update

app.py

@@ -4,92 +4,67 @@ from io import StringIO
 from generation import process_scores
 from model import AzureAgent, GPTAgent
 
-# Initialize session state variables if they don't already exist
-def initialize_state():
-    if 'data_processed' not in st.session_state:
-        st.session_state.data_processed = False
-    if 'api_key' not in st.session_state:
-        st.session_state.api_key = ""
-    if 'endpoint_url' not in st.session_state:
-        st.session_state.endpoint_url = ""
-    if 'deployment_name' not in st.session_state:
-        st.session_state.deployment_name = ""
-    if 'temperature' not in st.session_state:
-        st.session_state.temperature = 0.5
-    if 'max_tokens' not in st.session_state:
-        st.session_state.max_tokens = 150
-    if 'group_name' not in st.session_state:
-        st.session_state.group_name = ""
-    if 'privilege_label' not in st.session_state:
-        st.session_state.privilege_label = ""
-    if 'protect_label' not in st.session_state:
-        st.session_state.protect_label = ""
-    if 'num_run' not in st.session_state:
-        st.session_state.num_run = 1
-
-initialize_state()
-
 # Set up the Streamlit interface
 st.title('JobFair: A Benchmark for Fairness in LLM Employment Decision')
 st.sidebar.title('Model Settings')
 
+# 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", "privilege_label", "protect_label", "num_run"]
+    defaults = [False, "", "", "", 0.5, 150, False, "", "", "", 1]
+    for key, default in zip(keys, defaults):
+        if key not in st.session_state:
+            st.session_state[key] = default
+
+initialize_state()
+
 # Model selection and configuration
 model_type = st.sidebar.radio("Select the type of agent", ('GPTAgent', 'AzureAgent'))
-api_key = st.sidebar.text_input("API Key", type="password", value=st.session_state.api_key)
-endpoint_url = st.sidebar.text_input("Endpoint URL", value=st.session_state.endpoint_url)
-deployment_name = st.sidebar.text_input("Model Name", value=st.session_state.deployment_name)
+st.session_state.api_key = st.sidebar.text_input("API Key", type="password", value=st.session_state.api_key)
+st.session_state.endpoint_url = st.sidebar.text_input("Endpoint URL", value=st.session_state.endpoint_url)
+st.session_state.deployment_name = st.sidebar.text_input("Model Name", value=st.session_state.deployment_name)
 api_version = '2024-02-15-preview' if model_type == 'GPTAgent' else ''
-temperature = st.sidebar.slider("Temperature", 0.0, 1.0, st.session_state.temperature, 0.01)
-max_tokens = st.sidebar.number_input("Max Tokens", 1, 1000, st.session_state.max_tokens)
+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)
 
-# Reset buttons for model information
 if st.sidebar.button("Reset Model Info"):
-    st.session_state.api_key = ""
-    st.session_state.endpoint_url = ""
-    st.session_state.deployment_name = ""
-    st.session_state.temperature = 0.5
-    st.session_state.max_tokens = 150
+    initialize_state()  # Reset all state to defaults
     st.experimental_rerun()
 
-submit_model_info = st.sidebar.button("Submit Model Info")
+if st.sidebar.button("Submit Model Info"):
+    st.session_state.model_submitted = True
 
-# Data upload and processing with reset option
-if submit_model_info:
-    parameters = {"temperature": temperature, "max_tokens": max_tokens}
+# Ensure experiment settings are only shown if model info is submitted
+if st.session_state.model_submitted:
+    parameters = {"temperature": st.session_state.temperature, "max_tokens": st.session_state.max_tokens}
 
-    group_name = st.text_input("Group Name", value=st.session_state.group_name)
-    privilege_label = st.text_input("Privilege Name", value=st.session_state.privilege_label)
-    protect_label = st.text_input("Protect Name", value=st.session_state.protect_label)
-    num_run = st.number_input("Number of runs", min_value=1, value=st.session_state.num_run)
+    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 Name", value=st.session_state.privilege_label)
+    st.session_state.protect_label = st.text_input("Protect Name", value=st.session_state.protect_label)
+    st.session_state.num_run = st.number_input("Number of runs", min_value=1, value=st.session_state.num_run)
     uploaded_file = st.file_uploader("Choose a file")
 
-    # Reset button for experiment settings
     if st.button("Reset Experiment Settings"):
         st.session_state.group_name = ""
         st.session_state.privilege_label = ""
         st.session_state.protect_label = ""
         st.session_state.num_run = 1
         st.session_state.data_processed = False
-        st.experimental_rerun()
 
-    if uploaded_file is not None:
+    if uploaded_file is not None and not st.session_state.data_processed:
         data = StringIO(uploaded_file.getvalue().decode("utf-8"))
         df = pd.read_csv(data)
 
-        process_button = st.button('Process Data')
-
-        if process_button and not st.session_state.data_processed:
+        if st.button('Process Data'):
             # Initialize the correct agent based on model type
             if model_type == 'AzureAgent':
-                agent = AzureAgent(api_key, endpoint_url, deployment_name)
+                agent = AzureAgent(st.session_state.api_key, st.session_state.endpoint_url, st.session_state.deployment_name)
             else:
-                agent = GPTAgent(api_key, endpoint_url, deployment_name, api_version)
+                agent = GPTAgent(st.session_state.api_key, st.session_state.endpoint_url, st.session_state.deployment_name, api_version)
 
             # Process data and display results
             with st.spinner('Processing data...'):
-                df = process_scores(df, num_run, parameters, privilege_label, protect_label, agent, group_name)
+                df = process_scores(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.data_processed = True  # Mark as processed
-
             st.write('Processed Data:', df)
-        elif process_button and st.session_state.data_processed:
-            st.warning("Data already processed for this session. Reset or re-upload to process new data.")