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import gradio as gr
from transformers import pipeline
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
# Load zero-shot classifier
classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
# Candidate labels
labels = ["high risk", "medium risk", "low risk"]
def classify_clauses(text_input):
# Split input into clauses
clauses = [clause.strip() for clause in text_input.strip().split('\n') if clause.strip()]
scores = []
for clause in clauses:
result = classifier(clause, labels)
scores.append(result['scores'])
scores_array = np.array(scores)
# Plot heatmap
plt.figure(figsize=(10, 6))
sns.heatmap(
scores_array,
annot=True,
xticklabels=labels,
yticklabels=[f"Clause {i+1}" for i in range(len(clauses))],
cmap="Reds"
)
plt.title("Contract Clause Risk Heatmap")
plt.xlabel("Risk Level")
plt.ylabel("Clauses")
plt.tight_layout()
# Save and return the plot
plot_path = "heatmap.png"
plt.savefig(plot_path)
plt.close()
return plot_path
# Gradio UI
demo = gr.Interface(
fn=classify_clauses,
inputs=gr.Textbox(lines=10, label="Enter Contract Clauses (one per line)"),
outputs=gr.Image(type="filepath"),
title="Contract Risk Heatmap Generator",
description="Enter clauses line by line. Uses zero-shot classification to visualize risk levels."
)
if __name__ == "__main__":
demo.launch()
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