analyze-gh-repo / app.py
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import gradio as gr
import os
import time
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 = [
("πŸ•΅οΈβ€β™‚οΈ", "Investigating the GitHub realm..."),
("🧬", "Decoding repository DNA..."),
("πŸ›", "Hunting for bugs and features..."),
("πŸ”", "Examining pull request tea leaves..."),
("🧠", "Activating AI brain cells..."),
("πŸ“", "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 "❌ Error: GITHUB_TOKEN environment variable not set.", gr.update(visible=True), gr.update(visible=False)
openrouter_api_key = os.environ.get("OPENROUTER_API_KEY")
if not openrouter_api_key:
return "❌ Error: OPENROUTER_API_KEY environment variable not set.", gr.update(visible=True), gr.update(visible=False)
progress_md = ""
yield progress_md, gr.update(visible=True), gr.update(visible=False) # Initial empty output
for emoji, message in PROGRESS_STEPS:
progress_md += f"{emoji} {message} \n"
yield progress_md, gr.update(visible=True), gr.update(visible=False)
time.sleep(4)
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_info = clone_repo(owner, repo_name, temp_dir)
repo_path = repo_info["local_path"]
progress_md += "πŸ”¬ Analyzing code structure... \n"
yield progress_md, gr.update(visible=True), gr.update(visible=False)
code_analysis = analyze_code(repo_path)
code_analysis['llm_analysis'] = llm_analyze_code(client, code_analysis)
progress_md += f"πŸ“Š Analyzing issues (max {max_issues})... \n"
yield progress_md, gr.update(visible=True), gr.update(visible=False)
issues_data = analyze_issues(github_repo, max_issues)
issues_analysis = llm_analyze_issues(client, issues_data, repo_url)
progress_md += f"πŸ”€ Analyzing pull requests (max {max_prs})... \n"
yield progress_md, gr.update(visible=True), gr.update(visible=False)
prs_data = analyze_pull_requests(github_repo, max_prs)
pr_analysis = llm_analyze_prs(client, prs_data, repo_url)
# progress_md += "🧠 Synthesizing findings... \n"
# yield progress_md, gr.update(visible=True), gr.update(visible=False)
# final_analysis = llm_synthesize_findings(
# client,
# code_analysis.get('llm_analysis', ''),
# issues_analysis.get('summary', ''),
# pr_analysis.get('summary', '')
# )
progress_md += "πŸ“ Generating report... \n"
yield progress_md, gr.update(visible=True), gr.update(visible=False)
report = generate_report(repo_info, code_analysis, issues_analysis, pr_analysis)
# Return the final Markdown report
yield progress_md + "βœ… Analysis complete!", gr.update(visible=False), gr.update(visible=True, value=report)
except Exception as e:
error_message = f"❌ An error occurred: {str(e)}"
traceback.print_exc()
yield progress_md + error_message, gr.update(visible=True), gr.update(visible=False)
# Define the Gradio interface
with gr.Blocks() as app:
gr.Markdown("# Patched GitHub Repo Analyzer")
gr.Markdown("## Build and run your identified patchflows with [patched](https://patched.codes)")
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.Markdown(label="Progress")
report_output = gr.Markdown(label="Analysis Report", visible=False)
analyze_button.click(
analyze_github_repo,
inputs=[repo_input, github_token],
outputs=[progress_output, progress_output, report_output],
)
# Launch the app
if __name__ == "__main__":
app.launch()