This repository has been archived by the owner on Jul 6, 2024. It is now read-only.
公的な情報発信用のWEBサイトやモバイルアプリに都政に対する意見表明への導線を追加してほしい #4
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: Issue Review | |
| on: | |
| issues: | |
| types: [opened] | |
| permissions: | |
| issues: write | |
| contents: read | |
| jobs: | |
| review_issue: | |
| runs-on: ubuntu-latest | |
| steps: | |
| - name: Checkout repository | |
| uses: actions/checkout@v2 | |
| - name: Set up Python | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: '3.x' | |
| - name: Install dependencies | |
| run: | | |
| python -m pip install --upgrade pip | |
| pip install openai | |
| pip install PyGithub | |
| pip install qdrant-client | |
| pip install regex | |
| - name: Review Issue with LLM | |
| env: | |
| OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} | |
| GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} | |
| QD_API_KEY: ${{ secrets.QD_API_KEY }} | |
| QD_URL: ${{ secrets.QD_URL }} | |
| run: | | |
| python <<EOF | |
| import github | |
| from github import Github | |
| import os | |
| import openai | |
| import regex as re | |
| from qdrant_client import QdrantClient | |
| from qdrant_client.models import PointStruct | |
| token = os.getenv("GITHUB_TOKEN") | |
| qd_api = os.getenv("QD_API_KEY") | |
| qd_url = os.getenv("QD_URL") | |
| g = Github(token) | |
| repo = g.get_repo("${{ github.repository }}") | |
| issue = repo.get_issue(${{ github.event.issue.number }}) | |
| issue_content = f"{issue.title}\n{issue.body}" | |
| try: | |
| repo.create_label(name="toxic", color="ff0000") | |
| repo.create_label(name="duplicated", color="708090") | |
| except: | |
| pass | |
| qdrant_client = QdrantClient( | |
| url=qd_url, | |
| api_key=qd_api, | |
| ) | |
| openai_client = openai.Client() | |
| embedding_model = "text-embedding-3-small" | |
| collection_name = "issue_collection" | |
| def validate_image(text): | |
| model_name = "gpt-4o" | |
| prompt = "この画像が暴力的、もしくは性的な画像の場合trueと返してください。" | |
| image_url = re.search(r"!\[[^\s]+\]\((https://[^\s]+)\)", text) | |
| if image_url and len(image_url) > 1: | |
| image_url = image_url[1] | |
| else: | |
| return False | |
| try: | |
| response = openai_client.chat.completions.create( | |
| model=model_name, | |
| messages=[ | |
| { | |
| "role": "user", | |
| "content": [ | |
| {"type": "text", "text": prompt}, | |
| { | |
| "type": "image_url", | |
| "image_url": { | |
| "url": image_url | |
| }, | |
| }, | |
| ], | |
| } | |
| ], | |
| max_tokens=1200, | |
| ) | |
| except: | |
| return True | |
| v = response.choices[0].message.content.lower() | |
| if "true" in v: | |
| return True | |
| else: | |
| return False | |
| def judge_violation(text): | |
| response = openai_client.moderations.create(input=text) | |
| flag = response.results[0].flagged | |
| video_flag = validate_image(text) | |
| if flag or video_flag: | |
| print(response) | |
| issue.add_to_labels("toxic") | |
| if video_flag | |
| warn = "不適切な画像です。アカウントBANの危険性があります。" | |
| else: | |
| warn = "不適切な投稿です。アカウントBANの危険性があります。" | |
| issue.create_comment(warn) | |
| issue.edit(state="closed") | |
| return True | |
| return flag | |
| def add_issue(text:str, iss_num:int): | |
| texts = [text] | |
| ids = [iss_num] | |
| result = openai_client.embeddings.create(input=texts, model=embedding_model) | |
| points = [ | |
| PointStruct( | |
| id=idx, | |
| vector=data.embedding, | |
| payload={"text": t}, | |
| ) | |
| for idx, data, t in zip(ids, result.data, texts) | |
| ] | |
| qdrant_client.upsert(collection_name, points) | |
| return text | |
| def merge_issue(iss:int): | |
| issue.add_to_labels("duplicated") | |
| print(f"merge to {iss}") | |
| issue.create_comment(f"#{iss} と重複しているかもしれません") | |
| return iss | |
| def qd_search(text:str): | |
| results = qdrant_client.search( | |
| collection_name=collection_name, | |
| query_vector=openai_client.embeddings.create( | |
| input=[text], | |
| model=embedding_model, | |
| ) | |
| .data[0] | |
| .embedding, | |
| ) | |
| return results | |
| def qd_add(text:str, iss_num:int): | |
| texts = [text] | |
| ids = [iss_num] | |
| result = openai_client.embeddings.create(input=texts, model=embedding_model) | |
| points = [ | |
| PointStruct( | |
| id=idx, | |
| vector=data.embedding, | |
| payload={"text": text}, | |
| ) | |
| for idx, data, text in zip(ids, result.data, texts) | |
| ] | |
| qdrant_client.upsert(collection_name, points) | |
| if judge_violation(issue_content): | |
| quit() | |
| results = qd_search(issue_content) | |
| if len(results) > 2: | |
| results = results[:3] | |
| else: | |
| results = results | |
| print(results) | |
| res = "" | |
| for i in results: | |
| res+=f'id:{i.id}\n内容:{i.payload["text"]}\n' | |
| res = res.strip() | |
| prompt= f""" | |
| 以下は市民から寄せられた政策提案です。 | |
| {issue_content} | |
| この投稿を読み、以下の過去提案の中に重複する提案があるかを判断してください。 | |
| {res} | |
| 重複する提案があればそのidを出力してください。 | |
| もし存在しない場合は0と出力してください。 | |
| [出力形式] | |
| id:0 | |
| """ | |
| print(prompt) | |
| completion = openai_client.chat.completions.create( | |
| model="gpt-4o", | |
| max_tokens= 1024, | |
| messages=[ | |
| {"role": "system", "content": prompt}, | |
| ] | |
| ) | |
| review = completion.choices[0].message.content | |
| if ":" in review: | |
| review = review.split(":")[-1] | |
| if review.isdecimal(): | |
| if review == "0": | |
| add_issue(issue_content, issue.number) | |
| else: | |
| merge_issue(int(review)) | |
| print(review) | |
| EOF |