import gradio as gr
import requests
import os  

# 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.Textbox(label="Assertion"), gr.Textbox(label="Citation")],
    outputs=[gr.Label(), gr.Textbox(label="Explanation")],
    live=False,
    title="👋🏻Welcome to 🥒🍆🫑Vectara - Hallucination Tester 🗣️😷",
    description='''
            ### How To Use Hallucination tester: 
            🗣️📝add any assertion from an LLM or a human 🗣️😷 add any citation from a RAG retriever or a source 👇🏻📩 Press send 🔴🟢 red means a hallucination, green means a credible assertion. 
            Check out the model [vectara/hallucination_evaluation_model](https://huggingface.co/vectara/hallucination_evaluation_model) You can also use 🥒🍆🫑Vectara - Hallucination Tester 🗣️😷 via API below or way by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/TeamTonic/vectara-hallucination_evaluation_model?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
            #### Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)"
            ''',
    theme='ParityError/Anime',
)

# Launch the interface
iface.launch()