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# Import necessary libraries
import streamlit as st
import autogen
from autogen.agentchat.contrib.math_user_proxy_agent import MathUserProxyAgent
# Function to run the query
def run_query(math_problem, api_key):
config_list = [
{
'model': 'gpt-3.5-turbo',
'api_key': api_key,
},
]
autogen.ChatCompletion.start_logging()
assistant = autogen.AssistantAgent(
name="assistant",
system_message="You are a helpful assistant.",
llm_config={
"request_timeout": 600,
"seed": 42,
"config_list": config_list,
}
)
mathproxyagent = MathUserProxyAgent(
name="mathproxyagent",
human_input_mode="NEVER",
code_execution_config={"use_docker": False},
)
return mathproxyagent.initiate_chat(assistant, problem=math_problem)
# Streamlit app
st.title('Math Problem Solver')
# Input fields for API key and math problem
api_key = st.text_input("Enter your API Key:")
math_problem = st.text_input("Enter your math problem:")
# When the button is pressed, call run_query and display the result
if st.button('Solve'):
if api_key and math_problem:
result = run_query(math_problem, api_key)
st.write(result)
else:
st.write("Please provide both API key and math problem.")
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