171 lines
4.7 KiB
Markdown
171 lines
4.7 KiB
Markdown
# New-API 本地模型网关 — 运维调试手册
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> 来源：2026-06-24 调试 m3 模型 Internal Server Error session
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> DB 路径：`/var/lib/new-api/one-api.db`（正确）
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> 旧备份：`~/.openclaw/workspace/one-api.db`（过期，勿用）
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---
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## 进程信息
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```bash
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# 进程查找
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ps aux | grep new-api | grep -v grep
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# /usr/local/bin/new-api --port 3000 --log-dir /var/log/new-api
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# 端口
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ss -tlnp | grep 3000
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# LISTEN 0 4096 *:3000 *:* users:(("new-api",pid=1062462,fd=9))
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```
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## 数据库路径（关键！）
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| 用途 | 路径 | 说明 |
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|------|------|------|
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| **生产数据库** | `/var/lib/new-api/one-api.db` | 实际运行中的数据 |
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| 旧备份（勿用） | `~/.openclaw/workspace/one-api.db` | 2026-04-27 过期备份 |
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**如果查询 channels/abilities/tokens 全为空，先确认用的是正确路径。**
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## 查询 Token
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```python
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# 用 Python 查询（sqlite3 命令行工具不可用时）
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python3 -c "
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import sqlite3
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db = '/var/lib/new-api/one-api.db'
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conn = sqlite3.connect(db)
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cur = conn.cursor()
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# 查所有 token
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cur.execute('SELECT id, name, key FROM tokens')
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for r in cur.fetchall():
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print(r)
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conn.close()
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"
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```
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当前 token（2026-06-24）：`0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP`
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## 查询渠道和 Abilities
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```python
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import sqlite3
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db = '/var/lib/new-api/one-api.db'
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conn = sqlite3.connect(db)
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cur = conn.cursor()
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# 所有渠道
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cur.execute('SELECT id, name, type, status, base_url FROM channels ORDER BY id')
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for r in cur.fetchall():
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print(r)
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# 特定模型的 abilities（如 m3）
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cur.execute('SELECT * FROM abilities WHERE model LIKE \"%m3%\" OR model LIKE \"%minimax%\"')
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for r in cur.fetchall():
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print(r)
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conn.close()
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```
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### abilities 表结构
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| 列 | 说明 |
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|----|------|
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| group | 路由组（通常 `default`）|
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| model | 模型名（如 `minimaxai/minimax-m3`）|
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| channel_id | 渠道 ID（对应 channels.id）|
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| enabled | 是否启用（1=启用）|
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| priority | 优先级（数字越小优先级越高）|
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| weight | 权重 |
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| tag | 标签 |
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### channels 表关键列
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| 列 | 说明 |
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|----|------|
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| id | 渠道 ID |
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| name | 渠道名称（如 NIM-k1）|
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| type | 类型 |
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| status | 状态（1=活跃）|
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| base_url | 上游 API 地址 |
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| models | 渠道支持的模型列表 |
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## 常见错误排查
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| 症状 | 原因 | 解法 |
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|------|------|------|
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| `Invalid token` (Hermes 报 Internal Server Error) | session 重置后 token 失效；或用了旧备份 DB | 查询 `/var/lib/new-api/one-api.db` 的 tokens 表取最新 token |
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| `GET /v1/models/xxx` 返回 404 | new-api 未配置该模型到 abilities | INSERT INTO abilities VALUES('default','minimaxai/minimax-m3', channel_id, 1, 10, 2, NULL) |
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| m3 报 503 Service Unavailable | 模型名拼写错误（如 `minimax-m3.0` 错误，应为 `minimax-m3`）| 用 `minimaxai/minimax-m3` |
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| abilities 查询全为空 | 用了错误数据库路径 | 改用 `/var/lib/new-api/one-api.db` |
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| channels 查询全为空 | 同上 | 同上 |
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## 添加模型到多个渠道
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```python
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import sqlite3
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db = '/var/lib/new-api/one-api.db'
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conn = sqlite3.connect(db)
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cur = conn.cursor()
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model_name = 'minimaxai/minimax-m3'
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channel_ids = [1, 4, 5, 6, 7, 8, 9, 10, 11] # NIM-k1~k9
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for cid in channel_ids:
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# 检查是否已存在
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cur.execute('SELECT COUNT(*) FROM abilities WHERE model=? AND channel_id=?', (model_name, cid))
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if cur.fetchone()[0] == 0:
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cur.execute('INSERT INTO abilities VALUES(?,?,?,1,10,?,NULL)',
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('default', model_name, cid, 2 if cid in [1,4,6,8,9] else 1))
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print(f'Added to channel {cid}')
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else:
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print(f'Already exists in channel {cid}')
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conn.commit()
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conn.close()
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```
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## 测试模型调用
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```bash
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TOKEN="0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
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curl -s -X POST http://127.0.0.1:3000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer $TOKEN" \
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-d '{"model":"minimaxai/minimax-m3","messages":[{"role":"user","content":"say hi in 3 words"}],"max_tokens":20}' \
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--max-time 60
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```
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## 日志位置
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```
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/var/log/new-api/oneapi-*.log
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```
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按 request ID 搜索：
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```bash
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grep "20260624131917" /var/log/new-api/oneapi-20260624211749.log | head -20
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```
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按模型搜索：
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```bash
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grep -i "minimax-m3\|m3\|500\|internal\|panic" /var/log/new-api/oneapi-20260624211749.log | tail -20
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```
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## Hermes 配置参考
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```yaml
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providers:
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newapi-local:
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api_key: 0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP
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base_url: http://127.0.0.1:3000/v1
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cost_factor: 0.0
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default_model: minimaxai/minimax-m3
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models:
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- minimaxai/minimax-m3
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- minimaxai/minimax-m2.7
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- minimaxai/minimax-m2.5
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```
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> ⚠️ 配置里的 api_key 格式：`sk-0Ex...`（旧格式可能有 sk- 前缀），实际 new-api 只认 `0Ex...`。 |