chore: import upstream snapshot with attribution
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This commit is contained in:
@@ -0,0 +1,620 @@
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import type { Logger } from '@sim/logger'
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||||
import { getErrorMessage } from '@sim/utils/errors'
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import OpenAI from 'openai'
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import type {
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ChatCompletionChunk,
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ChatCompletionCreateParamsStreaming,
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} from 'openai/resources/chat/completions'
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import type { CompletionUsage } from 'openai/resources/completions'
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import type { StreamingExecution } from '@/executor/types'
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import { MAX_TOOL_ITERATIONS } from '@/providers'
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import { formatMessagesForProvider } from '@/providers/attachments'
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import { createStreamingExecution } from '@/providers/streaming-execution'
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import { adaptOpenAIChatToolSchema } from '@/providers/tool-schema-adapter'
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import { enrichLastModelSegmentFromChatCompletions } from '@/providers/trace-enrichment'
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import type { Message, ProviderRequest, ProviderResponse, TimeSegment } from '@/providers/types'
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import { ProviderError } from '@/providers/types'
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import {
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calculateCost,
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generateSchemaInstructions,
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prepareToolExecution,
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sumToolCosts,
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} from '@/providers/utils'
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import { executeTool } from '@/tools'
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/**
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* Ollama enforces JSON mode (`json_object`) but ignores `json_schema`, so
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* structured outputs use JSON mode with the schema described in-prompt. Mutates
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* `payload.response_format` and returns the messages with instructions appended.
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*/
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function applyJsonResponseFormat(
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payload: { response_format?: unknown },
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messages: Message[],
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responseFormat: NonNullable<ProviderRequest['responseFormat']>
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): Message[] {
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payload.response_format = { type: 'json_object' }
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const schema = responseFormat.schema || responseFormat
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return [
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...messages,
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{ role: 'user', content: generateSchemaInstructions(schema, responseFormat.name) },
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]
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}
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/**
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* Per-provider hooks for the shared Ollama execution logic. The self-hosted
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* `ollama` and hosted `ollama-cloud` providers differ only in client
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* construction and labels; both pass those in here.
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*/
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export interface OllamaCoreConfig {
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/** Provider id used for trace enrichment (`ollama`, `ollama-cloud`). */
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providerId: string
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/** Human-readable label used in log messages. */
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providerLabel: string
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/** Builds the OpenAI-compatible client (base URL + credentials per provider). */
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createClient: () => OpenAI
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createStream: (
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stream: AsyncIterable<ChatCompletionChunk>,
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onComplete?: (content: string, usage: CompletionUsage) => void
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) => ReadableStream<Uint8Array>
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logger: Logger
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}
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/**
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* Shared execution logic for the Ollama-family providers, which speak the same
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* OpenAI-compatible Ollama API. Ollama ignores `tool_choice`, so tools are sent
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* as `tool_choice: 'auto'` (forced tools degrade to auto) and the final post-tool
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* call drops tools entirely rather than relying on `tool_choice: 'none'`.
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*/
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export async function executeOllamaProviderRequest(
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request: ProviderRequest,
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config: OllamaCoreConfig
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): Promise<ProviderResponse | StreamingExecution> {
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const { providerId, providerLabel, logger } = config
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logger.info(`Preparing ${providerLabel} request`, {
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model: request.model,
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hasSystemPrompt: !!request.systemPrompt,
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hasMessages: !!request.messages?.length,
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hasTools: !!request.tools?.length,
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toolCount: request.tools?.length || 0,
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hasResponseFormat: !!request.responseFormat,
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stream: !!request.stream,
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})
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const ollama = config.createClient()
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const allMessages: Message[] = []
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if (request.systemPrompt) {
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allMessages.push({
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role: 'system',
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content: request.systemPrompt,
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})
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}
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if (request.context) {
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allMessages.push({
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role: 'user',
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content: request.context,
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})
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}
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if (request.messages) {
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allMessages.push(...request.messages)
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}
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const formattedMessages = formatMessagesForProvider(allMessages, providerId) as Message[]
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const tools = request.tools?.length
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? request.tools.map((tool) => adaptOpenAIChatToolSchema(tool))
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: undefined
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const payload: any = {
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model: request.model,
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messages: formattedMessages,
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}
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if (request.temperature !== undefined) payload.temperature = request.temperature
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if (request.maxTokens != null) payload.max_tokens = request.maxTokens
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let hasActiveTools = false
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if (tools?.length) {
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const filteredTools = tools.filter((tool) => {
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const toolId = tool.function?.name
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const toolConfig = request.tools?.find((t) => t.id === toolId)
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return toolConfig?.usageControl !== 'none'
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})
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const hasForcedTools = tools.some((tool) => {
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const toolId = tool.function?.name
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const toolConfig = request.tools?.find((t) => t.id === toolId)
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return toolConfig?.usageControl === 'force'
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})
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if (hasForcedTools) {
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logger.warn(
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`${providerLabel} does not support forced tool selection (tool_choice parameter is ignored). ` +
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'Tools marked with usageControl="force" will behave as "auto" instead.'
