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# import databutton as db
import streamlit as st
from langchain.agents import Tool
from langchain.chains.conversation.memory import ConversationBufferMemory
from langchain.chat_models import ChatOpenAI
from langchain.agents import initialize_agent
from llama_index import StorageContext, load_index_from_storage
from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader
import os
# user = db.user.get()
# name = user.name if user.name else "you"
# user = db.user.get()
# name = user.name if user.name else "you"
st.title("🤖 Personalized Bot with Memory 🧠 ")
st.markdown(
"""
#### 🗨️ Chat with a bot with additional information 📜 with `Conversational Buffer Memory`
> *powered by [LangChain]('https://langchain.readthedocs.io/en/latest/modules/memory.html#memory') +
[OpenAI]('https://platform.openai.com/docs/models/gpt-3-5') + [DataButton](https://www.databutton.io/) + [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/index.html)*
----
"""
)
option = st.selectbox(
'Which data do you want to use?',
('Finite-size effects of avalanche dynamics', 'A Review of ChatGPT Applications'))
st.write('You selected:', option)
os.environ["OPENAI_API_KEY"] = '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'
if option:
if option == 'Finite-size effects of avalanche dynamics':
storage_context = StorageContext.from_defaults(persist_dir="./storage1")
if option == 'A Review of ChatGPT Applications':
storage_context = StorageContext.from_defaults(persist_dir="./storage")
index = load_index_from_storage(storage_context)
tools = [
Tool(
name="GPT Index",
func=lambda q: str(index.as_query_engine().query(q)),
description="useful for when you want to answer questions about the author. The input to this tool should be a complete english sentence.",
return_direct=True
),
]
if "memory" not in st.session_state:
st.session_state.memory = ConversationBufferMemory(
memory_key="chat_history"
)
llm = ChatOpenAI(temperature=0)
agent_chain = initialize_agent(tools, llm, agent="conversational-react-description", memory=st.session_state.memory)
wtf = st.text_input(
"**What's on your mind?**",
placeholder="Ask me anything from {}"
)
if wtf:
with st.spinner(
"Generating Answer to your Query : `{}` ".format(wtf)
):
res = agent_chain.run(input=wtf)
st.info(res, icon="🤖")
with st.expander("History/Memory"):
st.session_state.memory
if st.button('forget the context.'):
st.session_state.memory = ConversationBufferMemory(
memory_key="chat_history"
) |