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fix: change lambda filter to smart function (#8558)

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* change lambda filter nme

* reverse change for lambda filter

---------

Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>
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Yuqi Tang 2025-06-20 11:52:11 -07:00 • committed by GitHub
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16
docs/docs/Components/components-processing.md
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@ -21,15 +21,15 @@ This component performs operations on [DataFrame](https://pandas.pydata.org/docs
To use this component in a flow, connect a component that outputs [DataFrame](/concepts-objects#dataframe-object) to the **DataFrame Operations** component.
This example fetches JSON data from an API. The **Lambda filter** component extracts and flattens the results into a tabular DataFrame. The **DataFrame Operations** component can then work with the retrieved data.
This example fetches JSON data from an API. The **Smart function** component extracts and flattens the results into a tabular DataFrame. The **DataFrame Operations** component can then work with the retrieved data.
![Dataframe operations with flattened dataframe](/img/component-dataframe-operations.png)
1. The **API Request** component retrieves data with only `source` and `result` fields.
For this example, the desired data is nested within the `result` field.
2. Connect a **Lambda Filter** to the API request component, and a **Language model** to the **Lambda Filter**. This example connects a **Groq** model component.
2. Connect a **Smart function** to the API request component, and a **Language model** to the **Smart function**. This example connects a **Groq** model component.
3. In the **Groq** model component, add your **Groq** API key.
4. To filter the data, in the **Lambda filter** component, in the **Instructions** field, use natural language to describe how the data should be filtered.
4. To filter the data, in the **Smart function** component, in the **Instructions** field, use natural language to describe how the data should be filtered.
For this example, enter:
```
I want to explode the result column out into a Data object
@ -37,8 +37,8 @@ I want to explode the result column out into a Data object
:::tip
Avoid punctuation in the **Instructions** field, as it can cause errors.
:::
5. To run the flow, in the **Lambda Filter** component, click <Icon name="Play" aria-label="Play icon" />.
6. To inspect the filtered data, in the **Lambda Filter** component, click <Icon name="TextSearch" aria-label="Inspect icon" />.
5. To run the flow, in the **Smart function** component, click <Icon name="Play" aria-label="Play icon" />.
6. To inspect the filtered data, in the **Smart function** component, click <Icon name="TextSearch" aria-label="Inspect icon" />.
The result is a structured DataFrame.
```text
id | name | company | username | email | address | zip
@ -263,14 +263,14 @@ curl -X POST "http://localhost:7860/api/v1/webhook/YOUR_FLOW_ID" \
</details>
## Lambda filter
## Smart function
This component uses an LLM to generate a Lambda function for filtering or transforming structured data.
To use the **Lambda filter** component, you must connect it to a [Language Model](/components-models#language-model) component, which the component uses to generate a function based on the natural language instructions in the **Instructions** field.
To use the **Smart function** component, you must connect it to a [Language Model](/components-models#language-model) component, which the component uses to generate a function based on the natural language instructions in the **Instructions** field.
This example gets JSON data from the `https://jsonplaceholder.typicode.com/users` API endpoint.
The **Instructions** field in the **Lambda filter** component specifies the task `extract emails`.
The **Instructions** field in the **Smart function** component specifies the task `extract emails`.
The connected LLM creates a filter based on the instructions, and successfully extracts a list of email addresses from the JSON data.
![](/img/component-lambda-filter.png)

11
src/backend/base/langflow/components/processing/lambda_filter.py
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@ -7,7 +7,6 @@ from typing import TYPE_CHECKING, Any
from langflow.custom.custom_component.component import Component
from langflow.io import DataInput, HandleInput, IntInput, MultilineInput, Output
from langflow.schema.data import Data
from langflow.schema.dataframe import DataFrame
from langflow.utils.data_structure import get_data_structure
if TYPE_CHECKING:
@ -67,11 +66,6 @@ class LambdaFilterComponent(Component):
name="filtered_data",
method="filter_data",
),
Output(
display_name="DataFrame",
name="dataframe",
method="as_dataframe",
),
]
def get_data_structure(self, data):
@ -157,8 +151,3 @@ class LambdaFilterComponent(Component):
return [Data(**item) if isinstance(item, dict) else Data(text=str(item)) for item in processed_data]
# If it's anything else, convert to string and wrap in a Data object
return [Data(text=str(processed_data))]
async def as_dataframe(self) -> DataFrame:
"""Return filtered data as a DataFrame."""
filtered_data = await self.filter_data()
return DataFrame(filtered_data)