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)
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}
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if (filteredTools?.length) {
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payload.tools = filteredTools
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payload.tool_choice = 'auto'
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hasActiveTools = true
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logger.info(`${providerLabel} request configuration:`, {
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toolCount: filteredTools.length,
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toolChoice: 'auto',
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forcedToolsIgnored: hasForcedTools,
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model: request.model,
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})
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}
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}
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// With tools, defer structured output to the final call so JSON mode doesn't preempt tool use.
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if (request.responseFormat && !hasActiveTools) {
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payload.messages = applyJsonResponseFormat(payload, payload.messages, request.responseFormat)
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logger.info(`Added JSON response format to ${providerLabel} request`)
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}
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const providerStartTime = Date.now()
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const providerStartTimeISO = new Date(providerStartTime).toISOString()
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try {
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if (request.stream && (!tools || tools.length === 0 || !hasActiveTools)) {
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logger.info(`Using streaming response for ${providerLabel} request`)
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const streamingParams: ChatCompletionCreateParamsStreaming = {
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...payload,
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stream: true,
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stream_options: { include_usage: true },
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}
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const streamResponse = await ollama.chat.completions.create(
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streamingParams,
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request.abortSignal ? { signal: request.abortSignal } : undefined
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)
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const streamingResult = createStreamingExecution({
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model: request.model,
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providerStartTime,
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providerStartTimeISO,
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timing: { kind: 'simple', segmentName: request.model },
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initialTokens: { input: 0, output: 0, total: 0 },
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initialCost: { input: 0, output: 0, total: 0 },
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createStream: ({ output, finalizeTiming }) =>
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config.createStream(streamResponse, (content, usage) => {
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output.content = content
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if (content && request.responseFormat) {
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output.content = content.replace(/```json\n?|\n?```/g, '').trim()
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}
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output.tokens = {
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input: usage.prompt_tokens,
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output: usage.completion_tokens,
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total: usage.total_tokens,
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}
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const costResult = calculateCost(
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request.model,
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usage.prompt_tokens,
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usage.completion_tokens
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)
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output.cost = {
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input: costResult.input,
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output: costResult.output,
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total: costResult.total,
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}
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finalizeTiming()
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}),
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})
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return streamingResult
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}
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const initialCallTime = Date.now()
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let currentResponse = await ollama.chat.completions.create(
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payload,
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request.abortSignal ? { signal: request.abortSignal } : undefined
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)
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const firstResponseTime = Date.now() - initialCallTime
