Create app.py

app.py

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+import gradio as gr
+import torch
+from transformers import DistilBertTokenizer, DistilBertModel
+
+class SimilarityPredictor:
+    def __init__(self):
+        self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+        self.model = DistilBertModel.from_pretrained('patent_similarity_model').to(self.device)
+        self.tokenizer = DistilBertTokenizer.from_pretrained('patent_similarity_model')
+        self.head = torch.nn.Sequential(torch.nn.Linear(768, 1), torch.nn.Sigmoid()).to(self.device)
+        self.head.load_state_dict(torch.load('patent_similarity_model/head.pt', map_location=self.device))
+        
+    def predict(self, anchor, target):
+        self.model.eval()
+        with torch.no_grad():
+            encoded = self.tokenizer(
+                [anchor], 
+                [target],
+                padding=True,
+                truncation=True,
+                max_length=64,
+                return_tensors='pt'
+            ).to(self.device)
+            
+            output = self.head(self.model(**encoded)[0][:,0,:]).squeeze()
+            return float(output)
+
+predictor = SimilarityPredictor()
+
+# Örnek seçenekler
+example_pairs = [
+    ["mobile phone", "cellphone"],
+    ["artificial intelligence", "machine learning"],
+    ["electric vehicle", "battery powered car"],
+    ["wireless communication", "radio transmission"],
+    ["solar panel", "photovoltaic cell"],
+    ["computer processor", "CPU"],
+    ["digital storage", "memory device"],
+    ["touch screen", "interactive display"],
+    ["biometric authentication", "fingerprint recognition"],
+    ["cloud computing", "remote server processing"]
+]
+
+def predict_similarity(anchor, target):
+    score = predictor.predict(anchor, target)
+    return round(score, 3)
+
+# Create Gradio interface with examples
+iface = gr.Interface(
+    fn=predict_similarity,
+    inputs=[
+        gr.Textbox(label="Anchor Phrase", placeholder="Enter first phrase..."),
+        gr.Textbox(label="Target Phrase", placeholder="Enter second phrase...")
+    ],
+    outputs=gr.Number(label="Similarity Score (0-1)"),
+    title="Patent Phrase Similarity Checker",
+    description="""Compare the similarity between two patent phrases.
+    
+    Score guide:
+    - 1.0: Very close match (exact or near-exact)
+    - 0.75: Close synonyms
+    - 0.5: Related terms
+    - 0.25: Somewhat related
+    - 0.0: Unrelated
+    
+    Try the examples below or enter your own phrases!""",
+    examples=example_pairs,
+    theme="huggingface",
+    css="footer {display: none !important;}"
+)
+
+iface.launch()