Update app.py

app.py

@@ -8,7 +8,7 @@ import joblib
 import validators
 import numpy as np
 import streamlit as st
-from typing import List, Dict
+from typing import List
 from numpy import ndarray
 from llama_cpp import Llama
 from statistical_chunker import StatisticalChunker
@@ -104,7 +104,7 @@ def transform_query(query: str) -> str:
     """
     return f'Represent this sentence for searching relevant passages: {query}'
 
-def main(query: str, client: QdrantClient, collection_name: str, llm, dense_model, sparse_model):
+def main(query: str, client: QdrantClient, collection_name: str, llm, dense_model: FastEmbedEncoder, sparse_model: SparseTextEmbedding):
     dense_query = list(dense_model(query,32))
     sparse_query = list(sparse_model.embed(query, 32))
 
@@ -327,7 +327,7 @@ def load_models_and_documents():
 
     return client, collection_name, llm, dense_model, sparse_model
 
-def chunk_documents(texts, metadatas, dense_model, sparse_model):
+def chunk_documents(texts: List[str], metadatas: List[dict], dense_model: FastEmbedEncoder, sparse_model: SparseTextEmbedding):
     import time
     text_splitter = StatisticalChunker(
         dense_model