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Vinitrajputt
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Parent(s):
67b6e62
Update app.py
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app.py
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import gradio as gr
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"""
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# You can specify the programming language here
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# based on the user's choice or default to a specific language.
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language = "Python" # Example: defaulting to Python
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# Your code generation logic goes here
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generated_code = generate_code(code, language) # Replace with your code generation function
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return generated_code
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generated_code = f"Generated {language} code: {code}"
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return generated_code
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#
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outputs = gr.outputs.Textbox(label="Generated code")
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interface = gr.Interface(
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fn=code_generation,
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inputs=inputs,
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outputs=outputs,
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title="Gardio App",
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description="An app that generates code based on user input.",
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examples=[
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["Example input code snippet"],
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["Another example input code snippet"],
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],
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allow_screenshot=True
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import gradio as gr
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import torch
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from transformers import GPT2LMHeadModel, GPT2Tokenizer
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# Load the model and tokenizer
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model_name = "abacaj/Replit-v2-CodeInstruct-3B-ggml"
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model = GPT2LMHeadModel.from_pretrained(model_name)
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tokenizer = GPT2Tokenizer.from_pretrained(model_name)
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# Define the code generation function
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def code_generation(code):
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inputs = tokenizer.encode(code, return_tensors="pt")
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outputs = model.generate(inputs, max_length=100, num_return_sequences=1)
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generated_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return generated_code
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# Create the Gradio interface
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iface = gr.Interface(
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fn=code_generation,
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inputs=gr.inputs.Textbox(lines=10, label="Enter your code"),
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outputs=gr.outputs.Textbox(label="Generated code"),
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title="Gardio App",
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description="An app that generates code based on user input.",
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examples=[
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["Example input code snippet"],
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["Another example input code snippet"],
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],
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allow_screenshot=True
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)
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# Launch the interface
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iface.launch()
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