refactor: rename model.max_concurrent_chunks to model.max_batch_size (#626)

3 files changed, 12 insertions, 12 deletions

diff --git a/src/client/common.rs b/src/client/common.rs
index de2fa50..796c632 100644
--- a/src/client/common.rs
+++ b/src/client/common.rs
@@ -392,7 +392,7 @@ pub trait Client: Sync + Send {
 
     async fn embeddings(&self, data: EmbeddingsData) -> Result<Vec<Vec<f32>>> {
         let client = self.build_client()?;
-        self.model().guard_max_concurrent_chunks(&data)?;
+        self.model().guard_max_batch_size(&data)?;
         self.embeddings_inner(&client, data)
             .await
             .context("Failed to fetch embeddings")
diff --git a/src/client/model.rs b/src/client/model.rs
index 0584f82..4c69d78 100644
--- a/src/client/model.rs
+++ b/src/client/model.rs
@@ -175,8 +175,8 @@ impl Model {
         self.data.default_chunk_size.unwrap_or(1000)
     }
 
-    pub fn max_concurrent_chunks(&self) -> usize {
-        self.data.max_concurrent_chunks.unwrap_or(1)
+    pub fn max_batch_size(&self) -> usize {
+        self.data.max_batch_size.unwrap_or(1)
     }
 
     pub fn max_tokens_param(&self) -> Option<isize> {
@@ -234,9 +234,9 @@ impl Model {
         Ok(())
     }
 
-    pub fn guard_max_concurrent_chunks(&self, data: &EmbeddingsData) -> Result<()> {
-        if data.texts.len() > self.max_concurrent_chunks() {
-            bail!("Exceed max_concurrent_chunks limit");
+    pub fn guard_max_batch_size(&self, data: &EmbeddingsData) -> Result<()> {
+        if data.texts.len() > self.max_batch_size() {
+            bail!("Exceed max_batch_size limit");
         }
         Ok(())
     }
@@ -262,7 +262,7 @@ pub struct ModelData {
 
     // embedding-only properties
     pub default_chunk_size: Option<usize>,
-    pub max_concurrent_chunks: Option<usize>,
+    pub max_batch_size: Option<usize>,
 }
 
 impl ModelData {
diff --git a/src/rag/mod.rs b/src/rag/mod.rs
index 628a9e4..116beea 100644
--- a/src/rag/mod.rs
+++ b/src/rag/mod.rs
@@ -414,13 +414,13 @@ impl Rag {
     ) -> Result<EmbeddingsOutput> {
         let EmbeddingsData { texts, query } = data;
         let mut output = vec![];
-        let chunks = texts.chunks(self.embedding_model.max_concurrent_chunks());
-        let chunks_len = chunks.len();
+        let batch_chunks = texts.chunks(self.embedding_model.max_batch_size());
+        let batch_chunks_len = batch_chunks.len();
         progress(
             &progress_tx,
-            format!("Creating embeddings [1/{chunks_len}]"),
+            format!("Creating embeddings [1/{batch_chunks_len}]"),
         );
-        for (index, texts) in chunks.enumerate() {
+        for (index, texts) in batch_chunks.enumerate() {
             let chunk_data = EmbeddingsData {
                 texts: texts.to_vec(),
                 query,
@@ -433,7 +433,7 @@ impl Rag {
             output.extend(chunk_output);
             progress(
                 &progress_tx,
-                format!("Creating embeddings [{}/{chunks_len}]", index + 1),
+                format!("Creating embeddings [{}/{batch_chunks_len}]", index + 1),
             );
         }
         Ok(output)