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let content = currentResponse.choices[0]?.message?.content || ''
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if (content && request.responseFormat) {
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content = content.replace(/```json\n?|\n?```/g, '')
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content = content.trim()
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}
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const tokens = {
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input: currentResponse.usage?.prompt_tokens || 0,
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output: currentResponse.usage?.completion_tokens || 0,
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total: currentResponse.usage?.total_tokens || 0,
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}
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const toolCalls = []
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const toolResults: Record<string, unknown>[] = []
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const currentMessages = [...formattedMessages]
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let iterationCount = 0
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let modelTime = firstResponseTime
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let toolsTime = 0
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const timeSegments: TimeSegment[] = [
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{
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type: 'model',
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name: request.model,
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startTime: initialCallTime,
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endTime: initialCallTime + firstResponseTime,
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duration: firstResponseTime,
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},
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]
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while (iterationCount < MAX_TOOL_ITERATIONS) {
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if (currentResponse.choices[0]?.message?.content) {
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content = currentResponse.choices[0].message.content
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if (request.responseFormat) {
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content = content.replace(/```json\n?|\n?```/g, '').trim()
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}
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}
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const toolCallsInResponse = currentResponse.choices[0]?.message?.tool_calls
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enrichLastModelSegmentFromChatCompletions(
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timeSegments,
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currentResponse,
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toolCallsInResponse,
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{
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model: request.model,
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provider: providerId,
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}
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)
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if (!toolCallsInResponse || toolCallsInResponse.length === 0) {
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break
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}
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logger.info(
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`Processing ${toolCallsInResponse.length} tool calls (iteration ${iterationCount + 1}/${MAX_TOOL_ITERATIONS})`
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)
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const toolsStartTime = Date.now()
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const toolExecutionPromises = toolCallsInResponse.map(async (toolCall) => {
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const toolCallStartTime = Date.now()
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const toolName = toolCall.function.name
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try {
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const toolArgs = JSON.parse(toolCall.function.arguments)
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const tool = request.tools?.find((t) => t.id === toolName)
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|
||||
if (!tool) return null
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const { toolParams, executionParams } = prepareToolExecution(tool, toolArgs, request)
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const result = await executeTool(toolName, executionParams, {
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||||
signal: request.abortSignal,
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||||
})
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||||
const toolCallEndTime = Date.now()
|
||||
|
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return {
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||||
toolCall,
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toolName,
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toolParams,
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||||
result,
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||||
startTime: toolCallStartTime,
|
||||
endTime: toolCallEndTime,
|
||||
duration: toolCallEndTime - toolCallStartTime,
|
||||
}
|
||||
} catch (error) {
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||||
const toolCallEndTime = Date.now()
|
||||
logger.error('Error processing tool call:', { error, toolName })
|
||||
|
||||
return {
|
||||
toolCall,
|
||||
toolName,
|
||||
toolParams: {},
|
||||
result: {
|
||||
success: false,
|
||||
output: undefined,
|
||||
error: getErrorMessage(error, 'Tool execution failed'),
