diff --git a/swiftide/src/transformers/openai_embed.rs b/swiftide/src/transformers/openai_embed.rs
index f5b76017..ea7e8453 100644
--- a/swiftide/src/transformers/openai_embed.rs
+++ b/swiftide/src/transformers/openai_embed.rs
@@ -9,12 +9,25 @@ use anyhow::Result;
 use async_trait::async_trait;
 use futures_util::{stream, StreamExt};
 
+/// A transformer that uses the OpenAI API to generate embeddings for data.
+///
+/// This file defines the `OpenAIEmbed` struct and its implementation of the `BatchableTransformer` trait.
+/// The primary purpose of this transformer is to embed data using the OpenAI API.
 #[derive(Debug)]
 pub struct OpenAIEmbed {
     client: Arc<OpenAI>,
 }
 
 impl OpenAIEmbed {
+    /// Creates a new instance of `OpenAIEmbed`.
+    ///
+    /// # Parameters
+    ///
+    /// * `client` - An instance of the OpenAI client.
+    ///
+    /// # Returns
+    ///
+    /// A new instance of `OpenAIEmbed`.
     pub fn new(client: OpenAI) -> Self {
         Self {
             client: Arc::new(client),
@@ -24,6 +37,19 @@ impl OpenAIEmbed {
 
 #[async_trait]
 impl BatchableTransformer for OpenAIEmbed {
+    /// Transforms a batch of `IngestionNode` objects by generating embeddings for them.
+    ///
+    /// # Parameters
+    ///
+    /// * `nodes` - A vector of `IngestionNode` objects to be transformed.
+    ///
+    /// # Returns
+    ///
+    /// An `IngestionStream` containing the transformed `IngestionNode` objects with their embeddings.
+    ///
+    /// # Errors
+    ///
+    /// If the embedding process fails, the function returns a stream with the error.
     #[tracing::instrument(skip_all, name = "transformers.openai_embed")]
     async fn batch_transform(&self, nodes: Vec<IngestionNode>) -> IngestionStream {
         // TODO: We should drop chunks that go over the token limit of the EmbedModel