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import { useEffect, useMemo, useRef, useState } from 'react';
import type React from 'react';
import type { ParsedApiError } from '../../api/error';
import { getParsedApiError } from '../../api/error';
import { systemConfigApi } from '../../api/systemConfig';
import type { LLMCapabilityCheck, LLMCapabilityCheckResult } from '../../types/systemConfig';
import { ApiErrorAlert, Badge, Button, InlineAlert, Input, Select, StatusDot, Tooltip } from '../common';
import type { ChannelProtocol } from './llmProviderTemplates';
import {
LLM_PROVIDER_CAPABILITY_LABELS,
LLM_PROVIDER_TEMPLATES,
MODEL_PLACEHOLDERS_BY_PROTOCOL,
getProviderTemplate,
isKnownProviderTemplate,
} from './llmProviderTemplates';
const PROTOCOL_OPTIONS: Array<{ value: ChannelProtocol; label: string }> = [
{ value: 'openai', label: 'OpenAI Compatible' },
{ value: 'deepseek', label: 'DeepSeek' },
{ value: 'gemini', label: 'Gemini' },
{ value: 'anthropic', label: 'Anthropic' },
{ value: 'vertex_ai', label: 'Vertex AI' },
{ value: 'ollama', label: 'Ollama' },
{ value: 'github_copilot', label: 'GitHub Copilot (OAuth)' },
];
const KNOWN_MODEL_PREFIXES = new Set([
'openai',
'anthropic',
'gemini',
'vertex_ai',
'deepseek',
'minimax',
'ollama',
'cohere',
'huggingface',
'bedrock',
'sagemaker',
'azure',
'replicate',
'together_ai',
'palm',
'text-completion-openai',
'command-r',
'groq',
'cerebras',
'fireworks_ai',
'friendliai',
]);
const FALSEY_VALUES = new Set(['0', 'false', 'no', 'off']);
const RUNTIME_CAPABILITY_OPTIONS: Array<{ value: LLMCapabilityCheck; label: string; hint: string }> = [
{ value: 'json', label: 'JSON', hint: '检测 response_format JSON 输出是否可用。' },
{ value: 'tools', label: 'Tools', hint: '检测 function/tool calling 是否可用。' },
{ value: 'stream', label: 'Stream', hint: '检测流式输出是否能返回有效 chunk。' },
{ value: 'vision', label: 'Vision', hint: '检测当前模型是否接受 image_url 输入。' },
];
const CAPABILITY_STATUS_LABELS: Record<LLMCapabilityCheckResult['status'], string> = {
passed: '通过',
failed: '失败',
skipped: '跳过',
};
interface ChannelConfig {
id: string;
name: string;
protocol: ChannelProtocol;
baseUrl: string;
apiKey: string;
models: string;
enabled: boolean;
}
interface ChannelTestState {
status: 'idle' | 'loading' | 'success' | 'error';
text?: string;
hint?: string;
}
interface ChannelDiscoveryState {
status: 'idle' | 'loading' | 'success' | 'error';
text?: string;
hint?: string;
models: string[];
}
interface ChannelCapabilityState {
selected: LLMCapabilityCheck[];
status: 'idle' | 'loading' | 'success' | 'error';
text?: string;
hint?: string;
results: Partial<Record<LLMCapabilityCheck, LLMCapabilityCheckResult>>;
}
interface RuntimeConfig {
primaryModel: string;
agentPrimaryModel: string;
fallbackModels: string[];
visionModel: string;
temperature: string;
}
interface LLMChannelEditorProps {
items: Array<{ key: string; value: string }>;
configVersion: string;
maskToken: string;
onSaved: (updatedItems: Array<{ key: string; value: string }>) => void | Promise<void>;
disabled?: boolean;
}
interface ChannelRowProps {
channel: ChannelConfig;
index: number;
busy: boolean;
visibleKey: boolean;
expanded: boolean;
testState?: ChannelTestState;
discoveryState?: ChannelDiscoveryState;
capabilityState?: ChannelCapabilityState;
onUpdate: (index: number, field: keyof ChannelConfig, value: string | boolean) => void;
onRemove: (index: number) => void;
onToggleExpand: (index: number) => void;
onToggleKeyVisibility: (index: number, nextVisible: boolean) => void;
onTest: (channel: ChannelConfig, index: number) => void;
onDiscoverModels: (channel: ChannelConfig) => void;
onToggleCapability: (channel: ChannelConfig, capability: LLMCapabilityCheck) => void;
onCheckCapabilities: (channel: ChannelConfig) => void;
}
const ChannelRow: React.FC<ChannelRowProps> = ({
channel,
index,
busy,
visibleKey,
expanded,
