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import gradio as gr
import requests
# Define the API parameters
API_URL = "https://api-inference.huggingface.co/models/vectara/hallucination_evaluation_model"
API_TOKEN = os.getenv("HF_AUTH_TOKEN")
if not API_TOKEN:
raise ValueError("Please set the HF_AUTH_TOKEN environment variable.")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
# Function to query the API
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.json()
# Function to be called by the Gradio interface
def evaluate_hallucination(input1, input2):
# Combine the inputs
combined_input = f"{input1}. {input2}"
# Make the API call
output = query({"inputs": combined_input})
# Extract the score from the output
score = output[0][0]['score']
# Return a red or green circle based on the score
if score < 0.5:
return "🔴", "The score is less than 0.5"
else:
return "🟢", "The score is greater than 0.5"
# Create the Gradio interface
iface = gr.Interface(
fn=evaluate_hallucination,
inputs=[gr.inputs.Textbox(label="Input 1"), gr.inputs.Textbox(label="Input 2")],
outputs=[gr.outputs.Label(), gr.outputs.Textbox(label="Explanation")],
live=False
)
# Launch the interface
iface.launch() |