release: 1.0.0

main/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "main"
-version = "0.2.7"
+version = "1.0.0"
 edition = "2021"
 repository = "https://github.com/perstarkse/minne"
 license = "AGPL-3.0-or-later"

main/src/main.rs

@@ -2,7 +2,9 @@ use api_router::{api_routes_v1, api_state::ApiState};
 use axum::{extract::FromRef, Router};
 use common::{
     storage::{
-        db::SurrealDbClient, indexes::ensure_runtime_indexes, store::StorageManager,
+        db::SurrealDbClient,
+        indexes::ensure_runtime_indexes,
+        store::StorageManager,
         types::{
             knowledge_entity::KnowledgeEntity, system_settings::SystemSettings,
             text_chunk::TextChunk,
@@ -75,22 +77,19 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
 
         // Re-embed text chunks
         info!("Re-embedding TextChunks");
-        if let Err(e) = TextChunk::update_all_embeddings_with_provider(
-            &db,
-            &embedding_provider,
-        )
-        .await
+        if let Err(e) =
+            TextChunk::update_all_embeddings_with_provider(&db, &embedding_provider).await
         {
-            error!("Failed to re-embed TextChunks: {}. Search results may be stale.", e);
+            error!(
+                "Failed to re-embed TextChunks: {}. Search results may be stale.",
+                e
+            );
         }
 
         // Re-embed knowledge entities
         info!("Re-embedding KnowledgeEntities");
-        if let Err(e) = KnowledgeEntity::update_all_embeddings_with_provider(
-            &db,
-            &embedding_provider,
-        )
-        .await
+        if let Err(e) =
+            KnowledgeEntity::update_all_embeddings_with_provider(&db, &embedding_provider).await
         {
             error!(
                 "Failed to re-embed KnowledgeEntities: {}. Search results may be stale.",

main/src/server.rs

@@ -51,9 +51,8 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     let storage = StorageManager::new(&config).await?;
 
     // Create embedding provider based on config
-    let embedding_provider = Arc::new(
-        EmbeddingProvider::from_config(&config, Some(openai_client.clone())).await?,
-    );
+    let embedding_provider =
+        Arc::new(EmbeddingProvider::from_config(&config, Some(openai_client.clone())).await?);
     info!(
         embedding_backend = ?config.embedding_backend,
         embedding_dimension = embedding_provider.dimension(),

main/src/worker.rs

@@ -1,7 +1,8 @@
 use std::sync::Arc;
 
 use common::{
-    storage::db::SurrealDbClient, storage::store::StorageManager,
+    storage::db::SurrealDbClient,
+    storage::store::StorageManager,
     utils::{config::get_config, embedding::EmbeddingProvider},
 };
 use ingestion_pipeline::{pipeline::IngestionPipeline, run_worker_loop};
@@ -40,9 +41,8 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     let reranker_pool = RerankerPool::maybe_from_config(&config)?;
 
     // Create embedding provider based on config
-    let embedding_provider = Arc::new(
-        EmbeddingProvider::from_config(&config, Some(openai_client.clone())).await?,
-    );
+    let embedding_provider =
+        Arc::new(EmbeddingProvider::from_config(&config, Some(openai_client.clone())).await?);
     info!(
         embedding_backend = ?config.embedding_backend,
         "Embedding provider initialized for worker"
@@ -51,17 +51,14 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
     // Create global storage manager
     let storage = StorageManager::new(&config).await?;
 
-    let ingestion_pipeline = Arc::new(
-        IngestionPipeline::new(
-            db.clone(),
-            openai_client.clone(),
-            config,
-            reranker_pool,
-            storage,
-            embedding_provider,
-        )
-        ?,
-    );
+    let ingestion_pipeline = Arc::new(IngestionPipeline::new(
+        db.clone(),
+        openai_client.clone(),
+        config,
+        reranker_pool,
+        storage,
+        embedding_provider,
+    )?);
 
     run_worker_loop(db, ingestion_pipeline).await
 }