feat: add csv output parser

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

@@ -5,6 +5,7 @@
 
 from langchain_core.language_models.llms import LLM
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
+from langchain_core.output_parsers import BaseOutputParser
 
 from langflow.base.constants import STREAM_INFO_TEXT
 from langflow.custom import Component
@@ -20,6 +21,9 @@ class LCModelComponent(Component):
     description: str = "Model Description"
     trace_type = "llm"
 
+    # Optional output parser to pass to the runnable. Subclasses may allow the user to input an `output_parser`
+    output_parser: BaseOutputParser | None = None
+
     _base_inputs: List[InputTypes] = [
         MessageInput(name="input_value", display_name="Input"),
         MessageTextInput(
@@ -163,6 +167,9 @@ def get_chat_result(
             messages.append(SystemMessage(content=system_message))
         inputs: Union[list, dict] = messages or {}
         try:
+            if self.output_parser is not None:
+                runnable = runnable | self.output_parser
+
             runnable = runnable.with_config(  # type: ignore
                 {
                     "run_name": self.display_name,

src/backend/base/langflow/base/prompts/api_utils.py

@@ -221,20 +221,4 @@ def process_prompt_template(
     # Update the input variables field in the template
     update_input_variables_field(input_variables, frontend_node_template)
 
-    # Optional: cleanup fields based on specific conditions
-    cleanup_prompt_template_fields(input_variables, frontend_node_template)
-
     return input_variables
-
-
-def cleanup_prompt_template_fields(input_variables, template):
-    """Removes unused fields if the conditions are met in the template."""
-    prompt_fields = [
-        key for key, field in template.items() if isinstance(field, dict) and field.get("type") == "prompt"
-    ]
-
-    if len(prompt_fields) == 1:
-        for key in list(template.keys()):  # Use list to copy keys
-            field = template.get(key, {})
-            if isinstance(field, dict) and field.get("type") != "code" and key not in input_variables + prompt_fields:
-                del template[key]

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

@@ -31,6 +31,7 @@
     "link_extractors",
     "memories",
     "outputs",
+    "output_parsers",
     "retrievers",
     "textsplitters",
     "toolkits",

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

@@ -1,5 +1,6 @@
 from langflow.field_typing.range_spec import RangeSpec
 from langchain_openai import ChatOpenAI
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.aiml_constants import AIML_CHAT_MODELS
@@ -59,6 +60,13 @@ class AIMLModelComponent(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/AmazonBedrockModel.py

@@ -1,6 +1,7 @@
 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
 
 
@@ -55,6 +56,13 @@ class AmazonBedrockComponent(LCModelComponent):
         MessageTextInput(name="region_name", display_name="Region Name", value="us-east-1"),
         DictInput(name="model_kwargs", display_name="Model Kwargs", advanced=True, is_list=True),
         MessageTextInput(name="endpoint_url", display_name="Endpoint URL", 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/AnthropicModel.py

@@ -1,3 +1,4 @@
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
@@ -49,6 +50,13 @@ class AnthropicModelComponent(LCModelComponent):
             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/AzureOpenAIModel.py

@@ -2,6 +2,7 @@
 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
 
 
@@ -47,6 +48,13 @@ 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/BaiduQianfanChatModel.py

@@ -1,4 +1,5 @@
 from langchain_community.chat_models.baidu_qianfan_endpoint import QianfanChatEndpoint
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
@@ -67,6 +68,13 @@ class QianfanChatEndpointComponent(LCModelComponent):
             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/CohereModel.py

@@ -1,4 +1,5 @@
 from langchain_cohere import ChatCohere
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
@@ -22,6 +23,13 @@ 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/GoogleGenerativeAIModel.py

@@ -1,3 +1,4 @@
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
@@ -48,6 +49,13 @@ 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/GroqModel.py

@@ -1,3 +1,4 @@
+from langflow.inputs.inputs import HandleInput
 import requests
 from typing import List
 from langchain_groq import ChatGroq
@@ -52,6 +53,13 @@ class GroqModel(LCModelComponent):
             options=[],
             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/HuggingFaceModel.py

@@ -1,3 +1,4 @@
+from langflow.inputs.inputs import HandleInput
 from tenacity import retry, stop_after_attempt, wait_fixed
 from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
 
@@ -27,6 +28,13 @@ 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 create_huggingface_endpoint(

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

@@ -4,6 +4,7 @@
 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):
@@ -33,6 +34,13 @@ 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/MistralModel.py

@@ -1,4 +1,5 @@
 from langchain_mistralai import ChatMistralAI
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
@@ -55,6 +56,13 @@ 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/NvidiaModel.py

@@ -3,6 +3,7 @@
 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
 
 
@@ -47,6 +48,13 @@ 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/OllamaModel.py

@@ -6,6 +6,7 @@
 
 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
 
 
@@ -204,6 +205,13 @@ def get_model(self, base_url_value: str) -> list[str]:
             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"],
+        ),
     ]
 
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

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

@@ -3,6 +3,7 @@
 
 from langflow.field_typing.range_spec import RangeSpec
 from langchain_openai import ChatOpenAI
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
@@ -75,6 +76,13 @@ class OpenAIModelComponent(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/PerplexityModel.py

@@ -1,4 +1,5 @@
 from langchain_community.chat_models import ChatPerplexity
+from langflow.inputs.inputs import HandleInput
 from pydantic.v1 import SecretStr
 
 from langflow.base.models.model import LCModelComponent
@@ -59,6 +60,13 @@ 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/VertexAiModel.py

@@ -3,6 +3,7 @@
 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
 
 
@@ -28,6 +29,13 @@ 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: