feat: fix RAG pipelines, Beep Graph branding, PWA, and ambient glow UI

Pipeline fixes:
- Fix agent getting empty response from graph-rag by combining answer +
  explain data in single message (RequestResponse returns first msg)
- Fix Doc RAG pipeline: add content field to Qdrant doc payload, seed 10
  document chunks, fix type mismatches across base/flow/client
- Forward explainability events from agent's KnowledgeQuery to client
- Add "agent" to TERM_BEARING_RESPONSE_SERVICES for triple translation
- Fix embeddings env var (OLLAMA_URL), user/collection threading, edge
  scoring threshold, and various protocol mismatches

Branding:
- Rename TrustGraph → Beep Graph (title, sidebar, settings, about)
- Custom lambda + ThugLife pixel glasses SVG logo component
- Forest green color palette (brand-50 through brand-900)
- SVG favicon + PNG icons (16/32/180/192/512)
- PWA manifest with service worker for offline shell caching
- Splash screen with animated logo pulse on app load
- Ambient glow background with drifting green radial blobs

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

ts/packages/flow/src/query/embeddings/qdrant-doc-service.ts

@@ -55,13 +55,17 @@ export class DocEmbeddingsQueryService extends FlowProcessor {
       for (const vector of msg.vectors ?? []) {
         const matches = await this.query.query({
           vector,
-          user: "default",
+          user: msg.user ?? "default",
           collection,
           limit: msg.limit ?? 10,
         });
 
         for (const match of matches) {
-          allChunks.push({ chunkId: match.chunkId, score: match.score });
+          allChunks.push({
+            chunkId: match.chunkId,
+            score: match.score,
+            content: match.content,
+          });
         }
       }
 

ts/packages/flow/src/query/embeddings/qdrant-doc.ts

@@ -17,6 +17,7 @@ export interface QdrantDocQueryConfig {
 export interface ChunkMatch {
   chunkId: string;
   score: number;
+  content?: string;
 }
 
 export interface DocEmbeddingsQueryRequest {
@@ -71,6 +72,7 @@ export class QdrantDocEmbeddingsQuery {
         chunks.push({
           chunkId,
           score: point.score,
+          content: (payload?.content as string) ?? undefined,
         });
       }
     }

ts/packages/flow/src/query/embeddings/qdrant-graph-service.ts

@@ -47,8 +47,9 @@ export class GraphEmbeddingsQueryService extends FlowProcessor {
     if (!requestId) return;
 
     const producer = flowCtx.flow.producer<GraphEmbeddingsResponse>("graph-embeddings-response");
-    const user = msg.collection ?? "default";
+    const user = msg.user ?? "default";
     const collection = msg.collection ?? "default";
+    console.log(`[GraphEmbeddingsQuery] Request: user=${user}, collection=${collection}, vectors=${msg.vectors?.length ?? 0}, limit=${msg.limit}`);
 
     try {
       // Query for each vector and aggregate results