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import gradio as gr
import os
import time
import markdown
import tempfile
import traceback
from github_repo_analyzer import get_repo_info, clone_repo, analyze_code, analyze_issues, analyze_pull_requests, llm_analyze_code, llm_analyze_issues, llm_analyze_prs, llm_synthesize_findings, generate_report
from github import Github
from openai import OpenAI
# Emojis and fun statements for progress updates
PROGRESS_STEPS = [
("π΅οΈββοΈ", "Investigating the GitHub realm..."),
("π§¬", "Decoding repository DNA..."),
("π", "Hunting for bugs and features..."),
("π", "Examining pull request tea leaves..."),
("π§ ", "Activating AI brain cells..."),
("π", "Crafting the legendary report..."),
]
def analyze_github_repo(repo_input, github_token=None):
if github_token:
os.environ["GITHUB_TOKEN"] = github_token
github_token = os.environ.get("GITHUB_TOKEN")
if not github_token:
return "<p>β Error: GITHUB_TOKEN environment variable not set.</p>", ""
openrouter_api_key = os.environ.get("OPENROUTER_API_KEY")
if not openrouter_api_key:
return "<p>β Error: OPENROUTER_API_KEY environment variable not set.</p>", ""
progress_html = ""
yield progress_html, "" # Initial empty output
for emoji, message in PROGRESS_STEPS:
progress_html += f"<p>{emoji} {message}</p>"
yield progress_html, ""
time.sleep(4) # Simulate work being done
try:
owner, repo_name = get_repo_info(repo_input)
repo_url = f"https://github.com/{owner}/{repo_name}"
g = Github(github_token)
github_repo = g.get_repo(f"{owner}/{repo_name}")
client = OpenAI(api_key=openrouter_api_key, base_url="https://openrouter.ai/api/v1")
max_issues = 4
max_prs = 4
with tempfile.TemporaryDirectory() as temp_dir:
repo_path = clone_repo(owner, repo_name, temp_dir)
progress_html += "<p>π¬ Analyzing code structure...</p>"
yield progress_html, ""
code_analysis = analyze_code(repo_path)
code_analysis['llm_analysis'] = llm_analyze_code(client, code_analysis)
progress_html += f"<p>π Analyzing issues (max {max_issues})...</p>"
yield progress_html, ""
issues_data = analyze_issues(github_repo, max_issues)
issues_analysis = llm_analyze_issues(client, issues_data, repo_url)
progress_html += f"<p>π Analyzing pull requests (max {max_prs})...</p>"
yield progress_html, ""
prs_data = analyze_pull_requests(github_repo, max_prs)
pr_analysis = llm_analyze_prs(client, prs_data, repo_url)
progress_html += "<p>π§ Synthesizing findings...</p>"
yield progress_html, ""
final_analysis = llm_synthesize_findings(
client,
code_analysis.get('llm_analysis', ''),
issues_analysis.get('summary', ''),
pr_analysis.get('summary', '')
)
repo_info = {
"owner": owner,
"repo_name": repo_name,
}
progress_html += "<p>π Generating report...</p>"
yield progress_html, ""
report = generate_report(repo_info, code_analysis, issues_analysis, pr_analysis, final_analysis)
# Convert markdown to HTML
html_report = markdown.markdown(report)
return progress_html + "<p>β
Analysis complete!</p>", html_report
except Exception as e:
error_message = f"<p>β An error occurred: {str(e)}</p>"
traceback.print_exc()
return progress_html + error_message, ""
# Define the Gradio interface
with gr.Blocks() as app:
gr.Markdown("# GitHub Repository Analyzer")
repo_input = gr.Textbox(label="Enter GitHub Repository Slug or URL")
with gr.Accordion("Advanced Settings", open=False):
github_token = gr.Textbox(label="GitHub Token (optional)", type="password")
analyze_button = gr.Button("Analyze Repository")
progress_output = gr.HTML(label="Progress")
report_output = gr.HTML(label="Analysis Report")
analyze_button.click(
analyze_github_repo,
inputs=[repo_input, github_token],
outputs=[progress_output, report_output],
)
# Launch the app
if __name__ == "__main__":
app.launch() |