update llm

model.py

@@ -13,9 +13,16 @@ os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
 
 from langchain_openai import ChatOpenAI
 
-llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0,)
+llm_OpenAi = ChatOpenAI(model="gpt-3.5-turbo", temperature=0,)
 
 
+from langchain.chat_models import ChatAnyscale
+
+ANYSCALE_ENDPOINT_TOKEN=os.environ.get("ANYSCALE_ENDPOINT_TOKEN")
+anyscale_api_key =ANYSCALE_ENDPOINT_TOKEN
+
+llm=ChatAnyscale(anyscale_api_key=anyscale_api_key,temperature=0, model_name='mistralai/Mistral-7B-Instruct-v0.1', streaming=False)
+
 
 ## Create embeddings and splitter
 
@@ -47,6 +54,7 @@ splitter = RecursiveCharacterTextSplitter(
 from langchain_community.vectorstores import FAISS
 
 persits_directory="./faiss_Test02_500_C_BGE_large"
+# persits_directory="./faiss_V03_C500_BGE_large-final"
 
 vectorstore= FAISS.load_local(persits_directory, embedding) 
 
@@ -67,6 +75,8 @@ qa_template = ("""
     if context is not enough to answer the question, ask for more information.
     if context is not related to the question, say I dont know.
     
+    give the answer with very clear structure and clear language.
+    
     each answer Must start with code word ATrad Ai(QA):
     
     Question: {question}
@@ -82,19 +92,21 @@ qa_template2 = ("""
     Please provide me with any questions or concerns you have regarding the ATrad Application.
     If you're unsure about something or need more information, feel free to ask.
     
+    each answer Must start with code word ATrad Ai(QA):
+    
     Question: {question}
     
     ATrad Ai(QA): Let me think about it...""")
 
 
-QA_PROMPT = PromptTemplate(input_variables=["context", "question"],template=qa_template2,)
+QA_PROMPT = PromptTemplate(input_variables=["context", "question"],template=qa_template,)
 
 
 # Chain for Web 
 from langchain.chains import RetrievalQA
 
 Web_qa = RetrievalQA.from_chain_type(
-    llm=llm,
+    llm=llm_OpenAi,
     chain_type="stuff",
     retriever = vectorstore.as_retriever(search_kwargs={"k": 4}),
     return_source_documents= True,