init

app.py

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+import gradio as gr
+import tiktoken
+
+def count_tokens(text):
+    """
+    Calculate the number of tokens in the input text using tiktoken.
+
+    Args:
+        text (str): The input text to be tokenized.
+
+    Returns:
+        int: The number of tokens in the input text.
+    """
+    # Choose the encoding based on the model you are targeting.
+    # Here, we use 'gpt-3.5-turbo' as an example.
+    encoding = tiktoken.encoding_for_model("gpt-4")
+    
+    # Encode the input text to get the list of token IDs
+    tokens = encoding.encode(text)
+    
+    # Return the number of tokens
+    return len(tokens)
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=count_tokens,                   # The function to call
+    inputs=gr.Textbox(lines=10, placeholder="Enter your text here..."),  # Input component
+    outputs="number",                  # Output component
+    title="Token Counter with tiktoken",
+    description="Enter text below to calculate the number of tokens using the tiktoken library.",
+    examples=[
+        ["Hello, how are you doing today?"],
+        ["Gradio makes it easy to create web apps for machine learning models."],
+        ["OpenAI's GPT models are powerful tools for natural language processing tasks."]
+    ],
+    theme="default"
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+tiktoken
+gradio