mirror of
https://github.com/google-gemini/gemini-cli.git
synced 2026-05-15 06:12:50 -07:00
Coco Sheng
106 lines
3.8 KiB
Python
106 lines
3.8 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/bugs.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_keywords(text):
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words = re.findall(r'\b[A-Z][a-zA-Z0-9]+\b|\b\w+\.tsx?\b|\b\w+Service\b|\b\w+Command\b', text)
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words = list(set([w for w in words if len(w) > 4]))
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return words[:8]
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def search_codebase(keywords):
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context = ""
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for kw in keywords:
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try:
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kw_clean = kw.replace('"', '\\"')
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cmd = f'grep -rn "{kw_clean}" ../../packages | grep -vE "node_modules|dist|build|\\.test\\." | head -n 8'
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out = subprocess.check_output(cmd, shell=True, text=True, stderr=subprocess.STDOUT)
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if out:
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context += f"\n--- Matches for {kw_clean} ---\n{out}\n"
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except:
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pass
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return context
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def process_issue(issue):
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if issue.get('analysis') and issue['analysis'] != "Failed to analyze autonomously" and len(issue['analysis']) > 30:
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return issue
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title = issue.get('title', '')
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body = issue.get('body', '')[:1500]
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keywords = extract_keywords(title + " " + body)
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code_context = search_codebase(keywords)
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prompt = f"""You are a senior software engineer analyzing bug reports for the gemini-cli codebase.
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Based on the bug description and the provided codebase search context, pinpoint exactly which files and logic are responsible for the bug.
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DO NOT GUESS. If the context isn't enough, provide your best technical hypothesis.
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Rating Effort Level:
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- small (1 day): Localized fix (1-2 files), clear cause.
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- medium (2-3 days): Touches multiple components or hard to trace.
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- large (>3 days): Architectural issues, Windows/WSL-specific, core protocols.
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Bug Title: {title}
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Bug Body: {body}
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Codebase Search Context:
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{code_context[:8000]}
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Output ONLY valid JSON (no markdown block):
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{{
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"analysis": "technical analysis of root cause and fix",
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"effort_level": "small|medium|large",
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"reasoning": "justification with specific files/lines found"
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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": 0.1}
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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=60) 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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txt = txt.replace('```json', '').replace('```', '').strip()
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parsed = json.loads(txt)
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issue['analysis'] = parsed.get('analysis', 'Failed to analyze')
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issue['effort_level'] = parsed.get('effort_level', 'medium')
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issue['reasoning'] = parsed.get('reasoning', 'Could not determine')
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print(f"Completed {issue['number']} -> {issue['effort_level']}", flush=True)
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except Exception as e:
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print(f"Failed {issue['number']}: {e}", flush=True)
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return issue
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def main():
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to_analyze = [b for b in bugs if b.get('analysis') == "Failed to analyze autonomously" or not b.get('analysis') or len(b.get('analysis', '')) < 30]
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# Only process 5 at a time
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to_analyze = to_analyze[:5]
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print(f"Starting single-turn analysis for {len(to_analyze)} bugs...", flush=True)
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with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
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list(executor.map(process_issue, to_analyze))
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# Final save
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with open(BUGS_FILE, 'w') as f:
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json.dump(bugs, f, indent=2)
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print("Done processing 5 bugs.", flush=True)
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if __name__ == '__main__':
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main()
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