|
||||
},
|
||||
startTime: toolCallStartTime,
|
||||
endTime: toolCallEndTime,
|
||||
duration: toolCallEndTime - toolCallStartTime,
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
const executionResults = await Promise.allSettled(toolExecutionPromises)
|
||||
|
||||
currentMessages.push({
|
||||
role: 'assistant',
|
||||
content: null,
|
||||
tool_calls: toolCallsInResponse.map((tc) => ({
|
||||
id: tc.id,
|
||||
type: 'function',
|
||||
function: {
|
||||
name: tc.function.name,
|
||||
arguments: tc.function.arguments,
|
||||
},
|
||||
})),
|
||||
})
|
||||
|
||||
for (const settledResult of executionResults) {
|
||||
if (settledResult.status === 'rejected' || !settledResult.value) continue
|
||||
|
||||
const { toolCall, toolName, toolParams, result, startTime, endTime, duration } =
|
||||
settledResult.value
|
||||
|
||||
timeSegments.push({
|
||||
type: 'tool',
|
||||
name: toolName,
|
||||
startTime: startTime,
|
||||
endTime: endTime,
|
||||
duration: duration,
|
||||
toolCallId: toolCall.id,
|
||||
})
|
||||
|
||||
let resultContent: any
|
||||
if (result.success && result.output) {
|
||||
toolResults.push(result.output)
|
||||
resultContent = result.output
|
||||
} else {
|
||||
resultContent = {
|
||||
error: true,
|
||||
message: result.error || 'Tool execution failed',
|
||||
tool: toolName,
|
||||
}
|
||||
}
|
||||
|
||||
toolCalls.push({
|
||||
name: toolName,
|
||||
arguments: toolParams,
|
||||
startTime: new Date(startTime).toISOString(),
|
||||
endTime: new Date(endTime).toISOString(),
|
||||
duration: duration,
|
||||
result: resultContent,
|
||||
success: result.success,
|
||||
})
|
||||
|
||||
currentMessages.push({
|
||||
role: 'tool',
|
||||
tool_call_id: toolCall.id,
|
||||
content: JSON.stringify(resultContent),
|
||||
})
|
||||
}
|
||||
|
||||
const thisToolsTime = Date.now() - toolsStartTime
|
||||
toolsTime += thisToolsTime
|
||||
|
||||
const nextPayload = {
|
||||
...payload,
|
||||
messages: currentMessages,
|
||||
}
|
||||
|
||||
const nextModelStartTime = Date.now()
|
||||
|
||||
currentResponse = await ollama.chat.completions.create(
|
||||
nextPayload,
|
||||
request.abortSignal ? { signal: request.abortSignal } : undefined
|
||||
)
|
||||
|
||||
const nextModelEndTime = Date.now()
|
||||
const thisModelTime = nextModelEndTime - nextModelStartTime
|
||||
|
||||
timeSegments.push({
|
||||
type: 'model',
|
||||
name: request.model,
|
||||
startTime: nextModelStartTime,
|
||||
endTime: nextModelEndTime,
|
||||
duration: thisModelTime,
|
||||
})
|
||||
|
||||
modelTime += thisModelTime
|
||||
|
||||
if (currentResponse.choices[0]?.message?.content) {
|
||||
content = currentResponse.choices[0].message.content
|
||||
if (request.responseFormat) {
|
||||
content = content.replace(/```json\n?|\n?```/g, '').trim()
|
||||
}
|
||||
}
|
||||
|
||||
if (currentResponse.usage) {
|
||||
tokens.input += currentResponse.usage.prompt_tokens || 0
|
||||
tokens.output += currentResponse.usage.completion_tokens || 0
|
||||
tokens.total += currentResponse.usage.total_tokens || 0
|
||||
}
|
||||
|
||||
iterationCount++
|
||||
}
|
||||
|
||||
if (iterationCount === MAX_TOOL_ITERATIONS) {
|
||||
enrichLastModelSegmentFromChatCompletions(
|
||||
timeSegments,
|
||||
currentResponse,
|
||||
currentResponse.choices[0]?.message?.tool_calls,
|
||||
{ model: request.model, provider: providerId }
|
||||
)
|
||||
}
|
||||
|
||||
if (request.stream) {
|
||||
logger.info(`Using streaming for final ${providerLabel} response after tool processing`)
|
||||
|
||||
const accumulatedCost = calculateCost(request.model, tokens.input, tokens.output)
|
||||
|
||||
const { tools: _tools, tool_choice: _toolChoice, ...streamPayload } = payload
|
||||
|
||||
const finalMessages = request.responseFormat
|
||||
? applyJsonResponseFormat(streamPayload, currentMessages, request.responseFormat)
|
||||
: currentMessages
|
||||
|
||||
const streamingParams: ChatCompletionCreateParamsStreaming = {
|
||||
...streamPayload,
|
||||
messages: finalMessages,
|
||||
stream: true,
|
||||
stream_options: { include_usage: true },
|
||||
}
|
||||
const streamResponse = await ollama.chat.completions.create(
|
||||
streamingParams,
|
||||
request.abortSignal ? { signal: request.abortSignal } : undefined
|
||||
)
|
||||
|
||||
const streamingResult = createStreamingExecution({
|
||||
model: request.model,
|
||||
providerStartTime,
|
||||
providerStartTimeISO,
|
||||
timing: {
|
||||
kind: 'accumulated',
|
||||
modelTime,
|
||||
toolsTime,
|
||||
firstResponseTime,
|
||||
iterations: iterationCount + 1,
|
||||
timeSegments,
|
||||
},
|
||||
initialTokens: {
|
||||
input: tokens.input,
|
||||
output: tokens.output,
|
||||
total: tokens.total,
|
||||
},
|
||||
initialCost: {
|
||||
input: accumulatedCost.input,
|
||||
output: accumulatedCost.output,
|
||||
total: accumulatedCost.total,
|
||||
},
|
||||
toolCalls:
|
||||
toolCalls.length > 0
|
||||
? {
|
||||
list: toolCalls,
|
||||
count: toolCalls.length,
|
||||
}
|
||||
: undefined,
|
||||
createStream: ({ output }) =>
|
||||
config.createStream(streamResponse, (content, usage) => {
|
||||
output.content = content
|
||||
|
||||
if (content && request.responseFormat) {
|
||||
output.content = content.replace(/```json\n?|\n?```/g, '').trim()
|
||||
}
|
||||
|
||||
output.tokens = {
|
||||
input: tokens.input + usage.prompt_tokens,
|
||||
output: tokens.output + usage.completion_tokens,
|
||||
total: tokens.total + usage.total_tokens,
|
||||
}
|
||||
|
||||
const streamCost = calculateCost(
|
||||
request.model,
|
||||
usage.prompt_tokens,
|
||||
usage.completion_tokens
|
||||
)
|
||||
const tc = sumToolCosts(toolResults)
|
||||
output.cost = {
|
||||
input: accumulatedCost.input + streamCost.input,
|
||||
output: accumulatedCost.output + streamCost.output,
|
||||
toolCost: tc || undefined,
|
||||
total: accumulatedCost.total + streamCost.total + tc,
|
||||
}
|
||||
}),
|
||||
})
|
||||
|
||||
return streamingResult
|
||||
}
|
||||
|
||||
// Deferred structured output: one final JSON-mode call now that tools have run.
