feat(sideQuery): add OpenAI and CoStrict provider support
- Route sideQuery to appropriate provider based on config - Add sideQueryCoStrict() for CoStrict API integration - Add sideQueryOpenAI() for OpenAI API integration - Both implementations return BetaMessage format for compatibility
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Askhz
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@ -1,5 +1,6 @@
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import type Anthropic from '@anthropic-ai/sdk'
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import type { BetaToolUnion } from '@anthropic-ai/sdk/resources/beta/messages.js'
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import OpenAI from 'openai'
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import {
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getLastApiCompletionTimestamp,
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setLastApiCompletionTimestamp,
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@ -14,9 +15,18 @@ import { logEvent } from '../services/analytics/index.js'
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import type { AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS } from '../services/analytics/metadata.js'
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import { getAPIMetadata } from '../services/api/claude.js'
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import { getAnthropicClient } from '../services/api/client.js'
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import { getOpenAIClient } from '../services/api/openai/client.js'
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import { resolveOpenAIModel } from '../services/api/openai/modelMapping.js'
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import { anthropicMessagesToOpenAI } from '../services/api/openai/convertMessages.js'
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import { createCoStrictFetch } from '../costrict/provider/fetch.js'
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import { loadCoStrictCredentials } from '../costrict/provider/credentials.js'
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import { getCoStrictBaseURL } from '../costrict/provider/auth.js'
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import { resolveCoStrictModel } from '../costrict/provider/modelMapping.js'
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import { getProxyFetchOptions } from './proxy.js'
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import { getModelBetas, modelSupportsStructuredOutputs } from './betas.js'
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import { computeFingerprint } from './fingerprint.js'
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import { normalizeModelStringForAPI } from './model/model.js'
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import { getAPIProvider } from './model/providers.js'
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type MessageParam = Anthropic.MessageParam
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type TextBlockParam = Anthropic.TextBlockParam
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@ -121,6 +131,15 @@ export async function sideQuery(opts: SideQueryOptions): Promise<BetaMessage> {
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stop_sequences,
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} = opts
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// Route to appropriate provider
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const provider = getAPIProvider()
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if (provider === 'costrict') {
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return sideQueryCoStrict(opts)
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}
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if (provider === 'openai') {
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return sideQueryOpenAI(opts)
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}
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const client = await getAnthropicClient({
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maxRetries,
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model,
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@ -220,3 +239,207 @@ export async function sideQuery(opts: SideQueryOptions): Promise<BetaMessage> {
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return response
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}
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/**
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* CoStrict provider implementation for sideQuery
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*/
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async function sideQueryCoStrict(opts: SideQueryOptions): Promise<BetaMessage> {
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const {
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model,
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system,
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messages,
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max_tokens = 1024,
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signal,
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skipSystemPromptPrefix,
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temperature,
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output_format,
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} = opts
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// Build system prompt
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const systemContent = skipSystemPromptPrefix
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? (typeof system === 'string' ? system : '')
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: `${getCLISyspromptPrefix({ isNonInteractive: false, hasAppendSystemPrompt: false })}
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${typeof system === 'string' ? system : ''}`
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// Resolve model and get base URL
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const costrictModel = resolveCoStrictModel(model)
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const creds = await loadCoStrictCredentials()
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const baseUrl = getCoStrictBaseURL(creds?.base_url)
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const chatBaseURL = `${baseUrl}/chat-rag/api/v1`
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// Create OpenAI client with CoStrict custom fetch
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const costrictFetch = createCoStrictFetch()
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const client = new OpenAI({
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apiKey: 'costrict-managed',
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baseURL: chatBaseURL,
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maxRetries: 0,
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timeout: parseInt(process.env.API_TIMEOUT_MS || String(600 * 1000), 10),
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dangerouslyAllowBrowser: true,
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fetchOptions: getProxyFetchOptions({ forAnthropicAPI: false }) as RequestInit,
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fetch: costrictFetch as any,
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})
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// Convert messages to OpenAI format
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const openaiMessages = anthropicMessagesToOpenAI(
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messages.map(m => ({
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...m,
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content: typeof m.content === 'string' ? m.content : m.content,
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})),
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systemContent,
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{ enableThinking: false }
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)
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// Build request
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const requestBody: OpenAI.Chat.Completions.ChatCompletionCreateParams = {
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model: costrictModel,
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messages: openaiMessages,
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max_tokens: max_tokens,
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...(temperature !== undefined && { temperature }),
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}
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// Add response_format for JSON schema if specified
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if (output_format?.type === 'json_schema') {
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(requestBody as any).response_format = {
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type: 'json_schema',
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json_schema: {
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name: 'response',
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schema: output_format.schema,
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strict: true,
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},
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}
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}
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const start = Date.now()
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const response = await client.chat.completions.create(requestBody, { signal })
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// Convert OpenAI response to Anthropic BetaMessage format
