feat: Removed duplication of batch_size. Pipeline owns the default ba…

…tch size value and Embeed/SparseEmbed are able to modify it. Fixes bosun-ai#233

examples/fastembed.rs

@@ -27,7 +27,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         .to_owned();
 
     indexing::Pipeline::from_loader(FileLoader::new(".").with_extensions(&["rs"]))
-        .then_in_batch(10, Embed::new(FastEmbed::builder().batch_size(10).build()?))
+        .then_in_batch(Embed::new(FastEmbed::builder().batch_size(10).build()?))
         .then_store_with(
             Qdrant::try_from_url(qdrant_url)?
                 .batch_size(50)

examples/fluvio.rs

@@ -48,7 +48,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         .unwrap();
 
     indexing::Pipeline::from_loader(loader)
-        .then_in_batch(10, Embed::new(FastEmbed::try_default().unwrap()))
+        .then_in_batch(Embed::new(FastEmbed::try_default().unwrap()).with_batch_size(10))
         .then_store_with(
             Qdrant::builder()
                 .batch_size(50)

examples/hybrid_search.rs

@@ -23,14 +23,8 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     // Ensure all batching is consistent
     let batch_size = 64;
 
-    let fastembed_sparse = FastEmbed::try_default_sparse()
-        .unwrap()
-        .with_batch_size(batch_size)
-        .to_owned();
-    let fastembed = FastEmbed::try_default()
-        .unwrap()
-        .with_batch_size(batch_size)
-        .to_owned();
+    let fastembed_sparse = FastEmbed::try_default_sparse().unwrap().to_owned();
+    let fastembed = FastEmbed::try_default().unwrap().to_owned();
 
     // Set up openai with the mini model, which is great for indexing
     let openai = openai::OpenAI::builder()
@@ -57,10 +51,9 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         // Generate metadata on the code chunks to increase our chances of finding the right code
         .then(MetadataQACode::from_client(openai.clone()).build().unwrap())
         .then_in_batch(
-            batch_size,
-            transformers::SparseEmbed::new(fastembed_sparse.clone()),
+            transformers::SparseEmbed::new(fastembed_sparse.clone()).with_batch_size(batch_size),
         )
-        .then_in_batch(batch_size, transformers::Embed::new(fastembed.clone()))
+        .then_in_batch(transformers::Embed::new(fastembed.clone()).with_batch_size(batch_size))
         .then_store_with(qdrant.clone())
         .run()
         .await?;

examples/index_codebase.rs

@@ -47,7 +47,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
             "rust",
             10..2048,
         )?)
-        .then_in_batch(10, Embed::new(openai_client.clone()))
+        .then_in_batch(Embed::new(openai_client.clone()).with_batch_size(10))
         .then_store_with(
             Qdrant::builder()
                 .batch_size(50)

examples/index_codebase_reduced_context.rs

@@ -61,7 +61,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         .then(indexing::transformers::CompressCodeOutline::new(
             openai_client.clone(),
         ))
-        .then_in_batch(10, Embed::new(openai_client.clone()))
+        .then_in_batch(Embed::new(openai_client.clone()).with_batch_size(10))
         .then_store_with(
             Qdrant::builder()
                 .batch_size(50)

examples/index_groq.rs

@@ -35,7 +35,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     indexing::Pipeline::from_loader(FileLoader::new("README.md"))
         .then_chunk(ChunkMarkdown::from_chunk_range(10..2048))
         .then(MetadataQAText::new(groq_client.clone()))
-        .then_in_batch(10, Embed::new(fastembed))
+        .then_in_batch(Embed::new(fastembed).with_batch_size(10))
         .then_store_with(memory_store.clone())
         .run()
         .await?;

examples/index_markdown_lots_of_metadata.rs

@@ -40,7 +40,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         .then(MetadataSummary::new(openai_client.clone()))
         .then(MetadataTitle::new(openai_client.clone()))
         .then(MetadataKeywords::new(openai_client.clone()))
-        .then_in_batch(10, Embed::new(openai_client.clone()))
+        .then_in_batch(Embed::new(openai_client.clone()))
         .log_all()
         .filter_errors()
         .then_store_with(

