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AI token price comparison platform that scrapes and aggregates prices across multiple platforms to help users find cheap, reliable AI account tokens
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| name | aibijia-price-comparison |
| description | AI token price comparison platform that scrapes and aggregates prices across multiple platforms to help users find cheap, reliable AI account tokens |
| triggers | ["compare AI token prices","find cheap ChatGPT plus","scrape AI account prices","build price comparison for AI tokens","submit token vendor to aibijia","aggregate AI CDK prices","find reliable AI token resellers","price scraping multiple platforms"] |
Skill by ara.so — Daily 2026 Skills collection.
Aibijia is a multi-platform price scraping and comparison website for AI tokens (ChatGPT Plus CDKs, API keys, etc.). It aggregates prices from various resellers/agents across platforms, helping users find the cheapest reliable source and avoid scams.
Live site: https://aibijia.org
Telegram: https://t.me/ai_bi_jia_notice
Since the repo is primarily a community/data project with a web frontend, the core components are:
AIbijia/
├── assets/ # Static assets (banner, images)
├── data/ # Price data / scraped results (JSON/CSV)
├── scrapers/ # Platform price scrapers
├── frontend/ # Website UI (aibijia.org)
└── SKILL.md
git clone https://github.com/ka-pi-ba-la/AIbijia.git
cd AIbijia
If Python-based scrapers:
pip install -r requirements.txt
If Node.js-based:
npm install
# or
pnpm install
| Token Type | Example Price Range | Notes |
|---|---|---|
| ChatGPT Plus CDK | ¥30–¥60 | Same upstream, different markup |
| GPT Pro (shared) | ~¥20/person | Split among multiple users |
| API Keys (各模型) | Varies | Per-token pricing |
| Claude / Gemini | Varies | Scraped from resellers |
import requests
from bs4 import BeautifulSoup
import json
from datetime import datetime
class TokenPriceScraper:
"""
Base scraper for AI token price platforms.
Each platform subclasses this with custom parsing.
"""
def __init__(self, platform_name: str, base_url: str):
self.platform_name = platform_name
self.base_url = base_url
self.session = requests.Session()
self.session.headers.update({
"User-Agent": "Mozilla/5.0 (compatible; Aibijia/1.0)"
})
def fetch_page(self, url: str) -> BeautifulSoup:
resp = self.session.get(url, timeout=10)
resp.raise_for_status()
return BeautifulSoup(resp.text, "html.parser")
def parse_prices(self, soup: BeautifulSoup) -> list[dict]:
"""Override in subclass to extract price data."""
raise NotImplementedError
def scrape(self) -> list[dict]:
soup = self.fetch_page(self.base_url)
prices = self.parse_prices(soup)
# Annotate with metadata
for item in prices:
item["platform"] = self.platform_name
item["scraped_at"] = datetime.utcnow().isoformat()
return prices
class KawangScraper(TokenPriceScraper):
"""Example scraper for a 卡网 (card platform)."""
def parse_prices(self, soup: BeautifulSoup) -> list[dict]:
results = []
# Adapt selectors to target platform's HTML structure
for card in soup.select(".product-card"):
name = card.select_one(".product-name")
price = card.select_one(".product-price")
stock = card.select_one(".product-stock")
if name and price:
results.append({
"name": name.get_text(strip=True),
"price_cny": float(
price.get_text(strip=True)
.replace("¥", "")
.replace(",", "")
),
"in_stock": stock and "有货" in stock.get_text(),
})
return results
import asyncio
import aiohttp
from dataclasses import dataclass
@dataclass
class PriceListing:
token_type: str
platform: str
price_cny: float
in_stock: bool
url: str
scraped_at: str
async def aggregate_all_platforms(platforms: list[TokenPriceScraper]) -> list[PriceListing]:
"""
Run all scrapers concurrently and merge results.
