app.py

import gradio as gr
import requests

def call_api(query: str) -> str:
    """
    Calls the public API with the given query.
    """
    url = "https://adityashriv-refudgee-crisis-deepseek.hf.space/query/"
    params = {"input_text": query}
    headers = {"accept": "application/json"}
    
    try:
        response = requests.get(url, params=params, headers=headers)
        response.raise_for_status()  # raise exception for HTTP errors
        json_data = response.json()
        if isinstance(json_data, dict):
            result = response["response"]
        else:
            result = json_data
    except Exception as e:
        result = f"Error: {e}"
    
    return result

def chat_response(user_message: str, history: list) -> tuple:
    """
    Processes a chat message by sending the query to the API and updating
    the conversation history in openai-style format.
    """
    reply = call_api(user_message)
    # Append the user's message and the API response using dictionary format.
    history.append({"role": "user", "content": user_message})
    history.append({"role": "assistant", "content": reply})
    return "", history

# Sample questions as lists, which will populate the input textbox.
sample_questions = [
    ["What are the primary mental health challenges faced by refugee children?"],
    ["What is the current status of the refugee crisis in Europe?"],
    ["Tell me about refugee trends in the Middle East."],
    ["How can technology aid in addressing the mental health needs of refugee children?"],
    ["What policies are in place to address refugee crises?"]
]

with gr.Blocks() as demo:
    gr.Markdown(
        """
        # Refugee Crisis Query Chat

        **Note:** The first query may take some time to respond due to model cold start.
        
        Enter your query below or select one of the sample questions to get started.
        """
    )
    
    user_input = gr.Textbox(show_label=False, placeholder="Enter your query here...", lines=1)
    
    gr.Examples(
        examples=sample_questions,
        inputs=[user_input],
        label="Sample Questions"
    )
    
    # Specify type="messages" for the Chatbot component.
    chatbot = gr.Chatbot(type="messages")
    state = gr.State([])
    send_button = gr.Button("Send")
    
    send_button.click(chat_response, inputs=[user_input, state], outputs=[user_input, chatbot])
    user_input.submit(chat_response, inputs=[user_input, state], outputs=[user_input, chatbot])

demo.launch(share=True)