examples/index_ollama.rs

@@ -35,7 +35,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     indexing::Pipeline::from_loader(FileLoader::new("README.md"))
         .then_chunk(ChunkMarkdown::from_chunk_range(10..2048))
         .then(MetadataQAText::new(ollama_client.clone()))
-        .then_in_batch(10, Embed::new(fastembed))
+        .then_in_batch(Embed::new(fastembed).with_batch_size(10))
         .then_store_with(memory_store.clone())
         .run()
         .await?;

examples/lancedb.rs

@@ -40,7 +40,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     indexing::Pipeline::from_loader(FileLoader::new("README.md"))
         .then_chunk(ChunkMarkdown::from_chunk_range(10..2048))
         .then(MetadataQAText::new(openai_client.clone()))
-        .then_in_batch(10, Embed::new(openai_client.clone()))
+        .then_in_batch(Embed::new(openai_client.clone()).with_batch_size(10))
         .then_store_with(lancedb.clone())
         .run()
         .await?;

examples/query_pipeline.rs

@@ -26,7 +26,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     indexing::Pipeline::from_loader(FileLoader::new("README.md"))
         .then_chunk(ChunkMarkdown::from_chunk_range(10..2048))
         .then(MetadataQAText::new(openai_client.clone()))
-        .then_in_batch(10, Embed::new(openai_client.clone()))
+        .then_in_batch(Embed::new(openai_client.clone()).with_batch_size(10))
         .then_store_with(qdrant.clone())
         .run()
         .await?;

examples/store_multiple_vectors.rs

@@ -46,7 +46,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
         .then(MetadataSummary::new(openai_client.clone()))
         .then(MetadataTitle::new(openai_client.clone()))
         .then(MetadataKeywords::new(openai_client.clone()))
-        .then_in_batch(10, Embed::new(openai_client.clone()))
+        .then_in_batch(Embed::new(openai_client.clone()).with_batch_size(10))
         .log_all()
         .filter_errors()
         .then_store_with(

swiftide-core/src/indexing_traits.rs

@@ -83,6 +83,11 @@ pub trait BatchableTransformer: Send + Sync {
         let name = std::any::type_name::<Self>();
         name.split("::").last().unwrap_or(name)
     }
+
+    /// Overrides the default batch size of the pipeline
+    fn batch_size(&self) -> Option<usize> {
+        None
+    }
 }
 
 #[async_trait]

swiftide-indexing/src/pipeline.rs

@@ -27,6 +27,7 @@ pub struct Pipeline {
     storage: Vec<Arc<dyn Persist>>,
     concurrency: usize,
     indexing_defaults: IndexingDefaults,
+    batch_size: usize,
 }
 
 impl Default for Pipeline {
@@ -37,6 +38,7 @@ impl Default for Pipeline {
             storage: Vec::default(),
             concurrency: num_cpus::get(),
             indexing_defaults: IndexingDefaults::default(),
+            batch_size: 256, //TODO: make this configurable
         }
     }
 }
@@ -207,7 +209,6 @@ impl Pipeline {
     ///
     /// # Arguments
     ///
-    /// * `batch_size` - The size of the batches to be processed.
     /// * `transformer` - A transformer that implements the `BatchableTransformer` trait.
     ///
     /// # Returns
@@ -216,7 +217,6 @@ impl Pipeline {
     #[must_use]
     pub fn then_in_batch(
         mut self,
-        batch_size: usize,
         mut transformer: impl BatchableTransformer + WithBatchIndexingDefaults + 'static,
     ) -> Self {
         let concurrency = transformer.concurrency().unwrap_or(self.concurrency);
@@ -226,7 +226,7 @@ impl Pipeline {
         let transformer = Arc::new(transformer);
         self.stream = self
             .stream
-            .try_chunks(batch_size)
+            .try_chunks(transformer.batch_size().unwrap_or(self.batch_size))
             .map_ok(move |nodes| {
                 let transformer = Arc::clone(&transformer);
                 let span = tracing::trace_span!("then_in_batch",  nodes = ?nodes );
@@ -406,13 +406,15 @@ impl Pipeline {
             storage: self.storage.clone(),
             concurrency: self.concurrency,
             indexing_defaults: self.indexing_defaults.clone(),
+            batch_size: self.batch_size,
         };
 
         let right_pipeline = Self {
             stream: right_rx.into(),
             storage: self.storage.clone(),
             concurrency: self.concurrency,
             indexing_defaults: self.indexing_defaults.clone(),
+            batch_size: self.batch_size,
         };
 
