| """Tests for _normalize_chat_content in the API server adapter.""" |
|
|
| from gateway.platforms.api_server import _normalize_chat_content |
|
|
|
|
| class TestNormalizeChatContent: |
| """Content normalization converts array-based content parts to plain text.""" |
|
|
| def test_none_returns_empty_string(self): |
| assert _normalize_chat_content(None) == "" |
|
|
| def test_plain_string_returned_as_is(self): |
| assert _normalize_chat_content("hello world") == "hello world" |
|
|
| def test_empty_string_returned_as_is(self): |
| assert _normalize_chat_content("") == "" |
|
|
| def test_text_content_part(self): |
| content = [{"type": "text", "text": "hello"}] |
| assert _normalize_chat_content(content) == "hello" |
|
|
| def test_input_text_content_part(self): |
| content = [{"type": "input_text", "text": "user input"}] |
| assert _normalize_chat_content(content) == "user input" |
|
|
| def test_output_text_content_part(self): |
| content = [{"type": "output_text", "text": "assistant output"}] |
| assert _normalize_chat_content(content) == "assistant output" |
|
|
| def test_multiple_text_parts_joined_with_newline(self): |
| content = [ |
| {"type": "text", "text": "first"}, |
| {"type": "text", "text": "second"}, |
| ] |
| assert _normalize_chat_content(content) == "first\nsecond" |
|
|
| def test_mixed_string_and_dict_parts(self): |
| content = ["plain string", {"type": "text", "text": "dict part"}] |
| assert _normalize_chat_content(content) == "plain string\ndict part" |
|
|
| def test_image_url_parts_silently_skipped(self): |
| content = [ |
| {"type": "text", "text": "check this:"}, |
| {"type": "image_url", "image_url": {"url": "https://example.com/img.png"}}, |
| ] |
| assert _normalize_chat_content(content) == "check this:" |
|
|
| def test_integer_content_converted(self): |
| assert _normalize_chat_content(42) == "42" |
|
|
| def test_boolean_content_converted(self): |
| assert _normalize_chat_content(True) == "True" |
|
|
| def test_deeply_nested_list_respects_depth_limit(self): |
| """Nesting beyond max_depth returns empty string.""" |
| content = [[[[[[[[[[[["deep"]]]]]]]]]]]] |
| result = _normalize_chat_content(content) |
| |
| assert isinstance(result, str) |
|
|
| def test_large_list_capped(self): |
| """Lists beyond MAX_CONTENT_LIST_SIZE are truncated.""" |
| content = [{"type": "text", "text": f"item{i}"} for i in range(2000)] |
| result = _normalize_chat_content(content) |
| |
| assert result.count("item") <= 1000 |
|
|
| def test_oversized_string_truncated(self): |
| """Strings beyond 64KB are truncated.""" |
| huge = "x" * 100_000 |
| result = _normalize_chat_content(huge) |
| assert len(result) == 65_536 |
|
|
| def test_empty_text_parts_filtered(self): |
| content = [ |
| {"type": "text", "text": ""}, |
| {"type": "text", "text": "actual"}, |
| {"type": "text", "text": ""}, |
| ] |
| assert _normalize_chat_content(content) == "actual" |
|
|
| def test_dict_without_type_skipped(self): |
| content = [{"foo": "bar"}, {"type": "text", "text": "real"}] |
| assert _normalize_chat_content(content) == "real" |
|
|
| def test_empty_list_returns_empty(self): |
| assert _normalize_chat_content([]) == "" |
|
|
