{"version":3,"file":"handlers.cjs","sources":["../../../src/tools/handlers.ts"],"sourcesContent":["/* eslint-disable no-console */\n// src/tools/handlers.ts\nimport { nanoid } from 'nanoid';\nimport { ToolMessage } from '@langchain/core/messages';\nimport type { AnthropicWebSearchResultBlockParam } from '@/llm/anthropic/types';\nimport type { ToolCall, ToolCallChunk } from '@langchain/core/messages/tool';\nimport type { Graph, MultiAgentGraph, StandardGraph } from '@/graphs';\nimport type { AgentContext } from '@/agents/AgentContext';\nimport type * as t from '@/types';\nimport {\n ToolCallTypes,\n GraphEvents,\n StepTypes,\n Providers,\n Constants,\n} from '@/common';\nimport {\n coerceAnthropicSearchResults,\n isAnthropicWebSearchResult,\n} from '@/tools/search/anthropic';\nimport { formatResultsForLLM } from '@/tools/search/format';\nimport { getMessageId } from '@/messages';\n\nexport async function handleToolCallChunks({\n graph,\n stepKey,\n toolCallChunks,\n metadata,\n}: {\n graph: StandardGraph | MultiAgentGraph;\n stepKey: string;\n toolCallChunks: ToolCallChunk[];\n metadata?: Record;\n}): Promise {\n let prevStepId: string;\n let prevRunStep: t.RunStep | undefined;\n try {\n prevStepId = graph.getStepIdByKey(stepKey);\n prevRunStep = graph.getRunStep(prevStepId);\n } catch {\n /** Edge Case: If no previous step exists, create a new message creation step */\n const message_id = getMessageId(stepKey, graph, true) ?? '';\n prevStepId = await graph.dispatchRunStep(\n stepKey,\n {\n type: StepTypes.MESSAGE_CREATION,\n message_creation: {\n message_id,\n },\n },\n metadata\n );\n prevRunStep = graph.getRunStep(prevStepId);\n }\n\n const _stepId = graph.getStepIdByKey(stepKey);\n\n /** Edge Case: Tool Call Run Step or `tool_call_ids` never dispatched */\n const tool_calls: ToolCall[] | undefined =\n prevStepId && prevRunStep && prevRunStep.type === StepTypes.MESSAGE_CREATION\n ? []\n : undefined;\n\n /**\n * Feed streaming tool call buffer — accumulate raw arg strings for truncation recovery.\n *\n * Provider chunk patterns:\n * - OpenAI/Anthropic: every chunk has {id, args} → direct append\n * - Bedrock: START chunk has {id, name, index}, DELTA chunks have {args, index} (no id)\n * → use index-to-id mapping to resolve the target buffer entry\n *\n * Duplicate detection: LangChain's `streamEvents` can emit the same `on_chat_model_stream`\n * event multiple times when the model is wrapped in nested runnables. The buffer's `append()`\n * tracks the last fragment per tool call and returns false for exact duplicates.\n * When ALL chunks in a batch are duplicates, we skip the entire delta dispatch.\n */\n let allDuplicates = true;\n for (const toolCallChunk of toolCallChunks) {\n const chunkIndex = toolCallChunk.index;\n\n // START chunk: has id (and usually name). Store index→id mapping for future DELTA chunks.\n if (toolCallChunk.id) {\n if (typeof chunkIndex === 'number') {\n graph.streamingToolCallBuffer.setIndexMapping(\n chunkIndex,\n toolCallChunk.id\n );\n }\n if (toolCallChunk.name) {\n graph.streamingToolCallBuffer.setToolName(\n toolCallChunk.id,\n toolCallChunk.name\n );\n }\n // Append args if present on the same chunk (OpenAI/Anthropic pattern)\n if (toolCallChunk.args) {\n const appended = graph.streamingToolCallBuffer.append(\n toolCallChunk.id,\n toolCallChunk.args\n );\n if (appended) allDuplicates = false;\n } else {\n // START chunk without args is never a duplicate (it sets up id/name)\n allDuplicates = false;\n }\n } else if (toolCallChunk.args && typeof chunkIndex === 'number') {\n // DELTA chunk: no id, but has args + index. Resolve id via index mapping (Bedrock pattern).\n const resolvedId = graph.streamingToolCallBuffer.getIdByIndex(chunkIndex);\n if (resolvedId) {\n const appended = graph.streamingToolCallBuffer.append(\n resolvedId,\n toolCallChunk.args\n );\n if (appended) allDuplicates = false;\n }\n } else {\n // Chunks without args or index are not duplicates\n allDuplicates = false;\n }\n }\n\n // If every chunk in this batch was an exact duplicate, skip the delta dispatch entirely.\n // This prevents the frontend from receiving doubled fragments that corrupt accumulated args.\n if (allDuplicates && toolCallChunks.length > 0) {\n return;\n }\n\n /** Edge Case: `id` and `name` fields cannot be empty strings */\n for (const toolCallChunk of toolCallChunks) {\n if (toolCallChunk.name === '') {\n toolCallChunk.name = undefined;\n }\n if (toolCallChunk.id === '') {\n toolCallChunk.id = undefined;\n } else if (\n tool_calls != null &&\n toolCallChunk.id != null &&\n toolCallChunk.name != null\n ) {\n tool_calls.push({\n args: {},\n id: toolCallChunk.id,\n name: toolCallChunk.name,\n type: ToolCallTypes.TOOL_CALL,\n });\n }\n }\n\n let stepId: string = _stepId;\n const alreadyDispatched =\n prevRunStep?.type === StepTypes.MESSAGE_CREATION &&\n graph.messageStepHasToolCalls.has(prevStepId);\n\n if (prevRunStep?.type === StepTypes.TOOL_CALLS) {\n /**\n * If previous step is already a tool_calls step, use that step ID\n * This ensures tool call deltas are dispatched to the correct step\n */\n stepId = prevStepId;\n } else if (\n !alreadyDispatched &&\n prevRunStep?.type === StepTypes.MESSAGE_CREATION\n ) {\n /**\n * Create tool_calls step as soon as we receive the first tool call chunk\n * This ensures deltas are always associated with the correct step\n *\n * NOTE: We do NOT dispatch an empty text block here because:\n * - Empty text blocks cause providers (Anthropic, Bedrock) to reject messages\n * - The tool_calls themselves are sufficient for the step\n * - Empty content with tool_call_ids gets stored in conversation history\n * and causes \"messages must have non-empty content\" errors on replay\n */\n graph.messageStepHasToolCalls.set(prevStepId, true);\n stepId = await graph.dispatchRunStep(\n stepKey,\n {\n type: StepTypes.TOOL_CALLS,\n tool_calls: tool_calls ?? [],\n },\n metadata\n );\n }\n\n await graph.dispatchRunStepDelta(stepId, {\n type: StepTypes.TOOL_CALLS,\n tool_calls: toolCallChunks,\n });\n}\n\nexport const handleToolCalls = async (\n toolCalls?: ToolCall[],\n metadata?: Record,\n graph?: Graph | StandardGraph | MultiAgentGraph\n): Promise => {\n if (!graph || !metadata) {\n console.warn('Graph or metadata not found in `handleToolCalls`');\n return;\n }\n\n if (!toolCalls) {\n return;\n }\n\n if (toolCalls.length === 0) {\n return;\n }\n\n const stepKey = graph.getStepKey(metadata);\n\n /**\n * Track whether we've already reused an empty TOOL_CALLS step created by\n * handleToolCallChunks during streaming. Only reuse it once (for the first\n * tool call); subsequent parallel tool calls must create their own steps.\n */\n let reusedChunkStepId: string | undefined;\n\n for (const tool_call of toolCalls) {\n const toolCallId = tool_call.id ?? `toolu_${nanoid()}`;\n tool_call.id = toolCallId;\n\n // If this tool call ID was already tracked via handleToolCallChunks,\n // the step exists but may lack the name (Bedrock sends name only at model end).\n // Dispatch a delta with the complete data so the client can fill in the name.\n if (toolCallId && graph.toolCallStepIds.has(toolCallId)) {\n const existingStepId = graph.toolCallStepIds.get(toolCallId);\n if (existingStepId != null && existingStepId !== '') {\n const argsStr =\n typeof tool_call.args === 'string'\n ? tool_call.args\n : JSON.stringify(tool_call.args);\n await graph.dispatchRunStepDelta(existingStepId, {\n type: StepTypes.TOOL_CALLS,\n tool_calls: [{ name: tool_call.name, args: argsStr, id: toolCallId }],\n });\n }\n continue;\n }\n\n let prevStepId = '';\n let prevRunStep: t.RunStep | undefined;\n try {\n prevStepId = graph.getStepIdByKey(stepKey);\n prevRunStep = graph.getRunStep(prevStepId);\n } catch {\n // no previous step\n }\n\n // If the previous step is TOOL_CALLS (created by handleToolCallChunks),\n // either reuse it (if empty) or dispatch a new TOOL_CALLS step directly —\n // skip the intermediate MESSAGE_CREATION to avoid orphaned gaps.\n if (prevRunStep?.type === StepTypes.TOOL_CALLS) {\n const details = prevRunStep.stepDetails as t.ToolCallsDetails;\n const isEmpty = !details.tool_calls || details.tool_calls.length === 0;\n if (isEmpty && prevStepId !