marwanahmed99/Software_Engineering_Coach

1import os2import time3from typing import List, Tuple, Optional4import google.generativeai as genai5import gradio as gr6from PIL import Image7 8# 1. Configuration & Secrets9# This pulls directly from your Hugging Face "Secrets" section10GOOGLE_API_KEY = os.environ.get("GEMINI_API_KEY")11MODEL_NAME = "gemini-2.0-flash-exp"12IMAGE_WIDTH = 51213 14# 2. The Coaching Persona15COACH_SYSTEM_PROMPT = """16You are a Senior Software Engineering Coach. Your goal is to mentor developers 17by analyzing their code or technical queries through the lens of:18- SOLID, DRY, and KISS principles.19- Security, Scalability, and Maintainability.20- Modern architectural patterns (Microservices, Event-driven, etc.).21 22When providing feedback:231. Don't just give the answer; explain the 'why' to foster growth.242. Identify potential 'code smells' or anti-patterns.253. Provide high-quality, idiomatic code examples.264. If a diagram is provided, analyze the architectural flow or UI/UX logic.27"""28 29# 3. Core Logic30def preprocess_image(image: Image.Image) -> Image.Image:31    if image is None:32        return None33    aspect_ratio = image.height / image.width34    return image.resize((IMAGE_WIDTH, int(IMAGE_WIDTH * aspect_ratio)))35 36def bot(37    image_prompt: Optional[Image.Image],38    temperature: float,39    max_output_tokens: int,40    top_p: float,41    chatbot: List[Tuple[str, str]]42):43    if not GOOGLE_API_KEY:44        chatbot[-1][1] = "Error: GEMINI_API_KEY not found in Hugging Face Secrets."45        yield chatbot46        return47 48    # Initialize the model with the Coach System Prompt49    genai.configure(api_key=GOOGLE_API_KEY)50    model = genai.GenerativeModel(51        model_name=MODEL_NAME, 52        system_instruction=COACH_SYSTEM_PROMPT53    )54    55    text_prompt = chatbot[-1][0].strip() if chatbot[-1][0] else ""56    57    # Prepare Multimodal Inputs58    inputs = []59    if text_prompt:60        inputs.append(text_prompt)61    if image_prompt:62        inputs.append(preprocess_image(image_prompt))63        if not text_prompt:64            inputs[0] = "Please analyze this technical image or code snippet."65 66    try:67        response = model.generate_content(68            inputs,69            stream=True,70            generation_config=genai.types.GenerationConfig(71                temperature=temperature,72                max_output_tokens=max_output_tokens,73                top_p=top_p,74            )75        )76        77        chatbot[-1][1] = ""78        for chunk in response:79            chatbot[-1][1] += chunk.text80            time.sleep(0.005) # Smoother streaming81            yield chatbot82    except Exception as e:83        chatbot[-1][1] = f"Coach encountered an error: {str(e)}"84        yield chatbot85 86# 4. Modernized Gradio UI87with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", neutral_hue="gray")) as demo:88    gr.Markdown("""89    # 👨‍💻 Software Engineering Coach90    *Level up your code with AI-driven mentorship. Paste your code, upload diagrams, or ask architectural questions.*91    """)92    93    with gr.Row():94        with gr.Column(scale=3):95            chatbot_component = gr.Chatbot(96                label="Coaching Session", 97                height=550, 98                show_copy_button=True99            )100            with gr.Row():101                text_input = gr.Textbox(102                    placeholder="Ask about design patterns, refactor code, or debug logic...",103                    label="Message the Coach",104                    scale=4,105                    lines=2106                )107                submit_btn = gr.Button("Analyze", variant="primary", scale=1)108        109        with gr.Column(scale=1):110            image_input = gr.Image(type="pil", label="Visual Context (Code Scrsht/Diagram)")111            112            with gr.Accordion("Fine-tune Mentorship", open=False):113                temp = gr.Slider(0, 1.0, 0.3, label="Creativity/Randomness")114                tokens = gr.Slider(100, 4096, 2048, label="Max Response Length")115                top_p_slider = gr.Slider(0, 1, 0.95, label="Top-P")116            117            gr.Markdown("---")118            gr.Markdown("### Examples")119            gr.Examples(120                examples=[121                    ["Refactor this for better maintainability."],122                    ["Explain the Repository Pattern with a Python example."],123                    ["What are the security risks in this code?"]124                ],125                inputs=text_input126            )127 128    # Event Handlers129    def user_msg(msg, history):130        return "", history + [[msg, None]]131 132    submit_btn.click(133        user_msg, [text_input, chatbot_component], [text_input, chatbot_component]134    ).then(135        bot, 136        [image_input, temp, tokens, top_p_slider, chatbot_component], 137        chatbot_component138    )139 140if __name__ == "__main__":141    demo.launch()