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const choice = response.choices[0]
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const content = choice?.message?.content || ''
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const betaMessage: BetaMessage = {
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id: response.id,
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type: 'message',
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role: 'assistant',
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model: costrictModel,
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content: [{ type: 'text', text: content }],
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stop_reason: choice?.finish_reason === 'stop' ? 'end_turn' : 'max_tokens',
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usage: {
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input_tokens: response.usage?.prompt_tokens || 0,
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output_tokens: response.usage?.completion_tokens || 0,
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},
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} as BetaMessage
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// Log analytics
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const now = Date.now()
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const lastCompletion = getLastApiCompletionTimestamp()
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logEvent('tengu_api_success', {
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requestId: response.id as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
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querySource: opts.querySource as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
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model: costrictModel as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
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inputTokens: response.usage?.prompt_tokens || 0,
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outputTokens: response.usage?.completion_tokens || 0,
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cachedInputTokens: 0,
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uncachedInputTokens: 0,
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durationMsIncludingRetries: now - start,
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timeSinceLastApiCallMs: lastCompletion !== null ? now - lastCompletion : undefined,
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})
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setLastApiCompletionTimestamp(now)
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return betaMessage
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}
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/**
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* OpenAI provider implementation for sideQuery
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*/
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async function sideQueryOpenAI(opts: SideQueryOptions): Promise<BetaMessage> {
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const {
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model,
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system,
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messages,
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max_tokens = 1024,
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signal,
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skipSystemPromptPrefix,
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temperature,
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output_format,
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} = opts
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// Build system prompt
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const systemContent = skipSystemPromptPrefix
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? (typeof system === 'string' ? system : '')
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: `${getCLISyspromptPrefix({ isNonInteractive: false, hasAppendSystemPrompt: false })}
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${typeof system === 'string' ? system : ''}`
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// Resolve model
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const openaiModel = resolveOpenAIModel(model)
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// Get OpenAI client
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const client = getOpenAIClient({ maxRetries: 0, source: 'side_query' })
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// Convert messages to OpenAI format
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const openaiMessages = anthropicMessagesToOpenAI(
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messages.map(m => ({
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...m,
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content: typeof m.content === 'string' ? m.content : m.content,
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})),
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systemContent,
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{ enableThinking: false }
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)
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// Build request
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const requestBody: OpenAI.Chat.Completions.ChatCompletionCreateParams = {
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model: openaiModel,
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messages: openaiMessages,
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max_tokens: max_tokens,
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...(temperature !== undefined && { temperature }),
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}
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// Add response_format for JSON schema if specified
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if (output_format?.type === 'json_schema') {
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(requestBody as any).response_format = {
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type: 'json_schema',
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json_schema: {
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name: 'response',
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schema: output_format.schema,
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strict: true,
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},
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}
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}
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const start = Date.now()
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const response = await client.chat.completions.create(requestBody, { signal })
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// Convert OpenAI response to Anthropic BetaMessage format
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const choice = response.choices[0]
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const content = choice?.message?.content || ''
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const betaMessage: BetaMessage = {
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id: response.id,
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type: 'message',
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role: 'assistant',
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model: openaiModel,
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content: [{ type: 'text', text: content }],
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stop_reason: choice?.finish_reason === 'stop' ? 'end_turn' : 'max_tokens',
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usage: {
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input_tokens: response.usage?.prompt_tokens || 0,
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output_tokens: response.usage?.completion_tokens || 0,
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},
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} as BetaMessage
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// Log analytics
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const now = Date.now()
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const lastCompletion = getLastApiCompletionTimestamp()
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logEvent('tengu_api_success', {
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requestId: response.id as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
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querySource: opts.querySource as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
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model: openaiModel as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
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inputTokens: response.usage?.prompt_tokens || 0,
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outputTokens: response.usage?.completion_tokens || 0,
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cachedInputTokens: 0,
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uncachedInputTokens: 0,
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durationMsIncludingRetries: now - start,
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timeSinceLastApiCallMs: lastCompletion !== null ? now - lastCompletion : undefined,
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})
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setLastApiCompletionTimestamp(now)
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return betaMessage
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}
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