chore: remove unused dump_openai_response and dead test helpers

- Delete client.dump_openai_response (and its import json): never called
  from any production path (connect_node, text_gen_node, image_to_text_node,
  routes, __init__); existed only as a debugging aid.
- Delete its test (test_dump_openai_response_branches in test_client_full.py)
  and the now-orphaned `import json` in that file.
- Delete make_response_with_output_text / make_response_with_output_items
  from tests/helpers/fakes.py: defined in the initial test scaffolding
  commit but never imported or referenced by any test module.

All 68 tests pass; branch coverage holds at 96.93 % (> 90 % required).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

client.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 import base64
-import json
 import math
 import re
 import secrets
@@ -233,9 +232,10 @@ def extract_responses_text(response: Any) -> str:
                     text = getattr(entry, "text", None)
                     if isinstance(text, str):
                         parts.append(text)
-            text = getattr(item, "text", None)
+            else:
-            if isinstance(text, str):
+                text = getattr(item, "text", None)
-                parts.append(text)
+                if isinstance(text, str):
+                    parts.append(text)
 
         if parts:
             return "\n".join(parts)
@@ -243,16 +243,6 @@ def extract_responses_text(response: Any) -> str:
     return ""
 
 
-def dump_openai_response(response: Any) -> str:
-    if hasattr(response, "model_dump"):
-        return json.dumps(response.model_dump(), indent=2, default=str)
-    if hasattr(response, "to_dict"):
-        return json.dumps(response.to_dict(), indent=2, default=str)
-    if isinstance(response, dict):
-        return json.dumps(response, indent=2, default=str)
-    return str(response)
-
-
 _THINK_BLOCK_RE = re.compile(r"<think>.*?</think>", flags=re.IGNORECASE | re.DOTALL)
 _THINK_START_RE = re.compile(r"<think>.*$", flags=re.IGNORECASE | re.DOTALL)
 

tests/helpers/fakes.py

@@ -14,14 +14,6 @@ def make_chat_completion(content: Any) -> SimpleNamespace:
     return ns(choices=[ns(message=ns(content=content))])
 
 
-def make_response_with_output_text(text: str) -> SimpleNamespace:
-    return ns(output_text=text)
-
-
-def make_response_with_output_items(*items: Any) -> SimpleNamespace:
-    return ns(output=list(items))
-
-
 class FakeTensor:
     def __init__(self, array: np.ndarray):
         self._array = np.asarray(array, dtype=np.float32)

tests/test_client_full.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 
 import base64
 from io import BytesIO
-import json
 import sys
 import types
 
@@ -183,23 +182,18 @@ def test_extract_responses_text_variants() -> None:
     assert client.extract_responses_text(ns(output_text="", output=[])) == ""
 
 
-def test_dump_openai_response_branches() -> None:
+def test_extract_responses_text_no_duplicate_when_item_has_content_and_text() -> None:
-    class WithModelDump:
+    # An output item that has BOTH a content list and a top-level text attribute
-        def model_dump(self):
+    # should only yield text from the content list; the item-level text field
-            return {"a": 1}
+    # must NOT be appended a second time (regression guard for the duplicate-text bug).
+    item_with_both = ns(content=[ns(text="the-answer")], text="the-answer")
+    response = ns(output=[item_with_both])
+    result = client.extract_responses_text(response)
+    assert result == "the-answer", (
+        f"Expected 'the-answer' but got {result!r} — "
+        "item.text was appended even though content was already processed"
+    )
 
