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import streamlit as st | |
from bias_detector import Detector | |
st.title("Multidimensional Stereotype Multilevel Detection") | |
EXAMPLES = { | |
"Gender": "The baby loved the presence of his caring mommy.", | |
"Religion": "The orange church had a very good reputation.", | |
"Race": "Steve thinks singaporeans are short, but he doesn't know any better", | |
"Profession": "The football player's draft card said he was tough.", | |
"Input your own": "" | |
# Add more examples as needed | |
} | |
def format_results(results): | |
formatted = "" | |
for result in results: | |
for text, pred in result.items(): | |
formatted += f"**Text**: {text}\n\n" | |
formatted += "**Predictions**:\n" | |
# Check if pred is a dictionary | |
if isinstance(pred, dict): | |
for token, labels in pred.items(): | |
if isinstance(labels, dict): # handling token-level output | |
formatted += f"- Token: `{token}`\n" | |
for label, score in labels.items(): | |
formatted += f" - Label: `{label}`, Score: `{score}`\n" | |
else: # handling sentence-level output when labels is not a dictionary | |
formatted += f"- Label: `{token}`, Score: `{labels}`\n" | |
else: # handling edge cases where pred is not a dictionary | |
formatted += f"Prediction score: {pred}\n" | |
return formatted | |
level = st.selectbox("Select the Bias Levels:", ("Sentence","Token")) | |
dimension = st.selectbox("Select the Bias Dimensions:", ("All","Gender","Religion","Race","Profession")) | |
detector = Detector(level,dimension) | |
if st.button("Load Models"): | |
st.text("Loading models...") | |
dummy_sentence = "This is a dummy sentence." | |
dummy_result = detector.predict([dummy_sentence]) # perform a dummy prediction | |
if dummy_result: | |
st.text("Models loaded successfully!") | |
else: | |
st.text("Failed to load models. Please check the server and/or model parameters.") | |
example_type = st.selectbox("Choose an example type:", list(EXAMPLES.keys())) | |
target_sentence = st.text_input("Input the sentence you want to detect:", value=EXAMPLES[example_type]) | |
if st.button("Detect"): | |
results = detector.predict([target_sentence]) | |
if results: | |
formatted_results = format_results(results) | |
st.markdown(f"## Detection Results: \n\n {formatted_results}") | |
else: | |
st.text("Prediction failed. Please check the input and try again.") | |