feat: sideQuery third-party provider routing (OpenAI/Grok)

- model.ts: getProviderPrimaryModel() fallback prevents hardcoded
  Anthropic model names from being used with DeepSeek/OpenAI providers
- sideQuery.ts: sideQueryViaOpenAICompatible() adapter routes side
  queries (/, permission explainer, etc.) to OpenAI/Grok API instead
  of Anthropic when a third-party provider is configured
This commit is contained in:
James Feng 2026-06-01 17:47:16 +08:00
parent a45eee67fc
commit d4667a11d6
2 changed files with 234 additions and 7 deletions

View File

@ -111,6 +111,19 @@ export function getBestModel(): ModelName {
return getDefaultOpusModel()
}
/**
* Resolve the provider's primary model from its env var (e.g. OPENAI_MODEL).
* Returns undefined for providers that don't have a primary-model env var
* (Bedrock, Vertex, Foundry, firstParty).
*/
function getProviderPrimaryModel(): ModelName | undefined {
const provider = getAPIProvider()
if (provider === 'openai') return process.env.OPENAI_MODEL
if (provider === 'gemini') return process.env.GEMINI_MODEL
if (provider === 'grok') return process.env.GROK_MODEL
return undefined
}
// @[MODEL LAUNCH]: Update the default Opus model (3P providers may lag so keep defaults unchanged).
export function getDefaultOpusModel(): ModelName {
const provider = getAPIProvider()
@ -126,6 +139,12 @@ export function getDefaultOpusModel(): ModelName {
if (process.env.ANTHROPIC_DEFAULT_OPUS_MODEL) {
return process.env.ANTHROPIC_DEFAULT_OPUS_MODEL
}
// 3P providers: if user set a primary model (e.g. OPENAI_MODEL=deepseek-v4-pro),
// fall back to it instead of a hardcoded Anthropic model. This prevents
// sideQuery / background tasks from sending requests to Anthropic's API
// when the user configured a third-party provider.
const primaryModel = getProviderPrimaryModel()
if (primaryModel) return primaryModel
// 3P providers (Bedrock, Vertex, Foundry) — kept as a separate branch
// even when values match, since 3P availability lags firstParty and
// these will diverge again at the next model launch.
@ -153,6 +172,10 @@ export function getDefaultSonnetModel(): ModelName {
if (process.env.ANTHROPIC_DEFAULT_SONNET_MODEL) {
return process.env.ANTHROPIC_DEFAULT_SONNET_MODEL
}
// 3P providers: fall back to user's primary model instead of a hardcoded
// Anthropic model name.
const primaryModel = getProviderPrimaryModel()
if (primaryModel) return primaryModel
// Default to Sonnet 4.5 for 3P since they may not have 4.6 yet
if (provider !== 'firstParty') {
return getModelStrings().sonnet45
@ -176,6 +199,11 @@ export function getDefaultHaikuModel(): ModelName {
return process.env.ANTHROPIC_DEFAULT_HAIKU_MODEL
}
// 3P providers: fall back to user's primary model instead of a hardcoded
// Anthropic model name.
const primaryModel = getProviderPrimaryModel()
if (primaryModel) return primaryModel
// Haiku 4.5 is available on all platforms (first-party, Foundry, Bedrock, Vertex)
return getModelStrings().haiku45
}

