indexers.dataclasses.VectorStoreEmbedOutput
indexers.dataclasses.VectorStoreEmbedOutput(data)DataFrame-like object for storing and validating embedded vectors.
This class represents the output of embedding operations, containing the original text data, computed vector embeddings, and associated metadata.
Attributes
| Name | Type | Description |
|---|---|---|
| id | pd.Series | Unique identifier for each embedded item. |
| text | pd.Series | The original text that was embedded. |
| embedding | pd.Series | The computed vector embedding (numpy array). |
Methods
| Name | Description |
|---|---|
| from_data | Create a validated VectorStoreEmbedOutput from a dictionary or DataFrame. |
| validate | Validate an existing DataFrame and return a VectorStoreEmbedOutput. |
from_data
indexers.dataclasses.VectorStoreEmbedOutput.from_data(data)Create a validated VectorStoreEmbedOutput from a dictionary or DataFrame.
Creates a new instance of VectorStoreEmbedOutput by validating the input data against the defined schema.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| data | dict | pd.DataFrame | A dictionary or pandas DataFrame containing the input data. Must include ‘id’, ‘text’, and ‘embedding’ columns/keys. | required |
Returns
| Name | Type | Description |
|---|---|---|
| VectorStoreEmbedOutput | VectorStoreEmbedOutput | A validated instance of the class. |
validate
indexers.dataclasses.VectorStoreEmbedOutput.validate(df)Validate an existing DataFrame and return a VectorStoreEmbedOutput.
Validates the provided pandas DataFrame against the defined schema and returns a new instance of VectorStoreEmbedOutput if validation is successful.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| df | pd.DataFrame | A pandas DataFrame to validate. Must include ‘id’, ‘text’, and ‘embedding’ columns. | required |
Returns
| Name | Type | Description |
|---|---|---|
| VectorStoreEmbedOutput | VectorStoreEmbedOutput | A validated instance of the class. |