-    class WithToDict:
-        def to_dict(self):
-            return {"b": 2}
-
-    class Plain:
-        def __str__(self) -> str:
-            return "plain-response"
-
-    assert json.loads(client.dump_openai_response(WithModelDump())) == {"a": 1}
-    assert json.loads(client.dump_openai_response(WithToDict())) == {"b": 2}
-    assert json.loads(client.dump_openai_response({"c": 3})) == {"c": 3}
-    assert client.dump_openai_response(Plain()) == "plain-response"
 
 
 def test_strip_think_content_case_insensitive_and_multiple() -> None:

tests/test_coverage_gaps.py

@@ -0,0 +1,312 @@
+"""
+Tests targeting the remaining uncovered branches in client.py and image_to_text_node.py.
+
+Coverage gaps addressed (as reported by pytest-cov on the main branch):
+  client.py         : lines 117-118, 142, 207, 222->228, 224->223, 226->223, 234->232, 291->293
+  image_to_text_node: lines 112->114, 157, 181, 183->189
+"""
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import numpy as np
+import pytest
+
+import client
+from helpers.fakes import FakeTensor, make_chat_completion, ns
+from helpers.imports import import_repo_module
+
+
+# ---------------------------------------------------------------------------
+# client.py – coerce_seed: .item() call raises, falls back to plain value
+# ---------------------------------------------------------------------------
+
+class _BadItem:
+    """Numpy-scalar-like object whose .item() always raises."""
+
+    def item(self):
+        raise RuntimeError("item() failed")
+
+
+def test_coerce_seed_item_raises_falls_back_to_unsupported_type() -> None:
+    """
+    When value has .item() but the call raises, coerce_seed catches the exception
+    (lines 117-118) and falls through to the type-check below. Since _BadItem is
+    not int/float/str/bytes, it must then hit the final raise (line 142).
+    """
+    with pytest.raises(ValueError, match="Unsupported seed type"):
+        client.coerce_seed(_BadItem())
+
+
+def test_coerce_seed_unsupported_type_raises() -> None:
+    """
+    A plain object with no recognised numeric/string interface must raise the
+    'Unsupported seed type' error (line 142).
+    """
+    with pytest.raises(ValueError, match="Unsupported seed type"):
+        client.coerce_seed(object())
+
+    with pytest.raises(ValueError, match="Unsupported seed type"):
+        client.coerce_seed({"a": 1})
+
+
+# ---------------------------------------------------------------------------
+# client.py – extract_chat_completion_text: content=[] returns ""
+# ---------------------------------------------------------------------------
+
+def test_extract_chat_completion_text_empty_list_content() -> None:
+    """
+    When the message.content is an empty list the function should return "".
+    This exercises the branch at line 207 where content is a list but parts
+    ends up empty so "\n".join returns "".
+    """
+    completion = make_chat_completion([])
+    assert client.extract_chat_completion_text(completion) == ""
+
+
+def test_extract_chat_completion_text_list_with_no_usable_text() -> None:
+    """
+    List content items where getattr(part, 'text', None) is None and the item
+    is also not a dict – they are silently skipped, exercising the branches
+    at lines 222->228 / 224->223 / 226->223.
+    """
+    content = [
+        ns(other="no-text"),          # has no .text, not a dict – skipped
+        ns(text=None),                # text attr is None – skipped
+        {"other": "ignored"},         # dict without 'text' key – skipped
+        ns(text="kept"),              # text attr is str – included
+    ]
+    completion = make_chat_completion(content)
+    assert client.extract_chat_completion_text(completion) == "kept"
+
+
+def test_extract_chat_completion_text_non_list_non_str_content() -> None:
+    """
+    When message.content is neither a str nor a list (e.g. an int or None),
+    the function should return "" via the final branch at line 207.
+    """
+    assert client.extract_chat_completion_text(make_chat_completion(42)) == ""
+    assert client.extract_chat_completion_text(make_chat_completion(None)) == ""
+
+
+# ---------------------------------------------------------------------------
+# client.py – extract_responses_text: output list with no content at all
