fix: do not crash on invalid embedding model

backend/open_webui/apps/retrieval/main.py

@@ -101,7 +101,13 @@ from open_webui.config import (
     AppConfig,
 )
 from open_webui.constants import ERROR_MESSAGES
-from open_webui.env import SRC_LOG_LEVELS, DEVICE_TYPE, DOCKER, BING_SEARCH_V7_ENDPOINT, BING_SEARCH_V7_SUBSCRIPTION_KEY
+from open_webui.env import (
+    SRC_LOG_LEVELS,
+    DEVICE_TYPE,
+    DOCKER,
+    BING_SEARCH_V7_ENDPOINT,
+    BING_SEARCH_V7_SUBSCRIPTION_KEY,
+)
 from open_webui.utils.misc import (
     calculate_sha256,
     calculate_sha256_string,
@@ -176,6 +182,7 @@ app.state.config.SEARCHAPI_ENGINE = SEARCHAPI_ENGINE
 app.state.config.RAG_WEB_SEARCH_RESULT_COUNT = RAG_WEB_SEARCH_RESULT_COUNT
 app.state.config.RAG_WEB_SEARCH_CONCURRENT_REQUESTS = RAG_WEB_SEARCH_CONCURRENT_REQUESTS
 
+
 def update_embedding_model(
     embedding_model: str,
     auto_update: bool = False,
@@ -183,11 +190,15 @@ def update_embedding_model(
     if embedding_model and app.state.config.RAG_EMBEDDING_ENGINE == "":
         from sentence_transformers import SentenceTransformer
 
-        app.state.sentence_transformer_ef = SentenceTransformer(
-            get_model_path(embedding_model, auto_update),
-            device=DEVICE_TYPE,
-            trust_remote_code=RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE,
-        )
+        try:
+            app.state.sentence_transformer_ef = SentenceTransformer(
+                get_model_path(embedding_model, auto_update),
+                device=DEVICE_TYPE,
+                trust_remote_code=RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE,
+            )
+        except Exception as e:
+            log.debug(f"Error loading SentenceTransformer: {e}")
+            app.state.sentence_transformer_ef = None
     else:
         app.state.sentence_transformer_ef = None
 
@@ -637,23 +648,21 @@ async def update_query_settings(
 ####################################
 
 
-def _get_docs_info(
-    docs: list[Document]
-) -> str:
+def _get_docs_info(docs: list[Document]) -> str:
     docs_info = set()
 
     # Trying to select relevant metadata identifying the document.
     for doc in docs:
-        metadata = getattr(doc, 'metadata', {})
-        doc_name = metadata.get('name', '')
+        metadata = getattr(doc, "metadata", {})
+        doc_name = metadata.get("name", "")
         if not doc_name:
-            doc_name = metadata.get('title', '')
+            doc_name = metadata.get("title", "")
         if not doc_name:
-            doc_name = metadata.get('source', '')
+            doc_name = metadata.get("source", "")
         if doc_name:
             docs_info.add(doc_name)
 
-    return ', '.join(docs_info)
+    return ", ".join(docs_info)
 
 
 def save_docs_to_vector_db(
@@ -664,7 +673,9 @@ def save_docs_to_vector_db(
     split: bool = True,
     add: bool = False,
 ) -> bool:
-    log.info(f"save_docs_to_vector_db: document {_get_docs_info(docs)} {collection_name}")
+    log.info(
+        f"save_docs_to_vector_db: document {_get_docs_info(docs)} {collection_name}"
+    )
 
     # Check if entries with the same hash (metadata.hash) already exist
     if metadata and "hash" in metadata:
@@ -1155,7 +1166,7 @@ def search_web(engine: str, query: str) -> list[SearchResult]:
         return search_jina(query, app.state.config.RAG_WEB_SEARCH_RESULT_COUNT)
     elif engine == "bing":
         return search_bing(
-            BING_SEARCH_V7_SUBSCRIPTION_KEY,            
+            BING_SEARCH_V7_SUBSCRIPTION_KEY,
             BING_SEARCH_V7_ENDPOINT,
             str(DEFAULT_LOCALE),
             query,