fix: Add missing inputs for HuggingFace model component and include pytest (#4291)

* fix: Add missing inputs for HuggingFace model component and include pytest

- Added missing inputs to the HuggingFace model component.
- Implemented pytest to ensure the inputs are correctly handled.

* remove print statement

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

@@ -8,7 +8,7 @@ from tenacity import retry, stop_after_attempt, wait_fixed
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
 from langflow.inputs.inputs import HandleInput
-from langflow.io import DictInput, DropdownInput, IntInput, SecretStrInput, StrInput
+from langflow.io import DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
 
 
 class HuggingFaceEndpointsComponent(LCModelComponent):
@@ -20,6 +20,45 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
     inputs = [
         *LCModelComponent._base_inputs,
         StrInput(name="model_id", display_name="Model ID", value="openai-community/gpt2"),
+        IntInput(
+            name="max_new_tokens", display_name="Max New Tokens", value=512, info="Maximum number of generated tokens"
+        ),
+        IntInput(
+            name="top_k",
+            display_name="Top K",
+            advanced=True,
+            info="The number of highest probability vocabulary tokens to keep for top-k-filtering",
+        ),
+        FloatInput(
+            name="top_p",
+            display_name="Top P",
+            value=0.95,
+            advanced=True,
+            info=(
+                "If set to < 1, only the smallest set of most probable tokens with "
+                "probabilities that add up to `top_p` or higher are kept for generation"
+            ),
+        ),
+        FloatInput(
+            name="typical_p",
+            display_name="Typical P",
+            value=0.95,
+            advanced=True,
+            info="Typical Decoding mass.",
+        ),
+        FloatInput(
+            name="temperature",
+            display_name="Temperature",
+            value=0.8,
+            advanced=True,
+            info="The value used to module the logits distribution",
+        ),
+        FloatInput(
+            name="repetition_penalty",
+            display_name="Repetition Penalty",
+            info="The parameter for repetition penalty. 1.0 means no penalty.",
+            advanced=True,
+        ),
         StrInput(
             name="inference_endpoint",
             display_name="Inference Endpoint",

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

@@ -0,0 +1,31 @@
+from langflow.inputs.inputs import DictInput, DropdownInput, FloatInput, HandleInput, IntInput, SecretStrInput, StrInput
+
+from src.backend.base.langflow.components.models.huggingface import HuggingFaceEndpointsComponent
+
+
+def test_huggingface_inputs():
+    component = HuggingFaceEndpointsComponent()
+    inputs = component.inputs
+
+    # Define expected input types and their names
+    expected_inputs = {
+        "model_id": StrInput,
+        "max_new_tokens": IntInput,
+        "top_k": IntInput,
+        "top_p": FloatInput,
+        "typical_p": FloatInput,
+        "temperature": FloatInput,
+        "repetition_penalty": FloatInput,
+        "inference_endpoint": StrInput,
+        "task": DropdownInput,
+        "huggingfacehub_api_token": SecretStrInput,
+        "model_kwargs": DictInput,
+        "retry_attempts": IntInput,
+        "output_parser": HandleInput,
+    }
+
+    # Check if all expected inputs are present
+    for name, input_type in expected_inputs.items():
+        assert any(
+            isinstance(inp, input_type) and inp.name == name for inp in inputs
+        ), f"Missing or incorrect input: {name}"