feat: update the output format of kaizen bot

[sauravpanda]

Something like this would be pretty:

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🔍 Code Review Summary

📊 Stats

• Total Issues: 3
• Critical: 2
• Important: 1
• Minor: 0
• Files Affected: 3
• Lines of Code Changed: 35

🏆 Code Quality

[██████████░░░░░░░░░░] 60% (Needs Improvement)

🚨 Critical Issues

Error Handling (2 issues)

1. Generic exception handling without specific logging

📁 File: backend/code_review/helper.py:520
⚖️ Severity: 10/10
🔍 Description: Using a generic exception handler can obscure the root cause of errors.
💡 Solution: Log the exception type and message for better clarity.

Current Code:

try:
    # Some code here
except Exception:
    pass  # Generic exception handling

Suggested Code:

import logging

try:
    # Some code here
except Exception as e:
    logging.error(f"An error occurred: {type(e).__name__}, {str(e)}")

2. Lack of error handling when parsing JSON from request body

📁 File: backend/code_scan/views.py:8
⚖️ Severity: 10/10
🔍 Description: If the request body is not valid JSON, this will raise a ValueError and potentially crash the application.
💡 Solution: Wrap the JSON parsing in a try-except block to handle potential errors gracefully.

Current Code:

data = json.loads(request.body)

Suggested Code:

from django.http import JsonResponse

try:
    data = json.loads(request.body)
except json.JSONDecodeError:
    return JsonResponse({"error": "Invalid JSON in request body"}, status=400)

🟠 Important Issues

New Functionality (1 issue)

1. New function update_scan_frequency lacks input validation

📁 File: backend/code_review/views.py:149
⚖️ Severity: 8/10
🔍 Description: The function assumes that the input data will always contain the required fields, which can lead to KeyErrors if not validated.
💡 Solution: Add validation to check for required fields in the input data.

Current Code:

def update_scan_frequency(data):
    project_id = data['project_id']
    new_frequency = data['frequency']
    # Update logic here

Suggested Code:

def update_scan_frequency(data):
    if 'project_id' not in data or 'frequency' not in data:
        raise ValueError("Missing required fields: project_id and frequency")
    
    project_id = data['project_id']
    new_frequency = data['frequency']
    # Update logic here

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