Update llm/utils.py

llm/utils.py

@@ -20,8 +20,6 @@ API_TOKEN=os.getenv("TOKEN")
 # Initialize langchain LLM chain
 def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vdb, 
                         thold=0.8, progress=gr.Progress()):
-    #global VDB
-    #global THOLD
     
     llm = HuggingFaceEndpoint(
             huggingfacehub_api_token = API_TOKEN,
@@ -36,12 +34,10 @@ def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vdb,
         output_key='answer',
         return_messages=True
     )
-    
-    #VDB=vdb
-    #THOLD=thold    
+        
     qa_chain = ConversationalRetrievalChain.from_llm(
         llm,
-        retriever=CustomRetriever(vectorstore=vdb, thold=thold),#RetrieverWithScores(),
+        retriever=CustomRetriever(vectorstore=vdb, thold=thold),
         chain_type="stuff",
         memory=memory,
         return_source_documents=True,
@@ -76,7 +72,7 @@ def postprocess(response):
         #Here should be a binary classification model.
         if not "I don't know" in result:            
             for doc in response['source_documents']:
-                file_doc="\n\nFile: " + doc.metadata["source"]
+                file_doc="\n\nFile: " + doc.metadata["source"].split('/')[-1]
                 page="\nPage: " + str(doc.metadata["page"])
                 content="\nFragment: " + doc.page_content.strip()
                 result+=file_doc+page+content