manually write test cases to be exhaustive

Author: alexander-alderman-webb

sentry_sdk/integrations/google_genai/utils.py

@@ -725,6 +725,7 @@ def extract_finish_reasons(
 
 def _transform_system_instruction_one_level(
     system_instructions: "ContentUnionDict",
+    can_be_content: bool,
 ) -> "list[TextPart]":
     text_parts: "list[TextPart]" = []
 
@@ -734,7 +735,7 @@ def _transform_system_instruction_one_level(
     if isinstance(system_instructions, Part) and system_instructions.text:
         return [{"type": "text", "content": system_instructions.text}]
 
-    if isinstance(system_instructions, Content):
+    if can_be_content and isinstance(system_instructions, Content):
         for part in system_instructions.parts or []:
             if part.text:
                 text_parts.append({"type": "text", "content": part.text})
@@ -744,6 +745,7 @@ def _transform_system_instruction_one_level(
         if system_instructions.get("text"):
             return [{"type": "text", "content": system_instructions["text"]}]
 
+    elif can_be_content and isinstance(system_instructions, dict):
         parts = system_instructions.get("parts", [])
         for part in parts:
             if isinstance(part, Part) and part.text:
@@ -763,14 +765,18 @@ def _transform_system_instructions(
     if isinstance(system_instructions, list):
         text_parts = list(
             chain.from_iterable(
-                _transform_system_instruction_one_level(instructions)
+                _transform_system_instruction_one_level(
+                    instructions, can_be_content=False
+                )
                 for instructions in system_instructions
             )
         )
 
         return text_parts
 
-    return _transform_system_instruction_one_level(system_instructions)
+    return _transform_system_instruction_one_level(
+        system_instructions, can_be_content=True
+    )
 
 
 def set_span_data_for_request(

tests/integrations/google_genai/test_google_genai.py

@@ -204,103 +204,32 @@ def test_nonstreaming_generate_content(
     assert invoke_span["data"][SPANDATA.GEN_AI_REQUEST_MAX_TOKENS] == 100
 
 
-# Threatened bot to generate as many cases as possible
 @pytest.mark.parametrize(
     "system_instructions,expected_texts",
     [
-        ("You are a helpful assistant", ["You are a helpful assistant"]),
-        (
-            ["You are a translator", "Translate to French"],
-            ["You are a translator", "Translate to French"],
-        ),
-        (
-            Content(role="user", parts=[Part(text="You are a helpful assistant")]),
-            ["You are a helpful assistant"],
-        ),
-        (
-            Content(
-                role="user",
-                parts=[
-                    Part(text="You are a translator"),
-                    Part(text="Translate to French"),
-                ],
-            ),
-            ["You are a translator", "Translate to French"],
-        ),
-        (
-            {"parts": [{"text": "You are a helpful assistant"}], "role": "user"},
-            ["You are a helpful assistant"],
-        ),
-        (
-            {
-                "parts": [
-                    {"text": "You are a translator"},
-                    {"text": "Translate to French"},
-                ],
-                "role": "user",
-            },
-            ["You are a translator", "Translate to French"],
-        ),
-        (Part(text="You are a helpful assistant"), ["You are a helpful assistant"]),
-        ({"text": "You are a helpful assistant"}, ["You are a helpful assistant"]),
-        (
-            [Part(text="You are a translator"), Part(text="Translate to French")],
-            ["You are a translator", "Translate to French"],
-        ),
-        (
-            [{"text": "You are a translator"}, {"text": "Translate to French"}],
-            ["You are a translator", "Translate to French"],
-        ),
-        (
-            [Part(text="First instruction"), {"text": "Second instruction"}],
-            ["First instruction", "Second instruction"],
-        ),
-        (
-            {
-                "parts": [
-                    Part(text="First instruction"),
-                    {"text": "Second instruction"},
-                ],
-                "role": "user",
-            },
-            ["First instruction", "Second instruction"],
-        ),
         (None, None),
         ("", []),
         ({}, []),
+        (Content(role="system", parts=[]), []),
         ({"parts": []}, []),
-        (Content(role="user", parts=[]), []),
+        ("You are a helpful assistant.", ["You are a helpful assistant."]),
+        (Part(text="You are a helpful assistant."), ["You are a helpful assistant."]),
         (
-            {
-                "parts": [
-                    {"text": "Text part"},
-                    {"file_data": {"file_uri": "gs://bucket/file.pdf"}},
-                ],
-                "role": "user",
-            },
-            ["Text part"],
+            Content(role="system", parts=[Part(text="You are a helpful assistant.")]),
+            ["You are a helpful assistant."],
         ),
+        ({"text": "You are a helpful assistant."}, ["You are a helpful assistant."]),
         (
-            {
-                "parts": [
-                    {"text": "First"},
-                    Part(text="Second"),
-                    {"text": "Third"},
-                ],
-                "role": "user",
-            },
-            ["First", "Second", "Third"],
+            {"parts": [Part(text="You are a helpful assistant.")]},
+            ["You are a helpful assistant."],
         ),
         (
-            {
-                "parts": [
-                    Part(text="First"),
-                    Part(text="Second"),
-                    Part(text="Third"),
-                ],
-            },
-            ["First", "Second", "Third"],
+            {"parts": [{"text": "You are a helpful assistant."}]},
+            ["You are a helpful assistant."],
         ),
+        (["You are a helpful assistant."], ["You are a helpful assistant."]),
+        ([Part(text="You are a helpful assistant.")], ["You are a helpful assistant."]),
+        ([{"text": "You are a helpful assistant."}], ["You are a helpful assistant."]),
     ],
 )
 def test_generate_content_with_system_instruction(