corgy-w commented on code in PR #7534:
URL: https://github.com/apache/seatunnel/pull/7534#discussion_r1740838060
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docs/en/transform-v2/embedding.md:
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+# Embedding
+
+> Embedding Transform Plugin
+
+## Description
+
+The `Embedding` transform plugin leverages embedding models to convert text
data into vectorized representations. This
+transformation can be applied to various fields. The plugin supports multiple
model providers and can be integrated with
+different API endpoints.
+
+## Options
+
+| Name | Type | Required | Default Value |
Description
|
+|--------------------------------|--------|----------|---------------|-------------------------------------------------------------------------------------------------------------|
+| model_provider | enum | yes | - | The
model provider for embedding. Options may include `QIANFAN`, `OPENAI`, etc.
|
+| api_key | string | yes | - | The API
key required to authenticate with the embedding service.
|
+| secret_key | string | yes | - | The
secret key required for additional authentication with the embedding service.
|
+| single_vectorized_input_number | int | no | 1 | The
number of inputs vectorized in one request. Default is 1.
|
+| vectorization_fields | map | yes | - | A
mapping between input fields and their corresponding output vector fields.
|
+| model | string | yes | - | The
specific model to use for embedding (e.g: `text-embedding-3-small` for OPENAI).
|
+| api_path | string | no | - | The API
endpoint for the embedding service. Typically provided by the model provider.
|
+| oauth_path | string | no | - | The API
endpoint for the oauth service.
|
+| custom_config | map | no | | Custom
configurations for the model.
|
+| custom_response_parse | string | no | |
Specifies how to parse the response from the model using JsonPath. Example:
`$.choices[*].message.content`. |
+| custom_request_headers | map | no | | Custom
headers for the request to the model.
|
+| custom_request_body | map | no | | Custom
body for the request. Supports placeholders like `${model}`, `${input}`,
`${prompt}`. |
+
+### model_provider
+
+The model provider to use for generating embeddings. Common options might
include `QIANFAN`, `OPENAI`, etc. Depending on
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