Update app.py

app.py

@@ -10,13 +10,15 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModel.from_pretrained(model_name)
 
 def encode_text(text):
-    inputs = tokenizer(text, return_tensors='pt', padding=True, truncation=True)
+    inputs = tokenizer(text, return_tensors='pt', padding=True, truncation=True, max_length=128)
     outputs = model(**inputs)
+    # Ensure the output is 2D by averaging the last hidden state along the sequence dimension
     return outputs.last_hidden_state.mean(dim=1).detach().numpy()
 
 def find_best_response(user_input, response_pool):
     user_embedding = encode_text(user_input)
     response_embeddings = np.array([encode_text(resp) for resp in response_pool])
+    # Check if response_embeddings need reshaping
     similarities = cosine_similarity(user_embedding, response_embeddings).flatten()
     best_response_index = np.argmax(similarities)
     return response_pool[best_response_index]
@@ -45,3 +47,4 @@ iface = gr.Interface(
 
 # Launch the interface
 iface.launch()
+