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‎.github/workflows/analyze_issue.py

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import os
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import json
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import io
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import time
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from openai import OpenAI
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from openai.types.beta.assistant_stream_event import ThreadRunRequiresAction, ThreadMessageCompleted
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from octokit import Octokit
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class IssueAnalyzer:
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def __init__(self):
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self.octokit = Octokit()
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self.openai = OpenAI()
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self.repo_full_name = os.getenv('GITHUB_REPOSITORY')
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def handle_event(self):
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with open(os.getenv('GITHUB_EVENT_PATH'), 'rb') as f:
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event = json.load(f)
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match os.getenv('GITHUB_EVENT_NAME'):
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case 'issues':
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issue = event['issue']
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case 'workflow_dispatch':
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issue_number = int(event['inputs']['issue'])
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owner, repo = self.repo_full_name.split('/')
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response = self.octokit.issues.get(owner=owner, repo=repo, issue_number=issue_number)
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issue = response.json
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assistant = self.openai.beta.assistants.retrieve(os.getenv('ASSISTANT_ID'))
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issue_file = self.openai.files.create(
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file=('BUG_REPORT.md', self.make_issue_content(issue, show_labels=False)),
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purpose='assistants'
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)
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thread = self.openai.beta.threads.create(
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metadata={
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'issue': f'{issue["number"]}: {issue["title"]}',
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'run_id': os.getenv('GITHUB_RUN_ID'),
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'model': f'{assistant.model} t={assistant.temperature} top_p={assistant.top_p}',
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},
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messages=[{
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'role': 'user',
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'content': 'We have a new issue report (attached as BUG_REPORT.md)',
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'attachments': [{
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'file_id': issue_file.id,
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'tools': [{'type': 'file_search'}]
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}]
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}
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]
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)
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print('Thread:', thread.id)
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thread_vstore_id = thread.tool_resources.file_search.vector_store_ids[0]
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self.wait_vector_store(thread_vstore_id)
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stream = self.openai.beta.threads.runs.create(
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assistant_id=assistant.id,
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thread_id=thread.id,
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stream=True
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)
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streams = [stream]
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while streams:
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stream = streams.pop(0)
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for event in stream:
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match event:
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case ThreadMessageCompleted():
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for c in event.data.content:
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print('Assistant:', c.text.value)
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case ThreadRunRequiresAction():
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tool_outputs = []
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for tool in event.data.required_action.submit_tool_outputs.tool_calls:
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args = json.loads(tool.function.arguments)
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print(f'Tool call:', tool.function.name, args)
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match tool.function.name:
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case 'search_github':
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query = f'repo:{self.repo_full_name} {args["query"]}'
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output = self.search_github(query, thread_vstore_id, exclude=[issue['number']])
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tool_outputs.append({'tool_call_id': tool.id, 'output': output})
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case 'add_issue_labels':
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tool_outputs.append({'tool_call_id': tool.id, 'output': 'Ok'})
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case 'set_issue_title':
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tool_outputs.append({'tool_call_id': tool.id, 'output': 'Ok'})
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case 'add_issue_comment':
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tool_outputs.append({'tool_call_id': tool.id, 'output': 'Ok'})
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new_stream = self.openai.beta.threads.runs.submit_tool_outputs(
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thread_id=thread.id,
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run_id=event.data.id,
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tool_outputs=tool_outputs,
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stream=True)
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streams.append(new_stream)
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def search_github(self, query: str, vstore_id: str, exclude:list=[], max_results=5) -> str:
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response = self.octokit.search.issues(q=query)
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if response.json.get('status'):
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return f'Search failed: {response.json["message"]}'
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result_lines = []
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for issue in response.json['items']:
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issue_number = issue['number']
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if issue_number in exclude:
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continue
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issue_file = self.openai.files.create(
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file=(f'ISSUE_{issue_number}.md', self.make_issue_content(issue, fetch_comments=True)),
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purpose='assistants'
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)
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self.openai.beta.vector_stores.files.create(
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vector_store_id=vstore_id,
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file_id=issue_file.id,
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)
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result_lines.append(f'Issue number: {issue_number}, file name: {issue_file.filename}')
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if len(result_lines) >= max_results:
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break
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self.wait_vector_store(vstore_id)
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result_lines.insert(0, f'Found {len(result_lines)} issues and attached as files to this thread:')
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return '\n'.join(result_lines)
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def make_issue_content(self, issue, fetch_comments=False, show_labels=True) -> bytes:
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f = io.StringIO()
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f.write(f'### Title: {issue["title"]}\n')
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f.write(f'### Author: {issue["user"]["login"]}\n')
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f.write(f'### State: {issue["state"]}\n')
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if show_labels:
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f.write(f'### Labels: {",".join(label["name"] for label in issue["labels"])}\n')
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f.write(f'\n{issue["body"]}\n')
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if fetch_comments:
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owner, repo = self.repo_full_name.split('/')
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comments = self.octokit.issues.list_issue_comments(
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owner=owner, repo=repo, issue_number=issue['number'])
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for comment in comments.json:
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f.write(f'### Comment by {comment["user"]["login"]}\n')
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f.write(f'\n{comment["body"]}\n')
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return f.getvalue().encode('utf-8')
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def wait_vector_store(self, vstore_id):
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vstore = self.openai.beta.vector_stores.retrieve(vstore_id)
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while vstore.status == 'in_progress':
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print('Waiting for vector store.')
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time.sleep(1)
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vstore = self.openai.beta.vector_stores.retrieve(vstore_id)
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if __name__ == '__main__':
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IssueAnalyzer().handle_event()

‎.github/workflows/analyze_issue.yml

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name: analyze_issue
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on:
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issues:
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types: [opened]
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workflow_dispatch:
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inputs:
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issue: null
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jobs:
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analyze_issue:
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runs-on: ubuntu-latest
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steps:
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- name: Check out repo
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uses: actions/checkout@v3
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.11"
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cache: 'pip'
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cache-dependency-path: .github/workflows/analyze_issue.yml
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- name: Install dependencies
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run: pip install openai octokitpy
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- name: Analysis
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env:
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GITHUB_TOKEN: ${{ github.token }}
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GITHUB_REPOSITORY: ${{ github.repository }}
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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ASSISTANT_ID: ${{ vars.ASSISTANT_ID }}
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PYTHONUNBUFFERED: 1
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run: |
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python .github/workflows/analyze_issue.py

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