more debug prints3

app/indexer/content_bases.py

@@ -14,16 +14,17 @@ def __init__(self, storage: IStorage):
     def index_documents(self, docs: List[Document]):
         file_uuid = docs[0].metadata["file_uuid"]
         content_base_uuid = docs[0].metadata["content_base_uuid"]
-
+        print("start _search_docs_by_content_base_uuid")
         results = self._search_docs_by_content_base_uuid(
             content_base_uuid=content_base_uuid,
             file_uuid=file_uuid,
         )
+        print("end _search_docs_by_content_base_uuid")
         ids = []
         if len(results) > 0:
             ids = [item["_id"] for item in results]
             self.storage.delete(ids=ids)
-
+        print("start save")
         return self.storage.save(docs)
 
     def index(self, texts: List, metadatas: dict):

app/store/elasticsearch_vector_store.py

@@ -14,6 +14,7 @@ def __init__(self, vectorstore: VectorStore, score=1.55):
         self.score = score
 
     def save(self, doc: Document) -> list[str]:
+        print("Entrou no save do ElasticsearchVectorStoreIndex")
         texts = [doc.page_content]
         metadatas = [doc.metadata]
         return self.vectorstore.add_texts(texts, metadatas)
@@ -59,7 +60,9 @@ def delete(self, ids: list[str] = []) -> bool:
 class ContentBaseElasticsearchVectorStoreIndex(ElasticsearchVectorStoreIndex):
 
     def save(self, docs: list[Document]) -> list[str]:
+        print("entrou no save do ContentBaseElasticsearchVectorStoreIndex")
         index = os.environ.get("INDEX_CONTENTBASES_NAME", "content_bases")
+        print("STARTOU FROM_DOCUMENTS")
         res = self.vectorstore.from_documents(
             docs,
             self.vectorstore.embeddings,
@@ -70,6 +73,7 @@ def save(self, docs: list[Document]) -> list[str]:
                 "max_chunk_bytes": 200000000
             }
         )
+        print("TERMINOU FROM_DOCUMENTS")
         return res
 
     def query_search(self, search_filter: dict) -> list[dict]: