feat: improve bot status configuration summary (#1174)

bot/commands/status.py

@@ -58,6 +58,8 @@ class StatusCommand(BotCommand):
     
     def _collect_status(self, config) -> dict:
         """收集系统状态信息"""
+        from src.config import _uses_direct_env_provider, get_configured_llm_models
+
         status = {
             "timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
             "python_version": f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}",
@@ -67,8 +69,39 @@ class StatusCommand(BotCommand):
         }
         
         # AI 配置状态
-        status["ai_gemini"] = bool(config.gemini_api_key)
-        status["ai_openai"] = bool(config.openai_api_key)
+        llm_channels = getattr(config, "llm_channels", []) or []
+        llm_model_list = getattr(config, "llm_model_list", []) or []
+        llm_model = (getattr(config, "litellm_model", "") or "").strip()
+        agent_model = (getattr(config, "agent_litellm_model", "") or "").strip()
+        status["ai_primary_model"] = llm_model
+        status["ai_agent_model"] = agent_model or ("继承主模型" if llm_model else "")
+        status["ai_channels"] = [
+            str(channel.get("name") or "").strip()
+            for channel in llm_channels
+            if str(channel.get("name") or "").strip()
+        ]
+        status["ai_yaml"] = (
+            getattr(config, "llm_models_source", "") == "litellm_config"
+            and bool(llm_model_list)
+        )
+        status["ai_legacy_keys"] = {
+            "Gemini": bool(getattr(config, "gemini_api_keys", [])),
+            "OpenAI": bool(getattr(config, "openai_api_keys", [])),
+            "Anthropic": bool(getattr(config, "anthropic_api_keys", [])),
+            "DeepSeek": bool(getattr(config, "deepseek_api_keys", [])),
+        }
+        has_direct_env_model = bool(llm_model) and _uses_direct_env_provider(llm_model)
+        available_router_model_set = set(get_configured_llm_models(llm_model_list))
+        primary_model_reachable = not (
+            available_router_model_set
+            and llm_model
+            and not _uses_direct_env_provider(llm_model)
+            and llm_model not in available_router_model_set
+        )
+        status["ai_available"] = bool(
+            llm_model
+            and (has_direct_env_model or (llm_model_list and primary_model_reachable))
+        )
         
         # 搜索服务状态
         status["search_bocha"] = len(config.bocha_api_keys) > 0
@@ -83,6 +116,29 @@ class StatusCommand(BotCommand):
         status["notify_feishu"] = bool(config.feishu_webhook_url)
         status["notify_telegram"] = bool(config.telegram_bot_token and config.telegram_chat_id)
         status["notify_email"] = bool(config.email_sender and config.email_password)
+        status["notify_custom"] = bool(getattr(config, "custom_webhook_urls", []))
+        status["notify_discord"] = bool(
+            getattr(config, "discord_webhook_url", None)
+            or (
+                getattr(config, "discord_bot_token", None)
+                and getattr(config, "discord_main_channel_id", None)
+            )
+        )
+        status["notify_slack"] = bool(
+            getattr(config, "slack_webhook_url", None)
+            or (
+                getattr(config, "slack_bot_token", None)
+                and getattr(config, "slack_channel_id", None)
+            )
+        )
+        status["notify_push"] = bool(
+            getattr(config, "pushplus_token", None)
+            or (
+                getattr(config, "pushover_user_key", None)
+                and getattr(config, "pushover_api_token", None)
+            )
+            or getattr(config, "serverchan3_sendkey", None)
+        )
         
         return status
     
@@ -114,8 +170,15 @@ class StatusCommand(BotCommand):
         lines.extend([
             "",
             "**🤖 AI 分析服务**",
-            f"• Gemini API: {icon(status['ai_gemini'])}",
-            f"• OpenAI API: {icon(status['ai_openai'])}",
+            f"• 主模型: {status['ai_primary_model'] or '未配置'}",
+            f"• Agent 模型: {status['ai_agent_model'] or '未配置'}",
+            f"• LLM 渠道: {', '.join(status['ai_channels']) if status['ai_channels'] else '未配置'}",
+            f"• LiteLLM YAML: {icon(status['ai_yaml'])}",
+            "• Legacy Key: "
+            + ", ".join(
+                f"{name}{icon(enabled)}"
+                for name, enabled in status["ai_legacy_keys"].items()
+            ),
             "",
             "**🔍 搜索服务**",
             f"• Bocha: {icon(status['search_bocha'])}",
@@ -130,11 +193,14 @@ class StatusCommand(BotCommand):
             f"• 飞书: {icon(status['notify_feishu'])}",
             f"• Telegram: {icon(status['notify_telegram'])}",
             f"• 邮件: {icon(status['notify_email'])}",
+            f"• 自定义 Webhook: {icon(status['notify_custom'])}",
+            f"• Discord: {icon(status['notify_discord'])}",
+            f"• Slack: {icon(status['notify_slack'])}",
+            f"• PushPlus/Pushover/Server酱3: {icon(status['notify_push'])}",
         ])
         
