用Python给一人团队搭一条内容生产流水线

# pip install openai
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.hunyuan.cloud.tencent.com/v1",  # 混元OpenAI兼容端点
)

def chat(prompt: str, model: str = "hunyuan-turbo") -> str:
    resp = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": prompt}],
        temperature=0.7,
    )
    return resp.choices[0].message.content

import json

def gen_topics(positioning: str, n: int = 14) -> list:
    prompt = (
        f"我的账号定位：{positioning}\n"
        f"请给出{n}个选题，每个选题包含标题和目标读者痛点，"
        "以JSON数组返回，字段为title和pain_point，不要输出其他内容。"
    )
    raw = chat(prompt)
    topics = json.loads(raw[raw.find("["): raw.rfind("]") + 1])
    with open("topics.json", "w", encoding="utf-8") as f:
        json.dump(topics, f, ensure_ascii=False, indent=2)
    return topics

import os

def gen_drafts(topics: list, out_dir: str = "drafts"):
    os.makedirs(out_dir, exist_ok=True)
    for t in topics:
        prompt = (
            f"围绕选题《{t['title']}》写一篇600字初稿，"
            f"读者痛点：{t['pain_point']}。要求：口语化，给可执行建议，不要编造数据。"
        )
        draft = chat(prompt)
        safe = "".join(c for c in t["title"] if c.isalnum())[:20]
        with open(f"{out_dir}/{safe}.md", "w", encoding="utf-8") as f:
            f.write(draft)
        print(f"已生成：{t['title']}")

# 每周一早上7点生成选题，周三生成初稿
0 7 * * 1 /usr/bin/python3 /opt/pipeline/gen_topics.py
0 7 * * 3 /usr/bin/python3 /opt/pipeline/gen_drafts.py