feat: Add DeepSeek Model component (#5443)

* feat: Add DeepSeek component

* Adiciona DeepseekModelComponent ao __init__.py

* [autofix.ci] apply automated fixes

* Add DeepSeek icon and update component files

* Add DeepSeek icon and update all related files

* [autofix.ci] apply automated fixes

* Change DeepSeek icon color to blue (#080c34)

* [autofix.ci] apply automated fixes

* Revert DeepSeek icon color to black

* [autofix.ci] apply automated fixes

* remove: name parameter from DeepSeekModel to avoid backwards compatibility issues

* test: add unit tests for DeepSeek model component with mocks

* fix: correct formatting issues in DeepSeek model tests

* feat: update DeepSeek icon color to #4c6cfc

* fix: make DeepSeek API key field required

* fix: format SecretStrInput to comply with line length limit in DeepSeekModelComponent

* feat: add dark mode support for component icon

* [autofix.ci] apply automated fixes

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Edwin Jose <edwin.jose@datastax.com>

src/backend/base/langflow/components/models/__init__.py

@@ -4,6 +4,7 @@ from .anthropic import AnthropicModelComponent
 from .azure_openai import AzureChatOpenAIComponent
 from .baidu_qianfan_chat import QianfanChatEndpointComponent
 from .cohere import CohereComponent
+from .deepseek import DeepSeekModelComponent
 from .google_generative_ai import GoogleGenerativeAIComponent
 from .groq import GroqModel
 from .huggingface import HuggingFaceEndpointsComponent
@@ -26,6 +27,7 @@ __all__ = [
     "ChatOllamaComponent",
     "ChatVertexAIComponent",
     "CohereComponent",
+    "DeepSeekModelComponent",
     "GoogleGenerativeAIComponent",
     "GroqModel",
     "HuggingFaceEndpointsComponent",

src/backend/base/langflow/components/models/deepseek.py

@@ -0,0 +1,135 @@
+import requests
+from pydantic.v1 import SecretStr
+from typing_extensions import override
+
+from langflow.base.models.model import LCModelComponent
+from langflow.field_typing import LanguageModel
+from langflow.field_typing.range_spec import RangeSpec
+from langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput
+
+DEEPSEEK_MODELS = ["deepseek-chat"]
+
+
+class DeepSeekModelComponent(LCModelComponent):
+    display_name = "DeepSeek"
+    description = "Generate text using DeepSeek LLMs."
+    icon = "DeepSeek"
+
+    inputs = [
+        *LCModelComponent._base_inputs,
+        IntInput(
+            name="max_tokens",
+            display_name="Max Tokens",
+            advanced=True,
+            info="Maximum number of tokens to generate. Set to 0 for unlimited.",
+            range_spec=RangeSpec(min=0, max=128000),
+        ),
+        DictInput(
+            name="model_kwargs",
+            display_name="Model Kwargs",
+            advanced=True,
+            info="Additional keyword arguments to pass to the model.",
+        ),
+        BoolInput(
+            name="json_mode",
+            display_name="JSON Mode",
+            advanced=True,
+            info="If True, it will output JSON regardless of passing a schema.",
+        ),
+        DropdownInput(
+            name="model_name",
+            display_name="Model Name",
+            info="DeepSeek model to use",
+            options=DEEPSEEK_MODELS,
+            value="deepseek-chat",
+            refresh_button=True,
+        ),
+        StrInput(
+            name="api_base",
+            display_name="DeepSeek API Base",
+            advanced=True,
+            info="Base URL for API requests. Defaults to https://api.deepseek.com",
+            value="https://api.deepseek.com",
+        ),
+        SecretStrInput(
+            name="api_key",
+            display_name="DeepSeek API Key",
+            info="The DeepSeek API Key",
+            advanced=False,
+            required=True,
+        ),
+        SliderInput(
+            name="temperature",
+            display_name="Temperature",
+            info="Controls randomness in responses",
+            value=1.0,
+            range_spec=RangeSpec(min=0, max=2, step=0.01),
+        ),
+        IntInput(
+            name="seed",
+            display_name="Seed",
+            info="The seed controls the reproducibility of the job.",
+            advanced=True,
+            value=1,
+        ),
+    ]
+
+    def get_models(self) -> list[str]:
+        if not self.api_key:
+            return DEEPSEEK_MODELS
+
+        url = f"{self.api_base}/models"
+        headers = {"Authorization": f"Bearer {self.api_key}", "Accept": "application/json"}
+
+        try:
+            response = requests.get(url, headers=headers, timeout=10)
+            response.raise_for_status()
+            model_list = response.json()
+            return [model["id"] for model in model_list.get("data", [])]
+        except requests.RequestException as e:
+            self.status = f"Error fetching models: {e}"
+            return DEEPSEEK_MODELS
+
+    @override
+    def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):
+        if field_name in {"api_key", "api_base", "model_name"}:
+            models = self.get_models()
+            build_config["model_name"]["options"] = models
+        return build_config
+
+    def build_model(self) -> LanguageModel:
+        try:
+            from langchain_openai import ChatOpenAI
+        except ImportError as e:
+            msg = "langchain-openai not installed. Please install with `pip install langchain-openai`"
+            raise ImportError(msg) from e
+
+        api_key = SecretStr(self.api_key).get_secret_value() if self.api_key else None
+        output = ChatOpenAI(
+            model=self.model_name,
+            temperature=self.temperature if self.temperature is not None else 0.1,
+            max_tokens=self.max_tokens or None,
+            model_kwargs=self.model_kwargs or {},
+            base_url=self.api_base,
+            api_key=api_key,
+            streaming=self.stream if hasattr(self, "stream") else False,
+            seed=self.seed,
+        )
+
+        if self.json_mode:
+            output = output.bind(response_format={"type": "json_object"})
+
+        return output
+
+    def _get_exception_message(self, e: Exception):
+        """Get message from DeepSeek API exception."""
+        try:
+            from openai import BadRequestError
+
+            if isinstance(e, BadRequestError):
+                message = e.body.get("message")
+                if message:
+                    return message
+        except ImportError:
+            pass
+        return None

