import { createLogger } from '@sim/logger' import { getErrorMessage, toError } from '@sim/utils/errors' import OpenAI from 'openai' import type { ChatCompletionCreateParamsStreaming } from 'openai/resources/chat/completions' import type { StreamingExecution } from '@/executor/types' import { MAX_TOOL_ITERATIONS } from '@/providers' import { formatMessagesForProvider } from '@/providers/attachments' import { getProviderDefaultModel, getProviderModels } from '@/providers/models' import { checkForForcedToolUsage, createReadableStreamFromOpenAIStream, supportsNativeStructuredOutputs, } from '@/providers/openrouter/utils' import { createStreamingExecution } from '@/providers/streaming-execution' import { adaptOpenAIChatToolSchema } from '@/providers/tool-schema-adapter' import { enrichLastModelSegmentFromChatCompletions } from '@/providers/trace-enrichment' import type { FunctionCallResponse, Message, ProviderConfig, ProviderRequest, ProviderResponse, TimeSegment, } from '@/providers/types' import { ProviderError } from '@/providers/types' import { calculateCost, generateSchemaInstructions, prepareToolExecution, prepareToolsWithUsageControl, sumToolCosts, } from '@/providers/utils' import { executeTool } from '@/tools' const logger = createLogger('OpenRouterProvider') /** * Applies structured output configuration to a payload based on model capabilities. * Uses json_schema with require_parameters for supported models, falls back to json_object with prompt instructions. */ async function applyResponseFormat( targetPayload: any, messages: any[], responseFormat: any, model: string ): Promise { const useNative = await supportsNativeStructuredOutputs(model) if (useNative) { logger.info('Using native structured outputs for OpenRouter model', { model }) targetPayload.response_format = { type: 'json_schema', json_schema: { name: responseFormat.name || 'response_schema', schema: responseFormat.schema || responseFormat, strict: responseFormat.strict !== false, }, } targetPayload.provider = { ...targetPayload.provider, require_parameters: true } return messages } logger.info('Using json_object mode with prompt instructions for OpenRouter model', { model }) const schema = responseFormat.schema || responseFormat const schemaInstructions = generateSchemaInstructions(schema, responseFormat.name) targetPayload.response_format = { type: 'json_object' } return [...messages, { role: 'user', content: schemaInstructions }] } export const openRouterProvider: ProviderConfig = { id: 'openrouter', name: 'OpenRouter', description: 'Unified access to many models via OpenRouter', version: '1.0.0', models: getProviderModels('openrouter'), defaultModel: getProviderDefaultModel('openrouter'), executeRequest: async ( request: ProviderRequest ): Promise => { if (!request.apiKey) { throw new Error('API key is required for OpenRouter') } const client = new OpenAI({ apiKey: request.apiKey, baseURL: 'https://openrouter.ai/api/v1', }) const requestedModel = request.model.replace(/^openrouter\//, '') logger.info('Preparing OpenRouter request', { model: requestedModel, hasSystemPrompt: !!request.systemPrompt, hasMessages: !!request.messages?.length, hasTools: !!request.tools?.length, toolCount: request.tools?.length || 0, hasResponseFormat: !!request.responseFormat, stream: !!request.stream, }) const allMessages: Message[] = [] if (request.systemPrompt) { allMessages.push({ role: 'system', content: request.systemPrompt }) } if (request.context) { allMessages.push({ role: 'user', content: request.context }) } if (request.messages) { allMessages.push(...request.messages) } const formattedMessages = formatMessagesForProvider(allMessages, 'openrouter') as Message[] const tools = request.tools?.length ? request.tools.map((tool) => adaptOpenAIChatToolSchema(tool)) : undefined const payload: any = { model: requestedModel, messages: formattedMessages, } if (request.temperature !