Create app.py

app.py

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+# app.py
+# Complaint Prioritization System wrapped in a Gradio app (and API)
+
+from typing import Dict, Any
+import gradio as gr
+
+# ================================
+# Configuration (default values)
+# ================================
+DEFAULT_PRIORITY_SCORE = {
+    "water": 0.9,
+    "electricity": 0.9,
+    "gas": 0.6,
+    "road": 0.5,
+    "garbage": 0.2
+}
+
+DEPARTMENT_WEIGHT = {
+    "water": 1.2,
+    "electricity": 1.2,
+    "gas": 1.0,
+    "road": 0.9,
+    "garbage": 0.8
+}
+
+# Helper to convert 0–1 score into labels
+def get_priority_label(score: float) -> str:
+    if score >= 0.75:
+        return "Critical"
+    elif score >= 0.55:
+        return "High"
+    elif score >= 0.35:
+        return "Medium"
+    else:
+        return "Low"
+
+# Calculate weighted score (0–1)
+def calculate_weighted_score(upvotes: int, complaints: int, alpha: float=0.6, beta: float=0.4) -> float:
+    # Normalize to 0–1 scale (cap at 1)
+    upvote_score = min(upvotes / 50.0, 1.0)       # assume 50 upvotes = max
+    complaint_score = min(complaints / 20.0, 1.0) # assume 20 complaints = max
+    weighted = (alpha * complaint_score) + (beta * upvote_score)
+    return weighted
+
+# Core handler
+def handle_complaint(text: str, category: str, complaints: int, upvotes: int) -> Dict[str, Any]:
+    if category is None:
+        category = ""
+    category_key = category.strip().lower()
+    default_score = DEFAULT_PRIORITY_SCORE.get(category_key, 0.3)
+    weighted_score = calculate_weighted_score(upvotes=upvotes, complaints=complaints)
+    department_bias = DEPARTMENT_WEIGHT.get(category_key, 1.0)
+
+    # Final score = (default + weighted)/2 * department bias
+    raw_final = 0.5 * default_score + 0.5 * weighted_score
+    final_score = min(raw_final * department_bias, 1.0)  # cap at 1.0
+
+    result = {
+        "text": text,
+        "category": category_key if category_key else "unknown",
+        "default_score": round(default_score, 2),
+        "weighted_score": round(weighted_score, 2),
+        "department_bias": department_bias,
+        "final_score": round(final_score, 2),
+        "final_label": get_priority_label(final_score)
+    }
+    return result
+
+# Gradio UI & API
+with gr.Blocks() as demo:
+    gr.Markdown("# Complaint Prioritization API")
+    gr.Markdown("Provide complaint text, category, number of complaints and upvotes. The endpoint `/api/predict` will return the same JSON.")
+    with gr.Row():
+        txt = gr.Textbox(lines=3, label="Complaint text", value="Pothole on main road causing damage.")
+        cat = gr.Textbox(lines=1, label="Category (water, electricity, gas, road, garbage)", value="road")
+    with gr.Row():
+        complaints_in = gr.Number(value=1, label="Number of distinct complaints (integer)")
+        upvotes_in = gr.Number(value=0, label="Number of upvotes/flags (integer)")
+    run_btn = gr.Button("Get Priority")
+    output = gr.JSON(label="Result")
+
+    run_btn.click(fn=handle_complaint,
+                  inputs=[txt, cat, complaints_in, upvotes_in],
+                  outputs=output)
+
+# Provide a simple example on load
+demo.load(lambda: {
+    "text": "Example: Water pipeline leakage near market area.",
+    "category": "water",
+    "default_score": DEFAULT_PRIORITY_SCORE["water"],
+    "weighted_score": 0.0,
+    "department_bias": DEPARTMENT_WEIGHT["water"],
+    "final_score": None,
+    "final_label": None
+}, outputs=output)
+
+if __name__ == "__main__":
+    demo.launch()