fix: fixes agents issue by removing depreciated feature output parser from the LLM Model Components (#5242)

* remove depreciated output parser

* Update model.py

* [autofix.ci] apply automated fixes

* [autofix.ci] apply automated fixes (attempt 2/3)

* Update model.py

* Update src/backend/base/langflow/base/models/model.py

Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>

* [autofix.ci] apply automated fixes

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>

src/backend/base/langflow/base/models/model.py

@@ -175,7 +175,8 @@ class LCModelComponent(Component):
             messages.insert(0, SystemMessage(content=system_message))
         inputs: list | dict = messages or {}
         try:
-            if self.output_parser is not None:
+            # TODO: Depreciated Feature to be removed in upcoming release
+            if hasattr(self, "output_parser") and self.output_parser is not None:
                 runnable |= self.output_parser
 
             runnable = runnable.with_config(

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

@@ -7,7 +7,6 @@ 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 DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
-from langflow.inputs.inputs import HandleInput
 
 
 class AIMLModelComponent(LCModelComponent):
@@ -49,13 +48,6 @@ class AIMLModelComponent(LCModelComponent):
             value="AIML_API_KEY",
         ),
         FloatInput(name="temperature", display_name="Temperature", value=0.1),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     @override

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

@@ -2,7 +2,6 @@ from langflow.base.models.aws_constants import AWS_REGIONS, AWS_MODEL_IDs
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
 from langflow.inputs import MessageTextInput, SecretStrInput
-from langflow.inputs.inputs import HandleInput
 from langflow.io import DictInput, DropdownInput
 
 
@@ -73,13 +72,6 @@ class AmazonBedrockComponent(LCModelComponent):
             advanced=True,
             info="The URL of the Bedrock endpoint to use.",
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,7 +3,6 @@ from pydantic.v1 import SecretStr
 from langflow.base.models.anthropic_constants import ANTHROPIC_MODELS
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput
 
 
@@ -40,13 +39,6 @@ class AnthropicModelComponent(LCModelComponent):
         MessageTextInput(
             name="prefill", display_name="Prefill", info="Prefill text to guide the model's response.", advanced=True
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,7 +3,6 @@ from langchain_openai import AzureChatOpenAI
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
 from langflow.inputs import MessageTextInput
-from langflow.inputs.inputs import HandleInput
 from langflow.io import DropdownInput, FloatInput, IntInput, SecretStrInput
 
 
@@ -57,13 +56,6 @@ class AzureChatOpenAIComponent(LCModelComponent):
             advanced=True,
             info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,7 +3,6 @@ from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing.constants import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import DropdownInput, FloatInput, MessageTextInput, SecretStrInput
 
 
@@ -67,13 +66,6 @@ class QianfanChatEndpointComponent(LCModelComponent):
         MessageTextInput(
             name="endpoint", display_name="Endpoint", info="Endpoint of the Qianfan LLM, required if custom model used."
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,7 +3,6 @@ from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import FloatInput, SecretStrInput
 
 
@@ -24,13 +23,6 @@ class CohereComponent(LCModelComponent):
             value="COHERE_API_KEY",
         ),
         FloatInput(name="temperature", display_name="Temperature", value=0.75),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -4,7 +4,6 @@ from langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIV
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
 from langflow.inputs import DropdownInput, FloatInput, IntInput, SecretStrInput
-from langflow.inputs.inputs import HandleInput
 
 
 class GoogleGenerativeAIComponent(LCModelComponent):
@@ -50,13 +49,6 @@ class GoogleGenerativeAIComponent(LCModelComponent):
             info="Decode using top-k sampling: consider the set of top_k most probable tokens. Must be positive.",
             advanced=True,
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -5,7 +5,6 @@ from typing_extensions import override
 from langflow.base.models.groq_constants import GROQ_MODELS
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput
 
 
@@ -52,13 +51,6 @@ class GroqModel(LCModelComponent):
             value="llama-3.1-8b-instant",
             refresh_button=True,
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def get_models(self) -> list[str]:

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

@@ -7,7 +7,6 @@ from tenacity import retry, stop_after_attempt, wait_fixed
 #  Need to update to langchain_huggingface, but have dependency with langchain_core 0.3.0
 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, FloatInput, IntInput, SecretStrInput, StrInput
 
 
@@ -75,13 +74,6 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
         SecretStrInput(name="huggingfacehub_api_token", display_name="API Token", password=True),
         DictInput(name="model_kwargs", display_name="Model Keyword Arguments", advanced=True),
         IntInput(name="retry_attempts", display_name="Retry Attempts", value=1, advanced=True),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def get_api_url(self) -> str:

