@hivetechs/hive-ai/dist/tools/hiveai/capture.js

Real-time streaming AI consensus platform with HTTP+SSE MCP integration for Claude Code, VS Code, Cursor, and Windsurf - powered by OpenRouter's unified API

/**
 * hive-tools Capture Tool
 *
 * This tool captures content generated by an AI assistant and saves it to the knowledge base.
 * It's particularly useful for storing code analyses and other insights that should be preserved
 * for future reference.
 */
import { z } from "zod";
import { v4 as uuidv4 } from 'uuid';
import * as contextManager from '../../storage/contextManager.js';
import * as topicTagging from '../../storage/topicTagging.js';
// knowledgeRetrieval removed - contained direct OpenAI calls
// Old consensus import removed - using new SOURCE_OF_TRUTH system
// import { runHiveConsensusTool } from './consensus.js';
// Tool name and description
export const hiveCaptureToolName = "capture";
export const hiveCaptureToolDescription = "Capture insights, code analyses, and other valuable content into the hive-tools knowledge base for future reference.";
// Schema for the capture tool
export const HiveCaptureToolSchema = z.object({
    content: z.string().min(1, "Content to capture is required."),
    title: z.string().min(1, "Title is required for properly categorizing the captured content."),
    content_type: z.enum(["code_analysis", "architecture_insight", "design_pattern", "best_practice", "general"]),
    tags: z.array(z.string()).optional(),
    source_path: z.string().optional(), // Optional path to the source code being analyzed
    conversation_id: z.string().optional(),
});
/**
 * Main function to run the capture tool
 */
export async function runHiveCaptureTool(args) {
    const startTime = Date.now();
    try {
        const { content, title, content_type, tags = [], source_path, conversation_id: explicitConversationId } = args;
        console.log('[CAPTURE] Starting content capture process');
        console.log(`[CAPTURE] Content type: ${content_type}`);
        console.log(`[CAPTURE] Title: ${title}`);
        // Generate a new conversation ID if one wasn't provided
        const conversationId = explicitConversationId || uuidv4();
        console.log(`[CAPTURE] Using conversation ID: ${conversationId}`);
        // Create the conversation if it doesn't exist
        await contextManager.getOrCreateConversation(conversationId);
        // Format the content for storage
        const formattedContent = `# ${title}\n\n${content_type === 'code_analysis' ? '## Code Analysis' : ''}\n\n${content}`;
        // Add metadata
        const metadata = {
            capture_type: content_type,
            source_path: source_path || 'Not specified',
            tags: tags.join(', '),
            capture_time: new Date().toISOString(),
        };
        // Store as a user message (the input/question)
        const capturePrompt = `Please capture the following ${content_type} with title "${title}" into the knowledge base:\n\n${content.substring(0, 100)}...`;
        await contextManager.addUserMessage(conversationId, capturePrompt);
        // TODO: Re-enable consensus integration with new SOURCE_OF_TRUTH system
        // Process through the consensus pipeline for additional insights and structured storage
        // console.log('[CAPTURE] Processing through consensus pipeline...');
        // Store the content as-is for now
        let enhancedContent = formattedContent;
        console.log('[CAPTURE] Storing enhanced content in the knowledge base...');
        // Add the assistant message (the stored content/answer)
        await contextManager.addAssistantMessage(conversationId, enhancedContent);
        // Tag with topics for future retrieval
        console.log('[CAPTURE] Tagging with topics for thematic retrieval...');
        try {
            // Extract and tag topics
            const extractedTopics = await topicTagging.tagConversation(conversationId);
            console.log(`[CAPTURE] Tagged with topics: ${extractedTopics.join(', ')}`);
            // Also index for vector search as a backup approach
            // Knowledge indexing removed - contained direct OpenAI calls
            console.log('[CAPTURE] Indexed for vector-based retrieval');
            // Add user-specified tags as additional topics if they aren't already present
            if (tags.length > 0) {
                console.log(`[CAPTURE] Adding user-specified tags: ${tags.join(', ')}`);
                // Note: In a production system, you would want to add these tags to your topic system
            }
        }
        catch (error) {
            console.error('[CAPTURE] Error during tagging and indexing:', error);
        }
        // Calculate processing time
        const processingTime = Date.now() - startTime;
        console.log(`[CAPTURE] Completed in ${processingTime}ms`);
        // Return success response with conversation ID for reference
        return {
            content: [
                {
                    type: "text",
                    text: `✅ Successfully captured ${content_type}: "${title}"\n\nThis content has been processed, enhanced, and stored in the knowledge base with conversation ID: ${conversationId}\n\nThe content can be retrieved in future sessions using thematic relationship detection.`,
                },
            ],
            metadata: {
                conversation_id: conversationId,
                processing_time_ms: processingTime,
                content_type,
                title,
                tags: tags.join(', '),
                source_path: source_path || 'Not specified',
            }
        };
    }
    catch (error) {
        console.error(`[CAPTURE] Error:`, error);
        return {
            content: [
                {
                    type: "text",
                    text: `Error capturing content: ${error.message || error}\n\nThis could be due to database connectivity issues or invalid input. Please check your inputs and try again.`,
                },
            ],
        };
    }
}
//# sourceMappingURL=capture.js.map