Update app.py

app.py

@@ -1,71 +1,71 @@
-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 = [
-    ["How many cases of refugee crises have we had in the US in 1 year?"],
-    ["What is the current status of the refugee crisis in Europe?"],
-    ["Tell me about refugee trends in the Middle East."],
-    ["How does the refugee crisis affect the economy in the US?"],
-    ["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])
-
-demo.launch()
+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 = [
+    ["How many cases of refugee crises have we had in the US in 1 year?"],
+    ["What is the current status of the refugee crisis in Europe?"],
+    ["Tell me about refugee trends in the Middle East."],
+    ["How does the refugee crisis affect the economy in the US?"],
+    ["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])
+
+demo.launch(share=True)