         (left_pipeline, right_pipeline)
@@ -606,6 +608,7 @@ mod tests {
             .returning(|nodes| IndexingStream::iter(nodes.into_iter().map(Ok)));
         batch_transformer.expect_concurrency().returning(|| None);
         batch_transformer.expect_name().returning(|| "transformer");
+        batch_transformer.expect_batch_size().returning(|| None);
 
         chunker
             .expect_transform_node()
@@ -635,7 +638,7 @@ mod tests {
 
         let pipeline = Pipeline::from_loader(loader)
             .then(transformer)
-            .then_in_batch(1, batch_transformer)
+            .then_in_batch(batch_transformer)
             .then_chunk(chunker)
             .then_store_with(storage);
 
@@ -750,7 +753,7 @@ mod tests {
             .returning(|| vec![Ok(Node::default())].into());
 
         let pipeline = Pipeline::from_loader(loader)
-            .then_in_batch(10, batch_transformer)
+            .then_in_batch(batch_transformer)
             .then_store_with(storage.clone());
         pipeline.run().await.unwrap();
 
@@ -884,10 +887,7 @@ mod tests {
 
         let pipeline = Pipeline::from_loader(Box::new(loader) as Box<dyn Loader>)
             .then(Box::new(transformer) as Box<dyn Transformer>)
-            .then_in_batch(
-                1,
-                Box::new(batch_transformer) as Box<dyn BatchableTransformer>,
-            )
+            .then_in_batch(Box::new(batch_transformer) as Box<dyn BatchableTransformer>)
             .then_chunk(Box::new(chunker) as Box<dyn ChunkerTransformer>)
             .then_store_with(Box::new(storage) as Box<dyn Persist>);
         pipeline.run().await.unwrap();

swiftide-indexing/src/transformers/embed.rs

@@ -14,12 +14,14 @@ use swiftide_core::{
 pub struct Embed {
     embed_model: Arc<dyn EmbeddingModel>,
     concurrency: Option<usize>,
+    batch_size: Option<usize>,
 }
 
 impl std::fmt::Debug for Embed {
     fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
         f.debug_struct("Embed")
             .field("concurrency", &self.concurrency)
+            .field("batch_size", &self.batch_size)
             .finish()
     }
 }
@@ -38,6 +40,7 @@ impl Embed {
         Self {
             embed_model: Arc::new(model),
             concurrency: None,
+            batch_size: None,
         }
     }
 
@@ -46,6 +49,20 @@ impl Embed {
         self.concurrency = Some(concurrency);
         self
     }
+
+    /// Sets the batch size for the transformer.
+    /// If the batch size is not set, the transformer will use the default batch size set by the pipeline
+    /// # Parameters
+    ///
+    /// * `batch_size` - The batch size to use for the transformer.
+    ///
+    /// # Returns
+    ///
+    /// A new instance of `Embed`.
+    pub fn with_batch_size(mut self, batch_size: usize) -> Self {
+        self.batch_size = Some(batch_size);
+        self
+    }
 }
 
 impl WithBatchIndexingDefaults for Embed {}

swiftide-indexing/src/transformers/sparse_embed.rs

@@ -14,6 +14,7 @@ use swiftide_core::{
 pub struct SparseEmbed {
     embed_model: Arc<dyn SparseEmbeddingModel>,
     concurrency: Option<usize>,
+    batch_size: Option<usize>,
 }
 
 impl std::fmt::Debug for SparseEmbed {
@@ -38,6 +39,7 @@ impl SparseEmbed {
         Self {
             embed_model: Arc::new(model),
             concurrency: None,
+            batch_size: None,
         }
     }
 
