Update functions.py

functions.py

@@ -140,7 +140,7 @@ def process_corpus(corpus, _tok, title, _embeddings, chunk_size=200, overlap=50)
         texts,
         _embeddings,
         index_name = "earnings-embeddings",
-        namespace = f'{title.lower()}-earnings',
+        namespace = f'{title}-earnings',
         metadatas = [
         {'source':i} for i in range(len(texts))]
     )
@@ -169,15 +169,14 @@ def embed_text(query,corpus,title,embedding_model,_emb_tok,chain_type='stuff'):
     
     '''Embed text and generate semantic search scores'''
 
+    title = title.split()[0].lower()
+    
     embeddings = gen_embeddings(embedding_model)
         
-    title = title[0]
     docsearch = process_corpus(corpus,_emb_tok,title, embeddings)
         
     docs = docsearch.similarity_search_with_score(query, k=3, namespace = f'{title}-earnings')
 
-    docs = [d[0] for d in docs]
-
     if chain_type == 'Normal':
 
         PROMPT = PromptTemplate(template=template, 
@@ -195,6 +194,8 @@ def embed_text(query,corpus,title,embedding_model,_emb_tok,chain_type='stuff'):
 
     elif chain_type == 'Refined':
 
+        docs = [d[0] for d in docs]
+        
         initial_qa_prompt = PromptTemplate(
     input_variables=["context_str", "question"], template=initial_qa_template
 )