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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. 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) ![Dataframe operations with flattened dataframe](/img/component-dataframe-operations.png)
1. The **API Request** component retrieves data with only `source` and `result` fields. 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. 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. 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: For this example, enter:
``` ```
I want to explode the result column out into a Data object 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 :::tip
Avoid punctuation in the **Instructions** field, as it can cause errors. 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" />. 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 **Lambda Filter** component, click <Icon name="TextSearch" aria-label="Inspect 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. The result is a structured DataFrame.
```text ```text
id | name | company | username | email | address | zip id | name | company | username | email | address | zip
@ -263,14 +263,14 @@ curl -X POST "http://localhost:7860/api/v1/webhook/YOUR_FLOW_ID" \
</details> </details>
## Lambda filter ## Smart function
This component uses an LLM to generate a Lambda function for filtering or transforming structured data. 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. 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. 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) ![](/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.custom.custom_component.component import Component
from langflow.io import DataInput, HandleInput, IntInput, MultilineInput, Output from langflow.io import DataInput, HandleInput, IntInput, MultilineInput, Output
from langflow.schema.data import Data from langflow.schema.data import Data
from langflow.schema.dataframe import DataFrame
from langflow.utils.data_structure import get_data_structure from langflow.utils.data_structure import get_data_structure
if TYPE_CHECKING: if TYPE_CHECKING:
@ -67,11 +66,6 @@ class LambdaFilterComponent(Component):
name="filtered_data", name="filtered_data",
method="filter_data", method="filter_data",
), ),
Output(
display_name="DataFrame",
name="dataframe",
method="as_dataframe",
),
] ]
def get_data_structure(self, data): 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] 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 # If it's anything else, convert to string and wrap in a Data object
return [Data(text=str(processed_data))] 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)