== reusedChunkStepId) {\n graph.toolCallStepIds.set(toolCallId, prevStepId);\n reusedChunkStepId = prevStepId;\n continue;\n }\n await graph.dispatchRunStep(\n stepKey,\n { type: StepTypes.TOOL_CALLS, tool_calls: [tool_call] },\n metadata\n );\n continue;\n }\n\n /**\n * NOTE: We do NOT dispatch empty text blocks with tool_call_ids because:\n * - Empty text blocks cause providers (Anthropic, Bedrock) to reject messages\n * - They get stored in conversation history and cause errors on replay:\n * \"messages must have non-empty content\" (Anthropic)\n * \"The content field in the Message object is empty\" (Bedrock)\n * - The tool_calls themselves are sufficient\n */\n\n /* If the previous step exists and is a message creation */\n if (prevStepId && prevRunStep) {\n graph.messageStepHasToolCalls.set(prevStepId, true);\n /* If the previous step doesn't exist */\n } else if (!prevRunStep) {\n const messageId = getMessageId(stepKey, graph, true) ?? '';\n const stepId = await graph.dispatchRunStep(\n stepKey,\n {\n type: StepTypes.MESSAGE_CREATION,\n message_creation: {\n message_id: messageId,\n },\n },\n metadata\n );\n graph.messageStepHasToolCalls.set(stepId, true);\n }\n\n await graph.dispatchRunStep(\n stepKey,\n {\n type: StepTypes.TOOL_CALLS,\n tool_calls: [tool_call],\n },\n metadata\n );\n }\n};\n\nexport const toolResultTypes = new Set([\n // 'tool_use',\n // 'server_tool_use',\n // 'input_json_delta',\n 'tool_result',\n 'web_search_result',\n 'web_search_tool_result',\n]);\n\n/**\n * Handles the result of a server tool call; in other words, a provider's built-in tool.\n * As of 2025-07-06, only Anthropic handles server tool calls with this pattern.\n */\nexport async function handleServerToolResult({\n graph,\n content,\n metadata,\n agentContext,\n}: {\n graph: StandardGraph | MultiAgentGraph;\n content?: string | t.MessageContentComplex[];\n metadata?: Record;\n agentContext?: AgentContext;\n}): Promise {\n let skipHandling = false;\n if (agentContext?.provider !== Providers.ANTHROPIC) {\n return skipHandling;\n }\n if (\n typeof content === 'string' ||\n content == null ||\n content.length === 0 ||\n (content.length === 1 &&\n (content[0] as t.ToolResultContent).tool_use_id == null)\n ) {\n return skipHandling;\n }\n\n for (const contentPart of content) {\n const toolUseId = (contentPart as t.ToolResultContent).tool_use_id;\n if (toolUseId == null || toolUseId === '') {\n continue;\n }\n const stepId = graph.toolCallStepIds.get(toolUseId);\n if (stepId == null || stepId === '') {\n console.warn(\n `Tool use ID ${toolUseId} not found in graph, cannot dispatch tool result.`\n );\n continue;\n }\n const runStep = graph.getRunStep(stepId);\n if (!runStep) {\n console.warn(\n `Run step for ${stepId} does not exist, cannot dispatch tool result.`\n );\n continue;\n } else if (runStep.type !== StepTypes.TOOL_CALLS) {\n console.warn(\n `Run step for ${stepId} is not a tool call step, cannot dispatch tool result.`\n );\n continue;\n }\n\n const toolCall =\n runStep.stepDetails.type === StepTypes.TOOL_CALLS\n ? (runStep.stepDetails.tool_calls?.find(\n (toolCall) => toolCall.id === toolUseId\n ) as ToolCall)\n : undefined;\n\n if (!toolCall) {\n continue;\n }\n\n if (\n contentPart.type === 'web_search_result' ||\n contentPart.type === 'web_search_tool_result'\n ) {\n await handleAnthropicSearchResults({\n contentPart: contentPart as t.ToolResultContent,\n toolCall,\n metadata,\n graph,\n });\n }\n\n if (!skipHandling) {\n skipHandling = true;\n }\n }\n\n return skipHandling;\n}\n\nasync function handleAnthropicSearchResults({\n contentPart,\n toolCall,\n metadata,\n graph,\n}: {\n contentPart: t.ToolResultContent;\n toolCall: Partial;\n metadata?: Record;\n graph: StandardGraph | MultiAgentGraph;\n}): Promise {\n if (!Array.isArray(contentPart.content)) {\n console.warn(\n `Expected content to be an array, got ${typeof contentPart.content}`\n );\n return;\n }\n\n if (!isAnthropicWebSearchResult(contentPart.content[0])) {\n console.warn(\n `Expected content to be an Anthropic web search result, got ${JSON.stringify(\n contentPart.content\n )}`\n );\n return;\n }\n\n const turn = graph.invokedToolIds?.size ?? 0;\n const searchResultData = coerceAnthropicSearchResults({\n turn,\n results: contentPart.content as AnthropicWebSearchResultBlockParam[],\n });\n\n const name = toolCall.name;\n const input = toolCall.args ?? {};\n const artifact = {\n [Constants.WEB_SEARCH]: searchResultData,\n };\n const { output: formattedOutput } = formatResultsForLLM(\n turn,\n searchResultData\n );\n const output = new ToolMessage({\n name,\n artifact,\n content: formattedOutput,\n tool_call_id: toolCall.id!,\n });\n const toolEndData: t.ToolEndData = {\n input,\n output,\n };\n await graph.handlerRegistry\n ?.getHandler(GraphEvents.TOOL_END)\n ?.handle(GraphEvents.TOOL_END, toolEndData, metadata, graph);\n\n if (graph.invokedToolIds == null) {\n graph.invokedToolIds = new Set();\n }\n\n 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