Update llm/utils.py

llm/utils.py

@@ -18,14 +18,13 @@ from langchain_core.runnables import chain
 API_TOKEN=os.getenv("TOKEN")
 
 
-
+#Because of bugs in pydantic it is not possible to take it out retr_func and RetrieverWithScores into a separate neat class. 
+#It is necessary to use dirty implementation through global variables.
 VDB=None
-
 THOLD=0.7
 
 @chain
-def retr_func(query: str)-> List[Document]: #(vdb, query: str)-> List[Document]:
-    #global VDB
+def retr_func(query: str)-> List[Document]:   
     
     docs, scores = zip(*VDB.similarity_search_with_relevance_scores(query))#similarity_search_with_score(query))
     result=[]
@@ -36,13 +35,7 @@ def retr_func(query: str)-> List[Document]: #(vdb, query: str)-> List[Document]:
         if len(result)==0:
             result.append(Document(metadata={}, page_content='No data'))
 
-    print()
-    print(THOLD)
-    print()
-    print(result)
-    print()
-
-    return result #docs
+    return result
     
 
 class RetrieverWithScores(BaseRetriever):                
@@ -74,7 +67,7 @@ def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vdb,
     VDB=vdb
     THOLD=thold
     #retr=CustomRetriever(vdb, thold=thold)    
-    #retriever=retr.retriever #vector_db.as_retriever()
+    #retriever=retr.retriever 
     qa_chain = ConversationalRetrievalChain.from_llm(
         llm,
         retriever=RetrieverWithScores(),#retriever,
@@ -90,14 +83,14 @@ def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vdb,
 # Initialize LLM
 def initialize_LLM(llm_temperature, max_tokens, top_k, vector_db, thold, progress=gr.Progress()):
     # print("llm_option",llm_option)
-    llm_name = "mistralai/Mistral-7B-Instruct-v0.2" #list_llm[llm_option]
+    llm_name = "mistralai/Mistral-7B-Instruct-v0.2" 
     #print("llm_name: ",llm_name)
     qa_chain = initialize_llmchain(llm_name, llm_temperature, max_tokens, top_k, vector_db, thold)
-    return qa_chain #, "QA chain initialized. Chatbot is ready!"
+    return qa_chain 
 
 
 
-def format_chat_history(chat_history):#message, chat_history): #no need message
+def format_chat_history(chat_history):
     formatted_chat_history = []
     for user_message, bot_message in chat_history:
         formatted_chat_history.append(f"User: {user_message}")
@@ -118,7 +111,7 @@ def postprocess(response):
                 result+=file_doc+page+content
         return result
     except:
-        return "I don't know." #response["answer"]
+        return "I don't know."