Issue on Callback Handler: LangChainDeprecationWarning #123
Description
Path: /api-reference/integrations/langchain
This is my code:
from langchain_community.document_loaders import PyPDFLoader, DirectoryLoader
from langchain.prompts import PromptTemplate
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores import FAISS
from langchain_community.llms import CTransformers
from langchain.chains import RetrievalQA
from langchain_community.chat_loaders.whatsapp import WhatsAppChatLoader
from langchain_openai import AzureChatOpenAI
from langchain_community.chat_loaders.base import ChatSession
from langchain_community.chat_loaders.utils import (
map_ai_messages,
merge_chat_runs,
)
import chainlit as cl
from db import handle_db_queries
DB_FAISS_PATH = 'C://Users//PRINCE CHOUDHARY//Downloads//Llama2-Medical-Chatbot-main//vectorstore//db_faiss'
custom_prompt_template = """Use the following pieces of information to answer the user's question.
If you don't know the answer, just say that you don't know, don't try to make up an answer.
Context: {context}
Question: {question}
Only return the helpful answer below and nothing else.
Helpful answer:
"""
def set_custom_prompt():
"""
Prompt template for QA retrieval for each vectorstore
"""
prompt = PromptTemplate(template=custom_prompt_template,
input_variables=['context', 'question'])
return prompt
#Retrieval QA Chain
def retrieval_qa_chain(llm, prompt, db):
qa_chain = RetrievalQA.from_chain_type(llm=llm,
chain_type='stuff',
retriever=db.as_retriever(search_kwargs={'k': 2}),
return_source_documents=True,
chain_type_kwargs={'prompt': prompt}
)
return qa_chain
#Loading the model
def load_llm():
# Load the locally downloaded model here
llm = CTransformers(
#model = "TheBloke/Llama-2-7B-Chat-GGML",
model="C://Users//PRINCE CHOUDHARY//Downloads//Llama2-Medical-Chatbot-main//llama-2-7b-chat.ggmlv3.q8_0.bin",
model_type="llama",
max_new_tokens = 512,
temperature = 0.5
)
return llm
#QA Model Function
def qa_bot():
embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2",
model_kwargs={'device': 'cpu'})
db = FAISS.load_local(DB_FAISS_PATH, embeddings, allow_dangerous_deserialization=True)
llm = load_llm()
qa_prompt = set_custom_prompt()
qa = retrieval_qa_chain(llm, qa_prompt, db)
return qa
#output function
def final_result(query):
qa_result = qa_bot()
response = qa_result({'query': query})
return response
#chainlit code
@cl.on_chat_start
async def start():
chain = qa_bot()
if chain is None:
print("Failed to initialize chain object")
else:
msg = cl.Message(content="Starting the bot...")
await msg.send()
msg.content = "Hi, Welcome to BotVerse. What is your query?"
await msg.update()
cl.user_session.set("chain", chain)
@cl.on_message
async def main(message: cl.Message):
chain = cl.user_session.get("chain")
cb = cl.AsyncLangchainCallbackHandler(
stream_final_answer=True, answer_prefix_tokens=["FINAL", "ANSWER"]
)
cb.answer_reached = True
if chain is None:
print("Error: The chain is not initialized.")
else:
# Determine if the message is a database query
if "Chinook DB" in message.content: # This is a simple example condition
response = handle_db_queries(message.content)
else:
# Use the existing chain for other types of queries
response = await chain.acall(message.content, callbacks=[cb])
answer = response.get("result") if isinstance(response, dict) else response
sources = response.get("source_documents") if isinstance(response, dict) else None
if sources:
answer += f"\nSources:" + str(sources)
else:
answer += "\nNo sources found"
await cl.Message(content=answer).send()
On running the application This issue is coming up:
C:\Users\PRINCE CHOUDHARY\Downloads\Llama2-Medical-Chatbot-main\venv\lib\site-packages\langchain_core_api\deprecation.py:117: LangChainDeprecationWarning: The function acall was deprecated in LangChain 0.1.0 and will be removed in 0.2.0. Use ainvoke instead.
warn_deprecated(
Can anyone help with thr issue?