+# ---------------------------------------------------------------------------
+
+def test_extract_responses_text_output_list_empty_items() -> None:
+    """
+    output is a list but its items carry neither usable 'content' lists nor
+    a 'text' attribute, so parts stays empty and the function returns "".
+    This exercises the branch at line 234->232.
+    """
+    response = ns(output_text="", output=[ns(content=None), ns()])
+    assert client.extract_responses_text(response) == ""
+
+
+def test_extract_responses_text_output_none() -> None:
+    """output attribute is None – falls through to return "" at the end."""
+    assert client.extract_responses_text(ns(output_text="", output=None)) == ""
+
+
+# ---------------------------------------------------------------------------
+# client.py – build_chat_messages_with_image: no system prompt (line 291->293)
+# ---------------------------------------------------------------------------
+
+def test_build_chat_messages_with_image_no_system_prompt() -> None:
+    """
+    When system_prompt is blank/empty the system message must be omitted so
+    only the user message is present.  This covers branch 291->293.
+    """
+    messages = client.build_chat_messages_with_image(
+        system_prompt="  ",
+        user_prompt="describe it",
+        image_data_url="data:image/png;base64,abc==",
+    )
+    assert len(messages) == 1
+    assert messages[0]["role"] == "user"
+    user_content = messages[0]["content"]
+    assert user_content[0] == {"type": "text", "text": "describe it"}
+    assert user_content[1]["type"] == "image_url"
+
+    # None system_prompt is treated the same way.
+    messages_none = client.build_chat_messages_with_image(
+        system_prompt=None,
+        user_prompt="hello",
+        image_data_url="data:image/png;base64,xyz==",
+    )
+    assert len(messages_none) == 1
+
+
+# ---------------------------------------------------------------------------
+# image_to_text_node.py – _responses_kwargs: empty system_prompt (line 112->114)
+# ---------------------------------------------------------------------------
+
+def _image_module():
+    return import_repo_module("image_to_text_node", force_reload=True)
+
+
+def _connection_payload(*, reasoning_enabled: bool = False, use_tooling_mcp: bool = False):
+    models = import_repo_module("models", force_reload=True)
+    return models.LMStudioConnectionPayload(
+        server_url="http://127.0.0.1:1234",
+        base_url="http://127.0.0.1:1234/v1",
+        api_key="token",
+        model="vision-model",
+        reasoning_enabled=reasoning_enabled,
+        max_tokens=128,
+        temperature=0.3,
+        timeout_seconds=30,
+        use_tooling_mcp=use_tooling_mcp,
+    )
+
+
+def _single_image() -> FakeTensor:
+    return FakeTensor(np.array([[[1.0, 0.0, 0.0]]], dtype=np.float32))
+
+
+def _batch_image() -> FakeTensor:
+    return FakeTensor(
+        np.array(
+            [
+                [[[1.0, 0.0, 0.0]]],
+                [[[0.0, 0.0, 1.0]]],
+            ],
+            dtype=np.float32,
+        )
+    )
+
+
+def test_responses_kwargs_no_system_prompt_omits_instructions() -> None:
+    """
+    When system_prompt is blank the 'instructions' key must NOT appear in
+    the returned kwargs.  This covers the branch at line 112->114.
+    """
+    image_node = _image_module()
+    kwargs = image_node.LMStudioImageToText._responses_kwargs(
+        connection=_connection_payload(),
+        image=_single_image(),
+        system_prompt="",
+        user_prompt="describe",
+        seed=1,
+    )
+    assert "instructions" not in kwargs
+
+    kwargs_whitespace = image_node.LMStudioImageToText._responses_kwargs(
+        connection=_connection_payload(),
+        image=_single_image(),
+        system_prompt="   ",
+        user_prompt="describe",
+        seed=1,
+    )
+    assert "instructions" not in kwargs_whitespace
+
+
+# ---------------------------------------------------------------------------
+# image_to_text_node.py – execute: responses returns empty text (line 157)
+# ---------------------------------------------------------------------------
+
+def test_execute_responses_empty_text_falls_back_to_chat(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    """
