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import streamlit as st
from langchain_core.messages import HumanMessage,AIMessage,ToolMessage
import json
class DisplayResultStreamlit:
def __init__(self,usecase,graph,user_message):
self.usecase= usecase
self.graph = graph
self.user_message = user_message
def display_result_on_ui(self):
usecase= self.usecase
graph = self.graph
user_message = self.user_message
if usecase =="Basic Chatbot":
print("I am here in basic chatbot")
for event in graph.stream({'messages':("user",user_message)}):
for value in event.values():
print(value['messages'])
with st.chat_message("user"):
st.write(user_message)
with st.chat_message("assistant"):
st.write(value["messages"].content)
elif usecase=="Chatbot with Tool":
# Prepare state and invoke the graph
print("I am here ")
initial_state = {"messages": [user_message]}
res = graph.invoke(initial_state)
for message in res['messages']:
if type(message) == HumanMessage:
with st.chat_message("user"):
st.write(message.content)
elif type(message)==ToolMessage:
with st.chat_message("ai"):
st.write("Tool Call Start")
st.write(message.content)
st.write("Tool Call End")
elif type(message)==AIMessage and message.content:
with st.chat_message("assistant"):
st.write(message.content)
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