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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.") | |