testState,
discoveryState,
capabilityState,
onUpdate,
onRemove,
onToggleExpand,
onToggleKeyVisibility,
onTest,
onDiscoverModels,
onToggleCapability,
onCheckCapabilities,
}) => {
const preset = getProviderTemplate(channel.name);
const showProviderTemplateDetails = isKnownProviderTemplate(channel.name);
const displayName = preset?.label || channel.name;
const providerCapabilities = showProviderTemplateDetails ? (preset?.capabilities || []) : [];
const providerSources = showProviderTemplateDetails ? (preset?.officialSources || []) : [];
const providerHint = showProviderTemplateDetails ? preset?.configHint : undefined;
const selectedModels = splitModels(channel.models);
const discoveredModels = discoveryState?.models || [];
const manualOnlyModels = selectedModels.filter(
(model) => !discoveredModels.some((discoveredModel) => areModelsEquivalent(model, discoveredModel, channel.protocol)),
);
const modelCount = selectedModels.length;
const hasKey = channel.apiKey.length > 0;
const statusVariant = testState?.status === 'success'
? 'success'
: testState?.status === 'error'
? 'danger'
: testState?.status === 'loading'
? 'warning'
: 'default';
const selectedCapabilities = capabilityState?.selected || [];
const capabilityResults = capabilityState?.results || {};
const capabilityBusy = capabilityState?.status === 'loading';
return (
<div className="mb-2 overflow-hidden rounded-xl border border-[var(--settings-border)] bg-[var(--settings-surface)] shadow-soft-card transition-[background-color,border-color,box-shadow] duration-200 hover:border-[var(--settings-border-strong)] hover:bg-[var(--settings-surface-hover)]">
<div
className="flex cursor-pointer select-none items-center gap-2.5 px-4 py-3 transition-colors"
onClick={() => onToggleExpand(index)}
onKeyDown={(e) => {
if (e.key === 'Enter' || e.key === ' ') {
e.preventDefault();
onToggleExpand(index);
}
}}
role="button"
tabIndex={0}
>
<span className={`w-4 shrink-0 text-[11px] text-muted-text transition-transform ${expanded ? 'rotate-90' : ''}`}>▶</span>
<input
type="checkbox"
checked={channel.enabled}
disabled={busy}
className="settings-input-checkbox h-4 w-4 shrink-0 rounded border-border/70 bg-base"
onClick={(e) => e.stopPropagation()}
onChange={(e) => onUpdate(index, 'enabled', e.target.checked)}
/>
<div className="min-w-0 flex-1">
<div className="flex items-center gap-2">
<span className="truncate text-sm font-semibold text-foreground">{displayName}</span>
<Badge variant="info" className="hidden sm:inline-flex">
{channel.protocol}
</Badge>
</div>
<p className="mt-0.5 truncate text-[11px] text-secondary-text">
{modelCount > 0 ? `${modelCount} 个模型已配置` : '未配置模型'}
</p>
</div>
<span className="flex shrink-0 items-center gap-2">
{testState?.status === 'success' ? (
<Tooltip content="连接正常">
<span className="inline-flex">
<StatusDot tone="success" />
</span>
</Tooltip>
) : null}
{testState?.status === 'error' ? (
<Tooltip content="连接失败">
<span className="inline-flex">
<StatusDot tone="danger" />
</span>
</Tooltip>
) : null}
{testState?.status === 'loading' ? (
<Tooltip content="测试中">
<span className="inline-flex">
<StatusDot tone="warning" pulse />
</span>
</Tooltip>
) : null}
{!hasKey && channel.protocol !== 'ollama' && channel.protocol !== 'github_copilot' ? <Badge variant="warning">未填 Key</Badge> : null}
{testState?.status !== 'idle' ? (
<Badge variant={statusVariant}>
{testState?.status === 'success' ? '连接正常' : testState?.status === 'error' ? '连接失败' : '测试中'}
</Badge>
) : null}
</span>
<Tooltip content="删除渠道">
<span className="inline-flex">
<Button
type="button"
variant="ghost"
size="sm"
className="h-8 shrink-0 px-2 text-xs text-muted-text hover:text-rose-300"
disabled={busy}
onClick={(e) => {
e.stopPropagation();
onRemove(index);
}}
>
✕
</Button>
</span>
</Tooltip>
</div>
{expanded ? (
<div className="settings-surface-overlay-soft space-y-4 px-4 py-4">
