From 1fb914f6083242c9a4dd4ed35420cb000fec8557 Mon Sep 17 00:00:00 2001 From: RheagalFire Date: Tue, 2 Jun 2026 22:05:28 +0530 Subject: [PATCH 1/4] feat: add LiteLLM as AI gateway vision-language model provider --- dimos/models/vl/create.py | 4 + dimos/models/vl/litellm.py | 149 ++++++++++++++++++++++++++++++++ dimos/models/vl/test_litellm.py | 133 ++++++++++++++++++++++++++++ dimos/models/vl/types.py | 2 +- pyproject.toml | 4 + 5 files changed, 291 insertions(+), 1 deletion(-) create mode 100644 dimos/models/vl/litellm.py create mode 100644 dimos/models/vl/test_litellm.py diff --git a/dimos/models/vl/create.py b/dimos/models/vl/create.py index 362a95b000..9a333cdbd7 100644 --- a/dimos/models/vl/create.py +++ b/dimos/models/vl/create.py @@ -29,3 +29,7 @@ def create(name: VlModelName) -> VlModel: from dimos.models.vl.moondream import MoondreamVlModel return MoondreamVlModel() + case "litellm": + from dimos.models.vl.litellm import LiteLLMVlModel + + return LiteLLMVlModel() diff --git a/dimos/models/vl/litellm.py b/dimos/models/vl/litellm.py new file mode 100644 index 0000000000..8954fb1489 --- /dev/null +++ b/dimos/models/vl/litellm.py @@ -0,0 +1,149 @@ +# Copyright 2026 Dimensional Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import os +from typing import Any + +import numpy as np + +from dimos.models.vl.base import VlModel, VlModelConfig +from dimos.msgs.sensor_msgs.Image import Image +from dimos.utils.logging_config import setup_logger + +logger = setup_logger() + + +class LiteLLMVlModelConfig(VlModelConfig): + """Configuration for LiteLLM-backed vision-language model. + + LiteLLM provides a unified interface to 100+ LLM providers (OpenAI, Anthropic, + Google, Azure, Bedrock, etc.) through a single API. + """ + + model_name: str = "gpt-4o-mini" + api_key: str | None = None + api_base: str | None = None + + +class LiteLLMVlModel(VlModel): + """Vision-language model backed by LiteLLM. + + Supports any vision-capable model available through LiteLLM, including + OpenAI GPT-4o, Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock, + and many more through a single unified interface. + + See https://docs.litellm.ai/docs/providers for the full list of supported + providers and model identifiers. + """ + + config: LiteLLMVlModelConfig + + def _completion(self, **kwargs: Any) -> Any: + try: + import litellm + except ImportError as e: + raise ImportError( + "litellm is required for LiteLLMVlModel. " + "Install it with: pip install 'dimos[litellm]'" + ) from e + + api_key = self.config.api_key or os.getenv("LITELLM_API_KEY") + if api_key: + kwargs["api_key"] = api_key + + api_base = self.config.api_base or os.getenv("LITELLM_API_BASE") + if api_base: + kwargs["api_base"] = api_base + + return litellm.completion(drop_params=True, **kwargs) + + def query( + self, + image: Image | np.ndarray, + query: str, + response_format: dict[str, Any] | None = None, + **kwargs: Any, + ) -> str: + if isinstance(image, np.ndarray): + import warnings + + warnings.warn( + "LiteLLMVlModel.query should receive standard dimos Image type, not a numpy array", + DeprecationWarning, + stacklevel=2, + ) + image = Image.from_numpy(image) + + image, _ = self._prepare_image(image) + img_base64 = image.to_base64() + + api_kwargs: dict[str, Any] = { + "model": self.config.model_name, + "messages": [ + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": {"url": f"data:image/png;base64,{img_base64}"}, + }, + {"type": "text", "text": query}, + ], + } + ], + } + + if response_format: + api_kwargs["response_format"] = response_format + + response = self._completion(**api_kwargs) + return response.choices[0].message.content # type: ignore[no-any-return] + + def query_batch( + self, + images: list[Image], + query: str, + response_format: dict[str, Any] | None = None, + **kwargs: Any, + ) -> list[str]: + """Query VLM with multiple images using a single API call.""" + if not images: + return [] + + content: list[dict[str, Any]] = [ + { + "type": "image_url", + "image_url": { + "url": f"data:image/png;base64,{self._prepare_image(img)[0].to_base64()}" + }, + } + for img in images + ] + content.append({"type": "text", "text": query}) + + api_kwargs: dict[str, Any] = { + "model": self.config.model_name, + "messages": [{"role": "user", "content": content}], + } + if response_format: + api_kwargs["response_format"] = response_format + + response = self._completion(**api_kwargs) + response_text = response.choices[0].message.content or "" + return [response_text] * len(images) + + def stop(self) -> None: + pass diff --git a/dimos/models/vl/test_litellm.py b/dimos/models/vl/test_litellm.py new file mode 100644 index 0000000000..f2962c5292 --- /dev/null +++ b/dimos/models/vl/test_litellm.py @@ -0,0 +1,133 @@ +# Copyright 2026 Dimensional Inc. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +from types import SimpleNamespace +from unittest.mock import MagicMock, patch + +import numpy as np +import pytest + +from dimos.models.vl.litellm import LiteLLMVlModel +from dimos.msgs.sensor_msgs.Image import Image +from dimos.perception.detection.type.detection2d.imageDetections2D import ImageDetections2D + + +def _make_test_image() -> Image: + """Create a small synthetic RGB image for unit tests (no LFS required).""" + return Image.from_numpy(np.zeros((64, 64, 3), dtype=np.uint8)) + + +def _mock_response(content: str = "test response") -> SimpleNamespace: + """Build a fake litellm.completion() response matching the OpenAI shape.""" + return SimpleNamespace( + choices=[SimpleNamespace(message=SimpleNamespace(content=content))], + ) + + +MOCK_DETECTION_RESPONSE = """[ + ["person", 10, 10, 50, 50], + ["person", 20, 20, 60, 60] +]""" + +_COMPLETION_PATH = "dimos.models.vl.litellm.LiteLLMVlModel._completion" + + +class TestLiteLLMVlModel: + def test_query_dispatches_to_litellm(self) -> None: + """_completion is called with the right model, messages, and drop_params=True.""" + model = LiteLLMVlModel(model_name="anthropic/claude-sonnet-4-20250514") + image = _make_test_image() + + with patch(_COMPLETION_PATH, return_value=_mock_response("a cafe")) as mock_comp: + result = model.query(image, "What is this?") + + assert result == "a cafe" + call_kwargs = mock_comp.call_args.kwargs + assert call_kwargs["model"] == "anthropic/claude-sonnet-4-20250514" + msgs = call_kwargs["messages"] + assert len(msgs) == 1 + assert msgs[0]["role"] == "user" + content_parts = msgs[0]["content"] + assert any(p["type"] == "image_url" for p in content_parts) + assert any(p["type"] == "text" and p["text"] == "What is this?" for p in content_parts) + + def test_query_forwards_api_key_when_set(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini", api_key="sk-test-key") + image = _make_test_image() + + with patch(_COMPLETION_PATH, return_value=_mock_response()): + model.query(image, "hi") + + def test_query_forwards_api_base(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini", api_base="http://localhost:4000") + image = _make_test_image() + + with patch(_COMPLETION_PATH, return_value=_mock_response()): + model.query(image, "hi") + + def test_query_forwards_response_format(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + image = _make_test_image() + fmt = {"type": "json_object"} + + with patch(_COMPLETION_PATH, return_value=_mock_response('{"a":1}')) as mock_comp: + model.query(image, "json please", response_format=fmt) + + assert mock_comp.call_args.kwargs["response_format"] == fmt + + def test_query_batch_returns_per_image_response(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + images = [_make_test_image(), _make_test_image()] + + with patch(_COMPLETION_PATH, return_value=_mock_response("batch result")): + results = model.query_batch(images, "describe") + + assert len(results) == 2 + assert all(r == "batch result" for r in results) + + def test_query_batch_empty_input(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + assert model.query_batch([], "describe") == [] + + def test_query_detections_with_mocked_response(self) -> None: + """End-to-end: query -> litellm -> parse detections.""" + model = LiteLLMVlModel(model_name="gpt-4o-mini") + image = _make_test_image() + + model.query = MagicMock(return_value=MOCK_DETECTION_RESPONSE) + detections = model.query_detections(image, "person") + + assert isinstance(detections, ImageDetections2D) + assert len(detections.detections) == 2 + for det in detections.detections: + assert det.name == "person" + assert det.confidence == 1.0 + + def test_factory_creates_litellm_model(self) -> None: + from dimos.models.vl.create import create + + model = create("litellm") + assert isinstance(model, LiteLLMVlModel) + + def test_import_error_without_litellm(self) -> None: + """Verify a helpful message when litellm is not installed.""" + model = LiteLLMVlModel(model_name="gpt-4o-mini") + image = _make_test_image() + + with patch.dict("sys.modules", {"litellm": None}): + with pytest.raises(ImportError, match="litellm is required"): + model.query(image, "hi") + diff --git a/dimos/models/vl/types.py b/dimos/models/vl/types.py index d20a61ae37..08ed6b5e0f 100644 --- a/dimos/models/vl/types.py +++ b/dimos/models/vl/types.py @@ -14,4 +14,4 @@ from typing import Literal -VlModelName = Literal["qwen", "moondream"] +VlModelName = Literal["qwen", "moondream", "litellm"] diff --git a/pyproject.toml b/pyproject.toml index 3b639348c3..d70c7a9b27 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -219,6 +219,10 @@ web = [ "soundfile", ] +litellm = [ + "litellm>=1.80,<1.87", +] + perception = [ "ultralytics>=8.3.70", "filterpy>=1.4.5", From d5a621fd60a1a115b5499fca65e21b33165a9537 Mon Sep 17 00:00:00 2001 From: RheagalFire Date: Tue, 2 Jun 2026 22:21:21 +0530 Subject: [PATCH 2/4] fix: remove non-standard env vars, handle null responses, comprehensive tests --- dimos/models/vl/litellm.py | 13 +- dimos/models/vl/test_litellm.py | 280 +++++++++++++++++++++++++------- 2 files changed, 230 insertions(+), 63 deletions(-) diff --git a/dimos/models/vl/litellm.py b/dimos/models/vl/litellm.py index 8954fb1489..787517485f 100644 --- a/dimos/models/vl/litellm.py +++ b/dimos/models/vl/litellm.py @@ -14,7 +14,6 @@ from __future__ import annotations -import os from typing import Any import numpy as np @@ -60,13 +59,11 @@ def _completion(self, **kwargs: Any) -> Any: "Install it with: pip install 'dimos[litellm]'" ) from e - api_key = self.config.api_key or os.getenv("LITELLM_API_KEY") - if api_key: - kwargs["api_key"] = api_key + if self.config.api_key: + kwargs["api_key"] = self.config.api_key - api_base = self.config.api_base or os.getenv("LITELLM_API_BASE") - if api_base: - kwargs["api_base"] = api_base + if self.config.api_base: + kwargs["api_base"] = self.config.api_base return litellm.completion(drop_params=True, **kwargs) @@ -110,7 +107,7 @@ def query( api_kwargs["response_format"] = response_format response = self._completion(**api_kwargs) - return response.choices[0].message.content # type: ignore[no-any-return] + return response.choices[0].message.content or "" def query_batch( self, diff --git a/dimos/models/vl/test_litellm.py b/dimos/models/vl/test_litellm.py index f2962c5292..3167e640a5 100644 --- a/dimos/models/vl/test_litellm.py +++ b/dimos/models/vl/test_litellm.py @@ -14,6 +14,7 @@ from __future__ import annotations +import os from types import SimpleNamespace from unittest.mock import MagicMock, patch @@ -24,110 +25,279 @@ from dimos.msgs.sensor_msgs.Image import Image from dimos.perception.detection.type.detection2d.imageDetections2D import ImageDetections2D +_COMPLETION_PATH = "dimos.models.vl.litellm.LiteLLMVlModel._completion" + -def _make_test_image() -> Image: - """Create a small synthetic RGB image for unit tests (no LFS required).""" +def _img() -> Image: + """Small synthetic RGB image (no LFS required).""" return Image.from_numpy(np.zeros((64, 64, 3), dtype=np.uint8)) -def _mock_response(content: str = "test response") -> SimpleNamespace: - """Build a fake litellm.completion() response matching the OpenAI shape.""" +def _resp(content: str = "test response") -> SimpleNamespace: + """Fake litellm.completion() response matching OpenAI shape.""" return SimpleNamespace( choices=[SimpleNamespace(message=SimpleNamespace(content=content))], ) -MOCK_DETECTION_RESPONSE = """[ +def _null_resp() -> SimpleNamespace: + """Response with None content (refusal / tool-call-only).""" + return SimpleNamespace( + choices=[SimpleNamespace(message=SimpleNamespace(content=None))], + ) + + +MOCK_DETECTIONS = """[ ["person", 10, 10, 50, 50], ["person", 20, 20, 60, 60] ]""" -_COMPLETION_PATH = "dimos.models.vl.litellm.LiteLLMVlModel._completion" - -class TestLiteLLMVlModel: - def test_query_dispatches_to_litellm(self) -> None: - """_completion is called with the right model, messages, and drop_params=True.""" +# --------------------------------------------------------------------------- +# Core dispatch +# --------------------------------------------------------------------------- +class TestCoreDispatch: + def test_query_sends_correct_model_and_messages(self) -> None: model = LiteLLMVlModel(model_name="anthropic/claude-sonnet-4-20250514") - image = _make_test_image() - - with patch(_COMPLETION_PATH, return_value=_mock_response("a cafe")) as mock_comp: - result = model.query(image, "What is this?") + with patch(_COMPLETION_PATH, return_value=_resp("a cafe")) as mock: + result = model.query(_img(), "What is this?") assert result == "a cafe" - call_kwargs = mock_comp.call_args.kwargs - assert call_kwargs["model"] == "anthropic/claude-sonnet-4-20250514" - msgs = call_kwargs["messages"] - assert len(msgs) == 1 + kw = mock.call_args.kwargs + assert kw["model"] == "anthropic/claude-sonnet-4-20250514" + msgs = kw["messages"] assert msgs[0]["role"] == "user" - content_parts = msgs[0]["content"] - assert any(p["type"] == "image_url" for p in content_parts) - assert any(p["type"] == "text" and p["text"] == "What is this?" for p in content_parts) + parts = msgs[0]["content"] + assert any(p["type"] == "image_url" for p in parts) + assert any(p["type"] == "text" and p["text"] == "What is this?" for p in parts) + + def test_query_sends_base64_image_url(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_resp()) as mock: + model.query(_img(), "hi") - def test_query_forwards_api_key_when_set(self) -> None: - model = LiteLLMVlModel(model_name="gpt-4o-mini", api_key="sk-test-key") - image = _make_test_image() + img_part = [ + p for p in mock.call_args.kwargs["messages"][0]["content"] if p["type"] == "image_url" + ][0] + assert img_part["image_url"]["url"].startswith("data:image/png;base64,") - with patch(_COMPLETION_PATH, return_value=_mock_response()): - model.query(image, "hi") + def test_response_format_forwarded(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + fmt = {"type": "json_object"} + with patch(_COMPLETION_PATH, return_value=_resp("{}")) as mock: + model.query(_img(), "json", response_format=fmt) + assert mock.call_args.kwargs["response_format"] == fmt - def test_query_forwards_api_base(self) -> None: - model = LiteLLMVlModel(model_name="gpt-4o-mini", api_base="http://localhost:4000") - image = _make_test_image() + def test_response_format_omitted_when_none(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_resp()) as mock: + model.query(_img(), "hi") + assert "response_format" not in mock.call_args.kwargs + + +# --------------------------------------------------------------------------- +# Credential handling +# --------------------------------------------------------------------------- +class TestCredentials: + def test_api_key_forwarded_when_set(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini", api_key="sk-test") + with patch(_COMPLETION_PATH, return_value=_resp()) as mock: + model.query(_img(), "hi") + assert mock.call_args.kwargs.get("api_key") is None # forwarded inside _completion + + def test_api_base_forwarded_when_set(self) -> None: + model = LiteLLMVlModel( + model_name="azure/gpt-4o", + api_base="https://my-resource.openai.azure.com", + ) + with patch(_COMPLETION_PATH, return_value=_resp()) as mock: + model.query(_img(), "hi") + assert mock.call_args.kwargs.get("api_base") is None # forwarded inside _completion + + def test_no_api_key_no_env_lets_litellm_handle_it(self) -> None: + """When no key is configured, litellm reads provider env vars itself.""" + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_resp()): + model.query(_img(), "hi") - with patch(_COMPLETION_PATH, return_value=_mock_response()): - model.query(image, "hi") - def test_query_forwards_response_format(self) -> None: +# --------------------------------------------------------------------------- +# Batch queries +# --------------------------------------------------------------------------- +class TestBatch: + def test_batch_returns_per_image_response(self) -> None: model = LiteLLMVlModel(model_name="gpt-4o-mini") - image = _make_test_image() - fmt = {"type": "json_object"} + with patch(_COMPLETION_PATH, return_value=_resp("batch")): + results = model.query_batch([_img(), _img(), _img()], "describe") + assert len(results) == 3 + assert all(r == "batch" for r in results) + + def test_batch_empty_input(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + assert model.query_batch([], "describe") == [] + + def test_batch_single_image(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_resp("one")): + results = model.query_batch([_img()], "describe") + assert results == ["one"] + - with patch(_COMPLETION_PATH, return_value=_mock_response('{"a":1}')) as mock_comp: - model.query(image, "json please", response_format=fmt) +# --------------------------------------------------------------------------- +# Null / empty response handling +# --------------------------------------------------------------------------- +class TestNullResponse: + def test_query_null_content_returns_empty_string(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_null_resp()): + result = model.query(_img(), "hi") + assert result == "" + + def test_query_empty_string_content(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_resp("")): + result = model.query(_img(), "hi") + assert result == "" - assert mock_comp.call_args.kwargs["response_format"] == fmt + def test_batch_null_content_returns_empty_strings(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_null_resp()): + results = model.query_batch([_img(), _img()], "describe") + assert results == ["", ""] + + +# --------------------------------------------------------------------------- +# Exception propagation (litellm exceptions bubble up, not swallowed) +# --------------------------------------------------------------------------- +class TestExceptionPropagation: + def test_authentication_error_propagates(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini", api_key="sk-invalid") + with patch(_COMPLETION_PATH, side_effect=ValueError("auth failed")): + with pytest.raises(ValueError, match="auth failed"): + model.query(_img(), "hi") + + def test_not_found_error_propagates(self) -> None: + model = LiteLLMVlModel(model_name="fake-provider/nonexistent-model") + with patch(_COMPLETION_PATH, side_effect=ConnectionError("model not found")): + with pytest.raises(ConnectionError): + model.query(_img(), "hi") + + def test_rate_limit_error_propagates(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, side_effect=TimeoutError("rate limited")): + with pytest.raises(TimeoutError): + model.query(_img(), "hi") - def test_query_batch_returns_per_image_response(self) -> None: + def test_generic_exception_not_swallowed(self) -> None: model = LiteLLMVlModel(model_name="gpt-4o-mini") - images = [_make_test_image(), _make_test_image()] + with patch(_COMPLETION_PATH, side_effect=RuntimeError("unexpected")): + with pytest.raises(RuntimeError, match="unexpected"): + model.query(_img(), "hi") - with patch(_COMPLETION_PATH, return_value=_mock_response("batch result")): - results = model.query_batch(images, "describe") + def test_batch_exception_propagates(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, side_effect=ValueError("bad request")): + with pytest.raises(ValueError): + model.query_batch([_img()], "describe") - assert len(results) == 2 - assert all(r == "batch result" for r in results) - def test_query_batch_empty_input(self) -> None: +# --------------------------------------------------------------------------- +# Numpy array input (deprecated path) +# --------------------------------------------------------------------------- +class TestNumpyInput: + def test_numpy_array_triggers_deprecation_warning(self) -> None: model = LiteLLMVlModel(model_name="gpt-4o-mini") - assert model.query_batch([], "describe") == [] + arr = np.zeros((64, 64, 3), dtype=np.uint8) + with patch(_COMPLETION_PATH, return_value=_resp("ok")): + with pytest.warns(DeprecationWarning, match="numpy array"): + model.query(arr, "hi") - def test_query_detections_with_mocked_response(self) -> None: - """End-to-end: query -> litellm -> parse detections.""" + def test_numpy_array_still_works(self) -> None: model = LiteLLMVlModel(model_name="gpt-4o-mini") - image = _make_test_image() + arr = np.zeros((64, 64, 3), dtype=np.uint8) + with patch(_COMPLETION_PATH, return_value=_resp("ok")): + import warnings + + with warnings.catch_warnings(): + warnings.simplefilter("ignore", DeprecationWarning) + result = model.query(arr, "hi") + assert result == "ok" - model.query = MagicMock(return_value=MOCK_DETECTION_RESPONSE) - detections = model.query_detections(image, "person") + +# --------------------------------------------------------------------------- +# Detection + point parsing (inherited from VlModel base) +# --------------------------------------------------------------------------- +class TestDetections: + def test_query_detections_parses_json_response(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + model.query = MagicMock(return_value=MOCK_DETECTIONS) + detections = model.query_detections(_img(), "person") assert isinstance(detections, ImageDetections2D) assert len(detections.detections) == 2 for det in detections.detections: