for_project.py

@@ -0,0 +1,38 @@
+from tests.settings import ROOT_DIR
+from openai import OpenAI
+
+
+def test_response_shows_developer_names():
+    client = OpenAI()
+    assert client is not None
+
+    system_prompt = f"""
+        You will get a description of a project, and your task is to tell me the best developers from the given list for the project
+         based on their skills.
+        Today's date is April 15th, 2025.
+        Pick only developers who are available after the project start date. Pick people with higher skill levels first.
+
+        Here is the skills data:
+        Sam Thomas - Objective-C
+        Drew Anderson - Swift, on vacation June 1st - June 10th
+        Joe Smith - Android
+        Robert Sanders - React Native
+        """
+
+    project_description = """
+        This is a mobile iOS project for a telecom company. The project starts June 3rd.
+        It will find exciting moments from sports highlights videos. The app should only work on iPhone, not iPad.
+        The tech stack is iOS Native.
+        """
+    completion = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": project_description},
+        ],
+    )
+    response = completion.choices[0].message.content
+    print(response)
+    assert "Sam Thomas" in response
+    for name in ["Drew Anderson", "Joe Smith", "Robert Sanders"]:
+        assert name not in response

examples/team_recommender/tests/example_1_unit/test_allocations_unit.py

@@ -34,13 +34,13 @@ def test_allocations():
         It will find exciting moments from sports highlights videos.
         """
     completion = client.chat.completions.create(
-        model="gpt-4o",
+        model="gpt-4-turbo",
         messages=[
             {"role": "system", "content": system_prompt},
             {"role": "user", "content": project_description},
         ],
         response_format={"type": "json_object"},
     )
     response = completion.choices[0].message.content
-    person_with_relevant_skill_was_selected = any(name in response for name in acceptable_people)
-    assert person_with_relevant_skill_was_selected
+    person_with_relevant_skill_was_selected = all(name in acceptable_people for name in response)
+    assert person_with_relevant_skill_was_selected, response