feat(vertex-ai): 重构 Vertex AI 为插件化 adapter,支持 service_account 认证与动态路由

将 Vertex AI 从 transport.py 的硬编码逻辑重构为独立的 plugin adapter,
支持 service_account/oauth 认证类型、模型格式自动识别、区域路由和 URL 构建。
前端新增 Key 认证类型选择和 Service Account 配置表单。

Co-authored-by: NyaDoo <65238336+NyaDoo@users.noreply.github.com>
Closes #194
This commit is contained in:
fawney19
2026-03-01 23:32:48 +08:00
parent a137601728
commit 4bf3a453e7
42 changed files with 1855 additions and 546 deletions

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@@ -0,0 +1,263 @@
"""vertex_ai_provider_type
Migrate legacy Vertex auth_type/provider_type into the new model:
- provider_type=vertex_ai
- auth_type=service_account (legacy vertex_ai renamed)
- fixed Vertex endpoints: gemini:chat + claude:chat
Revision ID: 2a624af8dd3a
Revises: 00b9161b8729
Create Date: 2026-02-28 15:00:00.000000+00:00
"""
from __future__ import annotations
import uuid
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "2a624af8dd3a"
down_revision = "00b9161b8729"
branch_labels = None
depends_on = None
_VERTEX_BASE_URL = "https://aiplatform.googleapis.com"
_VERTEX_ENDPOINTS: tuple[tuple[str, str, str], ...] = (
("gemini:chat", "gemini", "chat"),
("claude:chat", "claude", "chat"),
)
_VERTEX_KEY_FORMATS_SA = '["gemini:chat","claude:chat"]'
_VERTEX_KEY_FORMATS_API_KEY = '["gemini:chat"]'
def _select_vertex_provider_ids(conn: sa.Connection) -> list[str]:
"""Collect providers that should be treated as Vertex after migration."""
rows = conn.execute(sa.text("""
SELECT DISTINCT p.id
FROM providers p
LEFT JOIN provider_api_keys pak ON pak.provider_id = p.id
WHERE lower(COALESCE(p.provider_type, '')) = 'vertex_ai'
OR pak.auth_type = 'vertex_ai'
"""))
return [str(row[0]) for row in rows if row[0]]
def _ensure_fixed_vertex_endpoints(conn: sa.Connection, provider_ids: list[str]) -> None:
"""Ensure every Vertex provider has fixed gemini:chat + claude:chat endpoints."""
for provider_id in provider_ids:
provider_max_retries = (
conn.execute(
sa.text("""
SELECT COALESCE(max_retries, 2)
FROM providers
WHERE id = :provider_id
"""),
{"provider_id": provider_id},
).scalar()
or 2
)
for api_format, api_family, endpoint_kind in _VERTEX_ENDPOINTS:
# Normalize existing fixed endpoint fields.
conn.execute(
sa.text("""
UPDATE provider_endpoints
SET
api_family = :api_family,
endpoint_kind = :endpoint_kind,
base_url = :base_url,
custom_path = NULL,
is_active = TRUE,
updated_at = CURRENT_TIMESTAMP
WHERE provider_id = :provider_id
AND api_format = :api_format
"""),
{
"provider_id": provider_id,
"api_format": api_format,
"api_family": api_family,
"endpoint_kind": endpoint_kind,
"base_url": _VERTEX_BASE_URL,
},
)
exists = conn.execute(
sa.text("""
SELECT 1
FROM provider_endpoints
WHERE provider_id = :provider_id
AND api_format = :api_format
LIMIT 1
"""),
{"provider_id": provider_id, "api_format": api_format},
).first()
if not exists:
conn.execute(
sa.text("""
INSERT INTO provider_endpoints (
id,
provider_id,
api_format,
api_family,
endpoint_kind,
base_url,
custom_path,
header_rules,
body_rules,
max_retries,
is_active,
config,
format_acceptance_config,
proxy,
created_at,
updated_at
)
VALUES (
:id,
:provider_id,
:api_format,
:api_family,
:endpoint_kind,
:base_url,
NULL,
NULL,
NULL,
:max_retries,
TRUE,
NULL,
NULL,
NULL,
CURRENT_TIMESTAMP,
CURRENT_TIMESTAMP
)
"""),
{
"id": str(uuid.uuid4()),
"provider_id": provider_id,
"api_format": api_format,
"api_family": api_family,
"endpoint_kind": endpoint_kind,
"base_url": _VERTEX_BASE_URL,
"max_retries": int(provider_max_retries),
},
)
# Vertex fixed-provider model: disable non-fixed endpoints.
conn.execute(
sa.text("""
UPDATE provider_endpoints
SET
is_active = FALSE,
updated_at = CURRENT_TIMESTAMP
WHERE provider_id = :provider_id
AND api_format NOT IN ('gemini:chat', 'claude:chat')
"""),
{"provider_id": provider_id},
)
def _normalize_vertex_key_formats(conn: sa.Connection, provider_ids: list[str]) -> None:
"""Normalize key.api_formats for Vertex keys by auth type."""
for provider_id in provider_ids:
# Service Account (and legacy vertex_ai) keys: allow Gemini + Claude models.
conn.execute(
sa.text("""
UPDATE provider_api_keys
SET
api_formats = CAST(:api_formats AS json),
updated_at = CURRENT_TIMESTAMP
WHERE provider_id = :provider_id
AND auth_type IN ('service_account', 'vertex_ai')
"""),
{
"provider_id": provider_id,
"api_formats": _VERTEX_KEY_FORMATS_SA,
},
)
# API Key mode on Vertex 仅支持 GeminiGoogle publisher
conn.execute(
sa.text("""
UPDATE provider_api_keys
SET
api_formats = CAST(:api_formats AS json),
updated_at = CURRENT_TIMESTAMP
WHERE provider_id = :provider_id
AND auth_type = 'api_key'
"""),
{
"provider_id": provider_id,
"api_formats": _VERTEX_KEY_FORMATS_API_KEY,
},
)
def upgrade() -> None:
conn = op.get_bind()
# 1) 收集目标 Provider兼容重复执行先识别 legacy/new 两种来源)。
provider_ids = _select_vertex_provider_ids(conn)
# 2) 先重命名 auth_typelegacy vertex_ai -> service_account
conn.execute(sa.text("""
UPDATE provider_api_keys
SET auth_type = 'service_account'
WHERE auth_type = 'vertex_ai'
"""))
if not provider_ids:
return
# 3) 归一 provider_type并启用格式转换Vertex 同时承载 Gemini/Claude
for provider_id in provider_ids:
conn.execute(
sa.text("""
UPDATE providers
SET
provider_type = 'vertex_ai',
enable_format_conversion = TRUE
WHERE id = :provider_id
"""),
{"provider_id": provider_id},
)
# 4) 固定端点落地gemini:chat + claude:chat。
_ensure_fixed_vertex_endpoints(conn, provider_ids)
# 5) 归一 key 的 api_formats避免调度命中旧格式。
_normalize_vertex_key_formats(conn, provider_ids)
def downgrade() -> None:
conn = op.get_bind()
provider_rows = conn.execute(sa.text("""
SELECT id
FROM providers
WHERE lower(COALESCE(provider_type, '')) = 'vertex_ai'
"""))
provider_ids = [str(row[0]) for row in provider_rows if row[0]]
if provider_ids:
for provider_id in provider_ids:
conn.execute(
sa.text("""
UPDATE provider_api_keys
SET auth_type = 'vertex_ai'
WHERE provider_id = :provider_id
AND auth_type = 'service_account'
"""),
{"provider_id": provider_id},
)
conn.execute(
sa.text("""
UPDATE providers
SET provider_type = 'custom'
WHERE id = :provider_id
"""),
{"provider_id": provider_id},
)

View File

@@ -56,7 +56,7 @@ export async function getModelCapabilities(modelName: string): Promise<ModelCapa
* 获取完整的 API Key用于查看和复制
*/
export interface RevealKeyResult {
auth_type: 'api_key' | 'vertex_ai' | 'oauth'
auth_type: 'api_key' | 'service_account' | 'oauth'
api_key?: string
refresh_token?: string
auth_config?: string | Record<string, unknown>
@@ -119,7 +119,7 @@ export async function addProviderKey(
data: {
api_formats: string[] // 支持的 API 格式列表(必填)
api_key: string
auth_type?: 'api_key' | 'vertex_ai' | 'oauth' // 认证类型
auth_type?: 'api_key' | 'service_account' | 'oauth' // 认证类型
auth_config?: Record<string, unknown> // 认证配置Vertex AI Service Account JSON
name: string
rate_multipliers?: Record<string, number> | null // 按 API 格式的成本倍率
@@ -147,7 +147,7 @@ export async function updateProviderKey(
data: Partial<{
api_formats: string[] // 支持的 API 格式列表
api_key: string
auth_type: 'api_key' | 'vertex_ai' | 'oauth' // 认证类型
auth_type: 'api_key' | 'service_account' | 'oauth' // 认证类型
auth_config: Record<string, unknown> // 认证配置Vertex AI Service Account JSON
name: string
rate_multipliers: Record<string, number> | null // 按 API 格式的成本倍率

View File

@@ -30,7 +30,7 @@ export async function updateProvider(
providerId: string,
data: Partial<{
name: string
provider_type: 'custom' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro'
provider_type: 'custom' | 'vertex_ai' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro'
description: string | null
website: string
provider_priority: number
@@ -62,7 +62,7 @@ export async function updateProvider(
export async function createProvider(
data: {
name: string
provider_type?: 'custom' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro'
provider_type?: 'custom' | 'vertex_ai' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro'
description?: string
website?: string
billing_type?: 'monthly_quota' | 'pay_as_you_go' | 'free_tier'

View File

@@ -204,7 +204,7 @@ export interface EndpointAPIKey {
api_formats: string[] // 支持的 endpoint signature 列表(如 "openai:chat"
api_key_masked: string
api_key_plain?: string | null
auth_type: 'api_key' | 'vertex_ai' | 'oauth' // 认证类型(必返回)
auth_type: 'api_key' | 'service_account' | 'oauth' // 认证类型(必返回)
name: string // 密钥名称(必填,用于识别)
rate_multipliers?: Record<string, number> | null // 按 endpoint signature 的成本倍率
internal_priority: number // Key 内部优先级
@@ -347,7 +347,7 @@ export interface EndpointAPIKeyUpdate {
api_formats?: string[] // 支持的 API 格式列表
name?: string
api_key?: string // 仅在需要更新时提供
auth_type?: 'api_key' | 'vertex_ai' | 'oauth' // 认证类型
auth_type?: 'api_key' | 'service_account' | 'oauth' // 认证类型
auth_config?: Record<string, unknown> // 认证配置Vertex AI Service Account JSON
rate_multipliers?: Record<string, number> | null // 按 API 格式的成本倍率
internal_priority?: number
@@ -436,7 +436,7 @@ export interface PublicEndpointStatusMonitorResponse {
formats: PublicEndpointStatusMonitor[]
}
export type ProviderType = 'custom' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro'
export type ProviderType = 'custom' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro' | 'vertex_ai'
export interface ClaudeCodeAdvancedConfig {
// 会话数量控制null/undefined 表示不限制

View File

@@ -13,7 +13,7 @@ export interface CandidateRecord {
key_id?: string
key_name?: string // 密钥名称
key_preview?: string // 密钥脱敏预览(如 sk-***abcOAuth 类型不返回
key_auth_type?: string // 密钥认证类型api_key, oauth, vertex_ai 等)
key_auth_type?: string // 密钥认证类型api_key, service_account, oauth 等)
key_oauth_plan_type?: string // OAuth 账号套餐类型free/plus/team/enterprise
key_capabilities?: Record<string, boolean> | null // Key 支持的能力
required_capabilities?: Record<string, boolean> | null // 请求实际需要的能力标签

View File

@@ -32,7 +32,7 @@
data-1p-ignore="true"
/>
</div>
<div>
<div v-if="providerType === 'vertex_ai'">
<Label :for="authTypeSelectId">认证类型</Label>
<Select
v-model="form.auth_type"
@@ -44,8 +44,8 @@
<SelectItem value="api_key">
API Key
</SelectItem>
<SelectItem value="vertex_ai">
Vertex AI
<SelectItem value="service_account">
Service Account
</SelectItem>
</SelectContent>
</Select>
@@ -55,10 +55,10 @@
<!-- API 密钥 / Service Account JSON -->
<div>
<Label :for="apiKeyInputId">
{{ form.auth_type === 'vertex_ai' ? 'Service Account JSON' : 'API 密钥' }}
{{ form.auth_type === 'service_account' ? 'Service Account JSON' : 'API 密钥' }}
{{ editingKey ? '' : '*' }}
</Label>
<template v-if="form.auth_type === 'vertex_ai'">
<template v-if="form.auth_type === 'service_account'">
<Textarea
:id="apiKeyInputId"
v-model="form.auth_config_text"
@@ -101,11 +101,11 @@
</div>
<!-- API 格式选择 -->
<div v-if="sortedApiFormats.length > 0">
<div v-if="visibleApiFormats.length > 0">
<Label class="mb-1.5 block">支持的 API 格式 *</Label>
<div class="grid grid-cols-2 gap-2">
<div
v-for="format in sortedApiFormats"
v-for="format in visibleApiFormats"
:key="format"
class="flex items-center justify-between rounded-md border px-2 py-1.5 transition-colors cursor-pointer"
:class="form.api_formats.includes(format)
@@ -309,7 +309,7 @@
</template>
<script setup lang="ts">
import { ref, computed, onMounted } from 'vue'
import { ref, computed, onMounted, watch } from 'vue'
import { Dialog, Button, Input, Label, Switch, Select, SelectTrigger, SelectValue, SelectContent, SelectItem, Textarea } from '@/components/ui'
import { Key, SquarePen } from 'lucide-vue-next'
import { useToast } from '@/composables/useToast'
@@ -346,8 +346,26 @@ const emit = defineEmits<{
const { success, error: showError } = useToast()
// 排序后的可用 API 格式列表
const sortedApiFormats = computed(() => sortApiFormats(props.availableApiFormats))
function getVertexAllowedFormatsByAuth(authType: 'api_key' | 'service_account'): Set<string> {
if (authType === 'api_key') {
return new Set(['gemini:chat'])
}
return new Set(['gemini:chat', 'claude:chat'])
}
function normalizeApiFormat(format: string): string {
return String(format || '').trim().toLowerCase()
}
// 按 provider/auth_type 过滤后的可用 API 格式列表
const visibleApiFormats = computed(() => {
const sorted = sortApiFormats(props.availableApiFormats)
if (props.providerType !== 'vertex_ai') {
return sorted
}
const allowed = getVertexAllowedFormatsByAuth(form.value.auth_type)
return sorted.filter(fmt => allowed.has(normalizeApiFormat(fmt)))
})
// 默认认证类型
const defaultAuthType = 'api_key' as const
@@ -370,8 +388,8 @@ const showAutoFetchWarning = computed(() => {
// 检查是否正在切换认证类型
const switchingToVertexAI = computed(() =>
!!props.editingKey &&
props.editingKey.auth_type !== 'vertex_ai' &&
form.value.auth_type === 'vertex_ai'
props.editingKey.auth_type !== 'service_account' &&
form.value.auth_type === 'service_account'
)
const switchingToApiKey = computed(() =>
!!props.editingKey &&
@@ -386,7 +404,7 @@ const canSave = computed(() => {
// 新增模式下根据认证类型判断必填字段
if (!props.editingKey) {
if (form.value.auth_type === 'api_key' && !form.value.api_key.trim()) return false
if (form.value.auth_type === 'vertex_ai' && !form.value.auth_config_text.trim()) return false
if (form.value.auth_type === 'service_account' && !form.value.auth_config_text.trim()) return false
} else {
// 编辑模式下切换认证类型时,必须填写对应字段
if (switchingToApiKey.value && !form.value.api_key.trim()) return false
@@ -409,15 +427,13 @@ const apiKeyFieldName = computed(() => `api-key-field-${formNonce.value}`)
// 可用的能力列表
const availableCapabilities = ref<CapabilityDefinition[]>([])
// 非 custom 提供商默认开启自动获取上游模型
const defaultAutoFetchModels = computed(() =>
!!props.providerType && props.providerType !== 'custom'
)
// 新增密钥时默认不自动开启上游模型获取
const defaultAutoFetchModels = computed(() => false)
const form = ref({
name: '',
api_key: '', // 标准 API Key
auth_type: 'api_key' as 'api_key' | 'vertex_ai', // 认证类型
auth_type: 'api_key' as 'api_key' | 'service_account', // 认证类型
auth_config_text: '', // Service Account JSON 文本(用于表单输入)
api_formats: [] as string[], // 支持的 API 格式列表
rate_multipliers: {} as Record<string, number>, // 按 API 格式的成本倍率
@@ -433,6 +449,21 @@ const form = ref({
model_exclude_patterns_text: '' // 排除规则文本(逗号分隔)
})
watch(
[() => form.value.auth_type, () => props.providerType, () => props.availableApiFormats],
() => {
if (props.providerType !== 'vertex_ai') {
return
}
const allowed = getVertexAllowedFormatsByAuth(form.value.auth_type)
const filtered = form.value.api_formats.filter(fmt => allowed.has(normalizeApiFormat(fmt)))
if (filtered.length !== form.value.api_formats.length) {
form.value.api_formats = [...filtered]
}
},
{ immediate: true }
)
// 加载能力列表
async function loadCapabilities() {
try {
@@ -517,7 +548,7 @@ function loadKeyData() {
form.value = {
name: props.editingKey.name,
api_key: '',
auth_type: props.editingKey.auth_type === 'vertex_ai' ? 'vertex_ai' : 'api_key',
auth_type: props.editingKey.auth_type === 'service_account' ? 'service_account' : 'api_key',
auth_config_text: '', // auth_config 不返回给前端,编辑时需要重新输入
api_formats: props.editingKey.api_formats?.length > 0
? [...props.editingKey.api_formats]
@@ -564,7 +595,7 @@ function parsePatternText(text: string): string[] {
// 解析 Service Account JSON 文本
function parseAuthConfig(): Record<string, unknown> | null {
if (form.value.auth_type !== 'vertex_ai') return null
if (form.value.auth_type !== 'service_account') return null
const text = form.value.auth_config_text.trim()
if (!text) return null
try {
@@ -588,7 +619,7 @@ async function handleSave() {
showError('请输入 API 密钥', '验证失败')
return
}
} else if (form.value.auth_type === 'vertex_ai') {
} else if (form.value.auth_type === 'service_account') {
if (!props.editingKey && !form.value.auth_config_text.trim()) {
showError('请输入 Service Account JSON', '验证失败')
return
@@ -664,7 +695,7 @@ async function handleSave() {
if (form.value.auth_type === 'api_key' && form.value.api_key.trim()) {
updateData.api_key = form.value.api_key
}
if (form.value.auth_type === 'vertex_ai' && authConfig) {
if (form.value.auth_type === 'service_account' && authConfig) {
updateData.auth_config = authConfig
}

View File

@@ -224,7 +224,7 @@
<div class="p-4 border-b border-border/60">
<div class="flex items-center justify-between">
<h3 class="text-sm font-semibold">
{{ provider.provider_type === 'custom' ? '密钥管理' : '账号管理' }}
{{ isKeyManagedProviderType(provider.provider_type) ? '密钥管理' : '账号管理' }}
</h3>
<div class="flex items-center gap-2">
<Button
@@ -235,7 +235,7 @@
@click="handleAddKeyToFirstEndpoint"
>
<Plus class="w-3.5 h-3.5 mr-1.5" />
{{ provider.provider_type === 'custom' ? '添加密钥' : '添加账号' }}
{{ isKeyManagedProviderType(provider.provider_type) ? '添加密钥' : '添加账号' }}
</Button>
</div>
</div>
@@ -301,7 +301,7 @@
</div>
<div class="flex items-center gap-1">
<span class="text-[11px] font-mono text-muted-foreground">
{{ key.auth_type === 'oauth' ? '[Refresh Token]' : (key.auth_type === 'vertex_ai' ? 'Vertex AI' : key.api_key_masked) }}
{{ key.auth_type === 'oauth' ? '[Refresh Token]' : (key.auth_type === 'service_account' ? '[Service Account]' : key.api_key_masked) }}
</span>
<Button
v-if="key.auth_type === 'oauth'"
@@ -844,7 +844,7 @@
v-if="shouldPaginateKeys"
class="px-4 py-2 flex items-center justify-between text-xs text-muted-foreground mt-auto"
>
<span>共 {{ allKeys.length }} 个{{ provider.provider_type === 'custom' ? '密钥' : '账号' }}</span>
<span>共 {{ allKeys.length }} 个{{ isKeyManagedProviderType(provider.provider_type) ? '密钥' : '账号' }}</span>
<div class="flex items-center gap-1.5">
<Button
variant="ghost"
@@ -876,11 +876,11 @@
>
<Key class="w-12 h-12 mx-auto mb-3 opacity-50" />
<p class="text-sm">
{{ provider.provider_type === 'custom' ? '暂无密钥配置' : '暂无账号配置' }}
{{ isKeyManagedProviderType(provider.provider_type) ? '暂无密钥配置' : '暂无账号配置' }}
</p>
<p class="text-xs mt-1">
{{ endpoints.length > 0
? (provider.provider_type === 'custom' ? '点击上方"添加密钥"按钮创建第一个密钥' : '点击上方"添加账号"按钮添加第一个账号')
? (isKeyManagedProviderType(provider.provider_type) ? '点击上方"添加密钥"按钮创建第一个密钥' : '点击上方"添加账号"按钮添加第一个账号')
: '请先添加端点,然后再添加密钥' }}
</p>
</div>
@@ -1100,6 +1100,7 @@ import {
} from '@/api/endpoints'
import type { UpstreamMetadata, AntigravityModelQuota } from '@/api/endpoints/types'
import { formatApiFormat } from '@/api/endpoints/types/api-format'
import { isOAuthAccountProviderType, isKeyManagedProviderType } from '../utils/providerTypeUtils'
// 扩展端点类型,包含密钥列表
interface ProviderEndpointWithKeys extends ProviderEndpoint {
@@ -1417,11 +1418,11 @@ function handleAddKey(endpoint: ProviderEndpoint) {
function handleAddKeyToFirstEndpoint() {
if (endpoints.value.length === 0) return
// 非自定义提供商:打开 OAuth 账号对话框
if (provider.value?.provider_type !== 'custom') {
// OAuth 账号型提供商:打开 OAuth 账号对话框
if (isOAuthAccountProviderType(provider.value?.provider_type)) {
oauthAccountDialogOpen.value = true
} else {
// 自定义提供商:打开密钥表单对话框
// 密钥型提供商custom/vertex_ai:打开密钥表单对话框
handleAddKey(endpoints.value[0])
}
}
@@ -1455,8 +1456,8 @@ async function copyFullKey(key: EndpointAPIKey) {
const result = await revealEndpointKey(key.id)
let textToCopy: string
if (result.auth_type === 'vertex_ai' && result.auth_config) {
// Vertex AI 类型:复制 auth_config JSON
if (result.auth_type === 'service_account' && result.auth_config) {
// Service Account 类型:复制 auth_config JSON
textToCopy = typeof result.auth_config === 'string'
? result.auth_config
: JSON.stringify(result.auth_config, null, 2)

View File

@@ -42,6 +42,9 @@
<SelectItem value="custom">
自定义
</SelectItem>
<SelectItem value="vertex_ai">
Vertex AI
</SelectItem>
<SelectItem value="claude_code">
ClaudeCode
</SelectItem>
@@ -60,6 +63,9 @@
<SelectItem value="custom">
自定义
</SelectItem>
<SelectItem value="vertex_ai">
Vertex AI
</SelectItem>
<SelectItem value="claude_code">
ClaudeCode
</SelectItem>
@@ -322,7 +328,7 @@ const defaultPriority = computed(() => {
// 表单数据
const form = ref({
name: '',
provider_type: 'custom' as 'custom' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro',
provider_type: 'custom' as 'custom' | 'vertex_ai' | 'claude_code' | 'codex' | 'gemini_cli' | 'antigravity' | 'kiro',
description: '',
website: '',
// 计费配置
@@ -414,10 +420,10 @@ const { isEditMode, handleDialogUpdate, handleCancel } = useFormDialog({
resetForm,
})
// 新建模式下切换 provider_type 时自动设置号池模式:非自定义类型默认开启
watch(() => form.value.provider_type, (newType) => {
// 新建模式下切换 provider_type 时自动开启号池模式
watch(() => form.value.provider_type, () => {
if (!isEditMode.value) {
form.value.pool_mode_enabled = newType !== 'custom'
form.value.pool_mode_enabled = false
}
})

View File

@@ -239,6 +239,7 @@ import Badge from '@/components/ui/badge.vue'
import { type ProviderWithEndpointsSummary, API_FORMAT_SHORT } from '@/api/endpoints'
import { formatBillingType } from '@/utils/format'
import { sortEndpoints, isEndpointAvailable, getEndpointDotColor, getEndpointTooltip } from '@/features/providers/composables/useEndpointStatus'
import { isKeyManagedProviderType } from '../utils/providerTypeUtils'
const props = defineProps<{
provider: ProviderWithEndpointsSummary
@@ -304,7 +305,6 @@ function handleDescriptionKeydown(event: KeyboardEvent) {
}
function getCredentialLabel(provider: ProviderWithEndpointsSummary): '账号' | '密钥' {
const providerType = String(provider.provider_type || '').trim().toLowerCase()
return providerType && providerType !== 'custom' ? '账号' : '密钥'
return isKeyManagedProviderType(provider.provider_type) ? '密钥' : '账号'
}
</script>

View File

@@ -775,14 +775,14 @@ const isCapabilityUsed = (cap: string): boolean => {
// 判断是否为 OAuth 类型provider_type 为具体值时也算 OAuth
const isOAuthType = (authType?: string): boolean => {
if (!authType) return false
return !['api_key', 'vertex_ai'].includes(authType)
return !['api_key', 'service_account'].includes(authType)
}
// 格式化认证类型(合并 plan 信息,避免冗余)
const formatAuthTypeWithPlan = (authType: string, planType?: string): string => {
const labels: Record<string, string> = {
'oauth': 'OAuth',
'vertex_ai': 'Vertex AI',
'service_account': 'Service Account',
'kiro': 'Kiro',
'codex': 'Codex',
'antigravity': 'Antigravity',

View File

@@ -131,17 +131,22 @@ export class GeminiParser implements ApiFormatParser {
apiFormat: 'gemini',
}
// Gemini 响应格式: { candidates: [{ content: { parts: [...] } }] }
const candidates = body.candidates as RawObject[] | undefined
const candidate = candidates?.[0] as RawObject | undefined
const candidateContent = candidate?.content as RawObject | undefined
if (candidateContent?.parts && Array.isArray(candidateContent.parts)) {
const contentBlocks = this.parseParts(candidateContent.parts as RawObject[])
// Gemini 原生响应格式: { candidates: [{ content: { parts: [...] } }] }
const candidateParts = this.getCandidateParts(body)
if (candidateParts.length > 0) {
const contentBlocks = this.parseParts(candidateParts)
if (contentBlocks.length > 0) {
result.messages.push(createMessage('assistant', contentBlocks))
return result
}
}
// 统一响应格式(例如 status/output/output_text
const unifiedMessages = this.parseUnifiedOutputMessages(body)
if (unifiedMessages.length > 0) {
result.messages.push(...unifiedMessages)
}
return result
} catch (e) {
return createEmptyConversation('gemini', `解析失败: ${e}`)
@@ -363,12 +368,10 @@ export class GeminiParser implements ApiFormatParser {
const body = responseBody as RawObject
const blocks: RenderBlock[] = []
// Gemini 响应格式: { candidates: [{ content: { parts: [...] } }] }
const candidates = body.candidates as RawObject[] | undefined
const candidate = candidates?.[0] as RawObject | undefined
const candidateContent = candidate?.content as RawObject | undefined
if (candidateContent?.parts && Array.isArray(candidateContent.parts)) {
const parts = candidateContent.parts as RawObject[]
// Gemini 原生响应格式: { candidates: [{ content: { parts: [...] } }] }
const candidateParts = this.getCandidateParts(body)
if (candidateParts.length > 0) {
const parts = candidateParts
const contentBlocks = this.renderParts(parts)
if (contentBlocks.length > 0) {
const badges = this.getBadgesForParts(parts)
@@ -376,9 +379,13 @@ export class GeminiParser implements ApiFormatParser {
roleLabel: 'Assistant',
badges: badges.length > 0 ? badges : undefined,
}))
return { blocks, isStream: false }
}
}
// 统一响应格式(例如 status/output/output_text
blocks.push(...this.renderUnifiedOutputMessages(body))
return { blocks, isStream: false }
} catch (e) {
return createEmptyRenderResult(`渲染失败: ${e}`)
@@ -582,6 +589,117 @@ export class GeminiParser implements ApiFormatParser {
return badges
}
/**
* 提取 Gemini candidates 中的 parts
*/
private getCandidateParts(body: RawObject): RawObject[] {
const candidates = body.candidates as RawObject[] | undefined
const candidate = candidates?.[0] as RawObject | undefined
const candidateContent = candidate?.content as RawObject | undefined
if (Array.isArray(candidateContent?.parts)) {
return candidateContent.parts as RawObject[]
}
return []
}
/**
* 解析统一响应格式中的 output 消息
*/
private parseUnifiedOutputMessages(body: RawObject): ParsedMessage[] {
const output = body.output
if (!Array.isArray(output)) {
return []
}
const messages: ParsedMessage[] = []
for (const rawItem of output) {
const item = rawItem as RawObject
if (item?.type !== 'message') {
continue
}
const texts = this.extractUnifiedOutputTexts(item.content)
if (texts.length === 0) {
continue
}
messages.push(createMessage(
this.mapUnifiedOutputRole(item.role),
texts.map(text => createTextBlock(text))
))
}
return messages
}
/**
* 渲染统一响应格式中的 output 消息
*/
private renderUnifiedOutputMessages(body: RawObject): RenderBlock[] {
const output = body.output
if (!Array.isArray(output)) {
return []
}
const blocks: RenderBlock[] = []
for (const rawItem of output) {
const item = rawItem as RawObject
if (item?.type !== 'message') {
continue
}
const texts = this.extractUnifiedOutputTexts(item.content)
if (texts.length === 0) {
continue
}
const role = this.mapUnifiedOutputRole(item.role)
blocks.push(createMessageBlock(
role,
texts.map(text => createTextRenderBlock(text)),
{ roleLabel: this.getRoleLabel(role) }
))
}
return blocks
}
/**
* 提取统一响应格式的文本内容
*/
private extractUnifiedOutputTexts(content: unknown): string[] {
if (typeof content === 'string') {
return content ? [content] : []
}
if (!Array.isArray(content)) {
return []
}
const texts: string[] = []
for (const rawPart of content) {
const part = rawPart as RawObject
if (
(part.type === 'output_text' || part.type === 'text' || part.type === 'input_text') &&
typeof part.text === 'string'
) {
texts.push(part.text)
}
}
return texts
}
/**
* 映射统一 output 结构的角色
*/
private mapUnifiedOutputRole(role: unknown): MessageRole {
if (role === 'assistant' || role === 'model') return 'assistant'
if (role === 'user') return 'user'
if (role === 'system') return 'system'
if (role === 'tool') return 'tool'
return 'assistant'
}
/**
* 获取已解析内容的徽章
*/

View File

@@ -21,6 +21,7 @@ from src.api.base.pipeline import ApiRequestPipeline
from src.core.api_format.signature import parse_signature_key
from src.core.exceptions import InvalidRequestException, NotFoundException
from src.core.logger import logger
from src.core.provider_templates.fixed_providers import FIXED_PROVIDERS
from src.core.provider_types import ProviderType
from src.database import get_db
from src.models.database import Provider, ProviderAPIKey, ProviderEndpoint
@@ -29,6 +30,7 @@ from src.models.endpoint_models import (
ProviderEndpointResponse,
ProviderEndpointUpdate,
)
from src.services.provider.stream_policy import UpstreamStreamPolicy, parse_upstream_stream_policy
router = APIRouter(tags=["Endpoint Management"])
pipeline = ApiRequestPipeline()
@@ -44,6 +46,17 @@ def mask_proxy_password(proxy_config: dict | None) -> dict | None:
return masked
def _is_fixed_provider(provider_type: str | None) -> bool:
"""Whether this provider_type is managed by fixed-provider templates."""
normalized = (provider_type or "custom").strip().lower()
if normalized == ProviderType.CUSTOM.value:
return False
try:
return ProviderType(normalized) in FIXED_PROVIDERS
except Exception:
return False
@router.get("/providers/{provider_id}/endpoints", response_model=list[ProviderEndpointResponse])
async def list_provider_endpoints(
provider_id: str,
@@ -283,8 +296,8 @@ class AdminCreateProviderEndpointAdapter(AdminApiAdapter):
raise NotFoundException(f"Provider {self.provider_id} 不存在")
# 固定类型 Provider禁止通过该接口新增 Endpoints端点由模板自动创建并锁定
provider_type = (getattr(provider, "provider_type", "custom") or "custom").strip()
if provider_type != ProviderType.CUSTOM:
provider_type = getattr(provider, "provider_type", "custom")
if _is_fixed_provider(provider_type):
raise InvalidRequestException("固定类型 Provider 不允许手动新增 Endpoint")
if self.endpoint_data.provider_id != self.provider_id:
@@ -424,12 +437,43 @@ class AdminUpdateProviderEndpointAdapter(AdminApiAdapter):
# 固定类型 Provider 的 endpoint锁定 base_url/custom_path前端禁用仅是 UX后端必须强校验
provider = db.query(Provider).filter(Provider.id == endpoint.provider_id).first()
if provider:
provider_type = (getattr(provider, "provider_type", "custom") or "custom").strip()
if provider_type != ProviderType.CUSTOM:
provider_type = getattr(provider, "provider_type", "custom")
if _is_fixed_provider(provider_type):
if "base_url" in update_data or "custom_path" in update_data:
raise InvalidRequestException(
"固定类型 Provider 的 Endpoint 不允许修改 base_url/custom_path"
)
normalized_provider_type = str(provider_type or "custom").strip().lower()
endpoint_sig = str(getattr(endpoint, "api_format", "") or "").strip().lower()
if (
normalized_provider_type == ProviderType.CODEX.value
and endpoint_sig == "openai:cli"
):
has_config_in_payload = "config" in update_data
cfg_payload = (
update_data.get("config")
if has_config_in_payload
else getattr(endpoint, "config", None)
)
cfg = dict(cfg_payload) if isinstance(cfg_payload, dict) else {}
requested = (
cfg.get("upstream_stream_policy")
or cfg.get("upstreamStreamPolicy")
or cfg.get("upstream_stream")
)
if (
has_config_in_payload
and requested is not None
and parse_upstream_stream_policy(requested)
!= UpstreamStreamPolicy.FORCE_STREAM
):
raise InvalidRequestException(
"Codex OpenAI CLI 端点固定为强制流式,不允许修改"
)
cfg.pop("upstreamStreamPolicy", None)
cfg.pop("upstream_stream", None)
cfg["upstream_stream_policy"] = "force_stream"
update_data["config"] = cfg
# 把 proxy 转换为 dict 存储,支持显式设置为 None 清除代理
if "proxy" in update_data:

View File

@@ -40,7 +40,7 @@ class CandidateResponse(BaseModel):
key_id: str | None = None
key_name: str | None = None # 密钥名称
key_preview: str | None = None # 密钥脱敏预览(如 sk-***abcOAuth 类型不返回
key_auth_type: str | None = None # 密钥认证类型api_key, oauth, vertex_ai 等
key_auth_type: str | None = None # 密钥认证类型api_key, service_account, oauth
key_oauth_plan_type: str | None = None # OAuth 账号套餐类型free/plus/team/enterprise
key_capabilities: dict | None = None # Key 支持的能力
required_capabilities: dict | None = None # 请求实际需要的能力标签

View File

@@ -160,13 +160,42 @@ class ProviderCompleteOAuthResponse(BaseModel):
# ==============================================================================
def _get_fixed_template(provider_type: str) -> Any | None:
try:
return FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
return None
def _supports_oauth(template: Any | None) -> bool:
if not template:
return False
oauth = getattr(template, "oauth", None)
if oauth is None:
return False
return bool(
str(getattr(oauth, "authorize_url", "") or "").strip()
and str(getattr(oauth, "token_url", "") or "").strip()
and str(getattr(oauth, "client_id", "") or "").strip()
)
def _require_fixed_provider(provider: Provider) -> str:
provider_type = (getattr(provider, "provider_type", "custom") or "custom").strip()
if provider_type == ProviderType.CUSTOM:
provider_type = str(getattr(provider, "provider_type", "custom") or "custom").strip().lower()
if not _get_fixed_template(provider_type):
raise InvalidRequestException("该 Provider 不是固定类型,无法使用 provider-oauth")
return provider_type
def _require_oauth_template(provider_type: str) -> Any:
template = _get_fixed_template(provider_type)
if not template:
raise InvalidRequestException("不支持的 provider_type")
if not _supports_oauth(template):
raise InvalidRequestException("该 Provider 不支持 OAuth 授权")
return template
def _resolve_proxy_for_oauth(
provider_proxy: dict[str, Any] | None,
proxy_node_id: str | None,
@@ -239,7 +268,7 @@ def _create_oauth_key(
api_formats: list[str],
flush_only: bool = False,
proxy: dict[str, Any] | None = None,
auto_fetch_models: bool = True,
auto_fetch_models: bool = False,
) -> "ProviderAPIKey":
"""创建 OAuth Key 记录并持久化。
@@ -247,7 +276,7 @@ def _create_oauth_key(
flush_only: True 时仅 flush批量导入场景False 时 commit + refresh。
proxy: Key 级别代理配置(如 {"node_id": "xxx", "enabled": True}
创建时设置后,后续 token 刷新、额度刷新等操作立即走代理,避免 IP 污染。
auto_fetch_models: 是否启用自动获取上游模型,非 custom 提供商默认开启
auto_fetch_models: 是否启用自动获取上游模型,默认关闭
"""
from src.models.database import ProviderAPIKey as ProviderAPIKeyModel
@@ -301,24 +330,6 @@ def _update_existing_oauth_key(
return existing_key
async def _trigger_auto_fetch_models(key_ids: list[str]) -> None:
"""为启用了 auto_fetch_models 的新建 Key 触发模型获取。"""
if not key_ids:
return
try:
from src.services.model.fetch_scheduler import get_model_fetch_scheduler
scheduler = get_model_fetch_scheduler()
for key_id in key_ids:
logger.info("[AUTO_FETCH] OAuth Key {} 默认开启自动获取模型,触发模型获取", key_id)
try:
await scheduler._fetch_models_for_key_by_id(key_id)
except Exception as e:
logger.error(f"[AUTO_FETCH] Key {key_id} 触发模型获取失败: {e}")
except Exception as e:
logger.error(f"[AUTO_FETCH] 获取 ModelFetchScheduler 失败: {e}")
async def _fetch_kiro_email(
auth_config: dict[str, Any],
proxy_config: dict[str, Any] | None = None,
@@ -517,6 +528,8 @@ async def supported_types(_: User = Depends(require_admin)) -> list[dict[str, An
# 不返回 client_secret
result: list[dict[str, Any]] = []
for provider_type, template in FIXED_PROVIDERS.items():
if not _supports_oauth(template):
continue
result.append(
{
"provider_type": (
@@ -553,12 +566,7 @@ async def start_oauth(
raise NotFoundException("Provider 不存在", "provider")
provider_type = _require_fixed_provider(provider)
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if not template:
raise InvalidRequestException("不支持的 provider_type")
template = _require_oauth_template(provider_type)
redis = await get_redis_client(require_redis=True)
assert redis is not None
@@ -646,12 +654,7 @@ async def complete_oauth(
raise NotFoundException("Provider 不存在", "provider")
provider_type = _require_fixed_provider(provider)
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if not template:
raise InvalidRequestException("不支持的 provider_type")
template = _require_oauth_template(provider_type)
# exchange token
token_url = template.oauth.token_url
@@ -815,12 +818,7 @@ async def refresh_oauth(
email=None,
)
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if not template:
raise InvalidRequestException("不支持的 provider_type")
template = _require_oauth_template(provider_type)
encrypted_auth_config = getattr(key, "auth_config", None)
if not encrypted_auth_config:
@@ -983,12 +981,7 @@ async def start_provider_oauth(
if provider_type == ProviderType.KIRO.value:
raise InvalidRequestException("Kiro 不支持 OAuth 授权,请使用导入授权。")
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if not template:
raise InvalidRequestException("不支持的 provider_type")
template = _require_oauth_template(provider_type)
redis = await get_redis_client(require_redis=True)
assert redis is not None
@@ -1073,12 +1066,7 @@ async def complete_provider_oauth(
if provider_type == ProviderType.KIRO.value:
raise InvalidRequestException("Kiro 不支持 OAuth 授权,请使用导入授权。")
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if not template:
raise InvalidRequestException("不支持的 provider_type")
template = _require_oauth_template(provider_type)
# exchange token
token_url = template.oauth.token_url
@@ -1190,9 +1178,6 @@ async def complete_provider_oauth(
proxy=key_proxy,
)
# 默认开启了 auto_fetch_models触发模型获取
await _trigger_auto_fetch_models([str(new_key.id)])
return ProviderCompleteOAuthResponse(
key_id=str(new_key.id),
provider_type=provider_type,
@@ -1441,9 +1426,6 @@ async def import_refresh_token(
proxy=key_proxy,
)
# 默认开启了 auto_fetch_models触发模型获取
await _trigger_auto_fetch_models([str(new_key.id)])
return ProviderCompleteOAuthResponse(
key_id=str(new_key.id),
provider_type=provider_type,
@@ -1453,12 +1435,7 @@ async def import_refresh_token(
replaced=replaced,
)
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if not template:
raise InvalidRequestException("不支持的 provider_type")
template = _require_oauth_template(provider_type)
# 用 refresh_token 换取 access_token
refresh_token = payload.refresh_token.strip()
@@ -1573,9 +1550,6 @@ async def import_refresh_token(
proxy=key_proxy,
)
# 默认开启了 auto_fetch_models触发模型获取
await _trigger_auto_fetch_models([str(new_key.id)])
return ProviderCompleteOAuthResponse(
key_id=str(new_key.id),
provider_type=provider_type,
@@ -1635,12 +1609,7 @@ async def batch_import_oauth(
)
# 标准 OAuth ProviderCodex、Antigravity、GeminiCli、ClaudeCode
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if not template:
raise InvalidRequestException(f"不支持的 provider_type: {provider_type}")
template = _require_oauth_template(provider_type)
# 解析 Token 列表
tokens = _parse_tokens_input(payload.credentials)
@@ -1860,11 +1829,6 @@ async def batch_import_oauth(
if success_count > 0:
db.commit()
# 批量导入完成后,触发所有成功 Key 的模型获取
success_key_ids = [r.key_id for r in results if r.status == "success" and r.key_id]
if success_key_ids:
await _trigger_auto_fetch_models(success_key_ids)
logger.info(
"[BATCH_IMPORT] Provider {} ({}): 成功 {}/{}, 失败 {}",
provider_id,
@@ -2014,11 +1978,6 @@ async def _batch_import_kiro_internal(
if success_count > 0:
db.commit()
# 批量导入完成后,触发所有成功 Key 的模型获取
success_key_ids = [r.key_id for r in results if r.status == "success" and r.key_id]
if success_key_ids:
await _trigger_auto_fetch_models(success_key_ids)
logger.info(
"[KIRO_BATCH_IMPORT] Provider {}: 成功 {}/{}, 失败 {}",
provider_id,
@@ -2427,8 +2386,6 @@ async def device_poll(
proxy=key_proxy,
)
await _trigger_auto_fetch_models([str(new_key.id)])
# 更新 Redis session 为已完成(短 TTL 让前端最后一次轮询能拿到结果)
session["status"] = "authorized"
session["key_id"] = str(new_key.id)