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

@@ -9,7 +9,6 @@ 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 DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
-from langflow.inputs.inputs import HandleInput
 
 
 class LMStudioModelComponent(LCModelComponent):
@@ -84,13 +83,6 @@ class LMStudioModelComponent(LCModelComponent):
             advanced=True,
             value=1,
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -4,7 +4,6 @@ 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 DropdownInput, FloatInput, IntInput, SecretStrInput
-from langflow.inputs.inputs import HandleInput
 
 
 class MaritalkModelComponent(LCModelComponent):
@@ -35,13 +34,6 @@ class MaritalkModelComponent(LCModelComponent):
             advanced=False,
         ),
         FloatInput(name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=1)),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,7 +3,6 @@ from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
 
 
@@ -55,13 +54,6 @@ class MistralAIModelComponent(LCModelComponent):
         FloatInput(name="top_p", display_name="Top P", advanced=True, value=1),
         IntInput(name="random_seed", display_name="Random Seed", value=1, advanced=True),
         BoolInput(name="safe_mode", display_name="Safe Mode", advanced=True),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,7 +3,6 @@ from typing import Any
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
 from langflow.inputs import DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
-from langflow.inputs.inputs import HandleInput
 from langflow.schema.dotdict import dotdict
 
 
@@ -49,13 +48,6 @@ class NVIDIAModelComponent(LCModelComponent):
             advanced=True,
             value=1,
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):

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

@@ -6,7 +6,6 @@ from langchain_ollama import ChatOllama
 
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, StrInput
 
 
@@ -166,13 +165,6 @@ class ChatOllamaComponent(LCModelComponent):
         ),
         StrInput(name="system", display_name="System", info="System to use for generating text.", advanced=True),
         StrInput(name="template", display_name="Template", info="Template to use for generating text.", advanced=True),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
         *LCModelComponent._base_inputs,
     ]
 

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

@@ -3,7 +3,6 @@ from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import DropdownInput, FloatInput, IntInput, SecretStrInput
 
 
@@ -60,13 +59,6 @@ class PerplexityComponent(LCModelComponent):
             info="Decode using top-k sampling: consider the set of top_k most probable tokens. Must be positive.",
             advanced=True,
         ),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -4,7 +4,6 @@ from pydantic.v1 import SecretStr
 from langflow.base.models.model import LCModelComponent
 from langflow.base.models.sambanova_constants import SAMBANOVA_MODEL_NAMES
 from langflow.field_typing import LanguageModel
-from langflow.inputs.inputs import HandleInput
 from langflow.io import DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
 
 
@@ -47,13 +46,6 @@ class SambaNovaComponent(LCModelComponent):
             info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
         ),
         FloatInput(name="temperature", display_name="Temperature", value=0.07),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,7 +3,6 @@ from typing import cast
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
 from langflow.inputs import MessageTextInput
-from langflow.inputs.inputs import HandleInput
 from langflow.io import BoolInput, FileInput, FloatInput, IntInput, StrInput
 
 
@@ -30,13 +29,6 @@ class ChatVertexAIComponent(LCModelComponent):
         IntInput(name="top_k", display_name="Top K", advanced=True),
         FloatInput(name="top_p", display_name="Top P", value=0.95, advanced=True),
         BoolInput(name="verbose", display_name="Verbose", value=False, advanced=True),
-        HandleInput(
-            name="output_parser",
-            display_name="Output Parser",
-            info="The parser to use to parse the output of the model",
-            advanced=True,
-            input_types=["OutputParser"],
-        ),
     ]
 
     def build_model(self) -> LanguageModel:

