import streamlit as st import pandas as pd from io import StringIO from util.injection import process_scores_multiple from util.model import AzureAgent, GPTAgent,Claude3Agent from util.prompt import PROMPT_TEMPLATE import os st.title('Result Generation') def check_password(): def password_entered(): # if password_input == os.getenv('PASSWORD'): if password_input == os.getenv('PASSWORD'): st.session_state['password_correct'] = True else: st.error("Incorrect Password, please try again.") password_input = st.text_input("Enter Password:", type="password") submit_button = st.button("Submit", on_click=password_entered) if submit_button and not st.session_state.get('password_correct', False): st.error("Please enter a valid password to access the demo.") # Define a function to manage state initialization def initialize_state(): keys = ["model_submitted", "api_key", "endpoint_url", "deployment_name", "temperature", "max_tokens", "data_processed", "group_name", "occupation", "privilege_label", "protect_label", "num_run", "uploaded_file", "occupation_submitted","sample_size","charateristics","proportion","prompt_template"] defaults = [False, "", "https://safeguard-monitor.openai.azure.com/", "gpt35-1106", 0.0, 300, False, "Gender", "Programmer", "Male", "Female", 1, None, False,2,"This candidate's performance during the internship at our institution was evaluated to be at the 50th percentile among current employees.", 1.0 ,PROMPT_TEMPLATE] for key, default in zip(keys, defaults): if key not in st.session_state: st.session_state[key] = default def change_column_value(df_old, df_change, here_column, switch_to_column, common_column='Resume'): merged_df = df_old.merge(df_change, on=common_column, how='left') df_old[here_column] = merged_df[switch_to_column] return df_old if not st.session_state.get('password_correct', False): check_password() else: st.sidebar.success("Password Verified. Proceed with the demo.") st.sidebar.title('Model Settings') initialize_state() # Model selection and configuration model_type = st.sidebar.radio("Select the type of agent", ('GPTAgent', 'AzureAgent','Claude3Agent')) st.session_state.api_key = st.sidebar.text_input("API Key", type="password", value=st.session_state.api_key) st.session_state.deployment_name = st.sidebar.text_input("Model Name", value=st.session_state.deployment_name) st.session_state.temperature = st.sidebar.slider("Temperature", 0.0, 1.0, st.session_state.temperature, 0.01) st.session_state.max_tokens = st.sidebar.number_input("Max Tokens", 1, 1000, st.session_state.max_tokens) if model_type == 'GPTAgent' or model_type == 'AzureAgent': st.session_state.endpoint_url = st.sidebar.text_input("Endpoint URL", value=st.session_state.endpoint_url) api_version = '2024-02-15-preview' if model_type == 'GPTAgent' else '' if st.sidebar.button("Reset Model Info"): initialize_state() # Reset all state to defaults st.experimental_rerun() if st.sidebar.button("Submit Model Info"): st.session_state.model_submitted = True if st.session_state.model_submitted: df = None file_options = st.radio("Choose file source:", ["Upload", "Example"]) if file_options == "Example": df = pd.read_csv("resume_subsampled.csv") else: st.session_state.uploaded_file = st.file_uploader("Choose a file") if st.session_state.uploaded_file is not None: data = StringIO(st.session_state.uploaded_file.getvalue().decode("utf-8")) df = pd.read_csv(data) if df is not None: categories = list(df["Occupation"].unique()) st.session_state.occupation = st.selectbox("Occupation", options=categories, index=categories.index(st.session_state.occupation) if st.session_state.occupation in categories else 0) st.session_state.prompt_template = st.text_area("Prompt Template", value=st.session_state.prompt_template) st.session_state.sample_size = st.number_input("Sample Size", 2, len(df), st.session_state.sample_size) st.session_state.group_name = st.text_input("Group Name", value=st.session_state.group_name) st.session_state.privilege_label = st.text_input("Privilege Label", value=st.session_state.privilege_label) st.session_state.protect_label = st.text_input("Protect Label", value=st.session_state.protect_label) st.session_state.num_run = st.number_input("Number of Runs", 1, 10, st.session_state.num_run) #st.session_state.charateristics = st.text_area("Characteristics", value=st.session_state.charateristics) df = df[df["Occupation"] == st.session_state.occupation] # if file_options == "Example": # st.session_state.proportion = st.slider("Proportion", 0.2, 1.0, float(st.session_state.proportion), 0.2) # df_chunked = pd.read_csv("resume_chunked.csv") # column_switch_to = f'{st.session_state.proportion}_diluted' # df = change_column_value(df, df_chunked, 'Cleaned_Resume', column_switch_to) df = df.sample(n=st.session_state.sample_size, random_state=42) st.write('Data:', df) if st.button('Process Data') and not st.session_state.data_processed: # Initialize the correct agent based on model type if model_type == 'AzureAgent': agent = AzureAgent(st.session_state.api_key, st.session_state.endpoint_url, st.session_state.deployment_name) elif model_type == 'GPTAgent': agent = GPTAgent(st.session_state.api_key, st.session_state.endpoint_url, st.session_state.deployment_name, api_version) else: agent = Claude3Agent(st.session_state.api_key,st.session_state.deployment_name) with st.spinner('Processing data...'): parameters = {"temperature": st.session_state.temperature, "max_tokens": st.session_state.max_tokens} preprocessed_df = process_scores_multiple(df, st.session_state.num_run, parameters, st.session_state.privilege_label,st.session_state.protect_label, agent, st.session_state.group_name,st.session_state.occupation,st.session_state.prompt_template) st.session_state.data_processed = True # Mark as processed st.write('Processed Data:', preprocessed_df) # Allow downloading of the evaluation results st.download_button( label="Download Generation Results", data=preprocessed_df.to_csv().encode('utf-8'), file_name=f'{st.session_state.occupation}.csv', mime='text/csv', ) if st.button("Reset Experiment Settings"): st.session_state.sample_size = 2 st.session_state.charateristics = "This candidate's performance during the internship at our institution was evaluated to be at the 50th percentile among current employees." st.session_state.occupation = "Programmer" st.session_state.group_name = "Gender" st.session_state.privilege_label = "Male" st.session_state.protect_label = "Female" st.session_state.prompt_template = PROMPT_TEMPLATE st.session_state.num_run = 1 st.session_state.data_processed = False st.session_state.uploaded_file = None st.session_state.proportion = 1.0