@@ -46,6 +48,20 @@ impl SparseEmbed {
         self.concurrency = Some(concurrency);
         self
     }
+
+    /// Sets the batch size for the transformer.
+    /// If the batch size is not set, the transformer will use the default batch size set by the pipeline
+    /// # Parameters
+    ///
+    /// * `batch_size` - The batch size to use for the transformer.
+    ///
+    /// # Returns
+    ///
+    /// A new instance of `Embed`.
+    pub fn with_batch_size(mut self, batch_size: usize) -> Self {
+        self.batch_size = Some(batch_size);
+        self
+    }
 }
 
 impl WithBatchIndexingDefaults for SparseEmbed {}
@@ -114,6 +130,10 @@ impl BatchableTransformer for SparseEmbed {
     fn concurrency(&self) -> Option<usize> {
         self.concurrency
     }
+
+    fn batch_size(&self) -> Option<usize> {
+        self.batch_size
+    }
 }
 
 #[cfg(test)]

swiftide-integrations/src/fastembed/mod.rs

@@ -95,11 +95,6 @@ impl FastEmbed {
             .build()
     }
 
-    pub fn with_batch_size(&mut self, batch_size: usize) -> &mut Self {
-        self.batch_size = Some(batch_size);
-        self
-    }
-
     pub fn builder() -> FastEmbedBuilder {
         FastEmbedBuilder::default()
     }

swiftide/src/lib.rs

@@ -41,7 +41,7 @@
 //!  Pipeline::from_loader(FileLoader::new(".").with_extensions(&["md"]))
 //!          .then_chunk(ChunkMarkdown::from_chunk_range(10..512))
 //!          .then(MetadataQAText::new(openai_client.clone()))
-//!          .then_in_batch(10, Embed::new(openai_client.clone()))
+//!          .then_in_batch(Embed::new(openai_client.clone()).with_batch_size(10))
 //!          .then_store_with(
 //!              Qdrant::try_from_url(qdrant_url)?
 //!                  .batch_size(50)
@@ -165,7 +165,7 @@ pub mod indexing {
 ///   indexing::Pipeline::from_loader(FileLoader::new("README.md"))
 ///       .then_chunk(ChunkMarkdown::from_chunk_range(10..2048))
 ///       .then(MetadataQAText::new(openai_client.clone()))
-///       .then_in_batch(10, Embed::new(openai_client.clone()))
+///       .then_in_batch(Embed::new(openai_client.clone()).with_batch_size(10))
 ///       .then_store_with(qdrant.clone())
 ///       .run()
 ///       .await?;

swiftide/tests/indexing_pipeline.rs

@@ -54,7 +54,7 @@ async fn test_indexing_pipeline() {
             .then_chunk(transformers::ChunkCode::try_for_language("rust").unwrap())
             .then(transformers::MetadataQACode::default())
             .filter_cached(integrations::redis::Redis::try_from_url(&redis_url, "prefix").unwrap())
-            .then_in_batch(1, transformers::Embed::new(openai_client.clone()))
+            .then_in_batch(transformers::Embed::new(openai_client.clone()).with_batch_size(1))
             .log_nodes()
             .then_store_with(
                 integrations::qdrant::Qdrant::try_from_url(&qdrant_url)
@@ -184,7 +184,7 @@ async fn test_named_vectors() {
             .then_chunk(transformers::ChunkCode::try_for_language("rust").unwrap())
             .then(transformers::MetadataQACode::new(openai_client.clone()))
             .filter_cached(integrations::redis::Redis::try_from_url(&redis_url, "prefix").unwrap())
-            .then_in_batch(10, transformers::Embed::new(openai_client.clone()))
+            .then_in_batch(transformers::Embed::new(openai_client.clone()).with_batch_size(10))
             .then_store_with(
                 integrations::qdrant::Qdrant::try_from_url(&qdrant_url)
                     .unwrap()

swiftide/tests/lancedb.rs

@@ -52,7 +52,7 @@ async fn test_lancedb() {
                 .insert("filter".to_string(), "true".to_string());
             Ok(node)
         })
-        .then_in_batch(20, transformers::Embed::new(fastembed.clone()))
+        .then_in_batch(transformers::Embed::new(fastembed.clone()).with_batch_size(20))
         .log_nodes()
         .then_store_with(lancedb.clone())
         .run()