mirror of
https://github.com/google-gemini/gemini-cli.git
synced 2026-05-14 22:02:59 -07:00
Coco Sheng
100 lines
3.6 KiB
Python
100 lines
3.6 KiB
Python
import json
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import urllib.request
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import os
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import subprocess
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import re
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import concurrent.futures
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API_KEY = "REDACTED_API_KEY"
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MODEL = "gemini-3-flash-preview"
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URL = f"https://generativelanguage.googleapis.com/v1beta/models/{MODEL}:generateContent?key={API_KEY}"
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BUGS_FILE = 'data/issues.json'
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with open(BUGS_FILE, 'r') as f:
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bugs = json.load(f)
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def extract_files(text):
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matches = re.findall(r'([\w\.\/\-]+\.(?:ts|tsx|js|json|md))', text)
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return set([m for m in matches if not m.startswith('http')])
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def get_file_content(filepath):
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try:
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filename = os.path.basename(filepath)
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cmd = f'find /Users/cocosheng/gemini-cli -type d -name "node_modules" -prune -o -type f -name "{filename}" -print | head -n 1'
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actual_path = subprocess.check_output(cmd, shell=True, text=True).strip()
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if actual_path and os.path.exists(actual_path):
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with open(actual_path, 'r') as f:
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content = f.read()
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return f"\n--- {filepath} ---\n" + "\n".join(content.splitlines()[:200]) + "\n"
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except:
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pass
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return ""
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def process_bug(bug):
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if bug.get('effort_level') != 'small':
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return bug
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if bug.get('recommended_implementation') and bug['recommended_implementation'].strip() != "":
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return bug
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title = bug.get('title', '')
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body = bug.get('body', '')[:1000]
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analysis = bug.get('analysis', '')
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reasoning = bug.get('reasoning', '')
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combined_text = f"{title} {body} {analysis} {reasoning}"
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files = extract_files(combined_text)
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code_context = ""
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for f in list(files)[:3]:
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code_context += get_file_content(f)
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prompt = f"""You are a senior software engineer working on the gemini-cli codebase.
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This bug has been classified as a "small" effort bug. Please provide a concise, actionable `recommended_implementation` (or "recommended fix") for it.
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It should be 1-3 sentences describing exactly what needs to be changed in the code (e.g., "In `file.ts`, change X to Y.").
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Bug Title: {title}
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Bug Body: {body}
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Analysis: {analysis}
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Reasoning: {reasoning}
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Codebase Context:
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{code_context[:8000]}
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Output ONLY a JSON object (no markdown formatting, no codeblocks):
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{{
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"recommended_implementation": "your suggested fix"
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}}
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"""
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data = {
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"contents": [{"role": "user", "parts": [{"text": prompt}]}],
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"generationConfig": {"temperature": 0.0, "response_mime_type": "application/json"}
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}
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try:
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req = urllib.request.Request(URL, data=json.dumps(data).encode('utf-8'), headers={'Content-Type': 'application/json'})
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with urllib.request.urlopen(req, timeout=30) as response:
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res = json.loads(response.read().decode('utf-8'))
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txt = res['candidates'][0]['content']['parts'][0]['text']
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parsed = json.loads(txt)
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bug['recommended_implementation'] = parsed.get('recommended_implementation', '')
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print(f"Generated fix for #{bug['number']}", flush=True)
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except Exception as e:
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print(f"Failed #{bug['number']}: {e}", flush=True)
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return bug
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def main():
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to_process = [b for b in bugs if b.get('effort_level') == 'small' and not b.get('recommended_implementation')]
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print(f"Starting LLM generation for {len(to_process)} small bugs...", flush=True)
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with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
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results = list(executor.map(process_bug, bugs))
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with open(BUGS_FILE, 'w') as f:
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json.dump(results, f, indent=2)
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print("Done generating fixes.", flush=True)
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if __name__ == '__main__':
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main() |