<div className="grid gap-2 sm:grid-cols-2">
<Input
label="渠道名称"
value={channel.name}
disabled={busy}
onChange={(e) => onUpdate(index, 'name', e.target.value.toLowerCase().replace(/[^a-z0-9_]/g, ''))}
placeholder="primary"
/>
<div className="space-y-2">
<label className="block text-sm font-medium text-foreground">协议</label>
<Select
value={channel.protocol}
onChange={(v) => onUpdate(index, 'protocol', normalizeProtocol(v))}
options={PROTOCOL_OPTIONS}
disabled={busy}
placeholder="选择协议"
/>
</div>
</div>
<Input
label="Base URL"
value={channel.baseUrl}
disabled={busy}
onChange={(e) => onUpdate(index, 'baseUrl', e.target.value)}
placeholder={
channel.protocol === 'gemini' || channel.protocol === 'anthropic'
? '官方接口可留空'
: preset?.baseUrl || 'https://api.example.com/v1'
}
/>
{showProviderTemplateDetails ? (
<div className="space-y-2 rounded-xl border border-[var(--settings-border)] bg-[var(--settings-surface-hover)] p-3">
<div className="flex flex-wrap items-center gap-2">
<span className="text-[11px] font-medium text-muted-text">配置参考</span>
{providerCapabilities.map((capability) => {
const capabilityMeta = LLM_PROVIDER_CAPABILITY_LABELS[capability];
return (
<Tooltip key={capability} content={capabilityMeta.hint}>
<span className="inline-flex">
<Badge variant="default" className="border-[var(--settings-border)] bg-[var(--settings-surface)] text-secondary-text">
{capabilityMeta.label}
</Badge>
</span>
</Tooltip>
);
})}
</div>
{providerHint ? (
<p className="text-[11px] leading-5 text-secondary-text">{providerHint}</p>
) : null}
{providerSources.length > 0 ? (
<p className="flex flex-wrap items-center gap-x-2 gap-y-1 text-[11px] leading-5 text-secondary-text">
<span>官方来源:</span>
{providerSources.map((source) => (
<a
key={source.url}
href={source.url}
target="_blank"
rel="noreferrer"
className="settings-accent-text underline-offset-2 hover:underline"
>
{source.label}
</a>
))}
</p>
) : null}
<p className="text-[11px] leading-5 text-muted-text">
能力标签仅用于配置参考,不代表运行时能力已验证通过。
</p>
</div>
) : null}
<Input
label="API Key"
type="password"
allowTogglePassword
iconType="key"
passwordVisible={visibleKey}
onPasswordVisibleChange={(nextVisible) => onToggleKeyVisibility(index, nextVisible)}
value={channel.apiKey}
disabled={busy}
onChange={(e) => onUpdate(index, 'apiKey', e.target.value)}
placeholder={
channel.protocol === 'ollama'
? '本地 Ollama 可留空'
: channel.protocol === 'github_copilot'
? '首次调用会触发 OAuth 设备流,留空即可'
: '支持多个 Key 逗号分隔'
}
/>
<div className="space-y-3 rounded-xl border border-[var(--settings-border)] bg-[var(--settings-surface-hover)] p-3">
<div className="flex flex-wrap items-center gap-2">
<Button
type="button"
variant="settings-secondary"
size="sm"
className="px-3 text-[11px] shadow-none"
disabled={busy}
onClick={() => onDiscoverModels(channel)}
>
{discoveryState?.status === 'loading' ? '获取中...' : '获取模型'}
</Button>
<span className={`text-xs ${
discoveryState?.status === 'success'
? 'text-success'
: discoveryState?.status === 'error'
? 'text-danger'
: 'text-muted-text'
}`}
>
{discoveryState?.text || '支持 `/models` 的 OpenAI Compatible 渠道可自动拉取模型。'}
</span>
</div>
{discoveryState?.hint ? (
<p className="text-[11px] text-secondary-text">
{discoveryState.hint}
</p>
) : null}
{discoveredModels.length > 0 ? (
<div>
<label className="mb-2 block text-sm font-medium text-foreground">可选模型(可多选)</label>
<div className="max-h-48 space-y-2 overflow-y-auto rounded-xl border border-[var(--settings-border)] bg-[var(--settings-surface)] p-3">
{discoveredModels.map((model) => (
<label key={model} className="flex items-center gap-2 text-sm text-secondary-text">
<input
type="checkbox"
checked={selectedModels.some((selectedModel) => (
areModelsEquivalent(selectedModel, model, channel.protocol)
))}
disabled={busy}
onChange={() => onUpdate(index, 'models', toggleModelSelection(channel.models, model, channel.protocol))}