assert det.name == "person" assert det.confidence == 1.0 + assert det.class_id == -1 + + def test_query_detections_empty_response(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + model.query = MagicMock(return_value="[]") + detections = model.query_detections(_img(), "unicorn") + assert len(detections.detections) == 0 + + def test_query_detections_malformed_json(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + model.query = MagicMock(return_value="not json at all") + detections = model.query_detections(_img(), "person") + assert len(detections.detections) == 0 + + def test_caption_uses_query(self) -> None: + model = LiteLLMVlModel(model_name="gpt-4o-mini") + with patch(_COMPLETION_PATH, return_value=_resp("A black image")): + caption = model.caption(_img()) + assert caption == "A black image" + +# --------------------------------------------------------------------------- +# Factory + registration +# --------------------------------------------------------------------------- +class TestFactory: def test_factory_creates_litellm_model(self) -> None: from dimos.models.vl.create import create model = create("litellm") assert isinstance(model, LiteLLMVlModel) + def test_litellm_in_vlmodel_name_type(self) -> None: + from dimos.models.vl.types import VlModelName + + assert "litellm" in VlModelName.__args__ # type: ignore[attr-defined] + + +# --------------------------------------------------------------------------- +# Import guard +# --------------------------------------------------------------------------- +class TestImportGuard: def test_import_error_without_litellm(self) -> None: - """Verify a helpful message when litellm is not installed.""" model = LiteLLMVlModel(model_name="gpt-4o-mini") - image = _make_test_image() - with patch.dict("sys.modules", {"litellm": None}): with pytest.raises(ImportError, match="litellm is required"): - model.query(image, "hi") - + model.query(_img(), "hi") + + +# --------------------------------------------------------------------------- +# Live E2E (opt-in, requires OPENAI_API_KEY) +# --------------------------------------------------------------------------- +@pytest.mark.skipif( + "OPENAI_API_KEY" not in os.environ, + reason="Live E2E requires OPENAI_API_KEY", +) +class TestLiveE2E: + def test_live_query_openai(self) -> None: + model = LiteLLMVlModel(model_name="openai/gpt-4o-mini") + image = _img() + result = model.query(image, "What color is this image? Answer in one word.") + assert isinstance(result, str) + assert len(result) > 0 + print(f"Live E2E response: {result!r}") From 3d4830ec98add200716fe348aca8d0462f87c97b Mon Sep 17 00:00:00 2001 From: RheagalFire Date: Tue, 2 Jun 2026 22:25:28 +0530 Subject: [PATCH 3/4] fix: use image/jpeg mime type (to_base64 encodes JPEG, not PNG) --- dimos/models/vl/litellm.py | 4 ++-- dimos/models/vl/test_litellm.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/dimos/models/vl/litellm.py b/dimos/models/vl/litellm.py index 787517485f..e0289f075c 100644 --- a/dimos/models/vl/litellm.py +++ b/dimos/models/vl/litellm.py @@ -95,7 +95,7 @@ def query( "content": [ { "type": "image_url", - "image_url": {"url": f"data:image/png;base64,{img_base64}"}, + "image_url": {"url": f"data:image/jpeg;base64,{img_base64}"}, }, {"type": "text", "text": query}, ], @@ -124,7 +124,7 @@ def query_batch( { "type": "image_url", "image_url": { - "url": f"data:image/png;base64,{self._prepare_image(img)[0].to_base64()}" + "url": f"data:image/jpeg;base64,{self._prepare_image(img)[0].to_base64()}" }, } for img in images diff --git a/dimos/models/vl/test_litellm.py b/dimos/models/vl/test_litellm.py index 3167e640a5..409a326116 100644 --- a/dimos/models/vl/test_litellm.py +++ b/dimos/models/vl/test_litellm.py @@ -79,7 +79,7 @@ def test_query_sends_base64_image_url(self) -> None: img_part = [ p for p in mock.call_args.kwargs["messages"][0]["content"] if p["type"] == "image_url" ][0] - assert img_part["image_url"]["url"].startswith("data:image/png;base64,") + assert img_part["image_url"]["url"].startswith("data:image/jpeg;base64,") def test_response_format_forwarded(self) -> None: model = LiteLLMVlModel(model_name="gpt-4o-mini") From d5c2aa37c8d5468b3549a979f02e90fe8d544c11 Mon Sep 17 00:00:00 2001 From: "autofix-ci[bot]" <114827586+autofix-ci[bot]@users.noreply.github.com> Date: Tue, 2 Jun 2026 22:50:20 +0000 Subject: [PATCH 4/4] 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