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

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* 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>
This commit is contained in:
Edwin Jose 2024-12-16 11:04:24 -05:00 • committed by GitHub
commit 13a468027b
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GPG key ID: B5690EEEBB952194
20 changed files with 4 additions and 159 deletions
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3
src/backend/base/langflow/base/models/model.py
View file

@ -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(

8
src/backend/base/langflow/components/models/aiml.py
View file

@ -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

8
src/backend/base/langflow/components/models/amazon_bedrock.py
View file

@ -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]

8
src/backend/base/langflow/components/models/anthropic.py
View file

@ -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]

8
src/backend/base/langflow/components/models/azure_openai.py
View file

@ -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]

8
src/backend/base/langflow/components/models/baidu_qianfan_chat.py
View file

@ -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]

8
src/backend/base/langflow/components/models/cohere.py
View file

@ -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]

8
src/backend/base/langflow/components/models/google_generative_ai.py
View file

@ -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]

8
src/backend/base/langflow/components/models/groq.py
View file

@ -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]:

8
src/backend/base/langflow/components/models/huggingface.py
View file

@ -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:

8
src/backend/base/langflow/components/models/lmstudiomodel.py
View file

@ -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]

8
src/backend/base/langflow/components/models/maritalk.py
View file

@ -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]

8
src/backend/base/langflow/components/models/mistral.py
View file

@ -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]

8
src/backend/base/langflow/components/models/nvidia.py
View file

@ -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):

8
src/backend/base/langflow/components/models/ollama.py
View file

@ -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,
]

8
src/backend/base/langflow/components/models/perplexity.py
View file

@ -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]

8
src/backend/base/langflow/components/models/sambanova.py
View file

@ -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]

8
src/backend/base/langflow/components/models/vertexai.py
View file

@ -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:

21
src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json
View file

@ -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,

3
src/backend/tests/unit/components/models/test_huggingface.py
View file

@ -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