Update app.py

app.py

@@ -1,71 +1,34 @@
 import gradio as gr
 from transformers import pipeline
-import time
 
-# Load the GPT-Neo model for text generation
-text_generator = pipeline('text-generation', model='EleutherAI/gpt-neo-125M')
+# Load a faster text generation model (DistilGPT-2)
+text_generator = pipeline('text-generation', model='distilgpt2')
 
 def get_completion(code_snippet):
-    print("Received code snippet, starting processing...")
-    start_time = time.time()
-
-    # Provide simplified examples
-    python_code_examples = """
-    Example 1:
-    x = 10
-    def foo():
-        global x
-        x = 5
-    foo()
-    print(x)
-    Expected output: 5
-    Explanation: The `global` keyword allows `foo` to modify the variable `x`.
-
-    Example 2:
-    def modify_list(input_list):
-        input_list.append(4)
-        input_list = [1, 2, 3]
-    my_list = [0]
-    modify_list(my_list)
-    print(my_list)
-    Expected output: [0, 4]
-    Explanation: The function modifies the original list by appending `4`.
-
-    Example 3:
-    print('hello')
-    Expected output: hello
-    Explanation: This line prints the string `hello`.
-    """
-
+    # Prompt to explain the code snippet provided by the user
     prompt = f"""
-    Explain the following code snippet step-by-step using these examples as references:
-    {python_code_examples}
-    
+    Please explain the following Python code snippet in detail, including what it does and the expected output:
+
     Code Snippet:
-    ```
+    ```python
     {code_snippet}
     ```
     
-    Provide a detailed breakdown of how the code works, including the expected output.
+    Include any relevant information that helps clarify how the code works.
     """
 
-    try:
-        print("Generating text...")
-        response = text_generator(prompt, max_new_tokens=100, num_return_sequences=1)
-        print("Text generation complete.")
-        return response[0]['generated_text'].strip()
-    except Exception as e:
-        return f"An error occurred: {str(e)}"
-    finally:
-        elapsed_time = time.time() - start_time
-        print(f"Processing time: {elapsed_time:.2f} seconds")
+    # Generate text using the model
+    response = text_generator(prompt, max_length=300, num_return_sequences=1, temperature=0.5)
+
+    return response[0]['generated_text'].strip()
 
 # Define the Gradio interface
 iface = gr.Interface(
     fn=get_completion,
     inputs=[gr.Textbox(label="Insert Code Snippet", lines=5)],
-    outputs=[gr.Textbox(label="Explanation Here", lines=8)],
-    title="Code Explainer"
+    outputs=[gr.Textbox(label="Explanation Here", lines=10)],
+    title="Code Explainer Using Transformers"
 )
 
+# Launch the Gradio interface
 iface.launch()