{"version":3,"file":"summarize.cjs","sources":["../../../src/messages/summarize.ts"],"sourcesContent":["import { HumanMessage, BaseMessage } from '@langchain/core/messages';\nimport type { TokenCounter } from '@/types/run';\n\nexport type SummarizeTier = 'full' | 'simple' | 'emergency';\n\nexport type SummarizeConfig = {\n /** Max tokens for the summary output */\n maxOutputTokens?: number;\n /** Token counter for validation */\n tokenCounter?: TokenCounter;\n /** Max tokens the summary should fit within */\n summaryBudget?: number;\n /** Whether this is a multi-agent conversation */\n isMultiAgent?: boolean;\n /** Current agent workflow state for multi-agent context */\n agentWorkflowState?: {\n currentAgentId: string;\n agentChain: string[];\n pendingAgents: string[];\n };\n};\n\nexport type SummarizeResult = {\n summary: string;\n tier: SummarizeTier;\n tokenCount?: number;\n messagesCompacted: number;\n};\n\nconst MAX_MESSAGE_CHARS = 4000;\nconst MAX_TRUNCATED_CHARS = 500;\nconst SIMPLE_MAX_TOKENS = 512;\n\nexport const FULL_SUMMARY_TEMPLATE = `Analyze this conversation and produce a structured summary covering each section below. Be precise and preserve actionable details.\n\n## 1. Task Overview & User Intent\nWhat the user originally asked for and their high-level goal.\n\n## 2. Technical Context\nLanguages, frameworks, libraries, APIs, and architectural patterns involved.\n\n## 3. Files & Code State\nAll file paths mentioned, their current state, and any pending modifications.\n\n## 4. Problem Resolution History\nProblems encountered, debugging steps taken, and their outcomes.\n\n## 5. Agent Workflow State\n{agent_workflow}\n\n## 6. Tool Results Summary\nTools called, their inputs, and key outputs (omit verbose raw data).\n\n## 7. Progress Tracking\nWhat has been completed, what remains, and any blockers.\n\n## 8. Active Working State\nVariables, configurations, and runtime state that must be preserved.\n\n## 9. Continuation Plan\nImmediate next steps and the order in which they should be executed.\n\n## 10. Critical Context\nAny constraints, warnings, edge cases, or decisions that must not be lost.\n\nConversation:\n{conversation}\n\nStructured Summary:`;\n\nexport const SIMPLE_SUMMARY_TEMPLATE =\n \"Summarize this conversation preserving: user's original request, key decisions, current task state, and any file paths mentioned.\\n\\nConversation:\\n{conversation}\\n\\nSummary:\";\n\nexport function formatMessagesForSummary(messages: BaseMessage[]): string {\n const parts: string[] = [];\n for (const message of messages) {\n const role = message.getType();\n const raw =\n typeof message.content === 'string'\n ? message.content\n : JSON.stringify(message.content);\n const content =\n raw.length > MAX_MESSAGE_CHARS\n ? raw.slice(0, MAX_MESSAGE_CHARS) + '...'\n : raw;\n parts.push(`${role}: ${content}`);\n }\n return parts.join('\\n');\n}\n\nexport function buildFullSummaryPrompt(\n conversation: string,\n config?: SummarizeConfig\n): string {\n let agentWorkflow = 'N/A (single-agent conversation)';\n if (config?.isMultiAgent === true && config.agentWorkflowState != null) {\n const { currentAgentId, agentChain, pendingAgents } =\n config.agentWorkflowState;\n agentWorkflow = [\n `Current agent: ${currentAgentId}`,\n `Agent chain: ${agentChain.join(' -> ')}`,\n `Pending agents: ${pendingAgents.length > 0 ? pendingAgents.join(', ') : 'none'}`,\n ].join('\\n');\n }\n\n return FULL_SUMMARY_TEMPLATE.replace(\n '{agent_workflow}',\n agentWorkflow\n ).replace('{conversation}', conversation);\n}\n\nexport function buildSimpleSummaryPrompt(conversation: string): string {\n return SIMPLE_SUMMARY_TEMPLATE.replace('{conversation}', conversation);\n}\n\nexport function createEmergencySummary(messages: BaseMessage[]): string {\n let firstUserContent = '';\n let lastAIContent = '';\n const toolNames = new Set();\n\n for (const message of messages) {\n const type = message.getType();\n const content =\n typeof message.content === 'string'\n ? message.content\n : JSON.stringify(message.content);\n\n if (type === 'human' && firstUserContent.length === 0) {\n firstUserContent = content.slice(0, MAX_TRUNCATED_CHARS);\n }\n if (type === 'ai') {\n lastAIContent = content.slice(0, MAX_TRUNCATED_CHARS);\n }\n if (type === 'tool') {\n const name = message.name;\n if (name != null && name.length > 0) {\n toolNames.add(name);\n }\n }\n }\n\n const toolList = toolNames.size > 0 ? [...toolNames].join(', ') : 'none';\n return [\n '[Emergency Context Summary]',\n `Original request: ${firstUserContent}`,\n `Last response: ${lastAIContent}`,\n `Tools used: ${toolList}`,\n `Messages compacted: ${messages.length}`,\n ].join('\\n');\n}\n\nexport function validateSummarySize(\n summary: string,\n budget: number,\n tokenCounter: TokenCounter\n): boolean {\n const count = tokenCounter(new HumanMessage(summary));\n return count <= budget;\n}\n\nexport async function summarize(\n messages: BaseMessage[],\n callback: (prompt: string, maxTokens: number) => Promise,\n config?: SummarizeConfig\n): Promise {\n const messageCount = messages.length;\n const maxOutputTokens = config?.maxOutputTokens ?? 1024;\n\n // Tier 1: Full structured summary\n try {\n const conversation = formatMessagesForSummary(messages);\n const prompt = buildFullSummaryPrompt(conversation, config);\n const result = await callback(prompt, maxOutputTokens);\n\n if (result != null && result.length > 0) {\n if (\n config?.summaryBudget != null &&\n config.summaryBudget > 0 &&\n config.tokenCounter != null\n ) {\n if (\n validateSummarySize(result, config.summaryBudget, config.tokenCounter)\n ) {\n return {\n summary: result,\n tier: 'full',\n messagesCompacted: messageCount,\n };\n }\n } else {\n return {\n summary: result,\n tier: 'full',\n messagesCompacted: messageCount,\n };\n }\n }\n } catch {\n // Fall through to Tier 2\n }\n\n // Tier 2: Simple summary\n try {\n const conversation = formatMessagesForSummary(messages);\n const prompt = buildSimpleSummaryPrompt(conversation);\n const result = await callback(prompt, SIMPLE_MAX_TOKENS);\n\n if (result != null && result.length > 0) {\n return {\n summary: result,\n tier: 'simple',\n messagesCompacted: messageCount,\n };\n }\n } catch {\n // Fall through to Tier 3\n }\n\n // Tier 3: Emergency (no LLM)\n const summary = createEmergencySummary(messages);\n return { summary, tier: 'emergency', messagesCompacted: messageCount 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