Create app.py

app.py

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+import gradio as gr
+import spacy
+import re
+
+nlp = spacy.load("en_core_web_sm")
+
+# --- Dictionaries ---
+VILLAGES = ["Triolet","Curepipe","Flacq","Moka","Port Louis"]
+FIRST_NAMES = ["Amit","Reena","Sanjay","Aisha","Sidharth"]
+LAST_NAMES = ["Ramgoolam","Pudaruth","Lalloo","Hossen"]
+PRODUCTS = ["Honda Fit","Suzuki Swift","Toyota Vitz","iPhone"]
+
+REGEX_PATTERNS = {
+    "NUMBER": r"\b\d+(?:,\d{3})*(?:\.\d+)?\b",
+    "TIME": r"\b\d{1,2}[:h]\d{2}(?:am|pm|AM|PM)?\b",
+    "DATE": r"\b\d{4}-\d{2}-\d{2}\b"
+}
+
+def detect_entities(text):
+    ents = []
+    
+    # 1. spaCy detection
+    doc = nlp(text)
+    for ent in doc.ents:
+        ents.append({"text": ent.text, "type": ent.label_})
+
+    # 2. Dictionary detection
+    for word in VILLAGES + FIRST_NAMES + LAST_NAMES + PRODUCTS:
+        for m in re.finditer(re.escape(word), text, flags=re.IGNORECASE):
+            ents.append({"text": m.group(), "type": "KNOWN"})
+
+    # 3. Regex detection
+    for etype, pattern in REGEX_PATTERNS.items():
+        for m in re.finditer(pattern, text):
+            ents.append({"text": m.group(), "type": etype})
+
+    return ents
+
+# --- Gradio Interface ---
+demo = gr.Interface(
+    fn=detect_entities,
+    inputs=gr.Textbox(label="Text"),
+    outputs="json",
+    title="Entity Detection API",
+    description="API for detecting names, places, numbers, times."
+)
+
+# API endpoint: /api/predict
+demo.launch()