View File

@@ -882,6 +882,8 @@ async def test_model(
auth_type=auth_type,
provider_type=p_type if p_type else None,
decrypted_auth_config=oauth_meta if oauth_meta else None,
provider_endpoint=endpoint,
provider_api_key=api_key,
proxy_config=test_proxy,
)
@@ -903,12 +905,58 @@ async def test_model(
return True
return False
def _extract_error_message(resp: dict) -> str:
"""从 check 响应中提取错误信息(用于判断是否值得回退)。"""
resp_data = resp.get("response", {}) if isinstance(resp, dict) else {}
body = resp_data.get("response_body", {})
parsed = body
if isinstance(body, str):
try:
parsed = json.loads(body)
except (json.JSONDecodeError, ValueError):
parsed = body
if isinstance(parsed, dict):
err = parsed.get("error")
if isinstance(err, dict):
msg = err.get("message")
if isinstance(msg, str):
return msg
if isinstance(err, str):
return err
err_raw = resp.get("error")
if isinstance(err_raw, str):
return err_raw
if isinstance(err_raw, dict):
msg = err_raw.get("message")
if isinstance(msg, str):
return msg
return ""
def _should_fallback_to_non_stream(resp: dict) -> bool:
"""仅在“流式特有失败”时回退到非流式,避免 429/鉴权错误的无效重试。"""
status = int(resp.get("status_code") or 0)
if status in {404, 405, 415, 501}:
return True
if status == 400:
msg = _extract_error_message(resp).lower()
stream_markers = ("stream", "sse", "streamgeneratecontent")
unsupported_markers = ("not support", "unsupported", "invalid argument")
if any(k in msg for k in stream_markers) and any(
k in msg for k in unsupported_markers
):
return True
return False
# 策略:优先流式,若失败回退到非流式
used_stream = True
logger.debug("[test-model] 尝试流式请求...")
response = await _do_check(check_request)
if _response_has_error(response):
if _response_has_error(response) and _should_fallback_to_non_stream(response):
logger.info(
"[test-model] 流式请求失败 (status={}),回退到非流式请求",
response.get("status_code", "?"),
@@ -984,21 +1032,32 @@ async def test_model(
else:
logger.warning("[test-model] Key {} 因 403 verify 已标记为异常", api_key.id)
upstream_status = int(
response.get("status_code", 0) or error_obj.get("code", 0) or 500
)
if not (400 <= upstream_status <= 599):
upstream_status = 500
raise HTTPException(
status_code=500,
status_code=upstream_status,
detail=str(error_message)[:500] if error_message else "Provider error",
)
else:
logger.debug(f"[test-model] Error: {error_obj}")
# error_obj 可能是字符串,截断以避免泄露过多上游信息
upstream_status = int(response.get("status_code", 0) or 500)
if not (400 <= upstream_status <= 599):
upstream_status = 500
raise HTTPException(
status_code=500,
status_code=upstream_status,
detail=str(error_obj)[:500] if error_obj else "Provider error",
)
elif "error" in response:
logger.debug(f"[test-model] Error: {response['error']}")
upstream_status = int(response.get("status_code", 0) or 500)
if not (400 <= upstream_status <= 599):
upstream_status = 500
raise HTTPException(
status_code=500,
status_code=upstream_status,
detail=str(response["error"])[:500],
)
else:
@@ -1315,6 +1374,8 @@ async def test_model_failover(
auth_type=auth_type,
provider_type=p_type if p_type else None,
decrypted_auth_config=oauth_meta if oauth_meta else None,
provider_endpoint=endpoint,
provider_api_key=key,
proxy_config=effective_proxy,
)
@@ -1343,9 +1404,7 @@ async def test_model_failover(
if not error_msg and isinstance(parsed, dict) and "error" in parsed:
err_val = parsed["error"]
error_msg = str(
err_val.get("message", err_val)
if isinstance(err_val, dict)
else err_val
err_val.get("message", err_val) if isinstance(err_val, dict) else err_val
)[:300]
attempts.append(
TestAttemptDetail(

View File

@@ -48,6 +48,7 @@ def _should_enable_format_conversion_by_default(provider_type: str | None) -> bo
ProviderType.CLAUDE_CODE.value,
ProviderType.CODEX.value,
ProviderType.KIRO.value,
ProviderType.VERTEX_AI.value,
}
return pt in envelope_provider_types
@@ -56,6 +57,15 @@ def _normalize_provider_type(provider_type: str | None) -> str:
return (provider_type or "custom").strip().lower()
def _get_fixed_provider_template(provider_type: str | None) -> Any | None:
"""Return fixed-provider template when provider_type is managed by FIXED_PROVIDERS."""
normalized = _normalize_provider_type(provider_type)
try:
return FIXED_PROVIDERS.get(ProviderType(normalized))
except Exception:
return None
def _merge_pool_advanced_config(
*,
provider_config: dict[str, Any] | None,
@@ -458,33 +468,31 @@ class AdminCreateProviderAdapter(AdminApiAdapter):
db.flush() # flush 获取 ID但不提交保持在同一事务中
# 固定类型 Provider自动创建并锁定预置 Endpoints同一事务
provider_type = (provider.provider_type or "custom").strip()
if provider_type != ProviderType.CUSTOM:
try:
template = FIXED_PROVIDERS.get(ProviderType(provider_type))
except Exception:
template = None
if template:
now = datetime.now(timezone.utc)
for sig in template.endpoint_signatures:
endpoint = ProviderEndpoint(
id=str(uuid.uuid4()),
provider_id=provider.id,
api_format=sig,
api_family=sig.split(":", 1)[0],
endpoint_kind=sig.split(":", 1)[1],
base_url=template.api_base_url,
custom_path=None,
header_rules=None,
max_retries=provider.max_retries or 2,
is_active=True,
config=None,
proxy=None,
format_acceptance_config=None,
created_at=now,
updated_at=now,
)
db.add(endpoint)
template = _get_fixed_provider_template(provider.provider_type)
if template:
now = datetime.now(timezone.utc)
for sig in template.endpoint_signatures:
endpoint_config: dict[str, str] | None = None
if provider.provider_type == ProviderType.CODEX.value and sig == "openai:cli":
endpoint_config = {"upstream_stream_policy": "force_stream"}
endpoint = ProviderEndpoint(
id=str(uuid.uuid4()),
provider_id=provider.id,
api_format=sig,
api_family=sig.split(":", 1)[0],
endpoint_kind=sig.split(":", 1)[1],
base_url=template.api_base_url,
custom_path=None,
header_rules=None,
max_retries=provider.max_retries or 2,
is_active=True,
config=endpoint_config,
proxy=None,
format_acceptance_config=None,
created_at=now,
updated_at=now,
)
db.add(endpoint)
db.commit()
db.refresh(provider)

View File

@@ -1576,7 +1576,7 @@ async def _resolve_provider_auth(
if account_id:
auth_headers["chatgpt-account-id"] = str(account_id)
elif auth_type == "vertex_ai":
elif auth_type in ("service_account", "vertex_ai"):
from src.api.handlers.base.request_builder import get_provider_auth
auth_info = await get_provider_auth(endpoint, provider_key)

View File

@@ -13,7 +13,9 @@ from src.api.handlers.base.utils import get_format_converter_registry
from src.core.exceptions import ThinkingSignatureException, UpstreamClientException
from src.core.logger import logger
from src.models.database import ProviderAPIKey
from src.services.provider.transport import get_vertex_ai_effective_format
from src.services.provider.adapters.vertex_ai.transport import (
get_effective_format as get_vertex_ai_effective_format,
)
from src.services.scheduling.aware_scheduler import ProviderCandidate
@@ -23,7 +25,7 @@ def _get_error_status_code(e: Exception, default: int = 400) -> int:
return code if isinstance(code, int) and code > 0 else default
def _resolve_vertex_ai_format(
def _resolve_dynamic_format(
key: ProviderAPIKey,
auth_info: Any,
model: str,
@@ -32,9 +34,9 @@ def _resolve_vertex_ai_format(
candidate: ProviderCandidate | None,
) -> tuple[str, bool]:
"""
解析 Vertex AI 动态格式并计算 needs_conversion
解析动态格式并计算 needs_conversion
当 auth_type=vertex_ai 时,同一个 GCP 项目可以访问 Gemini 和 Claude
对于 Vertex AI 等跨格式 Provider同一个项目可以访问 Gemini 和 Claude
但它们的请求/响应格式不同,需要根据模型名动态选择。
用户可通过 auth_config.model_format_mapping 配置自定义映射。
@@ -49,9 +51,13 @@ def _resolve_vertex_ai_format(
Returns:
(effective_provider_format, needs_conversion) 元组
"""
key_auth_type = getattr(key, "auth_type", "api_key")
from src.core.provider_types import ProviderType
if key_auth_type == "vertex_ai":
# 判断是否为 Vertex AI provider基于 provider_type 而非 auth_type
provider = getattr(key, "provider", None)
provider_type = getattr(provider, "provider_type", None) if provider else None
if provider_type == ProviderType.VERTEX_AI:
vertex_auth_config = auth_info.decrypted_auth_config if auth_info else None
effective_format = get_vertex_ai_effective_format(model, vertex_auth_config)
if effective_format.upper() != provider_api_format.upper():

View File

@@ -41,7 +41,7 @@ from src.api.handlers.base.base_handler import (
from src.api.handlers.base.chat_error_utils import (
_build_error_json_payload,
_get_error_status_code,
_resolve_vertex_ai_format,
_resolve_dynamic_format,
)
from src.api.handlers.base.parsers import get_parser_for_format
from src.api.handlers.base.request_builder import PassthroughRequestBuilder, get_provider_auth
@@ -681,11 +681,11 @@ class ChatHandlerBase(BaseMessageHandler, ABC):
流式和非流式请求共享此逻辑,唯一差异是 client_is_stream 参数。
"""
# 提前获取认证信息(Vertex AI 格式判断需要使用 auth_config
# 提前获取认证信息(动态格式判断需要使用 auth_config
auth_info = await get_provider_auth(endpoint, key)
# 解析 Vertex AI 动态格式并计算 needs_conversion
provider_api_format, needs_conversion = _resolve_vertex_ai_format(
# 解析动态格式并计算 needs_conversionVertex AI 等跨格式 Provider
provider_api_format, needs_conversion = _resolve_dynamic_format(
key, auth_info, model, provider_api_format, client_api_format, candidate
)

View File

@@ -73,6 +73,7 @@ async def run_endpoint_check(
db: Any | None = None, # Session对象需要时才导入
user: Any | None = None, # User对象
proxy_config: dict[str, Any] | None = None, # 原始代理配置(支持 tunnel 模式)
is_stream: bool | None = None, # 显式流式标记(优先于 body/url 推断)
) -> dict[str, Any]:
"""
执行端点检查(重构版本,使用新的架构):
@@ -95,6 +96,7 @@ async def run_endpoint_check(
user=user,
request_id=str(uuid.uuid4())[:8],
proxy_config=proxy_config,
is_stream=is_stream,
)
# 使用协调器执行检查
@@ -567,6 +569,7 @@ class EndpointCheckRequest:
request_id: str | None = None
timeout: float = 30.0
proxy_config: dict[str, Any] | None = None # 原始代理配置(支持 tunnel 模式)
is_stream: bool | None = None # 显式流式标记(优先于 body/url 推断)
@dataclass
@@ -593,8 +596,22 @@ class HttpRequestExecutor:
start_time = time.time()
request_id = request.request_id or str(uuid.uuid4())[:8]
# 检查是否是流式请求
is_stream = request.json_body.get("stream", False) if request.json_body else False
# 检查是否是流式请求(优先显式参数,其次 body最后 URL 推断)
if request.is_stream is not None:
is_stream = bool(request.is_stream)
else:
is_stream = request.json_body.get("stream", False) if request.json_body else False
if not is_stream:
lowered_url = (request.url or "").lower()
if any(
marker in lowered_url
for marker in (
":streamgeneratecontent",
"/stream",
"stream=true",
)
):
is_stream = True
try:
from src.services.proxy_node.resolver import build_proxy_client_kwargs

View File

@@ -338,6 +338,8 @@ class HandlerAdapterBase(ApiAdapter):
auth_type: str | None = None,
provider_type: str | None = None,
decrypted_auth_config: dict[str, Any] | None = None,
provider_endpoint: Any | None = None,
provider_api_key: Any | None = None,
# 代理配置
proxy_config: dict[str, Any] | None = None,
) -> dict[str, Any]:
@@ -352,8 +354,10 @@ class HandlerAdapterBase(ApiAdapter):
from src.core.provider_types import ProviderType
is_antigravity = provider_type == ProviderType.ANTIGRAVITY
is_vertex = provider_type == ProviderType.VERTEX_AI
is_kiro = provider_type == ProviderType.KIRO
is_oauth = auth_type == "oauth"
vertex_auth_info: Any | None = None
# ---- URL ----
if is_kiro:
@@ -381,6 +385,28 @@ class HandlerAdapterBase(ApiAdapter):
effective_base_url = ordered_urls[0] if ordered_urls else base_url
path = V1INTERNAL_PATH_TEMPLATE.format(action="generateContent")
url = f"{str(effective_base_url).rstrip('/')}{path}"
elif is_vertex and provider_endpoint is not None and provider_api_key is not None:
from src.services.provider.auth import get_provider_auth
from src.services.provider.transport import build_provider_url
vertex_auth_info = await get_provider_auth(provider_endpoint, provider_api_key)
effective_auth_config = (
vertex_auth_info.decrypted_auth_config
if vertex_auth_info
else decrypted_auth_config
)
if effective_auth_config:
decrypted_auth_config = effective_auth_config
effective_model_name = model_name or request_data.get("model", "")
path_params = {"model": effective_model_name} if effective_model_name else None
url = build_provider_url(
provider_endpoint,
path_params=path_params,
is_stream=bool(request_data.get("stream", False)),
key=provider_api_key,
decrypted_auth_config=effective_auth_config,
)
else:
url = cls.build_endpoint_url(base_url, request_data, model_name)
@@ -412,15 +438,24 @@ class HandlerAdapterBase(ApiAdapter):
)
merged_extra.update(kiro_headers)
headers = cls.build_headers_with_extra(api_key, merged_extra if merged_extra else None)
if is_vertex and provider_endpoint is not None and provider_api_key is not None:
headers = dict(merged_extra)
if (
vertex_auth_info
and getattr(vertex_auth_info, "auth_header", None)
and getattr(vertex_auth_info, "auth_value", None)
):
headers[str(vertex_auth_info.auth_header)] = str(vertex_auth_info.auth_value)
else:
headers = cls.build_headers_with_extra(api_key, merged_extra if merged_extra else None)
if is_oauth:
from src.core.api_format import get_auth_config_for_endpoint
if is_oauth:
from src.core.api_format import get_auth_config_for_endpoint
default_auth_header, _ = get_auth_config_for_endpoint(cls.FORMAT_ID)
if default_auth_header.lower() != "authorization":
headers.pop(default_auth_header, None)
headers["Authorization"] = f"Bearer {api_key}"
default_auth_header, _ = get_auth_config_for_endpoint(cls.FORMAT_ID)
if default_auth_header.lower() != "authorization":
headers.pop(default_auth_header, None)
headers["Authorization"] = f"Bearer {api_key}"
# ---- Body ----
body = cls.build_request_body(request_data, base_url=base_url)
@@ -464,6 +499,8 @@ class HandlerAdapterBase(ApiAdapter):
else:
ep_auth_header, _ = _get_auth_cfg(cls.FORMAT_ID)
protected_keys = {ep_auth_header.lower(), "content-type"}
if vertex_auth_info and getattr(vertex_auth_info, "auth_header", None):
protected_keys.add(str(vertex_auth_info.auth_header).lower())
header_builder = HeaderBuilder()
header_builder.add_many(headers)
@@ -479,6 +516,7 @@ class HandlerAdapterBase(ApiAdapter):
headers=headers,
json_body=body,
api_format=cls.FORMAT_ID,
is_stream=bool(request_data.get("stream", False)),
db=db,
user=user,
provider_name=provider_name,

