Update app.py

app.py

@@ -17,11 +17,12 @@ client = OpenAI(api_key=api_key)
 def encode_text(text):
     inputs = bi_tokenizer(text, return_tensors='pt', padding=True, truncation=True, max_length=128)
     outputs = bi_model(**inputs)
-    return outputs.last_hidden_state.mean(dim=1).detach().numpy()
+    return outputs.last_hidden_state.mean(dim=1).detach().numpy().flatten()  # Ensure the output is 2D
 
 def retrieve_relevant_context(user_input, context_texts):
-    user_embedding = encode_text(user_input)
+    user_embedding = encode_text(user_input).reshape(1, -1)
     context_embeddings = np.array([encode_text(text) for text in context_texts])
+    context_embeddings = context_embeddings.reshape(len(context_embeddings), -1)  # Flatten each embedding
     similarities = cosine_similarity(user_embedding, context_embeddings).flatten()
     most_relevant_idx = np.argmax(similarities)
     return context_texts[most_relevant_idx]
@@ -40,7 +41,7 @@ def generate_response(user_input, relevant_context):
         frequency_penalty=0.5,
         presence_penalty=0.0
     )
-    return response.choices[0].message['content']
+    return response.choices[0].message.content.strip()
 
 def chatbot(user_input, context=""):
     context_texts = context.split("\n")
@@ -61,7 +62,8 @@ iface = gr.Interface(
 )
 
 # Launch the interface
-iface.launch()
+iface.launch(share=True)
+