className="settings-input-checkbox h-4 w-4 rounded border-border/70 bg-base"
/>
<span>{model}</span>
</label>
))}
</div>
</div>
) : null}
<Input
label={discoveredModels.length > 0 ? '手动模型(逗号分隔)' : '模型(逗号分隔)'}
value={channel.models}
disabled={busy}
onChange={(e) => onUpdate(index, 'models', e.target.value)}
placeholder={preset?.placeholderModels || MODEL_PLACEHOLDERS_BY_PROTOCOL[channel.protocol]}
hint={
discoveredModels.length > 0
? '如有自定义模型名未出现在列表中,可继续手动补充,保存格式仍为逗号分隔。'
: '若渠道不支持自动发现或请求失败,可直接手动填写模型列表。'
}
/>
{manualOnlyModels.length > 0 ? (
<p className="text-[11px] text-secondary-text">
额外手动模型:{manualOnlyModels.join(',')}
</p>
) : null}
</div>
<div className="flex items-center gap-2 pt-1">
<Button
type="button"
variant="settings-secondary"
size="sm"
className="px-3 text-[11px] shadow-none"
disabled={busy}
onClick={() => onTest(channel, index)}
>
{testState?.status === 'loading' ? '测试中...' : '测试连接'}
</Button>
{testState?.text ? (
<div className="space-y-1">
<span className={`block text-xs ${
testState.status === 'success'
? 'text-success'
: testState.status === 'error'
? 'text-danger'
: 'text-muted-text'
}`}
>
{testState.text}
</span>
{testState.hint ? (
<p className="text-[11px] text-secondary-text">
{testState.hint}
</p>
) : null}
</div>
) : null}
</div>
<div className="space-y-3 rounded-xl border border-[var(--settings-border)] bg-[var(--settings-surface-hover)] p-3">
<div className="flex flex-wrap items-center justify-between gap-2">
<div>
<p className="text-[11px] font-medium text-muted-text">运行时能力检测(可选)</p>
<p className="mt-0.5 text-[11px] text-secondary-text">
仅在手动触发时发起真实 LLM 请求;多选可能需要 20-40 秒。
</p>
</div>
<Button
type="button"
variant="settings-secondary"
size="sm"
className="px-3 text-[11px] shadow-none"
disabled={busy || capabilityBusy || selectedCapabilities.length === 0}
onClick={() => onCheckCapabilities(channel)}
>
{capabilityBusy ? '检测中...' : '检测能力'}
</Button>
</div>
<div className="flex flex-wrap gap-2">
{RUNTIME_CAPABILITY_OPTIONS.map((option) => (
<Tooltip key={option.value} content={option.hint}>
<label className="inline-flex cursor-pointer items-center gap-1.5 rounded-lg border border-[var(--settings-border)] bg-[var(--settings-surface)] px-2 py-1 text-[11px] text-secondary-text">
<input
type="checkbox"
checked={selectedCapabilities.includes(option.value)}
disabled={busy || capabilityBusy}
onChange={() => onToggleCapability(channel, option.value)}
className="settings-input-checkbox h-3.5 w-3.5 rounded border-border/70 bg-base"
/>
<span>{option.label}</span>
</label>
</Tooltip>
))}
</div>
{capabilityState?.text ? (
<div className="space-y-1">
<p className={`text-xs ${
capabilityState.status === 'success'
? 'text-success'
: capabilityState.status === 'error'
? 'text-danger'
: 'text-muted-text'
}`}
>
{capabilityState.text}
</p>
{capabilityState.hint ? (
<p className="text-[11px] text-secondary-text">{capabilityState.hint}</p>
) : null}
</div>
) : null}
{Object.keys(capabilityResults).length > 0 ? (
<div className="flex flex-wrap gap-2">
{RUNTIME_CAPABILITY_OPTIONS.map((option) => {
const result = capabilityResults[option.value];
if (!result) return null;
return (
<Tooltip key={option.value} content={result.message}>
<span className="inline-flex">
<Badge variant={getCapabilityResultVariant(result.status)}>
{option.label} {CAPABILITY_STATUS_LABELS[result.status]}
</Badge>
</span>
</Tooltip>
);
})}
</div>
) : null}
</div>
</div>
) : null}
</div>
);
};
function normalizeProtocol(value: string): ChannelProtocol {
const normalized = value.trim().toLowerCase().replace(/-/g, '_');
if (normalized === 'vertex' || normalized === 'vertexai') {
return 'vertex_ai';
}
if (normalized === 'claude') {
return 'anthropic';
}
if (normalized === 'google') {
return 'gemini';
}
if (normalized === 'deepseek') {
return 'deepseek';
}
if (normalized === 'gemini') {
return 'gemini';
}
