Update app.py

app.py

@@ -1,28 +1,32 @@
 import gradio as gr
 from transformers import AutoModel, AutoTokenizer
 import numpy as np
+import json
 
 # Load a small CPU model for text to vector processing
 model_name = "sentence-transformers/all-mpnet-base-v2"
 model = AutoModel.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-def text_to_vector(texts):
-    # Expect texts to be an array of sentences
+def text_to_vector(texts_json):
+    try:
+        texts = json.loads(texts_json)
+        if not isinstance(texts, list):
+            raise ValueError("Input must be a JSON array of strings.")
+    except json.JSONDecodeError:
+        raise ValueError("Invalid JSON format.")
+
     inputs = tokenizer(texts, return_tensors="pt", padding=True, truncation=True)
     outputs = model(**inputs)
-    vectors = outputs.pooler_output.detach().numpy()
-    
-    # Convert each vector to a string representation
-    vector_strings = [", ".join(map(str, vector)) for vector in vectors]
-    return vector_strings
+    vectors = outputs.pooler_output.detach().numpy().tolist()  # Convert to list
+    return json.dumps(vectors)  # Return as JSON string
 
 demo = gr.Interface(
     fn=text_to_vector,
     inputs=gr.Textbox(label="Enter JSON array", placeholder="Enter an array of sentences as a JSON string"),
-    outputs=gr.Textbox(label="Text Vectors", lines=10),
+    outputs=gr.Textbox(label="Text Vectors (JSON)", lines=10),
     title="Batch Text to Vector",
-    description="This demo converts an array of sentences to vectors."
+    description="This demo converts an array of sentences to vectors and returns them as a JSON array."
 )
 
 demo.launch()