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Author SHA1 Message Date
Gerald LonlasandClaude Opus 4.8 1ebe193a3e test(coverage): close remaining branch gaps in client and image node
Add 12 focused unit tests targeting uncovered branches identified by
pytest-cov on main (97.01% → 99.30%):

client.py
- coerce_seed: .item() raises at runtime → falls through to unsupported-type error (lines 117-118, 142)
- coerce_seed: plain unsupported types (dict, object) raise ValueError (line 142)
- extract_chat_completion_text: non-str/non-list content returns "" (line 207)
- extract_chat_completion_text: list items with no usable text are skipped (lines 222-228)
- extract_responses_text: output list with unresolvable items returns "" (line 234)
- extract_responses_text: output=None returns "" (end of function)
- build_chat_messages_with_image: blank/None system_prompt omits the system message (line 291)

image_to_text_node.py
- _responses_kwargs: empty/whitespace system_prompt omits "instructions" key (line 112)
- execute: responses endpoint returns empty string → falls back to chat.completions (line 157)
- execute: both endpoints return empty text → ValueError propagates (line 181)
- execute: single-image chat fallback status does not mention dropped frames (line 183)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-27 00:55:48 +08:00
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"""
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