# Import required libraries
import os                    # Used to access environment variables (API keys)
import gradio as gr          # Used to create a simple web UI
from groq import Groq        # Groq SDK to interact with Groq LLM API


# -------------------------------------------------------------------
# Read the Groq API key from environment variables
# In Hugging Face Spaces, secrets like API keys are stored securely
# in Settings -> Secrets and injected as environment variables.
# This avoids hardcoding sensitive credentials in the source code.
# -------------------------------------------------------------------
api_key = os.environ.get("GROQ_API_KEY")


# -------------------------------------------------------------------
# Initialize the Groq client only if the API key is available.
# If the key is missing, we set the client to None so we can
# handle the error gracefully instead of crashing the app.
# -------------------------------------------------------------------
if api_key:
    client = Groq(api_key=api_key)
else:
    client = None


# -------------------------------------------------------------------
# Core function that performs the AI code review.
# This function will be triggered when a user submits code
# through the Gradio interface.
# -------------------------------------------------------------------
def review_code(code):

    # ---------------------------------------------------------------
    # Basic validation: check if user submitted empty input.
    # strip() removes whitespace and newline characters.
    # ---------------------------------------------------------------
    if not code.strip():
        return "⚠️ Please paste some code before submitting."

    # ---------------------------------------------------------------
    # Ensure the Groq client is initialized.
    # If the API key is missing, inform the user instead of failing.
    # ---------------------------------------------------------------
    if client is None:
        return "❌ Groq API key not found. Please add GROQ_API_KEY in Hugging Face Space Secrets."

    # ---------------------------------------------------------------
    # Prompt Engineering:
    # We construct a structured prompt to guide the LLM to act
    # as a professional code reviewer and provide useful feedback.
    # ---------------------------------------------------------------
    prompt = f"""
You are an expert software engineer acting as a code reviewer.

Analyze the following code and provide feedback on:

1. Readability
2. Structure
3. Maintainability
4. Best Practices

Also suggest an improved version of the code.

Code:
{code}
"""

    try:

        # -----------------------------------------------------------
        # Send request to Groq LLM using the chat completion API.
        #
        # Model used:
        # llama-3.3-70b-versatile
        # A powerful general-purpose model suitable for reasoning
        # and code analysis.
        #
        # Temperature:
        # Lower value (0.2) ensures more deterministic responses,
        # which is ideal for code analysis instead of creativity.
        # -----------------------------------------------------------
        completion = client.chat.completions.create(
            model="llama-3.3-70b-versatile",
            messages=[
                {"role": "user", "content": prompt}
            ],
            temperature=0.2
        )

        # -----------------------------------------------------------
        # Extract the generated AI response from the API result
        # and return it to the Gradio interface.
        # -----------------------------------------------------------
        return completion.choices[0].message.content

    except Exception as e:

        # -----------------------------------------------------------
        # Error handling:
        # If something goes wrong (API error, network issue, etc.),
        # we catch the exception and display the error message
        # instead of crashing the application.
        # -----------------------------------------------------------
        return f"⚠️ Error while reviewing code: {str(e)}"


# -------------------------------------------------------------------
# Create the Gradio user interface.
# Gradio automatically creates a web application from this config.
# -------------------------------------------------------------------
demo = gr.Interface(

    # Function that will run when user submits input
    fn=review_code,

    # Input component: a code editor with syntax highlighting
    inputs=gr.Code(
        label="Paste your code here",
        language="python"
    ),

    # Output component: rendered as Markdown for better formatting
    outputs=gr.Markdown(label="AI Code Review"),

    # UI Title
    title="Smart Code Reviewer",

    # Description shown under the title
    description="AI assistant that reviews code for readability, structure, maintainability, and best practices."
)


# -------------------------------------------------------------------
# Launch the Gradio application.
# On Hugging Face Spaces this automatically deploys
# the interface as a public web app.
# -------------------------------------------------------------------
demo.launch()