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import gradio as gr |
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import subprocess |
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from huggingface_hub import InferenceClient |
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") |
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question = "Fibonacci series." |
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prompt = f"You are an expert in coding. your task is to explain error and give hint to understand question{question}.Do not give complete answer.Do not give implemmentation." |
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def respond( |
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message, |
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history: list[tuple[str, str]], |
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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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messages = [{"role": "system", "content": system_message}] |
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for val in history: |
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if val[0]: |
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messages.append({"role": "user", "content": val[0]}) |
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if val[1]: |
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messages.append({"role": "assistant", "content": val[1]}) |
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messages.append({"role": "user", "content": message}) |
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response = "" |
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for message in client.chat_completion( |
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messages, |
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max_tokens=max_tokens, |
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stream=True, |
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temperature=temperature, |
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top_p=top_p, |
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): |
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token = message.choices[0].delta.content |
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response += token |
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yield response |
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def run_python_code(code): |
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try: |
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result = subprocess.run(['python3', '-c', code], capture_output=True, text=True) |
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output = result.stdout if result.stdout else result.stderr |
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return output |
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except Exception as e: |
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return str(e) |
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def AI_analyse(output): |
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try: |
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system_message = prompt |
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max_tokens = 512 |
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temperature = 0.7 |
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top_p = 0.95 |
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message = prompt + "Please analyse the following code:\n" + output |
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response = respond(message, [], system_message, max_tokens, temperature, top_p) |
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for word in response: |
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res=str(word) |
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return res |
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except Exception as e: |
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return str(e) |
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with gr.Blocks() as demo: |
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gr.Markdown("# Code Wiz") |
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with gr.Row(): |
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with gr.Column(): |
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gr.Textbox(label="Question: Write a program to print Fibonacci series.", lines=1,interactive=False) |
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with gr.Row(): |
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with gr.Column(): |
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code = gr.Code(label="Python Code", language="python", lines=5,elem_id="box") |
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run_button = gr.Button("Run") |
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with gr.Row(): |
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with gr.Column(): |
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output = gr.Textbox(label="Output", lines=3, max_lines=20, interactive=False, elem_id="box") |
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with gr.Row(): |
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with gr.Column(): |
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analyse_button = gr.Button("Analyse") |
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ai_suggestion = gr.Textbox(label="AI Suggest", lines=7, placeholder="AI suggestions will be displayed here", interactive=False,elem_id="box") |
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run_button.click(fn=run_python_code, inputs=code, outputs=output) |
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analyse_button.click(fn=AI_analyse, inputs=output, outputs=ai_suggestion) |
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demo.css = """ |
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#box { |
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overflow-y: scroll; |
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} |
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""" |
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if __name__ == "__main__": |
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demo.launch() |
