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