Codex CLI 接入 AIHubMix 教程

npm install -g @openai/codex

profile = "aihubmix"

[model_providers.aihubmix]
name = "aihubmix"
base_url = "https://aihubmix.com/v1"
personality = "pragmatic"
wire_api = "responses"

[profiles.aihubmix]
model = "gpt-5.2"
model_provider = "aihubmix"
model_reasoning_effort = "high"

{
  "OPENAI_API_KEY": "AIHUBMIX_API_KEY"
}

cd /你的项目路径
codex

codex -h

Usage
  $ codex [options] <prompt>

Options
  -h, --help                 显示帮助信息并退出
  -m, --model <model>        指定使用的模型 (默认: codex-mini-latest)
  -i, --image <path>         包含图像输入的文件路径
  -v, --view <rollout>       查看之前保存的会话记录
  -q, --quiet                非交互模式，仅打印助手的最终输出
  -a, --approval-mode <mode> 覆盖审批策略: 'suggest', 'auto-edit', 或 'full-auto'

  --auto-edit                自动批准文件编辑；仍会提示确认命令
  --full-auto                自动批准沙箱环境中的编辑和命令

  --no-project-doc           不自动包含仓库中的 'codex.md' 文件
  --project-doc <file>       包含指定的 Markdown 文件作为上下文
  --full-stdout              不截断命令输出的 stdout/stderr

危险选项
  --dangerously-auto-approve-everything
                             跳过所有确认提示并直接执行命令（无沙箱保护）
                             仅用于临时本地测试环境

实验性选项
  -f, --full-context         以"完整上下文"模式启动，将整个仓库加载到上下文中
                             并在一次操作中应用批量编辑
                             仅兼容 --model 参数

示例
  $ codex "编写并运行一个打印 ASCII 艺术的 Python 程序"
  $ codex -q "修复构建问题"

{
  "models": [
    {
      "slug": "glm-5.2",
      "display_name": "GLM 5.2",
      "description": "GLM 5.2 (via AIHubMix)",
      "context_window": 1000000,
      "max_context_window": 1000000,
      "supported_reasoning_levels": [
        { "effort": "low",    "description": "Fast responses" },
        { "effort": "medium", "description": "Balanced" },
        { "effort": "high",   "description": "Deeper reasoning" }
      ],
      "shell_type": "shell_command",
      "visibility": "list",
      "supported_in_api": true,
      "priority": 0,
      "availability_nux": null,
      "upgrade": null,
      "base_instructions": "You are Codex, a coding agent.",
      "supports_reasoning_summaries": true,
      "support_verbosity": false,
      "default_verbosity": null,
      "apply_patch_tool_type": null,
      "truncation_policy": { "mode": "tokens", "limit": 10000 },
      "supports_parallel_tool_calls": true,
      "experimental_supported_tools": []
    }
  ]
}

mkdir -p ~/.codex/model-catalogs

# 1) 取一个内置模型当模板：它自带 base_instructions 等全部必填字段
codex debug models --bundled > /tmp/_tpl.json

# 2) 拉 AIHubMix 模型列表
curl -s "https://aihubmix.com/api/v1/models?type=llm" > /tmp/_aihubmix.json

# 3) 克隆模板逐个生成条目，只覆盖每个模型独有的字段
python3 - <<'PY' > ~/.codex/model-catalogs/custom-models.json
import json, sys
tpl = json.load(open("/tmp/_tpl.json"))["models"][0]   # 任意内置模型当模板
api = json.load(open("/tmp/_aihubmix.json"))["data"]
# 跳过图像生成模型（types 含 image_generation），再取前 30
api = [m for m in api if "image_generation" not in (m.get("types") or "")][:30]
out = []
for i, m in enumerate(api):
    e = dict(tpl)                                       # 克隆模板的全部字段
    ctx = m.get("context_length") or 200000
    e["slug"] = m["model_id"]                           # 必须与接口 model_id 一致
    e["display_name"] = m.get("model_name") or m["model_id"]
    e["description"] = (m.get("model_name") or m["model_id"]) + " (via AIHubMix)"
    e["context_window"] = ctx
    e["max_context_window"] = ctx
    e["visibility"] = "list"
    e["supported_in_api"] = True
    e["priority"] = i
    e["availability_nux"] = None
    e["upgrade"] = None
    out.append(e)
json.dump({"models": out}, sys.stdout, ensure_ascii=False, indent=2)
PY

# ⚠️ model_catalog_json 必须写在根级别，不能放进 [model_providers.*] 段里
model_provider = "aihubmix"
model_catalog_json = "~/.codex/model-catalogs/custom-models.json"

[model_providers.aihubmix]
name = "Aihubmix"
base_url = "https://aihubmix.com/v1"
wire_api = "responses"
env_key = "AIHUBMIX_API_KEY"

model = "glm-5.2"                   # 启动默认模型，需在目录文件里存在
model_provider = "aihubmix"
model_catalog_json = "~/.codex/model-catalogs/custom-models.json"
model_reasoning_effort = "high"     # 默认推理档位：minimal / low / medium / high

[model_providers.aihubmix]
name = "Aihubmix"
base_url = "https://aihubmix.com/v1"
wire_api = "responses"
env_key = "AIHUBMIX_API_KEY"

export AIHUBMIX_API_KEY=sk-xxx

codex
# 在交互界面里输入 /model，即可看到上一步声明的 30 个模型并切换