feat: implement interactive Knowledge Graph visualization with AI-driven content analysis and handbook synchronization tools

src/lib/extractionPipeline.js

@@ -24,8 +24,48 @@ ALWAYS return a valid JSON object in the following format:
     }
   ]
 }
+}
 Return JSON only. No markdown blocks or other text.`;
 
+const HANDBOOK_SYSTEM_PROMPT = `You are analyzing an update to the Respellion Employee Handbook.
+Your task is to identify changes and extract structural knowledge.
+
+CRITICAL INSTRUCTION:
+You must explicitly identify and create relations between Roles, Processes, and Concepts.
+Every Process must have a Role attached (who does it).
+Every Concept must have a relation to a Process or Role.
+
+Return a JSON object:
+{
+  "topics": [
+    { "id": "...", "label": "...", "type": "role | process | concept", "description": "...", "metadata": { "source": "github_handbook" } }
+  ],
+  "relations": [
+    { "source": "role-id", "target": "process-id", "type": "executes | related_to | depends_on | part_of", "description": "Brief metadata about this specific relation" }
+  ]
+}
+Return JSON only. No markdown blocks or other text.`;
+
+export async function analyzeHandbookDelta(fileContent, filePath) {
+  try {
+    const responseText = await anthropicApi.generateContent(HANDBOOK_SYSTEM_PROMPT, `Analyze the following handbook file update (${filePath}):\n\n${fileContent}`);
+
+    let extractedData;
+    try {
+      const jsonMatch = responseText.match(/\{[\s\S]*\}/);
+      const jsonStr = jsonMatch ? jsonMatch[0] : responseText;
+      extractedData = JSON.parse(jsonStr);
+    } catch (e) {
+      console.error('[Pipeline] AI returned non-JSON response for handbook delta:', responseText?.substring(0, 500));
+      throw new Error(`AI response was not valid JSON. The model responded with: "${responseText?.substring(0, 120)}..."`);
+    }
+
+    await mergeKnowledgeGraph(extractedData);
+    return { success: true, data: extractedData };
+  } catch (error) {
+    throw error;
+  }
+}
 export async function processSourceText(textContent, sourceName) {
   // Deduplicate: skip if a source with the same name was already successfully processed
   const existing = await db.getSources();
@@ -71,7 +111,16 @@ async function mergeKnowledgeGraph(newData) {
 
   if (newData.topics && Array.isArray(newData.topics)) {
     for (const t of newData.topics) {
-      if (!topicsMap.has(t.id)) {
+      if (topicsMap.has(t.id)) {
+        // Upsert: merge new data into existing topic
+        const existing = topicsMap.get(t.id);
+        topicsMap.set(t.id, { 
+          ...existing, 
+          ...t, 
+          // Keep existing description if new one is empty, or combine them if needed. Here we prefer the new one.
+          description: t.description || existing.description 
+        });
+      } else {
         topicsMap.set(t.id, t);
       }
     }