test: add agent test coverage and standardize test suite (#2051)

- Add 104 comprehensive tests for agent system
- Integrate agent tests into CI/CD pipeline
- Standardize tests with @pytest.mark.unit markers
- Fix cross-platform path compatibility
- Clean up unused imports and dependencies

tests/llm/test_openai_llm.py

@@ -1,6 +1,6 @@
 import types
-import pytest
 
+import pytest
 from application.llm.openai import OpenAILLM
 
 
@@ -42,16 +42,16 @@ class FakeChatCompletions:
 
     def create(self, **kwargs):
         self.last_kwargs = kwargs
-        # default non-streaming: return content
         if not kwargs.get("stream"):
-            return FakeChatCompletions._Response(choices=[
-                FakeChatCompletions._Choice(content="hello world")
-            ])
-        # streaming: yield line objects each with choices[0].delta.content
-        return FakeChatCompletions._Response(lines=[
-            FakeChatCompletions._StreamLine(["part1"]),
-            FakeChatCompletions._StreamLine(["part2"]),
-        ])
+            return FakeChatCompletions._Response(
+                choices=[FakeChatCompletions._Choice(content="hello world")]
+            )
+        return FakeChatCompletions._Response(
+            lines=[
+                FakeChatCompletions._StreamLine(["part1"]),
+                FakeChatCompletions._StreamLine(["part2"]),
+            ]
+        )
 
 
 class FakeClient:
@@ -71,16 +71,29 @@ def openai_llm(monkeypatch):
     return llm
 
 
+@pytest.mark.unit
 def test_clean_messages_openai_variants(openai_llm):
     messages = [
         {"role": "system", "content": "sys"},
-        {"role": "model", "content": "asst"}, 
-        {"role": "user", "content": [
-            {"text": "hello"},
-            {"function_call": {"call_id": "c1", "name": "fn", "args": {"a": 1}}},
-            {"function_response": {"call_id": "c1", "name": "fn", "response": {"result": 42}}},
-            {"type": "image_url", "image_url": {"url": "data:image/png;base64,AAA"}},
-        ]},
+        {"role": "model", "content": "asst"},
+        {
+            "role": "user",
+            "content": [
+                {"text": "hello"},
+                {"function_call": {"call_id": "c1", "name": "fn", "args": {"a": 1}}},
+                {
+                    "function_response": {
+                        "call_id": "c1",
+                        "name": "fn",
+                        "response": {"result": 42},
+                    }
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {"url": "data:image/png;base64,AAA"},
+                },
+            ],
+        },
     ]
 
     cleaned = openai_llm._clean_messages_openai(messages)
@@ -89,17 +102,27 @@ def test_clean_messages_openai_variants(openai_llm):
     assert roles.count("assistant") >= 1
     assert any(m["role"] == "tool" for m in cleaned)
 
-    assert any(isinstance(m["content"], list) and any(
-        part.get("type") == "image_url" for part in m["content"] if isinstance(part, dict)
-    ) for m in cleaned if m["role"] == "user")
+    assert any(
+        isinstance(m["content"], list)
+        and any(
+            part.get("type") == "image_url"
+            for part in m["content"]
+            if isinstance(part, dict)
+        )
+        for m in cleaned
+        if m["role"] == "user"
+    )
 
 
+@pytest.mark.unit
 def test_raw_gen_calls_openai_client_and_returns_content(openai_llm):
     msgs = [
         {"role": "system", "content": "sys"},
         {"role": "user", "content": "hello"},
     ]
-    content = openai_llm._raw_gen(openai_llm, model="gpt-4o", messages=msgs, stream=False)
+    content = openai_llm._raw_gen(
+        openai_llm, model="gpt-4o", messages=msgs, stream=False
+    )
     assert content == "hello world"
 
     passed = openai_llm.client.chat.completions.last_kwargs
@@ -108,16 +131,20 @@ def test_raw_gen_calls_openai_client_and_returns_content(openai_llm):
     assert passed["stream"] is False
 
 
+@pytest.mark.unit
 def test_raw_gen_stream_yields_chunks(openai_llm):
     msgs = [
         {"role": "user", "content": "hi"},
     ]
-    gen = openai_llm._raw_gen_stream(openai_llm, model="gpt", messages=msgs, stream=True)
+    gen = openai_llm._raw_gen_stream(
+        openai_llm, model="gpt", messages=msgs, stream=True
+    )
     chunks = list(gen)
     assert "part1" in "".join(chunks)
     assert "part2" in "".join(chunks)
 
 
+@pytest.mark.unit
 def test_prepare_structured_output_format_enforces_required_and_strict(openai_llm):
     schema = {
         "type": "object",
@@ -134,8 +161,8 @@ def test_prepare_structured_output_format_enforces_required_and_strict(openai_ll
     assert js["schema"]["additionalProperties"] is False
 
 
+@pytest.mark.unit
 def test_prepare_messages_with_attachments_image_and_pdf(openai_llm, monkeypatch):
-
     monkeypatch.setattr(openai_llm, "_get_base64_image", lambda att: "AAA=")
     monkeypatch.setattr(openai_llm, "_upload_file_to_openai", lambda att: "file_xyz")
 
@@ -146,12 +173,15 @@ def test_prepare_messages_with_attachments_image_and_pdf(openai_llm, monkeypatch
     ]
     out = openai_llm.prepare_messages_with_attachments(messages, attachments)
 
-    # last user message should have list content with text and two attachments
     user_msg = next(m for m in out if m["role"] == "user")
     assert isinstance(user_msg["content"], list)
-    types_in_content = [p.get("type") for p in user_msg["content"] if isinstance(p, dict)]
+    types_in_content = [
+        p.get("type") for p in user_msg["content"] if isinstance(p, dict)
+    ]
     assert "image_url" in types_in_content or any(
         isinstance(p, dict) and p.get("image_url") for p in user_msg["content"]
     )
-    assert any(isinstance(p, dict) and p.get("file", {}).get("file_id") == "file_xyz" for p in user_msg["content"])
-
+    assert any(
+        isinstance(p, dict) and p.get("file", {}).get("file_id") == "file_xyz"
+        for p in user_msg["content"]
+    )