         # AI 服务总体状态
-        ai_available = status['ai_gemini'] or status['ai_openai']
-        if ai_available:
+        if status["ai_available"]:
             lines.extend([
                 "",
                 "---",
@@ -145,7 +211,7 @@ class StatusCommand(BotCommand):
                 "",
                 "---",
                 "⚠️ **AI 服务未配置，分析功能不可用**",
-                "请配置 Gemini 或 OpenAI API Key",
+                "请配置 LITELLM_MODEL、LLM_CHANNELS、LITELLM_CONFIG 或任一 provider API Key",
             ])
         
         return "\n".join(lines)

docs/CHANGELOG.md

@@ -15,6 +15,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/).
 - [修复] 统一持仓快照输出现价/市值/浮盈亏/收益率与价格元信息，并为 LLM 渠道测试补充结构化诊断与设置页排障提示。
 - [文档] 补充 LLM 渠道编辑器的官方来源、依赖兼容窗口、保存时的运行时模型清理规则，以及旧配置回退路径说明。
 - [测试] 补齐 task_queue 运行时配置同步回归证据，明确 `tests/test_task_queue_config_sync.py` 作为本轮验收项。
+- [改进] Bot `/status` 展示统一 LLM 主模型、Agent 模型、渠道模式、YAML 配置和更多通知渠道状态。
 
 ## [3.14.2] - 2026-04-30
 

docs/bot-command.md

@@ -195,7 +195,34 @@ class CommandDispatcher:
 
 | /status | /s, 状态 | 系统状态 | `/status` |
 
-## 五、Webhook 路由
+## 五、`/status` 与模型配置诊断说明
+
+### 可配置层级与可用性判断依据
+
+- `/status` 显示的 LLM 可用性遵循系统统一运行时优先级：
+  - `LITELLM_CONFIG`（LiteLLM YAML）
+  - `LLM_CHANNELS`
+  - legacy provider 键（`GEMINI_API_KEY` / `OPENAI_API_KEY` / `ANTHROPIC_API_KEY` / `DEEPSEEK_API_KEY`）
+- 当主模型（`LITELLM_MODEL` 或 `AGENT_LITELLM_MODEL`）在当前激活层无可用来源时，会展示“AI 服务未配置”，并保留用户可见原因行。
+- 本仓库 `requirements.txt` 的运行时依赖窗口为 `litellm>=1.80.10,<1.82.7`，该窗口内本链路以现有兼容行为为准。
+- 该诊断规则与 `GET /api/v1/system/config/setup/status` 的 LLM 检查保持一致：`LITELLM_CONFIG`/`LLM_CHANNELS` 为高优先级；模式切换时不会做静默迁移，切回旧模式由用户显式恢复历史值或回滚。
+
+### 回退与迁移边界
+
+- `LITELLM_CONFIG` 与 `LLM_CHANNELS` 任一生效时，下层 legacy 配置会被该层忽略（不会继续作为本次调用来源）。
+- 本次修复仅增强诊断，不进行 silent migration：不会主动清空/删除 `GEMINI_*`、`OPENAI_*`、`ANTHROPIC_*`、`LITELLM_*` 的历史值，仅在可用性诊断上提示。
+
+### 官方兼容来源（用于排障核对）
+
+- LiteLLM 官网：<https://docs.litellm.ai/>
+- LiteLLM OpenAI Compatible 说明：<https://docs.litellm.ai/docs/providers/openai_compatible>
+- OpenAI Chat API：<https://platform.openai.com/docs/api-reference/chat>
+- DeepSeek API 文档：<https://api-docs.deepseek.com/>
+- Kimi Moonshot 兼容说明：<https://platform.moonshot.ai/docs/guide/compatibility>
+- Gemini OpenAI 兼容说明：<https://ai.google.dev/gemini-api/docs/openai>
+- Ollama API 文档：<https://github.com/ollama/ollama/blob/main/docs/api.md>
+
+## 六、Webhook 路由
 
