pull:初次提交

n8n-n8n-1.109.2/packages/@n8n/ai-workflow-builder.ee/src/chains/conversation-compact.ts

@@ -0,0 +1,78 @@
+import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import type { BaseMessage } from '@langchain/core/messages';
+import { AIMessage, HumanMessage } from '@langchain/core/messages';
+import { PromptTemplate } from '@langchain/core/prompts';
+import z from 'zod';
+
+const compactPromptTemplate = PromptTemplate.fromTemplate(
+	`Please summarize the following conversation between a user and an AI assistant building an n8n workflow:
+
+<previous_summary>
+{previousSummary}
+</previous_summary>
+
+<conversation>
+{conversationText}
+</conversation>
+
+Provide a structured summary that captures the key points, decisions made, current state of the workflow, and suggested next steps.`,
+);
+
+export async function conversationCompactChain(
+	llm: BaseChatModel,
+	messages: BaseMessage[],
+	previousSummary: string = '',
+) {
+	// Use structured output for consistent summary format
+	const CompactedSession = z.object({
+		summary: z.string().describe('A concise summary of the conversation so far'),
+		key_decisions: z.array(z.string()).describe('List of key decisions and actions taken'),
+		current_state: z.string().describe('Description of the current workflow state'),
+		next_steps: z.string().describe('Suggested next steps based on the conversation'),
+	});
+
+	const modelWithStructure = llm.withStructuredOutput(CompactedSession);
+
+	// Format messages for summarization
+	const conversationText = messages
+		.map((msg) => {
+			if (msg instanceof HumanMessage) {
+				// eslint-disable-next-line @typescript-eslint/no-base-to-string, @typescript-eslint/restrict-template-expressions
+				return `User: ${msg.content}`;
+			} else if (msg instanceof AIMessage) {
+				if (typeof msg.content === 'string') {
+					return `Assistant: ${msg.content}`;
+				} else {
+					return 'Assistant: Used tools';
+				}
+			}
+
+			return '';
+		})
+		.filter(Boolean)
+		.join('\n');
+
+	const compactPrompt = await compactPromptTemplate.invoke({
+		previousSummary,
+		conversationText,
+	});
+
+	const structuredOutput = await modelWithStructure.invoke(compactPrompt);
+
+	const formattedSummary = `## Previous Conversation Summary
+
+**Summary:** ${structuredOutput.summary}
+
+**Key Decisions:**
+${(structuredOutput.key_decisions as string[]).map((d: string) => `- ${d}`).join('\n')}
+
+**Current State:** ${structuredOutput.current_state}
+
+**Next Steps:** ${structuredOutput.next_steps}`;
+
+	return {
+		success: true,
+		summary: structuredOutput,
+		summaryPlain: formattedSummary,
+	};
+}