Update functions.py

functions.py

@@ -155,7 +155,7 @@ def gen_embeddings(embedding_model):
     return embeddings
     
 @st.experimental_memo(suppress_st_warning=True)
-def embed_text(query,corpus,title,embedding_model,_emb_tok,_chain_type):
+def embed_text(query,corpus,title,embedding_model,_emb_tok,chain_type):
     
     '''Embed text and generate semantic search scores'''
 
@@ -165,7 +165,7 @@ def embed_text(query,corpus,title,embedding_model,_emb_tok,_chain_type):
         
     docs = docsearch.similarity_search_with_score(query, k=3)
 
-    if _chain_type == 'Normal':
+    if chain_type == 'Normal':
 
         docs = [d[0] for d in docs]
 
@@ -181,7 +181,7 @@ def embed_text(query,corpus,title,embedding_model,_emb_tok,_chain_type):
         answer = chain({"input_documents": docs, "question": query}, return_only_outputs=False)
 
 
-    elif _chain_type == 'Refined':
+    elif chain_type == 'Refined':
 
         docs = [d[0] for d in docs]