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Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline, AutoTokenizer
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# Load the StarChat beta model
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MODEL_NAME = "HuggingFaceH4/starchat-beta"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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generator = pipeline(
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"text-generation",
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model=MODEL_NAME,
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tokenizer=tokenizer,
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device="cpu", # Free tier uses CPU
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)
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def generate_code(natural_language_input):
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try:
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# Create a proper prompt for the model
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chat_prompt = [
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{"role": "system", "content": "You are a helpful AI assistant that generates Python code based on natural language descriptions."},
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{"role": "user", "content": f"Write Python code that: {natural_language_input}"}
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]
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# Generate the prompt for the model
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prompt = tokenizer.apply_chat_template(chat_prompt, tokenize=False, add_generation_prompt=True)
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# Generate code with appropriate parameters for code generation
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generated = generator(
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prompt,
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max_new_tokens=256,
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temperature=0.2,
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top_p=0.95,
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do_sample=True,
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pad_token_id=tokenizer.eos_token_id,
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eos_token_id=tokenizer.eos_token_id,
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)
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# Extract and clean the generated code
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full_response = generated[0]['generated_text']
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code_response = full_response.replace(prompt, "").strip()
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# Sometimes the model adds non-code text - we'll try to extract just the code blocks
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if "```python" in code_response:
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code_response = code_response.split("```python")[1].split("```")[0]
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elif "```" in code_response:
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code_response = code_response.split("```")[1].split("```")[0]
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return code_response
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except Exception as e:
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return f"Error generating code: {str(e)}"
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# Gradio interface
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("""
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# 🚀 Text to Python Code Generator
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### Powered by StarChat Beta
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Describe what you want the code to do in natural language, and get Python code!
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""")
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with gr.Row():
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with gr.Column(scale=3):
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input_text = gr.Textbox(
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label="Describe your code task",
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placeholder="e.g., 'create a Flask web server with two routes'",
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lines=3,
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max_lines=6
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)
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with gr.Row():
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generate_btn = gr.Button("Generate Code", variant="primary")
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clear_btn = gr.Button("Clear")
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gr.Markdown("**Tips:** Be specific in your description for better results.")
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with gr.Column(scale=4):
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output_code = gr.Code(
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label="Generated Python Code",
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language="python",
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interactive=True,
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lines=10
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)
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with gr.Row():
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copy_btn = gr.Button("Copy to Clipboard")
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refresh_btn = gr.Button("Try Again")
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# Examples
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examples = gr.Examples(
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examples=[
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["create a function to calculate factorial recursively"],
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["write code to download a file from URL and save it locally"],
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["create a pandas DataFrame from a dictionary and plot a bar chart"],
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["implement a simple REST API using FastAPI with GET and POST endpoints"]
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],
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inputs=input_text,
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label="Click any example to try it"
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)
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# Button actions
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generate_btn.click(
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fn=generate_code,
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inputs=input_text,
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outputs=output_code
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)
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clear_btn.click(
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fn=lambda: ("", ""),
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inputs=None,
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outputs=[input_text, output_code]
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)
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refresh_btn.click(
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fn=generate_code,
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inputs=input_text,
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outputs=output_code
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)
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copy_btn.click(
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fn=lambda code: gr.Clipboard().copy(code),
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inputs=output_code,
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outputs=None,
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api_name="copy_code"
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)
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demo.launch(debug=True)
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