 在 [api/v1/router.py](../api/v1/router.py) 中注册路由：
 
@@ -262,4 +289,3 @@ telegram_webhook_secret: str           # 新增：Webhook 密钥
     bot_rate_limit_window: int = 60       # 频率限制：窗口时间（秒）
     bot_admin_users: List[str] = field(default_factory=list)  # 管理员用户 ID 列表，限制敏感操作
 ```
-

docs/bot-command_EN.md

@@ -164,7 +164,34 @@ class BotCommand(ABC):
 
 ---
 
-## 5. Webhook Routes
+## 5. `/status` and LLM configuration diagnostics
+
+### Configuration precedence for readiness in `/status`
+
+- The AI availability displayed by `/status` follows runtime precedence:
+  - `LITELLM_CONFIG` (LiteLLM YAML)
+  - `LLM_CHANNELS`
+  - legacy provider keys (`GEMINI_API_KEY` / `OPENAI_API_KEY` / `ANTHROPIC_API_KEY` / `DEEPSEEK_API_KEY`)
+- If the primary model (`LITELLM_MODEL` or `AGENT_LITELLM_MODEL`) has no configured source in the active layer, `/status` shows `AI 服务未配置` and keeps the explicit reason line.
+- Runtime dependency range in this repository is `litellm>=1.80.10,<1.82.7`; current status semantics are aligned with this window.
+- This diagnostic follows the same readiness rules as `GET /api/v1/system/config/setup/status` for LLM checks: channels/yaml are active higher priority than legacy keys, and no silent migration is performed when toggling modes.
+
+### Fallback and migration boundary
+
+- When `LITELLM_CONFIG` or `LLM_CHANNELS` is active, lower-priority legacy provider keys are ignored as the active source for that run (no silent downgrade).
+- This change only improves diagnosis and does not perform automatic migration: legacy configuration values are not deleted or rewritten during startup or status collection.
+
+### Official compatibility references (for triage)
+
+- LiteLLM docs: https://docs.litellm.ai/
+- LiteLLM OpenAI-compatible provider: https://docs.litellm.ai/docs/providers/openai_compatible
+- OpenAI Chat API: https://platform.openai.com/docs/api-reference/chat
+- DeepSeek API docs: https://api-docs.deepseek.com/
+- Kimi Moonshot compatibility: https://platform.moonshot.ai/docs/guide/compatibility
+- Gemini OpenAI compatibility: https://ai.google.dev/gemini-api/docs/openai
+- Ollama API docs: https://github.com/ollama/ollama/blob/main/docs/api.md
+
+## 6. Webhook Routes
 
 Handler functions for each platform live in `bot/handler.py`.
 These routes are **not yet wired** into the FastAPI application — you must mount them manually.
@@ -190,7 +217,7 @@ async def dingtalk_webhook(request: Request):
 
 ---
 
-## 6. Configuration
+## 7. Configuration
 
 Add the following to your `.env`. Some of these bot-specific keys are already listed in `.env.example` (for example the DingTalk and Feishu app credentials), while others are not, so treat this section as a consolidated reference for bot setup:
 

tests/test_bot_status_command.py

@@ -0,0 +1,237 @@
+# -*- coding: utf-8 -*-
+"""Tests for bot /status command output."""
+
+from bot.commands.status import StatusCommand
+from src.config import Config
+
+
+def test_status_command_reports_unified_llm_and_notification_channels():
+    model_list = [
+        {
+            "model_name": "deepseek/deepseek-v4-flash",
+            "litellm_params": {
+                "model": "deepseek/deepseek-v4-flash",
+                "api_key": "sk-test",
+            },
+        }
+    ]
+    config = Config(
+        stock_list=["600519", "AAPL"],
+        litellm_model="deepseek/deepseek-v4-flash",
+        agent_litellm_model="openai/gpt-4o-mini",
+        llm_channels=[
+            {
+                "name": "deepseek",
+                "models": ["deepseek/deepseek-v4-flash"],
+            }
+        ],
+        llm_models_source="llm_channels",
+        llm_model_list=model_list,
+        custom_webhook_urls=["https://example.com/webhook"],
+        slack_webhook_url="https://hooks.slack.com/services/T/B/C",
+        serverchan3_sendkey="SCT123",
+    )
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_available"] is True
+    assert "主模型: deepseek/deepseek-v4-flash" in text
+    assert "Agent 模型: openai/gpt-4o-mini" in text
+    assert "LLM 渠道: deepseek" in text
+    assert "自定义 Webhook: ✅" in text
+    assert "Slack: ✅" in text
+    assert "PushPlus/Pushover/Server酱3: ✅" in text
+    assert "系统就绪" in text
+
+
+def test_status_command_warns_when_no_llm_source_configured():
+    config = Config(stock_list=["600519"])
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_available"] is False
+    assert "主模型: 未配置" in text
+    assert "AI 服务未配置" in text
+    assert "LITELLM_MODEL" in text
+
+
+def test_status_command_does_not_treat_managed_model_name_as_ready():
+    config = Config(
+        stock_list=["600519"],
+        litellm_model="openai/gpt-4o-mini",
