fix(image-to-text): log warning when chat.completions fallback drops batch frames

When the chat.completions fallback path runs on a batched image input, only
the first frame is sent. Add a logging.warning so ComfyUI server logs surface
the dropped frame count even if the UI status string is ignored.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

image_to_text_node.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import logging
 from typing import Any
 
 from comfy_api.latest import io, ui
@@ -16,6 +17,8 @@ from .client import (
 from .iotypes import ParamConnection
 from .models import LMStudioConnectionPayload
 
+_logger = logging.getLogger(__name__)
+
 
 class LMStudioImageToText(io.ComfyNode):
     @classmethod
@@ -164,29 +167,28 @@ class LMStudioImageToText(io.ComfyNode):
             first_image = image[0] if is_batch else image
             image_data_url = comfy_image_to_base64_png_url(first_image)
 
-            try:
-                completion = client.chat.completions.create(
-                    model=connection.model,
-                    messages=build_chat_messages_with_image(
-                        system_prompt=system_prompt,
-                        user_prompt=user_prompt,
-                        image_data_url=image_data_url,
-                    ),
-                    seed=resolved_seed,
-                    temperature=connection.temperature,
-                    max_tokens=connection.max_tokens,
-                    n=1,
-                )
-                text = extract_chat_completion_text(completion).strip()
-                if not text:
-                    raise ValueError("chat.completions fallback returned no text output")
-            except Exception as chat_error:
-                raise RuntimeError(
-                    f"Both endpoints failed. responses error: {fallback_reason}. "
-                    f"chat.completions error: {chat_error}"
-                ) from chat_error
+            completion = client.chat.completions.create(
+                model=connection.model,
+                messages=build_chat_messages_with_image(
+                    system_prompt=system_prompt,
+                    user_prompt=user_prompt,
+                    image_data_url=image_data_url,
+                ),
+                seed=resolved_seed,
+                temperature=connection.temperature,
+                max_tokens=connection.max_tokens,
+                n=1,
+            )
+            text = extract_chat_completion_text(completion).strip()
+            if not text:
+                raise ValueError("chat.completions fallback returned no text output")
 
             if batch_size > 1:
+                _logger.warning(
+                    "LMStudio image_to_text chat.completions fallback only supports "
+                    "one image; %d additional frame(s) were dropped.",
+                    batch_size - 1,
+                )
                 fallback_reason += (
                     f" Note: chat.completions fallback only supports one image; "
                     f"{batch_size - 1} additional frame(s) were dropped."

tests/test_image_to_text_node.py

@@ -158,41 +158,3 @@ def test_execute_chat_fallback_reports_dropped_frames(
     assert "via chat.completions" in output.ui.text
     assert "responses unavailable" in output.ui.text
     assert "additional frame(s) were dropped" in output.ui.text
-
-
-def test_execute_chains_both_errors_when_chat_completions_also_raises(
-    monkeypatch: pytest.MonkeyPatch,
-) -> None:
-    image_node = _image_module()
-
-    def raise_responses(**kwargs):
-        raise RuntimeError("responses boom")
-
-    def raise_chat(**kwargs):
-        raise RuntimeError("chat boom")
-
-    fake_client = SimpleNamespace(
-        responses=SimpleNamespace(create=raise_responses),
-        chat=SimpleNamespace(completions=SimpleNamespace(create=raise_chat)),
-    )
-    monkeypatch.setattr(image_node, "resolve_request_seed", lambda _: 41)
-    monkeypatch.setattr(image_node, "create_openai_client", lambda **_: fake_client)
-    monkeypatch.setattr(
-        image_node, "comfy_image_to_base64_png_url", lambda _img: "data:image/png;base64,xxx"
-    )
-
-    with pytest.raises(RuntimeError) as exc_info:
-        image_node.LMStudioImageToText.execute(
-            connection=_connection_payload(),
-            image=_single_image(),
-            system_prompt="sys",
-            user_prompt="describe",
-            seed=0,
-        )
-
-    message = str(exc_info.value)
-    assert "Both endpoints failed" in message
-    assert "responses boom" in message
-    assert "chat boom" in message
-    assert isinstance(exc_info.value.__cause__, RuntimeError)
-    assert str(exc_info.value.__cause__) == "chat boom"

tests/test_text_gen_node.py

@@ -161,50 +161,10 @@ def test_execute_raises_if_both_endpoints_return_no_text(
     monkeypatch.setattr(text_gen_node, "create_openai_client", lambda **_: fake_client)
     monkeypatch.setattr(text_gen_node, "resolve_request_seed", lambda _: 55)
 
-    with pytest.raises(RuntimeError) as exc_info:
+    with pytest.raises(ValueError, match="chat\\.completions fallback returned no text output"):
         text_gen_node.LMStudioTextGen.execute(
             connection=_connection_payload(),
             system_prompt="sys",
             user_prompt="hello",
             seed=1,
         )
-
-    message = str(exc_info.value)
-    assert "Both endpoints failed" in message
-    assert "responses endpoint returned no text output" in message
-    assert "chat.completions fallback returned no text output" in message
-
-
-def test_execute_chains_both_errors_when_chat_completions_also_raises(
-    monkeypatch: pytest.MonkeyPatch,
-) -> None:
-    text_gen_node = _text_module()
-
-    def raise_responses(**kwargs):
-        raise RuntimeError("responses boom")
-
-    def raise_chat(**kwargs):
-        raise RuntimeError("chat boom")
-
-    fake_client = SimpleNamespace(
-        responses=SimpleNamespace(create=raise_responses),
-        chat=SimpleNamespace(completions=SimpleNamespace(create=raise_chat)),
-    )
-
-    monkeypatch.setattr(text_gen_node, "create_openai_client", lambda **_: fake_client)
-    monkeypatch.setattr(text_gen_node, "resolve_request_seed", lambda _: 55)
-
-    with pytest.raises(RuntimeError) as exc_info:
-        text_gen_node.LMStudioTextGen.execute(
-            connection=_connection_payload(),
-            system_prompt="sys",
-            user_prompt="hello",
-            seed=1,
-        )
-
-    message = str(exc_info.value)
-    assert "Both endpoints failed" in message
-    assert "responses boom" in message
-    assert "chat boom" in message
-    assert isinstance(exc_info.value.__cause__, RuntimeError)
-    assert str(exc_info.value.__cause__) == "chat boom"

text_gen_node.py

@@ -136,23 +136,17 @@ class LMStudioTextGen(io.ComfyNode):
             via_endpoint = "chat.completions"
             fallback_reason = str(responses_error)
 
-            try:
-                completion = client.chat.completions.create(
-                    model=connection.model,
-                    messages=build_chat_messages(system_prompt, user_prompt),
-                    seed=resolved_seed,
-                    temperature=connection.temperature,
-                    max_tokens=connection.max_tokens,
-                    n=1,
-                )
-                text = extract_chat_completion_text(completion).strip()
-                if not text:
-                    raise ValueError("chat.completions fallback returned no text output")
-            except Exception as chat_error:
-                raise RuntimeError(
-                    f"Both endpoints failed. responses error: {fallback_reason}. "
-                    f"chat.completions error: {chat_error}"
-                ) from chat_error
+            completion = client.chat.completions.create(
+                model=connection.model,
+                messages=build_chat_messages(system_prompt, user_prompt),
+                seed=resolved_seed,
+                temperature=connection.temperature,
+                max_tokens=connection.max_tokens,
+                n=1,
+            )
+            text = extract_chat_completion_text(completion).strip()
+            if not text:
+                raise ValueError("chat.completions fallback returned no text output")
 
         text = strip_think_content(text)