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"nbformat": 4,
"nbformat_minor": 5,
"metadata": {
"colab": {
"name": "Arena Playwright API Colab Test",
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Arena Playwright API — Google Colab 測試\n",
"\n",
"先在 Colab 左側的鑰匙圖示（Secrets）新增 `BRIDGE_API_KEY`，值設定為 Hugging Face Space 的同名 Secret。不要直接把 API Key 寫進 Notebook。"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip -q install openai requests"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from google.colab import userdata\n",
"import json\n",
"import requests\n",
"\n",
"# 改成你的直接 Space 網址，不是 huggingface.co/spaces/... 頁面。\n",
"SPACE_URL = \"https://YOUR-SPACE.hf.space\".rstrip(\"/\")\n",
"API_KEY = userdata.get(\"BRIDGE_API_KEY\")\n",
"\n",
"assert \"YOUR-SPACE\" not in SPACE_URL, \"請先修改 SPACE_URL\"\n",
"assert API_KEY, \"請在 Colab Secrets 新增 BRIDGE_API_KEY\"\n",
"\n",
"HEADERS = {\"Authorization\": f\"Bearer {API_KEY}\"}\n",
"print(\"設定已載入；API Key 不會顯示。\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Health Check"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"response = requests.get(f\"{SPACE_URL}/health\", timeout=60)\n",
"print(\"HTTP\", response.status_code)\n",
"print(json.dumps(response.json(), ensure_ascii=False, indent=2))\n",
"response.raise_for_status()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"正常應顯示 `status: ok`、`configured: true`、`browser_ready: true`。"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. 取得模型清單"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"response = requests.get(\n",
" f\"{SPACE_URL}/v1/models\",\n",
" headers=HEADERS,\n",
" timeout=180,\n",
")\n",
"print(\"HTTP\", response.status_code)\n",
"if not response.ok:\n",
" print(response.text)\n",
"response.raise_for_status()\n",
"\n",
"model_ids = [item[\"id\"] for item in response.json().get(\"data\", [])]\n",
"print(f\"找到 {len(model_ids)} 個模型\")\n",
"print(\"前 20 個：\")\n",
"for model_id in model_ids[:20]:\n",
" print(\"-\", model_id)\n",
"\n",
"MODEL = \"Max\" if \"Max\" in model_ids else model_ids[0]\n",
"print(\"測試模型：\", MODEL)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. 非串流 Chat Completions"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"payload = {\n",
" \"model\": MODEL,\n",
" \"messages\": [\n",
" {\"role\": \"user\", \"content\": \"請只回答：Colab 測試成功\"}\n",
" ],\n",
" \"stream\": False,\n",
"}\n",
"\n",
"response = requests.post(\n",
" f\"{SPACE_URL}/v1/chat/completions\",\n",
" headers={**HEADERS, \"Content-Type\": \"application/json\"},\n",
" json=payload,\n",
" timeout=300,\n",
")\n",
"print(\"HTTP\", response.status_code)\n",
"if not response.ok:\n",
" print(response.text)\n",
"response.raise_for_status()\n",
"result = response.json()\n",
"print(result[\"choices\"][0][\"message\"][\"content\"] )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. SSE 串流測試"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"payload[\"messages\"] = [{\"role\": \"user\", \"content\": \"用三個短句介紹台北。\"}]\n",
"payload[\"stream\"] = True\n",
"\n",
"with requests.post(\n",
" f\"{SPACE_URL}/v1/chat/completions\",\n",
" headers={**HEADERS, \"Content-Type\": \"application/json\"},\n",
" json=payload,\n",
" stream=True,\n",
" timeout=300,\n",
") as response:\n",
" print(\"HTTP\", response.status_code)\n",
" if not response.ok:\n",
" print(response.text)\n",
" response.raise_for_status()\n",
" for raw_line in response.iter_lines(decode_unicode=True):\n",
" if not raw_line or not raw_line.startswith(\"data: \" ) or raw_line == \"data: [DONE]\":\n",
" continue\n",
" event = json.loads(raw_line[6:])\n",
" if \"error\" in event:\n",
" print(\"\\nERROR:\", event[\"error\"])\n",
" break\n",
" delta = event.get(\"choices\", [{}])[0].get(\"delta\", {}).get(\"content\", \"\")\n",
" print(delta, end=\"\", flush=True)\n",
"print()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5. 使用 OpenAI Python SDK"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from openai import OpenAI\n",
"\n",
"client = OpenAI(\n",
" base_url=f\"{SPACE_URL}/v1\",\n",
" api_key=API_KEY,\n",
" timeout=300,\n",
")\n",
"\n",
"completion = client.chat.completions.create(\n",
" model=MODEL,\n",
" messages=[{\"role\": \"user\", \"content\": \"請回答：OpenAI SDK 測試成功\"}],\n",
")\n",
"print(completion.choices[0].message.content)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 常見結果\n",
"\n",
"- `401`：Colab 的 `BRIDGE_API_KEY` 與 Space Secret 不一致。\n",
"- `503 arena_login_required`：Playwright 尚未登入成功，請到 `/admin` 重試。\n",
"- `404 model_not_found`：模型清單已變更，重新執行 models cell。\n",
"- `504 upstream_timeout`：Arena 回應過慢，可重試或改用較快模型。\n",
"- Private Space 可能先被 Hugging Face 存取控制擋住；先在瀏覽器確認 Space 可存取。"
]
}
]
}
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