AI Code Review Reporter
This tool generates comprehensive reports based on AI code review feedback for a given codebase. It connects to AI reviewers like Claude AI, analyzes their outputs, and formats the results into developer-friendly reports, highlighting issues, suggestions, and actionable insights. The reports can be exported as markdown or HTML for easy sharing.
What It Does
This tool generates comprehensive reports based on AI code review feedback for a given codebase. It connects to AI reviewers like OpenAI's GPT-4, analyzes their outputs, and formats the results into developer-friendly reports, highlighting issues, suggestions, and actionable insights.
Installation
- Python 3.7+
openaijinja2
Install dependencies using:
pip install -r requirements.txtUsage
python ai_code_review_reporter.py --file example.py --output report.md --format markdown --api_key sk-xxxxxxThis will generate a markdown report based on the AI review of example.py and save it as report.md.
Source Code
import argparse
import openai
import os
from jinja2 import Template
import sys
def fetch_ai_review(file_content, api_key):
"""
Fetch code review feedback from OpenAI's API.
Args:
file_content (str): The content of the code file.
api_key (str): OpenAI API key.
Returns:
str: AI review feedback.
"""
openai.api_key = api_key
try:
response = openai.ChatCompletion.create(
model="gpt-4",
messages=[
{"role": "system", "content": "You are a code reviewer."},
{"role": "user", "content": f"Please review the following code:\n{file_content}"}
]
)
return response['choices'][0]['message']['content']
except Exception as e:
raise RuntimeError(f"Failed to fetch AI review: {e}")
def generate_report(feedback, output_format):
"""
Generate a report based on AI feedback.
Args:
feedback (str): AI feedback text.
output_format (str): Format of the output report ('markdown' or 'html').
Returns:
str: The formatted report.
"""
template_str = """
{% if format == 'markdown' %}
# AI Code Review Report
{{ feedback }}
{% elif format == 'html' %}
<html>
<head><title>AI Code Review Report</title></head>
<body>
<h1>AI Code Review Report</h1>
<pre>{{ feedback }}</pre>
</body>
</html>
{% endif %}
"""
template = Template(template_str)
return template.render(feedback=feedback, format=output_format)
def main():
parser = argparse.ArgumentParser(description="AI Code Review Reporter")
parser.add_argument('--file', required=True, help="Path to the code file to review.")
parser.add_argument('--output', required=True, help="Path to save the generated report.")
parser.add_argument('--format', choices=['markdown', 'html'], default='markdown', help="Output format of the report.")
parser.add_argument('--api_key', required=True, help="OpenAI API key.")
args = parser.parse_args()
if not os.path.isfile(args.file):
print(f"Error: File {args.file} does not exist.", file=sys.stderr)
sys.exit(1)
try:
with open(args.file, 'r') as f:
file_content = f.read()
if not file_content.strip():
print("Error: The file is empty.", file=sys.stderr)
sys.exit(1)
feedback = fetch_ai_review(file_content, args.api_key)
report = generate_report(feedback, args.format)
with open(args.output, 'w') as f:
f.write(report)
print(f"Report successfully generated at {args.output}")
except Exception as e:
print(f"Error: {e}", file=sys.stderr)
sys.exit(1)
if __name__ == "__main__":
main()
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Details
- Tool Name
- ai_code_review_reporter
- Category
- AI Code Review Automation
- Generated
- May 12, 2026
- Tests
- Passing ✅
- Fix Loops
- 4
Quick Install
Clone just this tool:
git clone --depth 1 --filter=blob:none --sparse \ https://github.com/ptulin/autoaiforge.git cd autoaiforge git sparse-checkout set generated_tools/2026-05-12/ai_code_review_reporter cd generated_tools/2026-05-12/ai_code_review_reporter pip install -r requirements.txt 2>/dev/null || true python ai_code_review_reporter.py