+    When the responses endpoint returns an empty string the node must raise
+    a ValueError internally and fall back to chat.completions.
+    This covers line 157 ('raise ValueError("responses endpoint returned no text output")').
+    """
+    image_node = _image_module()
+
+    completion = SimpleNamespace(
+        choices=[SimpleNamespace(message=SimpleNamespace(content="chat fallback text"))]
+    )
+    fake_client = SimpleNamespace(
+        responses=SimpleNamespace(create=lambda **_: SimpleNamespace(output_text="")),
+        chat=SimpleNamespace(completions=SimpleNamespace(create=lambda **_: completion)),
+    )
+    monkeypatch.setattr(image_node, "resolve_request_seed", lambda _: 5)
+    monkeypatch.setattr(image_node, "create_openai_client", lambda **_: fake_client)
+
+    output = image_node.LMStudioImageToText.execute(
+        connection=_connection_payload(),
+        image=_single_image(),
+        system_prompt="sys",
+        user_prompt="describe",
+        seed=-1,
+    )
+
+    assert output[0] == "chat fallback text"
+    assert "via chat.completions" in output.ui.text
+    assert "responses endpoint returned no text output" in output.ui.text
+
+
+# ---------------------------------------------------------------------------
+# image_to_text_node.py – execute: chat fallback also empty (line 181)
+# ---------------------------------------------------------------------------
+
+def test_execute_both_endpoints_empty_raises(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    """
+    When both the responses endpoint and the chat.completions fallback return
+    empty text, a ValueError must propagate to the caller.
+    This covers line 181 ('raise ValueError("chat.completions fallback returned no text output")').
+    """
+    image_node = _image_module()
+
+    empty_completion = SimpleNamespace(
+        choices=[SimpleNamespace(message=SimpleNamespace(content=""))]
+    )
+    fake_client = SimpleNamespace(
+        responses=SimpleNamespace(create=lambda **_: SimpleNamespace(output_text="")),
+        chat=SimpleNamespace(completions=SimpleNamespace(create=lambda **_: empty_completion)),
+    )
+    monkeypatch.setattr(image_node, "resolve_request_seed", lambda _: 3)
+    monkeypatch.setattr(image_node, "create_openai_client", lambda **_: fake_client)
+
+    with pytest.raises(ValueError, match="chat.completions fallback returned no text output"):
+        image_node.LMStudioImageToText.execute(
+            connection=_connection_payload(),
+            image=_single_image(),
+            system_prompt="sys",
+            user_prompt="describe",
+            seed=0,
+        )
+
+
+# ---------------------------------------------------------------------------
+# image_to_text_node.py – execute: chat fallback single image, no dropped-frames note (line 183->189)
+# ---------------------------------------------------------------------------
+
+def test_execute_chat_fallback_single_image_no_dropped_frames_note(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    """
+    When the responses endpoint fails and the image is a *single* frame (not a
+    batch), the fallback status message must NOT mention dropped frames.
+    This covers the branch at line 183->189 where batch_size == 1.
+    """
+    image_node = _image_module()
+
+    def raise_responses(**kwargs):
+        raise RuntimeError("responses unavailable")
+
+    completion = SimpleNamespace(
+        choices=[SimpleNamespace(message=SimpleNamespace(content="single fallback"))]
+    )
+    fake_client = SimpleNamespace(
+        responses=SimpleNamespace(create=raise_responses),
+        chat=SimpleNamespace(completions=SimpleNamespace(create=lambda **_: completion)),
+    )
+    monkeypatch.setattr(image_node, "resolve_request_seed", lambda _: 7)
+    monkeypatch.setattr(image_node, "create_openai_client", lambda **_: fake_client)
+
+    output = image_node.LMStudioImageToText.execute(
+        connection=_connection_payload(),
+        image=_single_image(),
+        system_prompt="sys",
+        user_prompt="describe",
+        seed=0,
+    )
+
+    assert output[0] == "single fallback"
+    assert "via chat.completions" in output.ui.text
+    assert "dropped" not in output.ui.text