View File

@@ -296,6 +296,8 @@ class GeminiChatAdapter(ChatAdapterBase):
auth_type: str | None = None,
provider_type: str | None = None,
decrypted_auth_config: dict[str, Any] | None = None,
provider_endpoint: Any | None = None,
provider_api_key: Any | None = None,
# 代理配置
proxy_config: dict[str, Any] | None = None,
) -> dict[str, Any]:
@@ -313,7 +315,9 @@ class GeminiChatAdapter(ChatAdapterBase):
}
is_antigravity = provider_type and provider_type.lower() == "antigravity"
is_vertex = provider_type and provider_type.lower() == "vertex_ai"
is_oauth = auth_type == "oauth"
vertex_auth_info: Any | None = None
# Antigravity provider 使用 v1internal 路径,而非标准 Gemini API 路径
if is_antigravity:
@@ -327,6 +331,27 @@ class GeminiChatAdapter(ChatAdapterBase):
ag_base = ordered_urls[0] if ordered_urls else base_url
path = V1INTERNAL_PATH_TEMPLATE.format(action="generateContent")
url = f"{str(ag_base).rstrip('/')}{path}"
elif is_vertex and provider_endpoint is not None and provider_api_key is not None:
# Vertex AI: test-model 必须走统一 provider transport/auth
# 否则会错误命中普通 Gemini URL导致 404
from src.services.provider.auth import get_provider_auth
from src.services.provider.transport import build_provider_url
vertex_auth_info = await get_provider_auth(provider_endpoint, provider_api_key)
effective_auth_config = (
vertex_auth_info.decrypted_auth_config
if vertex_auth_info
else decrypted_auth_config
)
if effective_auth_config:
decrypted_auth_config = effective_auth_config
url = build_provider_url(
provider_endpoint,
path_params={"model": effective_model_name},
is_stream=bool(request_data.get("stream", False)),
key=provider_api_key,
decrypted_auth_config=effective_auth_config,
)
else:
# 使用基类配置方法但重写URL构建逻辑
base_url_resolved = cls.build_endpoint_url(base_url)
@@ -337,16 +362,25 @@ class GeminiChatAdapter(ChatAdapterBase):
merged_extra = dict(extra_headers) if extra_headers else {}
if is_antigravity:
merged_extra.update(get_v1internal_extra_headers())
headers = cls.build_headers_with_extra(api_key, merged_extra if merged_extra else None)
if is_vertex and provider_endpoint is not None and provider_api_key is not None:
headers = dict(merged_extra)
if (
vertex_auth_info
and getattr(vertex_auth_info, "auth_header", None)
and getattr(vertex_auth_info, "auth_value", None)
):
headers[str(vertex_auth_info.auth_header)] = str(vertex_auth_info.auth_value)
else:
headers = cls.build_headers_with_extra(api_key, merged_extra if merged_extra else None)
# OAuth 统一处理替换端点默认认证头x-goog-api-key为 Authorization: Bearer
if is_oauth:
from src.core.api_format import get_auth_config_for_endpoint
# OAuth 统一处理替换端点默认认证头x-goog-api-key为 Authorization: Bearer
if is_oauth:
from src.core.api_format import get_auth_config_for_endpoint
default_auth_header, _ = get_auth_config_for_endpoint(cls.FORMAT_ID)
if default_auth_header.lower() != "authorization":
headers.pop(default_auth_header, None)
headers["Authorization"] = f"Bearer {api_key}"
default_auth_header, _ = get_auth_config_for_endpoint(cls.FORMAT_ID)
if default_auth_header.lower() != "authorization":
headers.pop(default_auth_header, None)
headers["Authorization"] = f"Bearer {api_key}"
body = cls.build_request_body(request_data)
@@ -373,6 +407,8 @@ class GeminiChatAdapter(ChatAdapterBase):
auth_header, _ = get_auth_config_for_endpoint(cls.FORMAT_ID)
protected_keys = {auth_header.lower(), "content-type"}
if vertex_auth_info and getattr(vertex_auth_info, "auth_header", None):
protected_keys.add(str(vertex_auth_info.auth_header).lower())
header_builder = HeaderBuilder()
header_builder.add_many(headers)
@@ -385,6 +421,7 @@ class GeminiChatAdapter(ChatAdapterBase):
headers=headers,
json_body=body,
api_format=cls.FORMAT_ID,
is_stream=bool(request_data.get("stream", False)),
# 用量计算参数(现在强制记录)
db=db,
user=user,

View File

@@ -212,7 +212,7 @@ class GeminiVeoHandler(VideoHandlerBase):
task_type="video",
submit_func=_submit,
extract_external_task_id=_extract_task_id,
supported_auth_types={"api_key", "vertex_ai"},
supported_auth_types={"api_key", "service_account", "vertex_ai"},
allow_format_conversion=True,
max_candidates=10,
)

View File

@@ -198,7 +198,7 @@ class OpenAIVideoHandler(VideoHandlerBase):
task_type="video",
submit_func=_submit,
extract_external_task_id=_extract_task_id,
supported_auth_types={"api_key", "vertex_ai"},
supported_auth_types={"api_key", "service_account", "vertex_ai"},
allow_format_conversion=True,
max_candidates=10,
)

View File

@@ -72,7 +72,7 @@ FIXED_PROVIDERS: dict[ProviderType, FixedProviderTemplate] = {
provider_type=ProviderType.CODEX,
display_name="Codex",
api_base_url="https://chatgpt.com/backend-api/codex",
endpoint_signatures=["openai:cli"],
endpoint_signatures=["openai:cli", "openai:compact"],
oauth=FixedProviderOAuth(
authorize_url="https://auth.openai.com/oauth/authorize",
token_url="https://auth.openai.com/oauth/token",
@@ -121,6 +121,23 @@ FIXED_PROVIDERS: dict[ProviderType, FixedProviderTemplate] = {
use_pkce=False,
),
),
ProviderType.VERTEX_AI: FixedProviderTemplate(
provider_type=ProviderType.VERTEX_AI,
display_name="Vertex AI",
# Vertex uses fixed global base URL; concrete upstream path is selected by transport hook.
api_base_url="https://aiplatform.googleapis.com",
endpoint_signatures=["gemini:chat", "claude:chat"],
# Vertex does not use this OAuth flow (it uses API Key / Service Account).
oauth=FixedProviderOAuth(
authorize_url="",
token_url="",
client_id="",
client_secret="",
scopes=[],
redirect_uri="",
use_pkce=False,
),
),
ProviderType.ANTIGRAVITY: FixedProviderTemplate(
provider_type=ProviderType.ANTIGRAVITY,
display_name="Antigravity",

View File

@@ -21,6 +21,7 @@ class ProviderType(str, Enum):
CODEX = "codex"
GEMINI_CLI = "gemini_cli"
ANTIGRAVITY = "antigravity"
VERTEX_AI = "vertex_ai"
# 所有有效 provider_type 值的集合(用于校验)

View File

@@ -1550,19 +1550,19 @@ class ProviderAPIKey(ExportMixin, Base):
# 认证类型
# - "api_key": 标准 API Key 认证(默认)
# - "vertex_ai": Google Vertex AI 认证(Service Account JSON
# - 未来可扩展oauth2, azure_ad, aws_iam 等
# - "service_account": GCP Service Account JSON 认证
# - "oauth": OAuth access_token / refresh_token 认证
auth_type = Column(String(20), default="api_key", nullable=False)
# API密钥加密存储
# - auth_type="api_key" 时:存储 API Key 字符串
# - auth_type="vertex_ai" :可为,敏感凭证存在 auth_config 中
# - auth_type="service_account"/"oauth" :可为占位符,敏感凭证存在 auth_config 中
api_key = Column(Text, nullable=False) # 使用 Text 支持加密后的 OAuth token
# 认证配置(加密存储)
# - auth_type="api_key" 时:可为空
# - auth_type="vertex_ai" 时:存储加密后的 Service Account JSON
# - auth_type="oauth2" 时:存储加密后的 {client_id, client_secret, token_url, scope}
# - auth_type="service_account" 时:存储加密后的 Service Account JSON
# - auth_type="oauth" 时:存储加密后的 {refresh_token, expires_at, ...}
auth_config = Column(Text, nullable=True)
name = Column(String(100), nullable=False) # 密钥名称(必填,用于识别)
note = Column(String(500), nullable=True) # 备注说明(可选)

View File

@@ -261,7 +261,7 @@ class ProviderEndpointCreate(BaseModel):
api_format: str = Field(
...,
description=(
"Endpoint signature例如: claude:chat/claude:cli, openai:chat/openai:cli/openai:video, gemini:chat/gemini:cli/gemini:video"
"Endpoint signature例如: claude:chat/claude:cli, openai:chat/openai:cli/openai:compact/openai:video, gemini:chat/gemini:cli/gemini:video"
),
)
base_url: str = Field(..., min_length=1, max_length=500, description="API 基础 URL")
@@ -435,14 +435,14 @@ class EndpointAPIKeyCreate(BaseModel):
api_key: str = Field(
default="", max_length=10000, description="API Key标准认证时必填将自动加密"
)
auth_type: Literal["api_key", "vertex_ai", "oauth"] = Field(
auth_type: Literal["api_key", "service_account", "oauth"] = Field(
default="api_key",
description="认证类型api_key标准 API Key/ vertex_aiVertex AI Service Account/ oauthOAuth access_token",
description="认证类型api_key标准 API Key/ service_accountGCP Service Account/ oauthOAuth access_token",
)
auth_config: dict[str, Any] | None = Field(
default=None,
description=(
"认证配置JSONvertex_ai 时存储完整 Service Account JSON"
"认证配置JSONservice_account 时存储完整 Service Account JSON"
"oauth 时存储 token/refresh/expires_at 等(后端加密存储,不在响应中返回)"
),
)
@@ -590,14 +590,14 @@ class EndpointAPIKeyUpdate(BaseModel):
max_length=10000,
description="API Key标准认证时使用将自动加密",
)
auth_type: Literal["api_key", "vertex_ai", "oauth"] | None = Field(
auth_type: Literal["api_key", "service_account", "oauth"] | None = Field(
default=None,
description="认证类型api_key标准 API Key/ vertex_aiVertex AI Service Account/ oauthOAuth access_token",
description="认证类型api_key标准 API Key/ service_accountGCP Service Account/ oauthOAuth access_token",
)
auth_config: dict[str, Any] | None = Field(
default=None,
description=(
"认证配置JSONvertex_ai 时存储完整 Service Account JSON"
"认证配置JSONservice_account 时存储完整 Service Account JSON"
"oauth 时存储 token/refresh/expires_at 等(后端加密存储,不在响应中返回)"
),
)
@@ -719,7 +719,9 @@ class EndpointAPIKeyResponse(BaseModel):
# Key 信息(脱敏)
api_key_masked: str = Field(..., description="脱敏后的 Key")
api_key_plain: str | None = Field(default=None, description="完整的 Key")
auth_type: str = Field(default="api_key", description="认证类型api_key 或 vertex_ai")
auth_type: str = Field(
default="api_key", description="认证类型api_key / service_account / oauth"
)
# auth_config 不在响应中返回(包含敏感信息),前端通过 auth_type 判断类型
name: str = Field(..., description="密钥名称")

View File

@@ -408,13 +408,15 @@ class ModelFetchScheduler:
db.commit()
return "error"
# Vertex AI 类型不支持自动获取模型
# Service Account 类型不支持自动获取模型Vertex AI SA / 旧 vertex_ai auth_type
auth_type = getattr(key, "auth_type", "api_key") or "api_key"
if auth_type == "vertex_ai":
key.last_models_fetch_error = "auto_fetch_models 暂不支持 Vertex AI 类型的 Key"
if auth_type in ("service_account", "vertex_ai"):
key.last_models_fetch_error = (
"auto_fetch_models 暂不支持 Service Account 类型的 Key"
)
key.last_models_fetch_at = now
db.commit()
logger.info(f"Key {key.id}Vertex AI 类型,跳过自动获取模型")
logger.info(f"Key {key.id}Service Account 类型,跳过自动获取模型")
return "skip"
# 基础校验:必须有 api_keyOAuth: 加密 access_tokenAPI Key: 加密 key

View File

@@ -31,6 +31,7 @@ def build_antigravity_url(
*,
is_stream: bool,
effective_query_params: dict[str, Any],
**_kwargs: Any,
) -> str:
"""构建 Antigravity v1internal URL。

View File

@@ -16,6 +16,7 @@ def build_claude_code_url(
*,
is_stream: bool,
effective_query_params: dict[str, Any],
**_kwargs: Any,
) -> str:
"""Build Claude Code upstream URL and avoid duplicate /v1/messages suffix."""
_ = is_stream

View File

@@ -37,6 +37,7 @@ def build_codex_url(
*,
is_stream: bool,
effective_query_params: dict[str, Any],
**_kwargs: Any,
) -> str:
"""构建 Codex OAuth URL。
@@ -48,7 +49,8 @@ def build_codex_url(
from src.services.provider.adapters.codex.context import get_codex_request_context
ctx = get_codex_request_context()
is_compact = ctx.is_compact if ctx else False
endpoint_sig = str(getattr(endpoint, "api_format", "") or "").strip().lower()
is_compact = bool((ctx.is_compact if ctx else False) or endpoint_sig == "openai:compact")
base = str(endpoint.base_url).rstrip("/")
# 如果用户已在 base_url 中包含了 /responses不要重复追加
@@ -110,10 +112,12 @@ def register_all() -> None:
# Envelope
register_envelope("codex", "openai:cli", codex_oauth_envelope)
register_envelope("codex", "openai:compact", codex_oauth_envelope)
register_envelope("codex", "", codex_oauth_envelope)
# Transport
register_transport_hook("codex", "openai:cli", build_codex_url)
register_transport_hook("codex", "openai:compact", build_codex_url)
# Auth
register_auth_enricher("codex", enrich_codex)

View File

@@ -42,6 +42,7 @@ def build_kiro_url(
*,
is_stream: bool,
effective_query_params: dict[str, Any],
**_kwargs: Any,
) -> str:
"""Build Kiro generateAssistantResponse URL.

View File

@@ -0,0 +1,60 @@
"""Vertex AI 认证处理。
- Service Account: GCP SA JSON → JWT → Access Token → Bearer header
- API Key: 通过 URL ?key= 查询参数认证auth 层返回 None由 transport hook 处理)
"""
from __future__ import annotations
import json
from typing import Any
from src.core.provider_auth_types import ProviderAuthInfo
async def _auth_service_account(key: Any) -> ProviderAuthInfo:
"""Service Account 认证SA JSON → JWT → Access Token。"""
from src.core.crypto import crypto_service
from src.core.exceptions import InvalidRequestException
from src.core.vertex_auth import VertexAuthError, VertexAuthService
try:
# 优先从 auth_config 读取,兼容从 api_key 读取(过渡期)
encrypted_auth_config = getattr(key, "auth_config", None)
if encrypted_auth_config:
if isinstance(encrypted_auth_config, dict):
sa_json = encrypted_auth_config
else:
decrypted_config = crypto_service.decrypt(encrypted_auth_config)
sa_json = json.loads(decrypted_config)
else:
# 兼容旧数据:从 api_key 读取
decrypted_key = crypto_service.decrypt(key.api_key)
if decrypted_key == "__placeholder__":
raise InvalidRequestException("认证配置丢失,请重新添加该密钥。")
sa_json = json.loads(decrypted_key)
if not isinstance(sa_json, dict):
raise InvalidRequestException("Service Account JSON 无效,请重新添加该密钥。")
# 获取 Access Token注入代理配置
from src.services.proxy_node.resolver import build_proxy_client_kwargs
service = VertexAuthService(sa_json)
access_token = await service.get_access_token(
httpx_client_kwargs=build_proxy_client_kwargs(timeout=30),
)
return ProviderAuthInfo(
auth_header="Authorization",
auth_value=f"Bearer {access_token}",
decrypted_auth_config=sa_json,
)
except InvalidRequestException:
raise
except VertexAuthError as e:
raise InvalidRequestException(f"Vertex AI 认证失败:{e}")
except json.JSONDecodeError:
raise InvalidRequestException("Service Account JSON 格式无效,请重新添加该密钥。")
except Exception:
raise InvalidRequestException("Vertex AI 认证失败,请检查 Key 的 auth_config")

View File

@@ -0,0 +1,45 @@
"""Vertex AI 常量配置。
从 transport.py 迁移,集中管理 Vertex AI 模型格式映射和 region 配置。
"""
from __future__ import annotations
# Vertex AI 模型前缀到 API 格式的映射
# 用于 provider_type=vertex_ai 时,根据模型名动态确定实际的请求/响应格式
# 格式:前缀 -> endpoint signaturefamily:kind
MODEL_FORMAT_MAPPING: dict[str, str] = {
"claude-": "claude:chat", # Anthropic Claude 模型
"gemini-": "gemini:chat", # Google Gemini 模型
"imagen-": "gemini:chat", # Google Imagen 模型(使用 Gemini chat 格式)
}
# Vertex AI 默认 endpoint signature当模型前缀不匹配时
DEFAULT_FORMAT: str = "gemini:chat"
# Vertex AI 模型默认 region 映射
# 用户可以通过 auth_config.model_regions 覆盖
DEFAULT_MODEL_REGIONS: dict[str, str] = {
# Gemini 3 系列(使用 global
"gemini-3.1-pro-preview": "global",
"gemini-3-pro-image-preview": "global",
# Gemini 2.0 系列
"gemini-2.0-flash": "us-central1",
"gemini-2.0-flash-exp": "us-central1",
"gemini-2.0-flash-001": "us-central1",
"gemini-2.0-pro-exp": "us-central1",
"gemini-2.0-flash-exp-image-generation": "us-central1",
# Gemini 1.5 系列
"gemini-1.5-pro": "us-central1",
"gemini-1.5-pro-001": "us-central1",
"gemini-1.5-pro-002": "us-central1",
"gemini-1.5-flash": "us-central1",
"gemini-1.5-flash-001": "us-central1",
"gemini-1.5-flash-002": "us-central1",
# Imagen 系列
"imagen-3.0-generate-001": "us-central1",
"imagen-3.0-fast-generate-001": "us-central1",
}
# API Key 认证的全局端点
API_KEY_BASE_URL = "https://aiplatform.googleapis.com"

View File

@@ -0,0 +1,474 @@
"""Vertex AI provider plugin — 统一注册入口。
注册 Vertex AI 对各通用 registry 的 hooks
- Transport Hook (URL 构建,支持 API Key / Service Account 双策略)
- Model Fetcher (专用上游模型获取链路,不走通用 /v1beta/models / /v1/models)
- Behavior Variants (跨格式支持:同一 Provider 同时访问 Gemini 和 Claude 模型)
"""
from __future__ import annotations
from typing import Any
import httpx
from src.core.logger import logger
from src.core.vertex_auth import VertexAuthError, VertexAuthService
from src.services.provider.adapters.vertex_ai.transport import get_effective_format
# Vertex AI 公共 API 根
_VERTEX_API_BASE = "https://aiplatform.googleapis.com"
# Gemini Developer APIAPI Key 场景兜底)
_GEMINI_DEV_BASE = "https://generativelanguage.googleapis.com"
_MODEL_PAGE_SIZE = 100
_MODEL_MAX_PAGES = 20
def _normalize_extra_headers(raw: Any) -> dict[str, str]:
if not isinstance(raw, dict):
return {}
return {str(k): str(v) for k, v in raw.items() if k and v is not None}
def _looks_like_service_account(auth_config: dict[str, Any] | None) -> bool:
if not isinstance(auth_config, dict):
return False
return all(
isinstance(auth_config.get(k), str) and str(auth_config.get(k)).strip()
for k in ("client_email", "private_key", "project_id")
)
def _extract_model_id(raw_name: str) -> str:
name = str(raw_name or "").strip()
if not name:
return ""
if "/models/" in name:
return name.split("/models/", 1)[-1].strip()
if name.startswith("models/"):
return name.split("models/", 1)[-1].strip()
return name
def _extract_publisher(item: dict[str, Any], fallback: str | None = None) -> str | None:
publisher = item.get("publisher")
if isinstance(publisher, str) and publisher.strip():
return publisher.strip()
raw_name = item.get("name")
if isinstance(raw_name, str) and "/publishers/" in raw_name:
try:
after = raw_name.split("/publishers/", 1)[1]
candidate = after.split("/", 1)[0].strip()
if candidate:
return candidate
except Exception:
pass
return fallback
def _extract_items(data: Any) -> list[dict[str, Any]]:
if isinstance(data, list):
return [item for item in data if isinstance(item, dict)]
if not isinstance(data, dict):
return []
for key in ("publisherModels", "models", "data", "items"):
value = data.get(key)
if isinstance(value, list):
return [item for item in value if isinstance(item, dict)]
return []
def _parse_models_payload(
data: Any,
*,
auth_config: dict[str, Any] | None,
fallback_publisher: str | None = None,
) -> list[dict[str, Any]]:
models: list[dict[str, Any]] = []
for item in _extract_items(data):
raw_name = item.get("id") or item.get("name") or item.get("model")
if not isinstance(raw_name, str):
continue
model_id = _extract_model_id(raw_name)
if not model_id:
continue
display_name_raw = (
item.get("displayName") or item.get("display_name") or item.get("title") or model_id
)
display_name = (
str(display_name_raw).strip() if isinstance(display_name_raw, str) else model_id
)
if not display_name:
display_name = model_id
models.append(
{
"id": model_id,
"owned_by": _extract_publisher(item, fallback=fallback_publisher),
"display_name": display_name,
"api_format": get_effective_format(model_id, auth_config),
}
)
return models
def _build_google_publisher_list_url(base_url: str) -> str:
base = str(base_url or "").rstrip("/")
if not base:
base = _VERTEX_API_BASE
if base.endswith("/v1"):
return f"{base}/publishers/google/models"
if base.endswith("/v1beta"):
return f"{base}/publishers/google/models"
return f"{base}/v1/publishers/google/models"
def _iter_endpoint_base_urls(ctx: Any) -> list[str]:
seen: set[str] = set()
urls: list[str] = []
for cfg in (ctx.format_to_endpoint or {}).values():
base_url = str(getattr(cfg, "base_url", "") or "").strip()
if not base_url:
continue
norm = base_url.rstrip("/")
if norm in seen:
continue
seen.add(norm)
urls.append(norm)
if _VERTEX_API_BASE not in seen:
urls.append(_VERTEX_API_BASE)
return urls
def _get_endpoint_headers(ctx: Any, api_format: str) -> dict[str, str]:
cfg = (ctx.format_to_endpoint or {}).get(api_format)
return _normalize_extra_headers(getattr(cfg, "extra_headers", None))
def _dedupe_models(models: list[dict[str, Any]]) -> list[dict[str, Any]]:
seen: set[str] = set()
result: list[dict[str, Any]] = []
for model in models:
model_id = str(model.get("id", "")).strip()
api_format = str(model.get("api_format", "")).strip()
if not model_id:
continue
unique_key = f"{model_id}:{api_format}"
if unique_key in seen:
continue
seen.add(unique_key)
result.append(model)
return result
def _is_soft_not_found(error: str) -> bool:
return str(error).strip().startswith("HTTP 404:")
def _iter_regions(auth_config: dict[str, Any] | None) -> list[str]:
seen: set[str] = set()
regions: list[str] = []
def _add(raw: Any) -> None:
if not isinstance(raw, str):
return
region = raw.strip()
if not region or region in seen:
return
seen.add(region)
regions.append(region)
if isinstance(auth_config, dict):
_add(auth_config.get("region"))
model_regions = auth_config.get("model_regions")
if isinstance(model_regions, dict):
for region in model_regions.values():
_add(region)
_add("global")
_add("us-central1")
return regions
async def _fetch_models_from_url(
client: httpx.AsyncClient,
*,
url: str,
headers: dict[str, str],
params: dict[str, Any],
auth_config: dict[str, Any] | None,
fallback_publisher: str | None = None,
) -> tuple[list[dict[str, Any]], str | None, bool]:
all_models: list[dict[str, Any]] = []
next_page_token: str | None = None
has_success = False
for _ in range(_MODEL_MAX_PAGES):
req_params = dict(params)
if next_page_token:
req_params["pageToken"] = next_page_token
try:
resp = await client.get(url, headers=headers, params=req_params)
except httpx.TimeoutException:
return [], "timeout", has_success
except Exception as exc:
return [], f"request error: {exc}", has_success
if resp.status_code != 200:
body = resp.text[:500] if resp.text else "(empty)"
return [], f"HTTP {resp.status_code}: {body}", has_success
has_success = True
try:
payload = resp.json()
except Exception:
body = resp.text[:500] if resp.text else "(empty)"
return [], f"invalid json body: {body}", has_success
all_models.extend(
_parse_models_payload(
payload,
auth_config=auth_config,
fallback_publisher=fallback_publisher,
)
)
if not isinstance(payload, dict):
break
token = payload.get("nextPageToken")
next_page_token = str(token).strip() if isinstance(token, str) else None
if not next_page_token:
break
return all_models, None, has_success
async def _fetch_models_vertex_api_key(
client: httpx.AsyncClient,
*,
ctx: Any,
auth_config: dict[str, Any] | None,
) -> tuple[list[dict[str, Any]], list[str], bool]:
api_key = str(ctx.api_key_value or "").strip()
if not api_key or api_key == "__placeholder__":
return [], ["vertex_ai(api_key): missing api key"], False
all_models: list[dict[str, Any]] = []
hard_errors: list[str] = []
soft_errors: list[str] = []
has_success = False
endpoint_headers = _get_endpoint_headers(ctx, "gemini:chat")
vertex_list_urls = [
_build_google_publisher_list_url(base) for base in _iter_endpoint_base_urls(ctx)
]
# 1) Vertex API list (publisher=google)
for url in vertex_list_urls:
headers = {"Accept": "application/json", **endpoint_headers}
models, err, success = await _fetch_models_from_url(
client,
url=url,
headers=headers,
params={"key": api_key, "pageSize": _MODEL_PAGE_SIZE},
auth_config=auth_config,
fallback_publisher="google",
)
if success:
has_success = True
if err:
labeled = f"{url}: {err}"
if _is_soft_not_found(err):
soft_errors.append(labeled)
else:
hard_errors.append(labeled)
continue
all_models.extend(models)
# 2) 兜底Gemini Developer API
if not all_models:
fallback_url = f"{_GEMINI_DEV_BASE}/v1beta/models"
headers = {"Accept": "application/json", **endpoint_headers}
models, err, success = await _fetch_models_from_url(
client,
url=fallback_url,
headers=headers,
params={"key": api_key, "pageSize": _MODEL_PAGE_SIZE},
auth_config=auth_config,
fallback_publisher="google",
)
if success:
has_success = True
if err:
labeled = f"{fallback_url}: {err}"
if _is_soft_not_found(err):
soft_errors.append(labeled)
else:
hard_errors.append(labeled)
else:
all_models.extend(models)
deduped = _dedupe_models(all_models)
if deduped:
return deduped, hard_errors, has_success or True
if hard_errors:
return [], hard_errors, has_success
if soft_errors:
return [], [soft_errors[0]], has_success
return [], [], has_success
async def _fetch_models_vertex_service_account(
client: httpx.AsyncClient,
*,
ctx: Any,
auth_config: dict[str, Any] | None,
client_kwargs: dict[str, Any],
) -> tuple[list[dict[str, Any]], list[str], bool]:
if not isinstance(auth_config, dict):
return [], ["vertex_ai(service_account): missing auth_config"], False
try:
auth_service = VertexAuthService(auth_config)
access_token = await auth_service.get_access_token(httpx_client_kwargs=client_kwargs)
except VertexAuthError as exc:
return [], [f"vertex_ai(service_account): auth failed: {exc}"], False
except Exception as exc:
return [], [f"vertex_ai(service_account): auth failed: {exc}"], False
project_id = str(auth_config.get("project_id") or "").strip()
if not project_id:
return [], ["vertex_ai(service_account): missing project_id"], False
all_models: list[dict[str, Any]] = []
hard_errors: list[str] = []
soft_errors: list[str] = []
has_success = False
gemini_headers = {"Accept": "application/json", **_get_endpoint_headers(ctx, "gemini:chat")}
claude_headers = {"Accept": "application/json", **_get_endpoint_headers(ctx, "claude:chat")}
gemini_headers["Authorization"] = f"Bearer {access_token}"
claude_headers["Authorization"] = f"Bearer {access_token}"
for region in _iter_regions(auth_config):
base = (
_VERTEX_API_BASE
if region == "global"
else f"https://{region}-aiplatform.googleapis.com"
)
requests = [
(
"google",
f"{base}/v1/projects/{project_id}/locations/{region}/publishers/google/models",
gemini_headers,
),
(
"anthropic",
f"{base}/v1/projects/{project_id}/locations/{region}/publishers/anthropic/models",
claude_headers,
),
]
for publisher, url, headers in requests:
models, err, success = await _fetch_models_from_url(
client,
url=url,
headers=headers,
params={"pageSize": _MODEL_PAGE_SIZE},
auth_config=auth_config,
fallback_publisher=publisher,
)
if success:
has_success = True
if err:
labeled = f"{url}: {err}"
if _is_soft_not_found(err):
soft_errors.append(labeled)
else:
hard_errors.append(labeled)
continue
all_models.extend(models)
deduped = _dedupe_models(all_models)
if deduped:
return deduped, hard_errors, has_success or True
if hard_errors:
return [], hard_errors, has_success
if soft_errors:
return [], [soft_errors[0]], has_success
return [], [], has_success
async def fetch_models_vertex_ai(
ctx: Any,
timeout_seconds: float,
) -> tuple[list[dict], list[str], bool, dict[str, Any] | None]:
"""Vertex AI 专用模型获取链路。
- API Key: 优先请求 Vertex publisher models失败时兜底 Gemini Developer API
- Service Account: 使用 SA 凭证换取 Bearer Token按 region + publisher 查询
"""
from src.services.proxy_node.resolver import build_proxy_client_kwargs
auth_config = ctx.auth_config if isinstance(ctx.auth_config, dict) else None
is_service_account = _looks_like_service_account(auth_config)
client_kwargs = build_proxy_client_kwargs(ctx.proxy_config, timeout=timeout_seconds)
async with httpx.AsyncClient(**client_kwargs) as client:
if is_service_account:
models, errors, has_success = await _fetch_models_vertex_service_account(
client,
ctx=ctx,
auth_config=auth_config,
client_kwargs=client_kwargs,
)
else:
models, errors, has_success = await _fetch_models_vertex_api_key(
client,
ctx=ctx,
auth_config=auth_config,
)
if not models and errors:
logger.warning("Vertex 模型获取失败: {}", "; ".join(errors))
return models, errors, has_success, None
def register_all() -> None:
"""一次性注册 Vertex AI 的所有 hooks 到各通用 registry。"""
from src.services.model.upstream_fetcher import UpstreamModelsFetcherRegistry
from src.services.provider.adapters.vertex_ai.transport import build_vertex_ai_url
from src.services.provider.behavior import register_behavior_variant
from src.services.provider.transport import register_transport_hook
# Transport: Vertex AI 同时支持 gemini:chat 和 claude:chat 格式
register_transport_hook("vertex_ai", "gemini:chat", build_vertex_ai_url)
register_transport_hook("vertex_ai", "claude:chat", build_vertex_ai_url)
# Model Fetcher: Vertex 走专用模型获取链路
UpstreamModelsFetcherRegistry.register(
provider_types=["vertex_ai"],
fetcher=fetch_models_vertex_ai,
)
# Behavior: 跨格式支持(同一 Vertex AI Provider 可同时访问 Gemini 和 Claude 模型)
register_behavior_variant("vertex_ai", cross_format=True)
__all__ = ["fetch_models_vertex_ai", "register_all"]

View File

@@ -0,0 +1,263 @@
"""Vertex AI URL 构建Transport Hook
根据 auth_type 选择两种完全不同的 URL 构建策略:
- API Key: 全局端点,简化路径
https://aiplatform.googleapis.com/v1/publishers/google/models/{model}:{action}?key={API_KEY}
- Service Account: 区域端点,完整路径
https://{region}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{region}/publishers/{publisher}/models/{model}:{action}
"""
from __future__ import annotations
import json
from typing import Any
from urllib.parse import urlencode
from src.core.logger import logger
from src.services.provider.adapters.vertex_ai.constants import (
API_KEY_BASE_URL,
DEFAULT_FORMAT,
DEFAULT_MODEL_REGIONS,
MODEL_FORMAT_MAPPING,
)
from src.services.provider.format import normalize_endpoint_signature
from src.services.provider.transport import redact_url_for_log
def get_effective_format(
model: str,
auth_config: dict[str, Any] | None = None,
) -> str:
"""获取 Vertex AI 模式下模型的实际 API 格式。
优先级:
1. auth_config.model_format_mapping 中的精确匹配
2. auth_config.model_format_mapping 中的前缀匹配
3. 内置 MODEL_FORMAT_MAPPING 前缀匹配
4. auth_config.default_format
5. 内置 DEFAULT_FORMAT
"""
user_format_mapping: dict[str, str] = {}
user_default_format: str | None = None
if auth_config:
user_format_mapping = auth_config.get("model_format_mapping", {})
user_default_format = auth_config.get("default_format")
# 1. 用户配置:精确匹配
if model in user_format_mapping:
try:
return normalize_endpoint_signature(user_format_mapping[model])
except Exception:
logger.warning(
"Invalid vertex_ai model_format_mapping value for model '{}': {!r}",
model,
user_format_mapping[model],
)
# 2. 用户配置:前缀匹配
for prefix, api_format in user_format_mapping.items():
if prefix.endswith("-") and model.startswith(prefix):
try:
return normalize_endpoint_signature(api_format)
except Exception:
logger.warning(
"Invalid vertex_ai model_format_mapping value for prefix '{}': {!r}",
prefix,
api_format,
)
break
# 3. 内置配置:前缀匹配
for prefix, api_format in MODEL_FORMAT_MAPPING.items():
if model.startswith(prefix):
return normalize_endpoint_signature(api_format)
# 4. 用户默认格式
if user_default_format:
try:
return normalize_endpoint_signature(user_default_format)
except Exception:
logger.warning("Invalid vertex_ai default_format: {!r}", user_default_format)
# 5. 内置默认格式
return DEFAULT_FORMAT
def build_vertex_ai_url(
endpoint: Any,
*,
is_stream: bool,
effective_query_params: dict[str, Any],
path_params: dict[str, Any] | None = None,
key: Any = None,
decrypted_auth_config: dict[str, Any] | None = None,
) -> str:
"""Vertex AI transport hook — 统一 URL 构建入口。
根据 key.auth_type 分派到 API Key 或 Service Account 两种策略。
"""
auth_type = getattr(key, "auth_type", "api_key") if key else "api_key"
if auth_type == "api_key":
return _build_api_key_url(
key=key,
path_params=path_params,
query_params=effective_query_params,
is_stream=is_stream,
)
else:
# service_account以及向后兼容旧的 "vertex_ai" auth_type
return _build_service_account_url(
key=key,
path_params=path_params,
query_params=effective_query_params,
is_stream=is_stream,
decrypted_auth_config=decrypted_auth_config,
)
def _build_api_key_url(
key: Any,
*,
path_params: dict[str, Any] | None = None,
query_params: dict[str, Any] | None = None,
is_stream: bool = False,
) -> str:
"""构建 API Key 认证的全局端点 URL。
格式: https://aiplatform.googleapis.com/v1/publishers/google/models/{model}:{action}?key={API_KEY}
"""
from src.core.crypto import crypto_service
from src.core.exceptions import InvalidRequestException
model = (path_params or {}).get("model", "")
if not model:
raise InvalidRequestException("Vertex AI 请求缺少 model 参数")
if str(model).startswith("claude-"):
raise InvalidRequestException(
"Vertex API Key 不支持 Claude 模型,请改用 Service Account 认证。"
)
action = "streamGenerateContent" if is_stream else "generateContent"
path = f"/v1/publishers/google/models/{model}:{action}"
url = f"{API_KEY_BASE_URL}{path}"
# 构建查询参数
params = dict(query_params) if query_params else {}
# 附加 API Key
api_key_value = crypto_service.decrypt(key.api_key) if key else ""
if api_key_value:
params["key"] = api_key_value
# Gemini 流式请求使用 SSE
if is_stream:
params.setdefault("alt", "sse")
params.pop("beta", None)
if params:
query_string = urlencode(params, doseq=True)
if query_string:
url = f"{url}?{query_string}"
logger.debug("Vertex AI (API Key) URL: {}", redact_url_for_log(url))
return url
def _build_service_account_url(
key: Any,
*,
path_params: dict[str, Any] | None = None,
query_params: dict[str, Any] | None = None,
is_stream: bool = False,
decrypted_auth_config: dict[str, Any] | None = None,
) -> str:
"""构建 Service Account 认证的区域端点 URL。
格式: https://{region}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{region}/publishers/{publisher}/models/{model}:{action}
"""
from src.core.crypto import crypto_service
from src.core.exceptions import InvalidRequestException
# 优先使用传入的已解密配置,避免重复解密
auth_config: dict[str, Any] = {}
if decrypted_auth_config:
auth_config = decrypted_auth_config
else:
# 兜底:从 key.auth_config 解密(理论上不应走到这里)
raw_auth_config = getattr(key, "auth_config", None) if key else None
if raw_auth_config:
try:
if isinstance(raw_auth_config, dict):
auth_config = raw_auth_config
else:
decrypted_config = crypto_service.decrypt(raw_auth_config)
auth_config = json.loads(decrypted_config)
except Exception as e:
logger.error("解密 Vertex AI auth_config 失败: {}", e)
auth_config = {}
# 获取必需的配置
project_id = auth_config.get("project_id")
if not project_id:
raise InvalidRequestException(
"Vertex AI 配置缺少 project_id请在 Key 的 auth_config 中提供)"
)
# 获取模型名
model = (path_params or {}).get("model", "")
if not model:
raise InvalidRequestException("Vertex AI 请求缺少 model 参数")
# 确定 region优先级用户配置 > 内置默认 > 用户默认 > 兜底)
user_model_regions = auth_config.get("model_regions", {})
user_default_region = auth_config.get("region")
if model in user_model_regions:
region = user_model_regions[model]
elif model in DEFAULT_MODEL_REGIONS:
region = DEFAULT_MODEL_REGIONS[model]
elif user_default_region:
region = user_default_region
else:
region = "global"
# 判断是 Claude 还是 Gemini 模型
is_claude_model = model.startswith("claude-")
# 根据模型类型确定 publisher 和 action
if is_claude_model:
publisher = "anthropic"
action = "streamRawPredict" if is_stream else "rawPredict"
else:
publisher = "google"
action = "streamGenerateContent" if is_stream else "generateContent"
# 构建 URLglobal region 使用不同的 URL 格式)
if region == "global":
base_url = "https://aiplatform.googleapis.com"
else:
base_url = f"https://{region}-aiplatform.googleapis.com"
path = f"/v1/projects/{project_id}/locations/{region}/publishers/{publisher}/models/{model}:{action}"
url = f"{base_url}{path}"
# 添加查询参数
effective_query_params = dict(query_params) if query_params else {}
# Gemini 流式请求使用 SSE 格式Claude 不需要
if is_stream and not is_claude_model:
effective_query_params.setdefault("alt", "sse")
# 移除不适用于 Vertex AI 的参数
effective_query_params.pop("beta", None)
if effective_query_params:
query_string = urlencode(effective_query_params, doseq=True)
if query_string:
url = f"{url}?{query_string}"
logger.debug("Vertex AI (SA) URL: {} (region={})", redact_url_for_log(url), region)
return url

View File

@@ -393,58 +393,12 @@ async def get_provider_auth(
auth_value=f"Bearer {effective_token}",
decrypted_auth_config=decrypted_auth_config,
)
if auth_type == "vertex_ai":
from src.core.vertex_auth import VertexAuthError, VertexAuthService
if auth_type in ("service_account", "vertex_ai"):
# service_account: GCP Service Account JSON → JWT → Access Token
# "vertex_ai" 保留为向后兼容(迁移期间旧数据可能仍使用该值)
from src.services.provider.adapters.vertex_ai.auth import _auth_service_account
try:
# 优先从 auth_config 读取,兼容从 api_key 读取(过渡期)
encrypted_auth_config = getattr(key, "auth_config", None)
if encrypted_auth_config:
# auth_config 可能是加密字符串或未加密的 dict
if isinstance(encrypted_auth_config, dict):
# 已经是 dict直接使用兼容未加密存储的情况
sa_json = encrypted_auth_config
else:
# 是加密字符串,需要解密
decrypted_config = crypto_service.decrypt(encrypted_auth_config)
sa_json = json.loads(decrypted_config)
else:
# 兼容旧数据:从 api_key 读取
decrypted_key = crypto_service.decrypt(key.api_key)
# 检查是否是占位符(表示 auth_config 丢失)
if decrypted_key == "__placeholder__":
raise InvalidRequestException("认证配置丢失,请重新添加该密钥。")
sa_json = json.loads(decrypted_key)
if not isinstance(sa_json, dict):
raise InvalidRequestException("Service Account JSON 无效,请重新添加该密钥。")
# 获取 Access Token注入代理配置core 层不依赖 services
from src.services.proxy_node.resolver import build_proxy_client_kwargs
service = VertexAuthService(sa_json)
access_token = await service.get_access_token(
httpx_client_kwargs=build_proxy_client_kwargs(timeout=30),
)
# Vertex AI 使用 Bearer token
return ProviderAuthInfo(
auth_header="Authorization",
auth_value=f"Bearer {access_token}",
decrypted_auth_config=sa_json,
)
except InvalidRequestException:
raise
except VertexAuthError as e:
raise InvalidRequestException(f"Vertex AI 认证失败:{e}")
except json.JSONDecodeError:
raise InvalidRequestException("Service Account JSON 格式无效,请重新添加该密钥。")
except Exception:
raise InvalidRequestException("Vertex AI 认证失败,请检查 Key 的 auth_config")
# 其他认证类型可在此扩展
# elif auth_type == "oauth2":
# ...
return await _auth_service_account(key)
# 标准 API Key返回 None由 build_headers 处理
return None

View File

@@ -157,11 +157,13 @@ def ensure_providers_bootstrapped() -> None:
)
from src.services.provider.adapters.codex.plugin import register_all as _reg_codex
from src.services.provider.adapters.kiro.plugin import register_all as _reg_kiro
from src.services.provider.adapters.vertex_ai.plugin import register_all as _reg_vertex_ai
_reg_antigravity()
_reg_claude_code()
_reg_codex()
_reg_kiro()
_reg_vertex_ai()
__all__ = [