|
||||
if (request.responseFormat && hasActiveTools) {
|
||||
const finalPayload: any = { model: payload.model }
|
||||
if (payload.temperature !== undefined) finalPayload.temperature = payload.temperature
|
||||
if (payload.max_tokens !== undefined) finalPayload.max_tokens = payload.max_tokens
|
||||
finalPayload.messages = applyJsonResponseFormat(
|
||||
finalPayload,
|
||||
currentMessages,
|
||||
request.responseFormat
|
||||
)
|
||||
|
||||
const finalStartTime = Date.now()
|
||||
const finalResponse = await ollama.chat.completions.create(
|
||||
finalPayload,
|
||||
request.abortSignal ? { signal: request.abortSignal } : undefined
|
||||
)
|
||||
const finalEndTime = Date.now()
|
||||
|
||||
timeSegments.push({
|
||||
type: 'model',
|
||||
name: 'Final structured response',
|
||||
startTime: finalStartTime,
|
||||
endTime: finalEndTime,
|
||||
duration: finalEndTime - finalStartTime,
|
||||
})
|
||||
modelTime += finalEndTime - finalStartTime
|
||||
|
||||
if (finalResponse.choices[0]?.message?.content) {
|
||||
content = finalResponse.choices[0].message.content.replace(/```json\n?|\n?```/g, '').trim()
|
||||
}
|
||||
if (finalResponse.usage) {
|
||||
tokens.input += finalResponse.usage.prompt_tokens || 0
|
||||
tokens.output += finalResponse.usage.completion_tokens || 0
|
||||
tokens.total += finalResponse.usage.total_tokens || 0
|
||||
}
|
||||
|
||||
enrichLastModelSegmentFromChatCompletions(
|
||||
timeSegments,
|
||||
finalResponse,
|
||||
finalResponse.choices[0]?.message?.tool_calls,
|
||||
{ model: request.model, provider: providerId }
|
||||
)
|
||||
}
|
||||
|
||||
const providerEndTime = Date.now()
|
||||
const providerEndTimeISO = new Date(providerEndTime).toISOString()
|
||||
const totalDuration = providerEndTime - providerStartTime
|
||||
|
||||
return {
|
||||
content,
|
||||
model: request.model,
|
||||
tokens,
|
||||
toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
|
||||
toolResults: toolResults.length > 0 ? toolResults : undefined,
|
||||
timing: {
|
||||
startTime: providerStartTimeISO,
|
||||
endTime: providerEndTimeISO,
|
||||
duration: totalDuration,
|
||||
modelTime: modelTime,
|
||||
toolsTime: toolsTime,
|
||||
firstResponseTime: firstResponseTime,
|
||||
iterations: iterationCount + 1,
|
||||
timeSegments: timeSegments,
|
||||
},
|
||||
}
|
||||
} catch (error) {
|
||||
const providerEndTime = Date.now()
|
||||
const providerEndTimeISO = new Date(providerEndTime).toISOString()
|
||||
const totalDuration = providerEndTime - providerStartTime
|
||||
|
||||
let errorMessage = getErrorMessage(error, 'Unknown error')
|
||||
let errorType: string | undefined
|
||||
let errorCode: string | undefined
|
||||
let status: number | undefined
|
||||
|
||||
if (error instanceof OpenAI.APIError) {
|
||||
errorMessage = error.message
|
||||
errorType = error.type
|
||||
errorCode = error.code ?? undefined
|
||||
status = error.status
|
||||
}
|
||||
|
||||
logger.error(`Error in ${providerLabel} request:`, {
|
||||
error: errorMessage,
|
||||
errorType,
|
||||
errorCode,
|
||||
status,
|
||||
duration: totalDuration,
|
||||
})
|
||||
|
||||
throw new ProviderError(errorMessage, {
|
||||
startTime: providerStartTimeISO,
|
||||
endTime: providerEndTimeISO,
|
||||
duration: totalDuration,
|
||||
})
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user