"""
results = []
async def run_scraper(scraper):
loop = asyncio.get_event_loop()
# Run sync scraper in thread pool
data = await loop.run_in_executor(None, scraper.scrape)
return data
tasks = [run_scraper(p) for p in platforms]
all_data = await asyncio.gather(*tasks, return_exceptions=True)
for platform_data in all_data:
if isinstance(platform_data, Exception):
print(f"Scraper error: {platform_data}")
continue
results.extend(platform_data)
return results
def find_cheapest(listings: list[PriceListing], token_type: str) -> list[PriceListing]:
"""Filter and sort by price for a specific token type."""
filtered = [
l for l in listings
if token_type.lower() in l.token_type.lower()
and l.in_stock
]
return sorted(filtered, key=lambda x: x.price_cny)
# Usage
async def main():
platforms = [
KawangScraper("platform_a", "https://example-card-site-a.com/chatgpt"),
KawangScraper("platform_b", "https://example-card-site-b.com/chatgpt"),
]
all_listings = await aggregate_all_platforms(platforms)
cheapest = find_cheapest(all_listings, "ChatGPT Plus")
print("Cheapest ChatGPT Plus CDKs:")
for listing in cheapest[:5]:
print(f" ¥{listing.price_cny} — {listing.platform}")
asyncio.run(main())
The site exposes a submission endpoint for community-sourced vendors:
import requests
import os
AIBIJIA_API = "https://aibijia.org/api" # hypothetical endpoint
def submit_vendor(vendor_info: dict) -> dict:
"""
Submit a new vendor/price source for review.
vendor_info keys:
- name: str Vendor/platform name
- url: str Purchase URL
- token_type: str e.g. "ChatGPT Plus CDK"
- price_cny: float Current price in RMB
- notes: str Optional reliability notes
"""
resp = requests.post(
f"{AIBIJIA_API}/submit",
json=vendor_info,
headers={
"Content-Type": "application/json",
# Use env var if auth is required:
"Authorization": f"Bearer {os.environ.get('AIBIJIA_API_KEY', '')}",
},
timeout=10,
)
resp.raise_for_status()
return resp.json()
# Example usage
result = submit_vendor({
"name": "某卡网",
"url": "https://example-card-site.com/gpt-plus",
"token_type": "ChatGPT Plus CDK",
"price_cny": 32.0,
"notes": "24h售后，支持补货",
})
print(result)
import json
import os
from pathlib import Path
from datetime import datetime
DATA_DIR = Path("./data")
def save_price_snapshot(listings: list[dict], token_type: str):
"""Save a timestamped price snapshot to data/."""
DATA_DIR.mkdir(exist_ok=True)
date_str = datetime.utcnow().strftime("%Y-%m-%d")
filename = DATA_DIR / f"{token_type.replace(' ', '_')}_{date_str}.json"
snapshot = {
"token_type": token_type,
"captured_at": datetime.utcnow().isoformat(),
"count": len(listings),
"listings": listings,
}
with open(filename, "w", encoding="utf-8") as f:
json.dump(snapshot, f, ensure_ascii=False, indent=2)
print(f"Saved {len(listings)} listings to {filename}")
def load_latest_snapshot(token_type: str) -> dict | None:
"""Load the most recent snapshot for a token type."""
