Create app.py

app.py

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+import gradio as gr
+from sentence_transformers import SentenceTransformer, util
+
+# Load the strong similarity model
+model = SentenceTransformer("intfloat/multilingual-e5-large-instruct")
+
+def compute_similarity(text1, text2):
+    if not text1.strip() or not text2.strip():
+        return {
+            "similarity_percent": 0,
+            "score": 0,
+            "message": "Both text fields are required."
+        }
+
+    emb1 = model.encode(text1, convert_to_tensor=True)
+    emb2 = model.encode(text2, convert_to_tensor=True)
+
+    score = float(util.cos_sim(emb1, emb2))
+    percent = round(score * 100, 2)
+
+    return {
+        "similarity_percent": percent,
+        "score": score,
+        "message": "Success"
+    }
+
+# Gradio API Interface
+iface = gr.Interface(
+    fn=compute_similarity,
+    inputs=[gr.Textbox(lines=5), gr.Textbox(lines=5)],
+    outputs="json",
+    title="Writenix Similarity Engine",
+    allow_flagging="never"
+)
+
+iface.launch()