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import streamlit as st
from lettucedetect.models.inference import HallucinationDetector
import streamlit.components.v1 as components
def create_interactive_text(text: str, spans: list[dict[str, int | float]]) -> str:
"""Create interactive HTML with highlighting and hover effects.
:param text: The text to create the interactive text for.
:param spans: The spans to highlight.
:return: The interactive text.
"""
html_text = text
for span in sorted(spans, key=lambda x: x["start"], reverse=True):
span_text = text[span["start"] : span["end"]]
highlighted_span = f'<span class="hallucination" title="Confidence: {span["confidence"]:.3f}">{span_text}</span>'
html_text = (
html_text[: span["start"]] + highlighted_span + html_text[span["end"] :]
)
return f"""
<style>
.container {{
font-family: Arial, sans-serif;
font-size: 16px;
line-height: 1.6;
padding: 20px;
}}
.hallucination {{
background-color: rgba(255, 99, 71, 0.3);
padding: 2px;
border-radius: 3px;
cursor: help;
}}
.hallucination:hover {{
background-color: rgba(255, 99, 71, 0.5);
}}
</style>
<div class="container">{html_text}</div>
"""
def main():
st.set_page_config(page_title="Lettuce Detective")
st.image(
"https://github.com/KRLabsOrg/LettuceDetect/blob/main/assets/lettuce_detective.png?raw=true",
width=600,
)
st.title("Let Us Detect Your Hallucinations")
@st.cache_resource
def load_detector():
return HallucinationDetector(
method="transformer",
model_path="KRLabsOrg/lettucedect-base-modernbert-en-v1",
)
detector = load_detector()
context = st.text_area(
"Context",
"France is a country in Europe. The capital of France is Paris. The population of France is 67 million.",
height=100,
)
question = st.text_area(
"Question",
"What is the capital of France? What is the population of France?",
height=100,
)
answer = st.text_area(
"Answer",
"The capital of France is Paris. The population of France is 69 million.",
height=100,
)
if st.button("Detect Hallucinations"):
predictions = detector.predict(
context=[context], question=question, answer=answer, output_format="spans"
)
html_content = create_interactive_text(answer, predictions)
components.html(html_content, height=200)
if __name__ == "__main__":
main()
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