Added 5 times bigger embedding model all-mpnet-base-v2

ai_generate.py

@@ -63,7 +63,7 @@ def load_llm(model: str, api_key: str, temperature: float = 1.0, max_length: int
 def create_db_with_langchain(path: list[str], url_content: dict):
     all_docs = []
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=CHUNK_SIZE, chunk_overlap=CHUNK_OVERLAP)
-    embedding_function = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")
+    embedding_function = SentenceTransformerEmbeddings(model_name="all-mpnet-base-v2")
     if path:
         for file in path:
             loader = PyMuPDFLoader(file)