View File

@@ -4,7 +4,7 @@
负责:
- 根据 API 格式或端点配置生成请求 URL
- URL 脱敏(用于日志记录)
- Vertex AI URL 自动构建
- Provider transport hook 路由
"""
from __future__ import annotations
@@ -154,7 +154,7 @@ def build_provider_url(
根据 endpoint 配置生成请求 URL
优先级:
1. Vertex AI 自动构建 - 当 key.auth_type == "vertex_ai"
1. Provider transport hook - 如有注册的 hook 则委托处理
2. endpoint.custom_path - 自定义路径(支持模板变量如 {model}
3. API 格式默认路径 - 根据 api_format 自动选择
@@ -169,17 +169,6 @@ def build_provider_url(
# 默认清理,避免上一次请求的 selected_base_url 泄漏到其他请求
set_selected_base_url(None)
# 检查是否为 Vertex AI 认证类型
auth_type = getattr(key, "auth_type", "api_key") if key else "api_key"
if auth_type == "vertex_ai":
return _build_vertex_ai_url(
key=key,
path_params=path_params,
query_params=query_params,
is_stream=is_stream,
decrypted_auth_config=decrypted_auth_config,
)
# endpoint signature新模式
raw_family = getattr(endpoint, "api_family", None)
raw_kind = getattr(endpoint, "endpoint_kind", None)
@@ -217,6 +206,9 @@ def build_provider_url(
endpoint,
is_stream=is_stream,
effective_query_params=effective_query_params,
path_params=path_params,
key=key,
decrypted_auth_config=decrypted_auth_config,
)
# 非 hook 路径:清除 contextvar避免跨请求污染
@@ -248,8 +240,8 @@ def build_provider_url(
path = _resolve_default_path(endpoint_sig)
# Codex OAuth 端点chatgpt.com/backend-api/codex使用 /responses 而非 /v1/responses
base_url = getattr(endpoint, "base_url", "") or ""
if endpoint_sig == "openai:cli" and is_codex_url(base_url):
path = "/responses"
if endpoint_sig in {"openai:cli", "openai:compact"} and is_codex_url(base_url):
path = "/responses/compact" if endpoint_sig == "openai:compact" else "/responses"
if effective_path_params:
try:
path = path.format(**effective_path_params)
@@ -286,248 +278,3 @@ def _resolve_default_path(endpoint_sig: str | None) -> str:
except Exception:
logger.warning(f"Unknown endpoint signature '{endpoint_sig}' for endpoint, fallback to '/'")
return "/"
# ==============================================================================
# Vertex AI 配置
# ==============================================================================
# Vertex AI 模型前缀到 API 格式的映射
# 用于 auth_type=vertex_ai 时,根据模型名动态确定实际的请求/响应格式
# 格式:前缀 -> endpoint signaturefamily:kind
VERTEX_AI_MODEL_FORMAT_MAPPING: dict[str, str] = {
"claude-": "claude:chat", # Anthropic Claude 模型
"gemini-": "gemini:chat", # Google Gemini 模型
"imagen-": "gemini:chat", # Google Imagen 模型(使用 Gemini chat 格式)
}
# Vertex AI 默认 endpoint signature当模型前缀不匹配时
VERTEX_AI_DEFAULT_FORMAT: str = "gemini:chat"
def get_vertex_ai_effective_format(
model: str,
auth_config: dict[str, Any] | None = None,
) -> str:
"""
获取 Vertex AI 模式下模型的实际 API 格式
优先级:
1. auth_config.model_format_mapping 中的精确匹配
2. auth_config.model_format_mapping 中的前缀匹配
3. 内置 VERTEX_AI_MODEL_FORMAT_MAPPING 前缀匹配
4. auth_config.default_format
5. 内置 VERTEX_AI_DEFAULT_FORMAT
auth_config 配置示例::
{
"project_id": "your-gcp-project-id",
"model_format_mapping": {
"claude-": "CLAUDE", # 前缀匹配
"my-custom-model": "OPENAI" # 精确匹配
},
"default_format": "GEMINI"
}
Args:
model: 模型名称
auth_config: 解密后的认证配置(可选),可包含 model_format_mapping 和 default_format
Returns:
实际应使用的 endpoint signature"claude:chat", "gemini:chat"
"""
# 用户配置的模型-格式映射
user_format_mapping: dict[str, str] = {}
user_default_format: str | None = None
if auth_config:
user_format_mapping = auth_config.get("model_format_mapping", {})
user_default_format = auth_config.get("default_format")
# 1. 用户配置:精确匹配
if model in user_format_mapping:
try:
return normalize_endpoint_signature(user_format_mapping[model])
except Exception:
logger.warning(
"Invalid vertex_ai model_format_mapping value for model '{}': {!r}",
model,
user_format_mapping[model],
)
# 2. 用户配置:前缀匹配
for prefix, api_format in user_format_mapping.items():
if prefix.endswith("-") and model.startswith(prefix):
try:
return normalize_endpoint_signature(api_format)
except Exception:
logger.warning(
"Invalid vertex_ai model_format_mapping value for prefix '{}': {!r}",
prefix,
api_format,
)
break
# 3. 内置配置:前缀匹配
for prefix, api_format in VERTEX_AI_MODEL_FORMAT_MAPPING.items():
if model.startswith(prefix):
return normalize_endpoint_signature(api_format)
# 4. 用户默认格式
if user_default_format:
try:
return normalize_endpoint_signature(user_default_format)
except Exception:
logger.warning("Invalid vertex_ai default_format: {!r}", user_default_format)
# 5. 内置默认格式
return VERTEX_AI_DEFAULT_FORMAT
# Vertex AI 模型默认 region 映射
# 用户可以通过 auth_config.model_regions 覆盖
VERTEX_AI_DEFAULT_MODEL_REGIONS: dict[str, str] = {
# Gemini 3 系列(使用 global
"gemini-3-pro-image-preview": "global",
# Gemini 2.0 系列
"gemini-2.0-flash": "us-central1",
"gemini-2.0-flash-exp": "us-central1",
"gemini-2.0-flash-001": "us-central1",
"gemini-2.0-pro-exp": "us-central1",
"gemini-2.0-flash-exp-image-generation": "us-central1",
# Gemini 1.5 系列
"gemini-1.5-pro": "us-central1",
"gemini-1.5-pro-001": "us-central1",
"gemini-1.5-pro-002": "us-central1",
"gemini-1.5-flash": "us-central1",
"gemini-1.5-flash-001": "us-central1",
"gemini-1.5-flash-002": "us-central1",
# Imagen 系列
"imagen-3.0-generate-001": "us-central1",
"imagen-3.0-fast-generate-001": "us-central1",
}
def _build_vertex_ai_url(
key: "ProviderAPIKey",
*,
path_params: dict[str, Any] | None = None,
query_params: dict[str, Any] | None = None,
is_stream: bool = False,
decrypted_auth_config: dict[str, Any] | None = None,
) -> str:
"""
构建 Vertex AI URL
Vertex AI URL 格式:
- Gemini: https://{region}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{region}/publishers/google/models/{model}:{action}
- Claude: https://{region}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{region}/publishers/anthropic/models/{model}:{action}
从 auth_config 中读取:
- project_id: GCP 项目 ID必需
- region: 默认 GCP 区域(覆盖内置默认值)
- model_regions: 模型到区域的映射(可选),覆盖内置和默认配置
Region 优先级:
1. auth_config.model_regions[model] - 用户为该模型指定的区域
2. VERTEX_AI_DEFAULT_MODEL_REGIONS[model] - 内置的模型默认区域
3. auth_config.region - 用户配置的默认区域
4. global - 最终兜底
Args:
key: Provider API Key包含 auth_config
path_params: 路径参数(需要 model
query_params: 查询参数
is_stream: 是否为流式请求
decrypted_auth_config: 已解密的认证配置(由 get_provider_auth 提供,避免重复解密)
Returns:
完整的 Vertex AI URL
"""
import json
from src.core.crypto import crypto_service
# 优先使用传入的已解密配置,避免重复解密
auth_config: dict[str, Any] = {}
if decrypted_auth_config:
auth_config = decrypted_auth_config
else:
# 兜底:从 key.auth_config 解密(理论上不应走到这里)
raw_auth_config = getattr(key, "auth_config", None)
if raw_auth_config:
try:
# auth_config 可能是加密字符串或未加密的 dict
if isinstance(raw_auth_config, dict):
auth_config = raw_auth_config
else:
decrypted_config = crypto_service.decrypt(raw_auth_config)
auth_config = json.loads(decrypted_config)
except Exception as e:
logger.error(f"解密 Vertex AI auth_config 失败: {e}")
auth_config = {}
from src.core.exceptions import InvalidRequestException
# 获取必需的配置
project_id = auth_config.get("project_id")
if not project_id:
raise InvalidRequestException(
"Vertex AI 配置缺少 project_id请在 Key 的 auth_config 中提供)"
)
# 获取模型名
model = (path_params or {}).get("model", "")
if not model:
raise InvalidRequestException("Vertex AI 请求缺少 model 参数")
# 确定 region优先级用户配置 > 内置默认 > 用户默认 > 兜底)
user_model_regions = auth_config.get("model_regions", {})
user_default_region = auth_config.get("region")
if model in user_model_regions:
region = user_model_regions[model]
elif model in VERTEX_AI_DEFAULT_MODEL_REGIONS:
region = VERTEX_AI_DEFAULT_MODEL_REGIONS[model]
elif user_default_region:
region = user_default_region
else:
region = "global"
# 判断是 Claude 还是 Gemini 模型
is_claude_model = model.startswith("claude-")
# 根据模型类型确定 publisher 和 action
if is_claude_model:
# Claude 模型使用 Anthropic publisher
publisher = "anthropic"
action = "streamRawPredict" if is_stream else "rawPredict"
else:
# Gemini 模型使用 Google publisher
publisher = "google"
action = "streamGenerateContent" if is_stream else "generateContent"
# 构建 URLglobal region 使用不同的 URL 格式)
if region == "global":
base_url = "https://aiplatform.googleapis.com"
else:
base_url = f"https://{region}-aiplatform.googleapis.com"
path = f"/v1/projects/{project_id}/locations/{region}/publishers/{publisher}/models/{model}:{action}"
url = f"{base_url}{path}"
# 添加查询参数
effective_query_params = dict(query_params) if query_params else {}
# Gemini 流式请求使用 SSE 格式Claude 不需要
if is_stream and not is_claude_model:
effective_query_params.setdefault("alt", "sse")
# 移除不适用于 Vertex AI 的参数
effective_query_params.pop("beta", None)
if effective_query_params:
query_string = urlencode(effective_query_params, doseq=True)
if query_string:
url = f"{url}?{query_string}"
logger.debug(f"Vertex AI URL: {redact_url_for_log(url)} (region={region})")
return url

View File

@@ -0,0 +1,150 @@
from __future__ import annotations
from unittest.mock import AsyncMock, patch
import pytest
from src.core.vertex_auth import VertexAuthService
from src.services.model.upstream_fetcher import (
EndpointFetchConfig,
UpstreamModelsFetchContext,
fetch_models_for_key,
)
@pytest.mark.asyncio
async def test_fetch_models_for_key_vertex_api_key_custom_fetcher() -> None:
ctx = UpstreamModelsFetchContext(
provider_type="vertex_ai",
api_key_value="test-api-key",
format_to_endpoint={
"gemini:chat": EndpointFetchConfig(base_url="https://aiplatform.googleapis.com"),
},
proxy_config=None,
auth_config={},
)
mocked_models = [
{
"id": "gemini-2.5-pro",
"owned_by": "google",
"display_name": "Gemini 2.5 Pro",
"api_format": "gemini:chat",
}
]
with (
patch(
"src.services.provider.adapters.vertex_ai.plugin._fetch_models_from_url",
AsyncMock(return_value=(mocked_models, None, True)),
),
patch(
"src.services.proxy_node.resolver.build_proxy_client_kwargs",
return_value={"timeout": 1.0},
),
):
models, errors, ok, meta = await fetch_models_for_key(ctx, timeout_seconds=1.0)
assert ok is True
assert errors == []
assert meta is None
assert [m.get("id") for m in models] == ["gemini-2.5-pro"]
@pytest.mark.asyncio
async def test_fetch_models_for_key_vertex_service_account_ignores_soft_404_when_success() -> None:
auth_config = {
"project_id": "demo-project",
"client_email": "svc@example.iam.gserviceaccount.com",
"private_key": "-----BEGIN PRIVATE KEY-----\nTEST\n-----END PRIVATE KEY-----\n",
"region": "global",
}
ctx = UpstreamModelsFetchContext(
provider_type="vertex_ai",
api_key_value="__placeholder__",
format_to_endpoint={
"gemini:chat": EndpointFetchConfig(base_url="https://aiplatform.googleapis.com"),
"claude:chat": EndpointFetchConfig(base_url="https://aiplatform.googleapis.com"),
},
proxy_config=None,
auth_config=auth_config,
)
fetch_side_effect = [
(
[
{
"id": "gemini-2.0-flash",
"owned_by": "google",
"display_name": "Gemini 2.0 Flash",
"api_format": "gemini:chat",
}
],
None,
True,
),
([], "HTTP 404: not found", False),
]
with (
patch.object(
VertexAuthService,
"get_access_token",
AsyncMock(return_value="ya29.test-token"),
),
patch(
"src.services.provider.adapters.vertex_ai.plugin._iter_regions",
return_value=["global"],
),
patch(
"src.services.provider.adapters.vertex_ai.plugin._fetch_models_from_url",
AsyncMock(side_effect=fetch_side_effect),
),
patch(
"src.services.proxy_node.resolver.build_proxy_client_kwargs",
return_value={"timeout": 1.0},
),
):
models, errors, ok, meta = await fetch_models_for_key(ctx, timeout_seconds=1.0)
assert ok is True
assert errors == []
assert meta is None
ids = {m.get("id") for m in models}
assert "gemini-2.0-flash" in ids
@pytest.mark.asyncio
async def test_fetch_models_for_key_vertex_api_key_returns_soft_404_when_all_failed() -> None:
ctx = UpstreamModelsFetchContext(
provider_type="vertex_ai",
api_key_value="test-api-key",
format_to_endpoint={
"gemini:chat": EndpointFetchConfig(base_url="https://aiplatform.googleapis.com"),
},
proxy_config=None,
auth_config={},
)
with (
patch(
"src.services.provider.adapters.vertex_ai.plugin._fetch_models_from_url",
AsyncMock(
side_effect=[
([], "HTTP 404: not found", False),
([], "HTTP 404: not found", False),
]
),
),
patch(
"src.services.proxy_node.resolver.build_proxy_client_kwargs",
return_value={"timeout": 1.0},
),
):
models, errors, ok, meta = await fetch_models_for_key(ctx, timeout_seconds=1.0)
assert ok is False
assert models == []
assert meta is None
assert errors
assert "HTTP 404" in errors[0]