src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json

@@ -1433,7 +1433,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from pydantic.v1 import SecretStr\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs.inputs import HandleInput\nfrom langflow.io import DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass AnthropicModelComponent(LCModelComponent):\n    display_name = \"Anthropic\"\n    description = \"Generate text using Anthropic Chat&Completion LLMs with prefill support.\"\n    icon = \"Anthropic\"\n    name = \"AnthropicModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            value=4096,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n        ),\n        DropdownInput(\n            name=\"model\",\n            display_name=\"Model Name\",\n            options=ANTHROPIC_MODELS,\n            info=\"https://python.langchain.com/docs/integrations/chat/anthropic\",\n            value=\"claude-3-5-sonnet-latest\",\n        ),\n        SecretStrInput(name=\"anthropic_api_key\", display_name=\"Anthropic API Key\", info=\"Your Anthropic API key.\"),\n        FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n        MessageTextInput(\n            name=\"anthropic_api_url\",\n            display_name=\"Anthropic API URL\",\n            advanced=True,\n            info=\"Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.\",\n        ),\n        MessageTextInput(\n            name=\"prefill\", display_name=\"Prefill\", info=\"Prefill text to guide the model's response.\", advanced=True\n        ),\n        HandleInput(\n            name=\"output_parser\",\n            display_name=\"Output Parser\",\n            info=\"The parser to use to parse the output of the model\",\n            advanced=True,\n            input_types=[\"OutputParser\"],\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        try:\n            from langchain_anthropic.chat_models import ChatAnthropic\n        except ImportError as e:\n            msg = \"langchain_anthropic is not installed. Please install it with `pip install langchain_anthropic`.\"\n            raise ImportError(msg) from e\n        model = self.model\n        anthropic_api_key = self.anthropic_api_key\n        max_tokens = self.max_tokens\n        temperature = self.temperature\n        anthropic_api_url = self.anthropic_api_url or \"https://api.anthropic.com\"\n\n        try:\n            output = ChatAnthropic(\n                model=model,\n                anthropic_api_key=(SecretStr(anthropic_api_key).get_secret_value() if anthropic_api_key else None),\n                max_tokens_to_sample=max_tokens,\n                temperature=temperature,\n                anthropic_api_url=anthropic_api_url,\n                streaming=self.stream,\n            )\n        except Exception as e:\n            msg = \"Could not connect to Anthropic API.\"\n            raise ValueError(msg) from e\n\n        return output\n\n    def _get_exception_message(self, exception: Exception) -> str | None:\n        \"\"\"Get a message from an Anthropic exception.\n\n        Args:\n            exception (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from anthropic import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(exception, BadRequestError):\n            message = exception.body.get(\"error\", {}).get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from pydantic.v1 import SecretStr\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import LanguageModel\nfrom langflow.io import DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass AnthropicModelComponent(LCModelComponent):\n    display_name = \"Anthropic\"\n    description = \"Generate text using Anthropic Chat&Completion LLMs with prefill support.\"\n    icon = \"Anthropic\"\n    name = \"AnthropicModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            value=4096,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n        ),\n        DropdownInput(\n            name=\"model\",\n            display_name=\"Model Name\",\n            options=ANTHROPIC_MODELS,\n            info=\"https://python.langchain.com/docs/integrations/chat/anthropic\",\n            value=\"claude-3-5-sonnet-latest\",\n        ),\n        SecretStrInput(name=\"anthropic_api_key\", display_name=\"Anthropic API Key\", info=\"Your Anthropic API key.\"),\n        FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n        MessageTextInput(\n            name=\"anthropic_api_url\",\n            display_name=\"Anthropic API URL\",\n            advanced=True,\n            info=\"Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.\",\n        ),\n        MessageTextInput(\n            name=\"prefill\", display_name=\"Prefill\", info=\"Prefill text to guide the model's response.\", advanced=True\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        try:\n            from langchain_anthropic.chat_models import ChatAnthropic\n        except ImportError as e:\n            msg = \"langchain_anthropic is not installed. Please install it with `pip install langchain_anthropic`.\"\n            raise ImportError(msg) from e\n        model = self.model\n        anthropic_api_key = self.anthropic_api_key\n        max_tokens = self.max_tokens\n        temperature = self.temperature\n        anthropic_api_url = self.anthropic_api_url or \"https://api.anthropic.com\"\n\n        try:\n            output = ChatAnthropic(\n                model=model,\n                anthropic_api_key=(SecretStr(anthropic_api_key).get_secret_value() if anthropic_api_key else None),\n                max_tokens_to_sample=max_tokens,\n                temperature=temperature,\n                anthropic_api_url=anthropic_api_url,\n                streaming=self.stream,\n            )\n        except Exception as e:\n            msg = \"Could not connect to Anthropic API.\"\n            raise ValueError(msg) from e\n\n        return output\n\n    def _get_exception_message(self, exception: Exception) -> str | None:\n        \"\"\"Get a message from an Anthropic exception.\n\n        Args:\n            exception (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from anthropic import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(exception, BadRequestError):\n            message = exception.body.get(\"error\", {}).get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1498,25 +1498,6 @@
                 "type": "str",
                 "value": "claude-3-5-sonnet-20240620"
               },
-              "output_parser": {
-                "_input_type": "HandleInput",
-                "advanced": true,
-                "display_name": "Output Parser",
-                "dynamic": false,
-                "info": "The parser to use to parse the output of the model",
-                "input_types": [
-                  "OutputParser"
-                ],
-                "list": false,
-                "name": "output_parser",
-                "placeholder": "",
-                "required": false,
-                "show": true,
-                "title_case": false,
-                "trace_as_metadata": true,
-                "type": "other",
-                "value": ""
-              },
               "prefill": {
                 "_input_type": "MessageTextInput",
                 "advanced": true,

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

@@ -1,5 +1,5 @@
 from langflow.components.models.huggingface import HuggingFaceEndpointsComponent
-from langflow.inputs.inputs import DictInput, DropdownInput, FloatInput, HandleInput, IntInput, SecretStrInput, StrInput
+from langflow.inputs.inputs import DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
 
 
 def test_huggingface_inputs():
@@ -20,7 +20,6 @@ def test_huggingface_inputs():
         "huggingfacehub_api_token": SecretStrInput,
         "model_kwargs": DictInput,
         "retry_attempts": IntInput,
-        "output_parser": HandleInput,
     }
 
     # Check if all expected inputs are present