== undefined) payload.temperature = request.temperature if (request.maxTokens != null) payload.max_tokens = request.maxTokens let preparedTools: ReturnType | null = null let hasActiveTools = false if (tools?.length) { preparedTools = prepareToolsWithUsageControl(tools, request.tools, logger, 'openrouter') const { tools: filteredTools, toolChoice } = preparedTools if (filteredTools?.length && toolChoice) { payload.tools = filteredTools payload.tool_choice = toolChoice hasActiveTools = true } } const providerStartTime = Date.now() const providerStartTimeISO = new Date(providerStartTime).toISOString() try { if (request.responseFormat && !hasActiveTools) { payload.messages = await applyResponseFormat( payload, payload.messages, request.responseFormat, requestedModel ) } if (request.stream && (!tools || tools.length === 0 || !hasActiveTools)) { const streamingParams: ChatCompletionCreateParamsStreaming = { ...payload, stream: true, stream_options: { include_usage: true }, } const streamResponse = await client.chat.completions.create( streamingParams, request.abortSignal ? { signal: request.abortSignal } : undefined ) const streamingResult = createStreamingExecution({ model: requestedModel, providerStartTime, providerStartTimeISO, timing: { kind: 'simple', segmentName: request.model }, initialTokens: { input: 0, output: 0, total: 0 }, initialCost: { input: 0, output: 0, total: 0 }, createStream: ({ output, finalizeTiming }) => createReadableStreamFromOpenAIStream(streamResponse, (content, usage) => { output.content = content output.tokens = { input: usage.prompt_tokens, output: usage.completion_tokens, total: usage.total_tokens, } const costResult = calculateCost( requestedModel, usage.prompt_tokens, usage.completion_tokens ) output.cost = { input: costResult.input, output: costResult.output, total: costResult.total, } finalizeTiming() }), }) return streamingResult } const initialCallTime = Date.now() const originalToolChoice = payload.tool_choice const forcedTools = preparedTools?.forcedTools || [] let usedForcedTools: string[] = [] let currentResponse = await client.chat.completions.create( payload, request.abortSignal ? { signal: request.abortSignal } : undefined ) const firstResponseTime = Date.now() - initialCallTime let content = currentResponse.choices[0]?.message?.content || '' const tokens = { input: currentResponse.usage?.prompt_tokens || 0, output: currentResponse.usage?.completion_tokens || 0, total: currentResponse.usage?.total_tokens || 0, } const toolCalls: FunctionCallResponse[] = [] const toolResults: Record[] = [] const currentMessages = [...formattedMessages] let iterationCount = 0 let modelTime = firstResponseTime let toolsTime = 0 let hasUsedForcedTool = false const timeSegments: TimeSegment[] = [ { type: 'model', name: request.model, startTime: initialCallTime, endTime: initialCallTime + firstResponseTime, duration: firstResponseTime, }, ] const forcedToolResult = checkForForcedToolUsage( currentResponse, originalToolChoice, forcedTools, usedForcedTools ) hasUsedForcedTool = forcedToolResult.hasUsedForcedTool usedForcedTools = forcedToolResult.usedForcedTools while (iterationCount < MAX_TOOL_ITERATIONS) { if (currentResponse.choices[0]?.message?.content) { content = currentResponse.choices[0].message.content } const toolCallsInResponse = currentResponse.choices[0]?.message?.tool_calls enrichLastModelSegmentFromChatCompletions( timeSegments, currentResponse, toolCallsInResponse, { model: request.model, provider: 'openrouter' } ) if (!toolCallsInResponse || toolCallsInResponse.length === 0) { break } const toolsStartTime = Date.now() const toolExecutionPromises = toolCallsInResponse.map(async (toolCall) => { const toolCallStartTime = Date.now() const toolName = toolCall.function.name try { const toolArgs = JSON.parse(toolCall.function.arguments) const tool = request.tools?.find((t) => t.id === toolName) if (!tool) return null const { toolParams, executionParams } = prepareToolExecution(tool, toolArgs, request) const result = await executeTool(toolName, executionParams, { signal: request.abortSignal, }) const toolCallEndTime = Date.now() return { toolCall, toolName, toolParams, result, startTime: toolCallStartTime, endTime: toolCallEndTime, duration: toolCallEndTime - toolCallStartTime, } } catch (error) { const toolCallEndTime = Date.now() logger.error('Error processing tool call (OpenRouter):', { error: toError(error).message, 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, } if (typeof originalToolChoice === 'object' && hasUsedForcedTool && forcedTools.length > 0) { const remainingTools = forcedTools.filter((tool) => !usedForcedTools.includes(tool)) if (remainingTools.length > 0) { nextPayload.tool_choice = { type: 'function', function: { name: remainingTools[0] } } } else { nextPayload.tool_choice = 'auto' } } const nextModelStartTime = Date.now() currentResponse = await client.chat.completions.create( nextPayload, request.abortSignal ? { signal: request.abortSignal } : undefined ) const nextForcedToolResult = checkForForcedToolUsage( currentResponse, nextPayload.tool_choice, forcedTools, usedForcedTools ) hasUsedForcedTool = nextForcedToolResult.hasUsedForcedTool usedForcedTools = nextForcedToolResult.usedForcedTools 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 (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: 'openrouter' } ) } if (request.stream) { const accumulatedCost = calculateCost(requestedModel, tokens.input, tokens.output) const streamingParams: ChatCompletionCreateParamsStreaming & { provider?: any } = { ...payload, messages: [...currentMessages], tool_choice: 'auto', stream: true, stream_options: { include_usage: true }, } if (request.responseFormat) { ;(streamingParams as any).messages = await applyResponseFormat( streamingParams as any, streamingParams.messages, request.responseFormat, requestedModel ) } const streamResponse = await client.chat.completions.create( streamingParams, request.abortSignal ? { signal: request.abortSignal } : undefined ) const streamingResult = createStreamingExecution({ model: requestedModel, 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 }) => createReadableStreamFromOpenAIStream(streamResponse, (content, usage) => { output.content = content output.tokens = { input: tokens.input + usage.prompt_tokens, output: tokens.output + usage.completion_tokens, total: tokens.total + usage.total_tokens, } const streamCost = calculateCost( requestedModel, 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 } if (request.responseFormat && hasActiveTools) { const finalPayload: any = { model: payload.model, messages: [...currentMessages], } if (payload.temperature !== undefined) { finalPayload.temperature = payload.temperature } if (payload.max_tokens !== undefined) { finalPayload.max_tokens = payload.max_tokens } finalPayload.messages = await applyResponseFormat( finalPayload, finalPayload.messages, request.responseFormat, requestedModel ) const finalStartTime = Date.now() const finalResponse = await client.chat.completions.create( finalPayload, request.abortSignal ? { signal: request.abortSignal } : undefined ) const finalEndTime = Date.now() const finalDuration = finalEndTime - finalStartTime timeSegments.push({ type: 'model', name: 'Final structured response', startTime: finalStartTime, endTime: finalEndTime, duration: finalDuration, }) modelTime += finalDuration if (finalResponse.choices[0]?.message?.content) { content = finalResponse.choices[0].message.content } 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: 'openrouter' } ) } const providerEndTime = Date.now() const providerEndTimeISO = new Date(providerEndTime).toISOString() const totalDuration = providerEndTime - providerStartTime return { content, model: requestedModel, 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 const errorDetails: Record = { error: toError(error).message, duration: totalDuration, } if (error && typeof error === 'object') { const err = error as any if (err.status) errorDetails.status = err.status if (err.code) errorDetails.code = err.code if (err.type) errorDetails.type = err.type if (err.error?.message) errorDetails.providerMessage = err.error.message if (err.error?.metadata) errorDetails.metadata = err.error.metadata } logger.error('Error in OpenRouter request:', errorDetails) throw new ProviderError(toError(error).message, { startTime: providerStartTimeISO, endTime: providerEndTimeISO, duration: totalDuration, }) } }, }