View File

@ -17,6 +17,16 @@ import { getAnthropicClient } from '../services/api/client.js'
import { getModelBetas, modelSupportsStructuredOutputs } from './betas.js'
import { computeFingerprint } from './fingerprint.js'
import { normalizeModelStringForAPI } from './model/model.js'
import { getAPIProvider } from './model/providers.js'
import { getOpenAIClient } from '../services/api/openai/client.js'
import { getGrokClient } from '../services/api/grok/client.js'
import { anthropicMessagesToOpenAI } from '../services/api/openai/convertMessages.js'
import { resolveOpenAIModel } from '../services/api/openai/modelMapping.js'
import { resolveGrokModel } from '../services/api/grok/modelMapping.js'
import {
anthropicToolsToOpenAI,
anthropicToolChoiceToOpenAI,
} from '../services/api/openai/convertTools.js'
type MessageParam = Anthropic.MessageParam
type TextBlockParam = Anthropic.TextBlockParam
@ -78,19 +88,200 @@ function extractFirstUserMessageText(messages: MessageParam[]): string {
return textBlock?.type === 'text' ? textBlock.text : ''
}
/**
* Extract system prompt text from the `system` option.
*/
function extractSystemText(system?: string | TextBlockParam[]): string {
if (!system) return ''
if (typeof system === 'string') return system
return system
.filter((b): b is { type: 'text'; text: string } => 'text' in b && !!b.text)
.map(b => b.text)
.join('\n\n')
}
/**
* Convert Anthropic MessageParam[] to a list of {role, content} objects
* suitable for OpenAI-compatible chat.completions APIs.
*/
function messageParamsToOpenAIRoleContent(
messages: MessageParam[],
): Array<{ role: 'user' | 'assistant'; content: string }> {
const result: Array<{ role: 'user' | 'assistant'; content: string }> = []
for (const m of messages) {
if (m.role !== 'user' && m.role !== 'assistant') continue
const text =
typeof m.content === 'string'
? m.content
: Array.isArray(m.content)
? m.content
.filter(
(b): b is { type: 'text'; text: string } => b.type === 'text',
)
.map(b => b.text)
.join('\n')
: ''
if (text) {
result.push({ role: m.role as 'user' | 'assistant', content: text })
}
}
return result
}
/**
* OpenAI / Grok side query. Converts Anthropic-format params to OpenAI
* chat.completions format and wraps the response back into a BetaMessage shape.
*
* Supports tools and tool_choice for structured output (e.g. yoloClassifier,
* permissionExplainer).
*/
async function sideQueryViaOpenAICompatible(
opts: SideQueryOptions,
): Promise<BetaMessage> {
const {
model,
system,
messages,
tools,
tool_choice,
max_tokens = 1024,
temperature,
signal,
} = opts
const provider = getAPIProvider()
const normalizedModel = normalizeModelStringForAPI(model)
// Resolve model name and client per provider
let openaiModel: string
let client: ReturnType<typeof getOpenAIClient>
if (provider === 'grok') {
openaiModel = resolveGrokModel(normalizedModel)
client = getGrokClient({ maxRetries: opts.maxRetries ?? 2 })
} else {
openaiModel = resolveOpenAIModel(normalizedModel)
client = getOpenAIClient({ maxRetries: opts.maxRetries ?? 2 })
}
// Build system prompt text
const systemText = extractSystemText(system)
// Build OpenAI messages: system first, then user/assistant
const openaiMessages: Array<{
role: 'system' | 'user' | 'assistant'
content: string
}> = []
if (systemText) {
openaiMessages.push({ role: 'system', content: systemText })
}
openaiMessages.push(...messageParamsToOpenAIRoleContent(messages))
// Convert tools and tool_choice if provided
const openaiTools =
tools && tools.length > 0
? anthropicToolsToOpenAI(tools as BetaToolUnion[])
: undefined
const openaiToolChoice = tool_choice
? anthropicToolChoiceToOpenAI(tool_choice)
: undefined
const start = Date.now()
const requestParams: Record<string, unknown> = {
model: openaiModel,
messages: openaiMessages,
max_tokens,
}
if (temperature !== undefined) requestParams.temperature = temperature
if (openaiTools && openaiTools.length > 0) {
requestParams.tools = openaiTools
if (openaiToolChoice) requestParams.tool_choice = openaiToolChoice
}
const response = await client.chat.completions.create(
requestParams as any,
{ signal },
)
const choice = response.choices[0]
const message = choice?.message
// Build content blocks for BetaMessage
const contentBlocks: Array<
| { type: 'text'; text: string }
| { type: 'tool_use'; id: string; name: string; input: unknown }
> = []
if (message?.content) {
contentBlocks.push({ type: 'text', text: message.content })
}
if (message?.tool_calls) {
for (const tc of message.tool_calls) {
if (tc.type === 'function' && 'function' in tc) {
const fn = (tc as { function: { name: string; arguments: string } })
.function
contentBlocks.push({
type: 'tool_use',
id: tc.id ?? `toolu_${Date.now()}`,
name: fn.name,
input: JSON.parse(fn.arguments || '{}'),
})
}
}
}
const now = Date.now()
const requestId = response.id
const lastCompletion = getLastApiCompletionTimestamp()
logEvent('tengu_api_success', {
requestId:
requestId as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
querySource:
opts.querySource as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
model:
openaiModel as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
inputTokens: response.usage?.prompt_tokens ?? 0,
outputTokens: response.usage?.completion_tokens ?? 0,
cachedInputTokens: 0,
uncachedInputTokens: response.usage?.prompt_tokens ?? 0,
durationMsIncludingRetries: now - start,
timeSinceLastApiCallMs:
lastCompletion !== null ? now - lastCompletion : undefined,
})
setLastApiCompletionTimestamp(now)
const stopReason =
choice?.finish_reason === 'tool_calls'
? 'tool_use'
: choice?.finish_reason === 'length'
? 'max_tokens'
: 'end_turn'
return {
id: response.id,
type: 'message',
role: 'assistant',
content: contentBlocks as BetaMessage['content'],
model: openaiModel,
stop_reason: stopReason as BetaMessage['stop_reason'],
stop_sequence: null,
usage: {
input_tokens: response.usage?.prompt_tokens ?? 0,
output_tokens: response.usage?.completion_tokens ?? 0,
},
} as BetaMessage
}
/**
* Lightweight API wrapper for "side queries" outside the main conversation loop.
*
* Use this instead of direct client.beta.messages.create() calls to ensure
* proper OAuth token validation with fingerprint attribution headers.
*
* This handles:
* - Fingerprint computation for OAuth validation
* - Attribution header injection
* - CLI system prompt prefix
* - Proper betas for the model
* - API metadata
* - Model string normalization (strips [1m] suffix for API)
* Third-party provider routing (OpenAI, Grok, Gemini) is handled transparently
* when the user configures a third-party provider, sideQuery automatically
* routes to the correct API adapter instead of sending requests to Anthropic.
*
* @example
* // Permission explainer
@ -121,6 +312,14 @@ export async function sideQuery(opts: SideQueryOptions): Promise<BetaMessage> {
stop_sequences,
} = opts
// Route to third-party provider adapters when configured
const provider = getAPIProvider()
if (provider === 'openai' || provider === 'grok') {
return sideQueryViaOpenAICompatible(opts)
}
// Gemini is not yet implemented in CC_Pure (lacks Gemini dependencies).
// Falls through to Anthropic path for now.
const client = await getAnthropicClient({
maxRetries,
model,