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app.py

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+import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# -------------------------
+# Load Model & Tokenizer
+# -------------------------
+model_name = "ibm-granite/granite-3.2-2b-instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+    device_map="auto" if torch.cuda.is_available() else None,
+    low_cpu_mem_usage=True
+)
+
+if tokenizer.pad_token is None:
+    tokenizer.pad_token = tokenizer.eos_token
+
+# -------------------------
+# Response Generator
+# -------------------------
+def generate_response(prompt, max_length=1024):
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
+    if torch.cuda.is_available():
+        inputs = {k: v.to(model.device) for k, v in inputs.items()}
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_length=max_length,
+            temperature=0.7,
+            do_sample=True,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    if response.startswith(prompt):
+        response = response[len(prompt):].strip()
+    return response
+
+# -------------------------
+# Task 1: City Analysis
+# -------------------------
+def city_analysis(city_name):
+    prompt = f"""
+Provide a detailed analysis of {city_name} including:
+1. Crime Index and safety statistics
+2. Accident rates and traffic safety information
+3. Overall safety assessment
+
+City: {city_name}
+Analysis:
+"""
+    return generate_response(prompt, max_length=1000)
+
+# -------------------------
+# Task 2: Citizen Interaction
+# -------------------------
+def citizen_interaction(query):
+    prompt = f"""
+As a government assistant, provide accurate and helpful information about the following citizen query related to public services, government policies, or civic issues:
+
+Query: {query}
+Response:
+"""
+    return generate_response(prompt, max_length=1000)
+
+# -------------------------
+# Login Function
+# -------------------------
+def login_user(name, city, mobile):
+    if not name or not city or not mobile:
+        return gr.update(visible=True), gr.update(visible=False), "⚠️ Please fill all details!"
+    else:
+        welcome_msg = f"✅ Welcome {name} from {city}! (Mobile: {mobile})"
+        return gr.update(visible=False), gr.update(visible=True), welcome_msg
+
+# -------------------------
+# Gradio UI with Login
+# -------------------------
+with gr.Blocks() as app:
+    gr.Markdown("# 🔐 Citizen-AI Login Page")
+
+    # --- Login Page ---
+    with gr.Group(visible=True) as login_page:
+        name_in = gr.Textbox(label="Name", placeholder="Enter your name")
+        city_in = gr.Textbox(label="City", placeholder="Enter your city")
+        mobile_in = gr.Textbox(label="Mobile Number", placeholder="Enter your mobile number")
+        login_btn = gr.Button("Login")
+        login_status = gr.Markdown("")
+
+    # --- Main App Page (Initially Hidden) ---
+    with gr.Group(visible=False) as main_page:
+        gr.Markdown("## 🏙️ Citizen-AI: City Analysis & Public Services Assistant")
+
+        with gr.Tabs():
+            with gr.TabItem("City Analysis"):
+                city_input = gr.Textbox(label="Enter City Name", placeholder="e.g., New York, London, Mumbai...")
+                city_output = gr.Textbox(label="City Analysis Result", lines=15)
+                gr.Button("Analyze City").click(city_analysis, inputs=city_input, outputs=city_output)
+
+            with gr.TabItem("Citizen Services"):
+                citizen_query = gr.Textbox(label="Your Query", placeholder="Ask about public services, government policies, civic issues...", lines=4)
+                citizen_output = gr.Textbox(label="Government Response", lines=15)
+                gr.Button("Get Info").click(citizen_interaction, inputs=citizen_query, outputs=citizen_output)
+
+    # Button Action → Switch Pages
+    login_btn.click(
+        fn=login_user,
+        inputs=[name_in, city_in, mobile_in],
+        outputs=[login_page, main_page, login_status]
+    )
+
+app.launch()

requirements.txt

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+torch
+transformers
+gradio