Update app.py

app.py

@@ -136,8 +136,8 @@ async def create_upload_file(text_field: str, file: UploadFile = File(...), ocr:
     
     
     indexing = Pipeline()
-    indexing.add_component("sparse_doc_embedder", FastembedSparseDocumentEmbedder(model="prithvida/Splade_PP_en_v1"))
-    indexing.add_component("dense_doc_embedder", FastembedDocumentEmbedder(model="BAAI/bge-small-en-v1.5"))
+    indexing.add_component("sparse_doc_embedder", FastembedSparseDocumentEmbedder(model="Qdrant/bm42-all-minilm-l6-v2-attentions"))
+    indexing.add_component("dense_doc_embedder", FastembedDocumentEmbedder(model="BAAI/bge-m3"))
     indexing.add_component("writer", DocumentWriter(document_store=document_store, policy=DuplicatePolicy.OVERWRITE))
     indexing.connect("sparse_doc_embedder", "dense_doc_embedder")
     indexing.connect("dense_doc_embedder", "writer")
@@ -167,9 +167,9 @@ def search(prompt: str):
     # Querying
 
     querying = Pipeline()
-    querying.add_component("sparse_text_embedder", FastembedSparseTextEmbedder(model="prithvida/Splade_PP_en_v1"))
+    querying.add_component("sparse_text_embedder", FastembedSparseTextEmbedder(model="Qdrant/bm42-all-minilm-l6-v2-attentions"))
     querying.add_component("dense_text_embedder", FastembedTextEmbedder(
-     model="BAAI/bge-small-en-v1.5", prefix="Represent this sentence for searching relevant passages: ")
+     model="BAAI/bge-m3", prefix="Represent this sentence for searching relevant passages: ")
      )
     querying.add_component("retriever", QdrantHybridRetriever(document_store=document_store))
     querying.add_component("document_joiner", DocumentJoiner())