if (normalized === 'anthropic') {
return 'anthropic';
}
if (normalized === 'vertex_ai') {
return 'vertex_ai';
}
if (normalized === 'ollama') {
return 'ollama';
}
return 'openai';
}
function inferProtocol(protocol: string, baseUrl: string, models: string[]): ChannelProtocol {
const explicit = normalizeProtocol(protocol);
if (protocol.trim()) {
return explicit;
}
const firstPrefixedModel = models.find((model) => model.includes('/'));
if (firstPrefixedModel) {
return normalizeProtocol(firstPrefixedModel.split('/', 1)[0]);
}
if (baseUrl.includes('127.0.0.1') || baseUrl.includes('localhost')) {
return 'openai';
}
return 'openai';
}
function parseEnabled(value: string | undefined): boolean {
if (!value) {
return true;
}
return !FALSEY_VALUES.has(value.trim().toLowerCase());
}
function splitModels(models: string): string[] {
return models
.split(',')
.map((entry) => entry.trim())
.filter(Boolean);
}
interface ParsedModelRef {
name: string;
provider: string;
hasProvider: boolean;
}
function parseModelRef(model: string): ParsedModelRef {
const trimmed = model.trim();
if (!trimmed) {
return { name: '', provider: '', hasProvider: false };
}
const delimiterIndex = trimmed.indexOf('/');
if (delimiterIndex < 0) {
return { name: trimmed.toLowerCase(), provider: '', hasProvider: false };
}
const rawProvider = trimmed.slice(0, delimiterIndex).trim();
const name = trimmed.slice(delimiterIndex + 1).trim();
if (!rawProvider || !name) {
return { name: '', provider: '', hasProvider: false };
}
const lowerProvider = rawProvider.toLowerCase();
return {
name: name.toLowerCase(),
provider: PROTOCOL_ALIASES[lowerProvider] || lowerProvider,
hasProvider: true,
};
}
function getModelComparisonKey(model: string, protocol: ChannelProtocol): string {
const normalizedModel = normalizeModelForRuntime(model, protocol).trim();
const parsed = parseModelRef(normalizedModel);
if (!parsed.name) {
return '';
}
return `${parsed.provider}/${parsed.name}`;
}
function areModelsEquivalent(a: string, b: string, protocol: ChannelProtocol): boolean {
const left = getModelComparisonKey(a, protocol);
const right = getModelComparisonKey(b, protocol);
return left !== '' && left === right;
}
function toggleModelSelection(models: string, targetModel: string, protocol: ChannelProtocol): string {
const selectedModels = splitModels(models);
const index = selectedModels.findIndex((model) => areModelsEquivalent(model, targetModel, protocol));
if (index >= 0) {
return selectedModels.filter((_, itemIndex) => itemIndex !== index).join(',');
}
return [...selectedModels, targetModel].join(',');
}
const PROTOCOL_ALIASES: Record<string, string> = {
vertexai: 'vertex_ai',
vertex: 'vertex_ai',
claude: 'anthropic',
google: 'gemini',
openai_compatible: 'openai',
openai_compat: 'openai',
};
function normalizeModelForRuntime(model: string, protocol: ChannelProtocol): string {
const trimmedModel = model.trim();
if (!trimmedModel) {
return trimmedModel;
}
if (trimmedModel.includes('/')) {
const rawPrefix = trimmedModel.split('/', 1)[0].trim();
const lowerPrefix = rawPrefix.toLowerCase();
const canonicalPrefix = PROTOCOL_ALIASES[lowerPrefix] || lowerPrefix;
if (KNOWN_MODEL_PREFIXES.has(lowerPrefix) || KNOWN_MODEL_PREFIXES.has(canonicalPrefix)) {
if (canonicalPrefix !== lowerPrefix && KNOWN_MODEL_PREFIXES.has(canonicalPrefix)) {
return `${canonicalPrefix}/${trimmedModel.split('/').slice(1).join('/')}`;
}
return trimmedModel;
}
return `${protocol}/${trimmedModel}`;
}
return `${protocol}/${trimmedModel}`;
}
function resolveModelPreview(models: string, protocol: ChannelProtocol): string[] {
return splitModels(models).map((model) => normalizeModelForRuntime(model, protocol));
}
function buildModelOptions(models: string[], selectedModel: string, autoLabel: string): Array<{ value: string; label: string }> {
const options: Array<{ value: string; label: string }> = [{ value: '', label: autoLabel }];