pattern = f"{token_type.replace(' ', '_')}_*.json"
files = sorted(DATA_DIR.glob(pattern), reverse=True)
if not files:
return None
with open(files[0], encoding="utf-8") as f:
return json.load(f)
Post scam reports as GitHub Issues or submit to the repo:
## 避雷报告模板
**平台名称：** xxx卡网
**购买时间：** 2026-04-28
**商品：** ChatGPT Plus CDK
**价格：** ¥35
**问题：** CDK已失效，无法联系售后
**证据：** [截图]
**建议：** 避免购买
# config.py — Aibijia scraper configuration
import os
CONFIG = {
# Scraping behavior
"request_timeout": int(os.environ.get("SCRAPE_TIMEOUT", "10")),
"rate_limit_seconds": float(os.environ.get("SCRAPE_RATE_LIMIT", "2.0")),
"max_retries": int(os.environ.get("SCRAPE_MAX_RETRIES", "3")),
# Proxy (optional, for bot detection avoidance)
"proxy": os.environ.get("HTTP_PROXY", None),
# Data output
"data_dir": os.environ.get("DATA_DIR", "./data"),
# Notifications (Telegram)
"telegram_bot_token": os.environ.get("TELEGRAM_BOT_TOKEN"),
"telegram_channel_id": os.environ.get("TELEGRAM_CHANNEL_ID"),
# Price alert threshold (alert if price drops below X CNY)
"alert_price_threshold": float(os.environ.get("ALERT_PRICE_CNY", "30.0")),
}
# .env (never commit this file)
SCRAPE_TIMEOUT=15
SCRAPE_RATE_LIMIT=3.0
HTTP_PROXY=http://proxy.example.com:8080
DATA_DIR=./data
TELEGRAM_BOT_TOKEN=your_bot_token_here
TELEGRAM_CHANNEL_ID=@ai_bi_jia_notice
ALERT_PRICE_CNY=28.0
import os
import asyncio
from telegram import Bot
async def send_price_alert(listings: list[dict], threshold: float):
"""
Send Telegram alert when ChatGPT Plus CDK drops below threshold price.
"""
bot = Bot(token=os.environ["TELEGRAM_BOT_TOKEN"])
channel = os.environ["TELEGRAM_CHANNEL_ID"]
cheap = [l for l in listings if l["price_cny"] <= threshold and l["in_stock"]]
if not cheap:
return
lines = [f"🔥 低价预警！ChatGPT Plus CDK ≤ ¥{threshold}\n"]
for l in cheap[:5]:
lines.append(f"• ¥{l['price_cny']} — {l['platform']}")
await bot.send_message(
chat_id=channel,
text="\n".join(lines),
disable_web_page_preview=True,
)
asyncio.run(send_price_alert(all_listings, threshold=30.0))
# .github/workflows/scrape.yml
name: Daily Price Scrape
on:
schedule:
- cron: "0 2 * * *" # 2 AM UTC daily
workflow_dispatch:
jobs:
scrape:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.12"
- run: pip install -r requirements.txt
- run: python scrapers/run_all.py
env:
TELEGRAM_BOT_TOKEN: ${{ secrets.TELEGRAM_BOT_TOKEN }}
TELEGRAM_CHANNEL_ID: ${{ secrets.TELEGRAM_CHANNEL_ID }}
- uses: actions/upload-artifact@v4
with:
name: price-data
path: data/
| Problem | Cause | Fix |
|---|---|---|
| Scraper returns empty results | Target site changed HTML structure | Update CSS selectors in parse_prices() |
| 403 / blocked requests | Bot detection on target platform | Add proxy via HTTP_PROXY env var or rotate User-Agent |
| Prices stale | Cron not running | Check GitHub Actions logs; run python scrapers/run_all.py manually |
| Telegram alerts not sending | Wrong token/channel | Verify TELEGRAM_BOT_TOKEN and TELEGRAM_CHANNEL_ID env vars |
| CDK already used / invalid | Upstream fraud | Report in repo issues with evidence; avoid that vendor |
import time
import random
def polite_get(session, url: str, min_delay=1.5, max_delay=4.0) -> str:
"""Add random delay between requests to avoid rate limiting."""
time.sleep(random.uniform(min_delay, max_delay))
resp = session.get(url, timeout=10)
resp.raise_for_status()
return resp.text
data/sources.json// data/sources.json entry format
{
"id": "vendor_slug",
"name": "平台名称",
"url": "https://example-card-site.com",
"token_types": ["ChatGPT Plus CDK", "Claude API"],
"verified": false,
"submitted_by": "github_username",
"notes": "24h售后，微信群支持"
}