+        llm_model_list=[],
+    )
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_available"] is False
+    assert "AI 服务未配置" in text
+
+
+def test_status_command_keeps_channel_mode_priority_over_legacy_keys():
+    config = Config(
+        stock_list=["600519"],
+        litellm_model="openai/gpt-4o-mini",
+        llm_channels=[
+            {
+                "name": "deepseek",
+                "models": ["deepseek/deepseek-v4-flash"],
+            }
+        ],
+        llm_models_source="llm_channels",
+        llm_model_list=[
+            {
+                "model_name": "deepseek/deepseek-v4-flash",
+                "litellm_params": {
+                    "model": "deepseek/deepseek-v4-flash",
+                    "api_key": "sk-test",
+                },
+            }
+        ],
+        openai_api_keys=["openai-legacy-key"],
+    )
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_available"] is False
+    assert "AI 服务未配置" in text
+    assert "主模型: openai/gpt-4o-mini" in text
+
+
+def test_status_command_requires_primary_model_in_configured_router_models():
+    config = Config(
+        stock_list=["600519"],
+        litellm_model="openai/gpt-4o-mini",
+        llm_channels=[
+            {
+                "name": "deepseek",
+                "models": ["deepseek/deepseek-v4-flash"],
+            }
+        ],
+        llm_models_source="llm_channels",
+        llm_model_list=[
+            {
+                "model_name": "deepseek/deepseek-v4-flash",
+                "litellm_params": {
+                    "model": "deepseek/deepseek-v4-flash",
+                    "api_key": "sk-test",
+                },
+            }
+        ],
+    )
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_available"] is False
+    assert "AI 服务未配置" in text
+    assert "系统就绪" not in text
+
+
+def test_status_command_requires_primary_model_for_yaml_router_models():
+    config = Config(
+        stock_list=["600519"],
+        litellm_model="",
+        llm_models_source="litellm_config",
+        llm_model_list=[
+            {
+                "model_name": "yaml-primary",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "sk-test",
+                },
+            }
+        ],
+    )
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_yaml"] is True
+    assert status["ai_available"] is False
+    assert "主模型: 未配置" in text
+    assert "AI 服务未配置" in text
+    assert "系统就绪" not in text
+
+
+def test_status_command_does_not_treat_invalid_yaml_path_as_active():
+    config = Config(
+        stock_list=["600519"],
+        litellm_config_path="missing.yaml",
+        llm_models_source="legacy_env",
+        llm_model_list=[],
+    )
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_yaml"] is False
+    assert status["ai_available"] is False
+    assert "LiteLLM YAML: ❌" in text
+    assert "AI 服务未配置" in text
+
+
+def test_status_command_treats_direct_env_provider_model_as_ready():
+    config = Config(
+        stock_list=["600519"],
+        litellm_model="cohere/command-r-plus",
+        llm_model_list=[],
+    )
+    command = StatusCommand()
+
+    status = command._collect_status(config)
+    text = command._format_status(status, "telegram")
+
+    assert status["ai_available"] is True
+    assert "系统就绪" in text
+
+
+def test_status_command_supports_legacy_key_compatibility_without_explicit_litellm_model(monkeypatch, tmp_path):
+    # When only legacy OpenAI-compatible keys are configured and LITELLM_MODEL is unset,
+    # runtime still infers a usable model path. /status should reflect this compatibility
+    # path instead of reporting hard failure.
+    env_file = tmp_path / ".env"
+    env_file.write_text("", encoding="utf-8")
+    monkeypatch.setenv("ENV_FILE", str(env_file))
+    for key in (
+        "GEMINI_API_KEYS",
+        "GEMINI_API_KEY",
+        "ANTHROPIC_API_KEYS",
+        "ANTHROPIC_API_KEY",
+        "DEEPSEEK_API_KEYS",
+        "DEEPSEEK_API_KEY",
+        "OPENAI_API_KEYS",
+        "AIHUBMIX_KEY",
+        "LITELLM_MODEL",
+        "LLM_CHANNELS",
+        "LITELLM_CONFIG",
+    ):
+        monkeypatch.delenv(key, raising=False)
+
+    monkeypatch.setenv("OPENAI_API_KEY", "sk-legacy-test-key")
+    monkeypatch.setenv("OPENAI_MODEL", "gpt-4o-mini")
+
+    Config.reset_instance()
+    try:
+        config = Config.get_instance()
+        command = StatusCommand()
+
+        status = command._collect_status(config)
+        text = command._format_status(status, "telegram")
+
+        assert status["ai_available"] is True
+        assert "主模型: openai/gpt-4o-mini" in text
+        assert "AI 服务未配置" not in text
+    finally:
+        Config.reset_instance()