src/backend/tests/unit/components/models/test_deepseek.py

@@ -0,0 +1,112 @@
+from unittest.mock import MagicMock
+
+import pytest
+from langflow.components.models import DeepSeekModelComponent
+from langflow.custom import Component
+from langflow.custom.utils import build_custom_component_template
+
+
+def test_deepseek_initialization():
+    component = DeepSeekModelComponent()
+    assert component.display_name == "DeepSeek"
+    assert component.description == "Generate text using DeepSeek LLMs."
+    assert component.icon == "DeepSeek"
+
+
+def test_deepseek_template():
+    deepseek = DeepSeekModelComponent()
+    component = Component(_code=deepseek._code)
+    frontend_node, _ = build_custom_component_template(component)
+
+    # Verify basic structure
+    assert isinstance(frontend_node, dict)
+
+    # Verify inputs
+    assert "template" in frontend_node
+    input_names = [input_["name"] for input_ in frontend_node["template"].values() if isinstance(input_, dict)]
+
+    expected_inputs = [
+        "max_tokens",
+        "model_kwargs",
+        "json_mode",
+        "model_name",
+        "api_base",
+        "api_key",
+        "temperature",
+        "seed",
+    ]
+
+    for input_name in expected_inputs:
+        assert input_name in input_names
+
+
+@pytest.mark.parametrize(
+    ("temperature", "max_tokens"),
+    [
+        (0.5, 100),
+        (1.0, 500),
+        (1.5, 1000),
+    ],
+)
+@pytest.fixture
+def mock_chat_openai(mocker):
+    return mocker.patch("langchain_openai.ChatOpenAI")
+
+
+def test_deepseek_build_model(mock_chat_openai):
+    component = DeepSeekModelComponent()
+    component.temperature = 0.7
+    component.max_tokens = 100
+    component.api_key = "test-key"
+
+    # Mock the ChatOpenAI instance
+    mock_instance = MagicMock()
+    mock_chat_openai.return_value = mock_instance
+
+    model = component.build_model()
+
+    # Verify ChatOpenAI was called with correct params
+    mock_chat_openai.assert_called_once_with(
+        max_tokens=100,
+        model_kwargs={},
+        model="deepseek-chat",
+        base_url="https://api.deepseek.com",
+        api_key="test-key",
+        temperature=0.7,
+        seed=1,
+        streaming=False,
+    )
+    assert model == mock_instance
+
+
+def test_deepseek_get_models(mocker):
+    component = DeepSeekModelComponent()
+
+    # Mock requests.get
+    mock_get = mocker.patch("requests.get")
+    mock_response = MagicMock()
+    mock_response.json.return_value = {"data": [{"id": "deepseek-chat"}, {"id": "deepseek-coder"}]}
+    mock_get.return_value = mock_response
+
+    # Test with API key
+    component.api_key = "test-key"
+    models = component.get_models()
+    assert models == ["deepseek-chat", "deepseek-coder"]
+
+    # Verify API call
+    mock_get.assert_called_once_with(
+        "https://api.deepseek.com/models",
+        headers={"Authorization": "Bearer test-key", "Accept": "application/json"},
+        timeout=10,
+    )
+
+
+def test_deepseek_error_handling(mock_chat_openai):
+    component = DeepSeekModelComponent()
+    component.api_key = "invalid-key"
+
+    # Mock ChatOpenAI to raise exception
+    mock_chat_openai.side_effect = Exception("Invalid API key")
+
+    with pytest.raises(Exception, match="Invalid API key"):
+        component.build_model()