if (selectedModel && !models.includes(selectedModel)) {
options.push({ value: selectedModel, label: `${selectedModel}(当前配置)` });
}
for (const model of models) {
options.push({ value: model, label: model });
}
return options;
}
const LLM_STAGE_LABELS: Record<string, string> = {
model_discovery: '模型发现',
chat_completion: '聊天调用',
response_parse: '响应解析',
capability_json: 'JSON 能力',
capability_tools: 'Tools 能力',
capability_stream: 'Stream 能力',
capability_vision: 'Vision 能力',
};
const LLM_ERROR_LABELS: Record<string, string> = {
auth: '鉴权失败',
timeout: '请求超时',
quota: '额度或限流',
model_not_found: '模型不存在',
empty_response: '空响应',
format_error: '格式异常',
network_error: '网络异常',
invalid_config: '配置无效',
unsupported_protocol: '协议暂不支持',
capability_unsupported: '能力不支持',
skipped: '已跳过',
};
const LLM_TROUBLESHOOTING_HINTS: Record<string, string> = {
auth: '请检查 API Key 是否正确、是否有多余空格,以及当前渠道是否需要额外组织/项目权限。',
timeout: '可重试;若持续超时,请检查 Base URL、网络代理、服务商可用区或本地防火墙。',
quota: '请检查余额、套餐额度、RPM/TPM 限流或并发设置,必要时稍后重试。',
model_not_found: '请确认模型名与渠道协议匹配,并先用“获取模型”核对该渠道实际可用模型列表。',
empty_response: '渠道已连通但未返回正文;可尝试切换兼容模型、关闭额外响应模式后再测试。',
network_error: '请检查 Base URL、代理、TLS/证书、中转网关或本地网络策略,并可稍后重试。',
invalid_config: '先补齐协议、Base URL、API Key 和模型配置,再执行一键测试。',
unsupported_protocol: '当前仅对 OpenAI Compatible / DeepSeek 渠道提供自动模型发现,请改为手动维护模型列表。',
};
const LLM_REASON_HINTS: Record<string, string> = {
missing_api_key: 'API Key 为空,或逗号分隔后没有任何可用 Key;请填入至少一个有效 Key 后再测试。',
api_key_rejected: '服务商拒绝了当前 API Key;请检查 Key、组织/项目权限、区域和账号状态。',
rate_limit: '服务商触发 RPM/TPM 或并发限流;请降低请求频率或稍后重试。',
insufficient_balance: '服务商返回余额、账单或额度不足;请检查账户余额和套餐状态。',
quota_exceeded: '服务商返回配额已耗尽;请确认账号套餐、余量和项目额度。',
dns_error: '域名解析失败;请检查 Base URL 域名、网络代理和 DNS 配置。',
tls_error: 'TLS/证书握手失败;请检查 HTTPS 证书、中转网关或公司代理策略。',
connection_refused: '目标服务拒绝连接;请确认 Base URL 端口、服务进程和防火墙配置。',
model_access_denied: '当前账号没有访问该模型的权限;请在服务商控制台确认模型开通状态。',
provider_prefix_mismatch: '模型 provider 前缀与当前渠道不匹配;请确认模型名是否应使用该渠道的 OpenAI-compatible 路由。',
capability_unsupported: '当前模型或兼容层不支持该能力;这不影响基础文本连接,可换模型或关闭该能力依赖。',
};
function getLlmStageLabel(stage?: string | null): string {
return LLM_STAGE_LABELS[stage || ''] || '连接测试';
}
function getLlmErrorCodeLabel(code?: string | null): string {
return LLM_ERROR_LABELS[code || ''] || '测试失败';
}
function getLlmTroubleshootingHint(
code?: string | null,
stage?: string | null,
context: 'test' | 'discovery' = 'test',
details?: Record<string, unknown>,
): string | undefined {
const reason = typeof details?.reason === 'string' ? details.reason : '';
if (reason && LLM_REASON_HINTS[reason]) {
return LLM_REASON_HINTS[reason];
}
if (code === 'format_error') {
return context === 'discovery' || stage === 'model_discovery'
? '该渠道返回的 /models 响应格式不兼容,请改为手动填写模型列表。'
: '返回结构与预期不一致,请确认该渠道兼容 Chat Completions 接口。';
}
if (code === 'empty_response' && (context === 'discovery' || stage === 'model_discovery')) {
return '该渠道的 /models 接口未返回可用模型 ID;请检查 Base URL 是否指向兼容的模型列表接口,或改为手动填写模型列表。';
}
return LLM_TROUBLESHOOTING_HINTS[code || ''];
}
function buildLlmFailureText(result: {
message: string;
error?: string | null;
stage?: string | null;
errorCode?: string | null;
}): string {
const prefix = `${getLlmStageLabel(result.stage)} · ${getLlmErrorCodeLabel(result.errorCode)}`;
const summary = result.message || '测试失败';
if (result.error && result.error !== result.message) {
return `${prefix}:${summary}(原始摘要:${result.error})`;
}
return `${prefix}:${summary}`;
}
function getCapabilityResultVariant(status: LLMCapabilityCheckResult['status']): 'success' | 'danger' | 'warning' {
if (status === 'passed') return 'success';
if (status === 'skipped') return 'warning';
return 'danger';
}
function summarizeCapabilityResults(results: Partial<Record<LLMCapabilityCheck, LLMCapabilityCheckResult>>): string {
const values = Object.values(results);
const passed = values.filter((result) => result?.status === 'passed').length;
const failed = values.filter((result) => result?.status === 'failed').length;
const skipped = values.filter((result) => result?.status === 'skipped').length;
return `能力检测完成:${passed} 通过 / ${failed} 失败 / ${skipped} 跳过`;
}
function getFirstCapabilityHint(
results: Partial<Record<LLMCapabilityCheck, LLMCapabilityCheckResult>>,
): string | undefined {
for (const result of Object.values(results)) {
if (!result || result.status === 'passed') continue;
const hint = getLlmTroubleshootingHint(result.errorCode, result.stage, 'test', result.details);
if (hint) return hint;
}
return undefined;
}
const MANAGED_PROVIDERS = new Set(['gemini', 'vertex_ai', 'anthropic', 'openai', 'deepseek']);
const LEGACY_PROVIDER_KEYS: Record<string, string[]> = {
gemini: ['GEMINI_API_KEYS', 'GEMINI_API_KEY'],
vertex_ai: ['GEMINI_API_KEYS', 'GEMINI_API_KEY'],
anthropic: ['ANTHROPIC_API_KEYS', 'ANTHROPIC_API_KEY'],
openai: ['OPENAI_API_KEYS', 'AIHUBMIX_KEY', 'OPENAI_API_KEY'],
deepseek: ['DEEPSEEK_API_KEYS', 'DEEPSEEK_API_KEY'],
};
function getRuntimeProvider(model: string): string {
if (!model) return '';
if (!model.includes('/')) return 'openai';
return model.split('/', 1)[0].trim().toLowerCase();
}
function usesDirectEnvProvider(model: string): boolean {
const provider = getRuntimeProvider(model);
return Boolean(provider) && !MANAGED_PROVIDERS.has(provider);
}
function hasLegacyRuntimeSource(model: string, itemMap: Map<string, string>): boolean {
const provider = PROTOCOL_ALIASES[getRuntimeProvider(model)] || getRuntimeProvider(model);
if (!provider || !MANAGED_PROVIDERS.has(provider)) {
return false;
}
return (LEGACY_PROVIDER_KEYS[provider] || []).some((key) => (itemMap.get(key) || '').trim().length > 0);
}
function isRuntimeModelAvailable(model: string, availableModels: string[], itemMap: Map<string, string>): boolean {
return availableModels.includes(model)
|| usesDirectEnvProvider(model)
|| (availableModels.length === 0 && hasLegacyRuntimeSource(model, itemMap));
}
function sanitizeRuntimeConfigForSave(
runtimeConfig: RuntimeConfig,
availableModels: string[],
itemMap: Map<string, string>,
): RuntimeConfig {
const primaryModel = runtimeConfig.primaryModel && !isRuntimeModelAvailable(runtimeConfig.primaryModel, availableModels, itemMap)
? ''
: runtimeConfig.primaryModel;
const agentPrimaryModel = runtimeConfig.agentPrimaryModel && !isRuntimeModelAvailable(runtimeConfig.agentPrimaryModel, availableModels, itemMap)
? ''
: runtimeConfig.agentPrimaryModel;
const visionModel = runtimeConfig.visionModel && !isRuntimeModelAvailable(runtimeConfig.visionModel, availableModels, itemMap)
? ''
: runtimeConfig.visionModel;
const fallbackModels = runtimeConfig.fallbackModels.filter((model) => isRuntimeModelAvailable(model, availableModels, itemMap));
return {
...runtimeConfig,
primaryModel,
agentPrimaryModel,
fallbackModels,
visionModel,
};
}
function runtimeConfigsAreEqual(left: RuntimeConfig, right: RuntimeConfig): boolean {
return left.primaryModel === right.primaryModel
&& left.agentPrimaryModel === right.agentPrimaryModel
&& left.visionModel === right.visionModel
&& left.temperature === right.temperature
&& left.fallbackModels.join(',') === right.fallbackModels.join(',');
}
function resolveTemperatureFromItems(itemMap: Map<string, string>): string {
const unified = itemMap.get('LLM_TEMPERATURE');
if (unified) return unified;
const primaryModel = itemMap.get('LITELLM_MODEL') || '';
const provider = primaryModel.includes('/') ? primaryModel.split('/')[0] : (primaryModel ? 'openai' : '');
const providerTemperatureEnv: Record<string, string> = {
gemini: 'GEMINI_TEMPERATURE',
vertex_ai: 'GEMINI_TEMPERATURE',
anthropic: 'ANTHROPIC_TEMPERATURE',
openai: 'OPENAI_TEMPERATURE',
deepseek: 'OPENAI_TEMPERATURE',
};
const preferredEnv = providerTemperatureEnv[provider];
if (preferredEnv) {
const val = itemMap.get(preferredEnv);
