Update app.py

app.py

@@ -1,6 +1,7 @@
 from sentence_transformers import SentenceTransformer
 import gradio as gr
 import update_packages
+import numpy as np
 
 # Load the pre-trained model
 embedding_model = SentenceTransformer('all-MiniLM-L6-v2')
@@ -8,14 +9,14 @@ embedding_model = SentenceTransformer('all-MiniLM-L6-v2')
 # Define the function to process requests
 def generate_embeddings(chunks):
     embeddings = embedding_model.encode(chunks, convert_to_tensor=False)
-    shape= embeddings.shape
-    return embeddings, shape  # Convert tensor to list for Gradio
+    shape = embeddings.shape
+    return embeddings.tolist(), shape  # Convert numpy array to list
 
 # Define the Gradio interface
 interface = gr.Interface(
     fn=generate_embeddings,
-    inputs=gr.Textbox(lines=5, placeholder="Enter text chunks here..."),
-    outputs=gr.JSON(),
+    inputs=gr.Textbox(lines=5, placeholder="Enter text chunks here...", type="list"),
+    outputs=[gr.JSON(label="Embeddings"), gr.Label(label="Shape")],
     title="Sentence Transformer Embeddings",
     description="Generate embeddings for input text chunks."
 )