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Update app.py
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app.py
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@@ -4,29 +4,26 @@ from huggingface_hub import InferenceClient
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# Initialize the Hugging Face Inference Client
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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def explain_code(
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system_message
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max_tokens,
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temperature,
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top_p
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):
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# Prepare messages for the model
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messages = [{"role": "system", "content": system_message}]
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messages.append({
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"role": "user",
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"content": f"Please provide a detailed explanation of the following code snippet:\n```{code_snippet}```"
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})
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response = ""
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try:
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# Generate the response using the model
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for msg in client.chat_completion(
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messages,
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max_tokens=
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stream=True,
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temperature=
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top_p=
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):
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token = msg["choices"][0]["delta"]["content"]
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response += token
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@@ -35,28 +32,13 @@ def explain_code(
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return response
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#
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examples = [
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["x = 5\nprint(x)"],
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["def add(a, b):\n return a + b\nresult = add(2, 3)\nprint(result)"],
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["for i in range(5):\n print(i)"],
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["if x > 0:\n print('Positive')\nelse:\n print('Non-positive')"],
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["squares = [i**2 for i in range(10)]\nprint(squares)"]
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]
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# Create the Gradio Interface
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demo = gr.Interface(
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fn=explain_code,
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inputs=
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gr.Textbox(placeholder="Enter your code snippet here...", label="Code Snippet", lines=10),
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gr.Textbox(value="You are an expert assistant that explains Python code snippets clearly and concisely.", label="System message"),
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gr.Slider(1, 2048, 512, step=1, label="Max new tokens"),
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gr.Slider(0.1, 4.0, 0.7, step=0.1, label="Temperature"),
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gr.Slider(0.1, 1.0, 0.95, step=0.05, label="Top-p (nucleus sampling)")
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],
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outputs=gr.Textbox(label="Explanation Here", lines=10),
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)
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if __name__ == "__main__":
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# Initialize the Hugging Face Inference Client
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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def explain_code(code_snippet):
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# Prepare a basic system message
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system_message = "You are an expert assistant that explains Python code snippets clearly and concisely."
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response = ""
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try:
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# Prepare the messages for the model
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messages = [{"role": "system", "content": system_message}]
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messages.append({
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"role": "user",
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"content": f"Please provide a detailed explanation of the following code snippet:\n```{code_snippet}```"
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})
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# Generate the response using the model
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for msg in client.chat_completion(
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messages,
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max_tokens=2047,
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stream=True,
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temperature=0.7,
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top_p=0.95
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):
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token = msg["choices"][0]["delta"]["content"]
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response += token
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return response
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# Create the Gradio Interface with only the necessary components
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demo = gr.Interface(
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fn=explain_code,
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inputs=gr.Textbox(placeholder="Enter your code snippet here...", label="Code Snippet", lines=10),
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outputs=gr.Textbox(label="Explanation Here", lines=10),
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title="Python Code Explainer",
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theme="default"
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)
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if __name__ == "__main__":
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