if (val) return val;
}
for (const envName of ['GEMINI_TEMPERATURE', 'ANTHROPIC_TEMPERATURE', 'OPENAI_TEMPERATURE']) {
const val = itemMap.get(envName);
if (val) return val;
}
return '0.7';
}
function normalizeAgentPrimaryModel(model: string): string {
const trimmedModel = model.trim();
if (!trimmedModel) {
return '';
}
if (trimmedModel.includes('/')) {
return trimmedModel;
}
return `openai/${trimmedModel}`;
}
function parseRuntimeConfigFromItems(items: Array<{ key: string; value: string }>): RuntimeConfig {
const itemMap = new Map(items.map((item) => [item.key, item.value]));
return {
primaryModel: itemMap.get('LITELLM_MODEL') || '',
agentPrimaryModel: normalizeAgentPrimaryModel(itemMap.get('AGENT_LITELLM_MODEL') || ''),
fallbackModels: splitModels(itemMap.get('LITELLM_FALLBACK_MODELS') || ''),
visionModel: itemMap.get('VISION_MODEL') || '',
temperature: resolveTemperatureFromItems(itemMap),
};
}
function parseChannelsFromItems(items: Array<{ key: string; value: string }>): ChannelConfig[] {
const itemMap = new Map(items.map((item) => [item.key, item.value]));
const channelNames = (itemMap.get('LLM_CHANNELS') || '')
.split(',')
.map((segment) => segment.trim())
.filter(Boolean);
return channelNames.map((name, index) => {
const upperName = name.toUpperCase();
const baseUrl = itemMap.get(`LLM_${upperName}_BASE_URL`) || '';
const rawModels = itemMap.get(`LLM_${upperName}_MODELS`) || '';
const models = splitModels(rawModels);
return {
id: `parsed:${index}:${upperName}`,
name: name.toLowerCase(),
protocol: inferProtocol(itemMap.get(`LLM_${upperName}_PROTOCOL`) || '', baseUrl, models),
baseUrl,
apiKey: itemMap.get(`LLM_${upperName}_API_KEYS`) || itemMap.get(`LLM_${upperName}_API_KEY`) || '',
models: rawModels,
enabled: parseEnabled(itemMap.get(`LLM_${upperName}_ENABLED`)),
};
});
}
function channelsToUpdateItems(
channels: ChannelConfig[],
previousChannelNames: string[],
runtimeConfig: RuntimeConfig,
includeRuntimeConfig: boolean,
): Array<{ key: string; value: string }> {
const updates: Array<{ key: string; value: string }> = [];
const activeNames = channels.map((channel) => channel.name.toUpperCase());
updates.push({ key: 'LLM_CHANNELS', value: channels.map((channel) => channel.name).join(',') });
if (includeRuntimeConfig) {
updates.push({ key: 'LITELLM_MODEL', value: runtimeConfig.primaryModel });
updates.push({ key: 'AGENT_LITELLM_MODEL', value: runtimeConfig.agentPrimaryModel });
updates.push({ key: 'LITELLM_FALLBACK_MODELS', value: runtimeConfig.fallbackModels.join(',') });
updates.push({ key: 'VISION_MODEL', value: runtimeConfig.visionModel });
updates.push({ key: 'LLM_TEMPERATURE', value: runtimeConfig.temperature });
}
for (const channel of channels) {
const prefix = `LLM_${channel.name.toUpperCase()}`;
const isMultiKey = channel.apiKey.includes(',');
updates.push({ key: `${prefix}_PROTOCOL`, value: channel.protocol });
updates.push({ key: `${prefix}_BASE_URL`, value: channel.baseUrl });
updates.push({ key: `${prefix}_ENABLED`, value: channel.enabled ? 'true' : 'false' });
updates.push({ key: `${prefix}_API_KEY${isMultiKey ? 'S' : ''}`, value: channel.apiKey });
updates.push({ key: `${prefix}_API_KEY${isMultiKey ? '' : 'S'}`, value: '' });
updates.push({ key: `${prefix}_MODELS`, value: channel.models });
}
for (const oldName of previousChannelNames) {
const upperName = oldName.toUpperCase();
if (activeNames.includes(upperName)) {
continue;
}
const prefix = `LLM_${upperName}`;
updates.push({ key: `${prefix}_PROTOCOL`, value: '' });
updates.push({ key: `${prefix}_BASE_URL`, value: '' });
updates.push({ key: `${prefix}_ENABLED`, value: '' });
updates.push({ key: `${prefix}_API_KEY`, value: '' });
updates.push({ key: `${prefix}_API_KEYS`, value: '' });
updates.push({ key: `${prefix}_MODELS`, value: '' });
updates.push({ key: `${prefix}_EXTRA_HEADERS`, value: '' });
}