| import gradio as gr |
| import subprocess |
| from huggingface_hub import InferenceClient |
|
|
| client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") |
| question = "Fibonacci series." |
| 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." |
| def respond( |
| message, |
| history: list[tuple[str, str]], |
| system_message, |
| max_tokens, |
| temperature, |
| top_p, |
| ): |
| messages = [{"role": "system", "content": system_message}] |
|
|
| for val in history: |
| if val[0]: |
| messages.append({"role": "user", "content": val[0]}) |
| if val[1]: |
| messages.append({"role": "assistant", "content": val[1]}) |
|
|
| messages.append({"role": "user", "content": message}) |
|
|
| response = "" |
|
|
| for message in client.chat_completion( |
| messages, |
| max_tokens=max_tokens, |
| stream=True, |
| temperature=temperature, |
| top_p=top_p, |
| ): |
| token = message.choices[0].delta.content |
| response += token |
| yield response |
|
|
| def run_python_code(code): |
| try: |
| result = subprocess.run(['python3', '-c', code], capture_output=True, text=True) |
| output = result.stdout if result.stdout else result.stderr |
| return output |
| except Exception as e: |
| return str(e) |
|
|
| def AI_analyse(output): |
| try: |
| system_message = prompt |
| max_tokens = 512 |
| temperature = 0.7 |
| top_p = 0.95 |
| message = prompt + "Please analyse the following code:\n" + output |
| response = respond(message, [], system_message, max_tokens, temperature, top_p) |
| for word in response: |
| res=str(word) |
| return res |
| except Exception as e: |
| return str(e) |
|
|
| with gr.Blocks() as demo: |
| gr.Markdown("# Code Wiz") |
|
|
| with gr.Row(): |
| with gr.Column(): |
| |
| gr.Textbox(label="Question: Write a program to print Fibonacci series.", lines=1,interactive=False) |
| with gr.Row(): |
| with gr.Column(): |
| code = gr.Code(label="Python Code", language="python", lines=5,elem_id="box") |
| run_button = gr.Button("Run") |
| with gr.Row(): |
| with gr.Column(): |
| output = gr.Textbox(label="Output", lines=3, max_lines=20, interactive=False, elem_id="box") |
| |
| with gr.Row(): |
| with gr.Column(): |
| analyse_button = gr.Button("Analyse") |
| ai_suggestion = gr.Textbox(label="AI Suggest", lines=7, placeholder="AI suggestions will be displayed here", interactive=False,elem_id="box") |
| |
|
|
| run_button.click(fn=run_python_code, inputs=code, outputs=output) |
| analyse_button.click(fn=AI_analyse, inputs=output, outputs=ai_suggestion) |
|
|
| |
| demo.css = """ |
| #box { |
| overflow-y: scroll; |
| } |
| """ |
|
|
| if __name__ == "__main__": |
| demo.launch() |
