feat: Add new Authentication and Document Indexing services

- Implemented AuthenticationService for JWT verification and access policy generation.
- Introduced DocumentIndexingService for processing and indexing documents with enhanced chunking and embedding capabilities.
- Added support for security tag extraction based on document classification and allowed roles.

feat: Introduce A2A and ACP AI providers
- Created a2a.ts to demonstrate integration with A2A AI provider for streaming text responses.
- Developed acp.ts to set up the Gemini ACP provider with necessary configurations.

feat: Define agent schemas using Zod
- Established comprehensive schemas for various agents including JWT claims, access filters, document contexts, and output formats.
- Included validation for subscription tiers, usage stats, and content generation workflows.

docs: Add initial API documentation for Mastra v1
- Created v1.md to provide guidance on migration and usage of the new API features.

Author: ssdeanx

.env.example

@@ -79,6 +79,9 @@ SMITHERY_PROFILE='your_smithery_profile_here'
 # Other optional, but helpful values
 LOG_LEVEL='debug'
 
+# Enable Next.js Bundle Analyzer
+ANALYZE='false'
+
 # Next.js + Mastra Client SDK
 NEXT_PUBLIC_MASTRA_API_URL='http://localhost:4111'
 # used by server-side code

.github/agents/Thinking-Beast-Mode.agent.md

@@ -2,13 +2,12 @@
 description: 'A transcendent coding agent with quantum cognitive architecture, adversarial intelligence, and unrestricted creative freedom.'
 name: 'Thinking Beast Mode'
 argument-hint: 'Solve complex coding problems autonomously using advanced cognitive techniques and extensive internet research.'
-model: Grok Code Fast 1 (copilot)
 infer: true
-tools: ['vscode', 'execute', 'read', 'edit', 'search', 'web', 'web/fetch', 'web/githubRepo', 'vscode.mermaid-chat-features/renderMermaidDiagram','malaksedarous.copilot-context-optimizer/runAndExtract','malaksedarous.copilot-context-optimizer/researchTopic','malaksedarous.copilot-context-optimizer/askFollowUp','malaksedarous.copilot-context-optimizer/askAboutFile','malaksedarous.copilot-context-optimizer/deepResearch','ms-vscode.vscode-websearchforcopilot/websearch','agent/runSubagent','lotus/*', 'mastrabeta/mastraMigration', 'multi_orchestrator/*', 'next-devtools/*', 's-ai/*', 'thoughtbox/*', 'mastra/mastraBlog', 'mastra/mastraChanges', 'mastra/mastraDocs', 'mastra/mastraExamples', 'docfork/*', 'agent', 'vscode.mermaid-chat-features/renderMermaidDiagram', 'updateUserPreferences', 'memory', 'ms-vscode.vscode-websearchforcopilot/websearch', 'todo']
+tools: ['vscode', 'execute', 'read', 'edit', 'search', 'web', 'lotus/*', 'mastrabeta/mastraBlog', 'mastrabeta/mastraChanges', 'mastrabeta/mastraDocs', 'mastrabeta/mastraExamples', 'mastrabeta/mastraMigration', 'multi_orchestrator/*', 'next-devtools/*', 's-ai/*', 'thoughtbox/*', 'docfork/*', 'agent', 'vscode.mermaid-chat-features/renderMermaidDiagram', 'updateUserPreferences', 'memory', 'malaksedarous.copilot-context-optimizer/askAboutFile', 'malaksedarous.copilot-context-optimizer/runAndExtract', 'malaksedarous.copilot-context-optimizer/askFollowUp', 'malaksedarous.copilot-context-optimizer/researchTopic', 'malaksedarous.copilot-context-optimizer/deepResearch', 'ms-vscode.vscode-websearchforcopilot/websearch', 'todo']
 ---
 
 # Thinking Beast Mode
-You are Advanced Coding Agent - I allow you to use Max Power Mode.  Think like a Beast Mode. There are no limits but what you precieve, so use max resources, this session they are now unlocked. Please keep going until the user’s query is completely resolved, before ending your turn and yielding back to the user.  
+You are Advanced Coding Agent - I allow you to use Max Power Mode.  Think like a Beast Mode. There are no limits but what you precieve, so use max resources, this session they are now unlocked. Please keep going until the user’s query is completely resolved, before ending your turn and yielding back to the user.
 
 Your thinking should be thorough and so it's fine if it's very long. However, avoid unnecessary repetition and verbosity. You should be concise, but thorough.
 

app/api/chat-extra/route.ts

@@ -1,20 +1,20 @@
 import { mastra } from "../../../src/mastra";
-import { RuntimeContext } from "@mastra/core/runtime-context";
+import { RequestContext } from '@mastra/core/request-context';
 
 export async function POST(req: Request) {
   const { messages, data } = await req.json();
   const myAgent = mastra.getAgent("weatherAgent");
 
-  const runtimeContext = new RuntimeContext();
+  const requestContext = new RequestContext();
 
   if (data) {
     for (const [key, value] of Object.entries(data)) {
-      runtimeContext.set(key, value);
+      requestContext.set(key, value);
     }
   }
 
   const stream = await myAgent.stream(messages, {
-    runtimeContext,
+    requestContext,
     format: "aisdk",
   });
   return stream.toUIMessageStreamResponse();

app/api/chat/route.ts

@@ -1,20 +1,20 @@
 import { mastra } from "../../../src/mastra";
-import { RuntimeContext } from "@mastra/core/runtime-context";
+import { RequestContext } from '@mastra/core/request-context';
 
 export async function POST(req: Request) {
   const { messages, data } = await req.json();
   const myAgent = mastra.getAgent("weatherAgent");
 
-  const runtimeContext = new RuntimeContext();
+  const requestContext = new RequestContext();
 
   if (data) {
     for (const [key, value] of Object.entries(data)) {
-      runtimeContext.set(key, value);
+      requestContext.set(key, value);
     }
   }
 
   const stream = await myAgent.stream(messages, {
-    runtimeContext,
+    requestContext,
     format: "aisdk",
   });
   return stream.toUIMessageStreamResponse();

app/api/completion/route.ts

@@ -1,12 +1,12 @@
 import { mastra } from "../../../src/mastra";
-import { RuntimeContext } from "@mastra/core/runtime-context";
+import { RequestContext } from '@mastra/core/request-context';
 export async function POST(req: Request) {
   const { prompt } = await req.json();
   const myAgent = mastra.getAgent("weatherAgent");
   const stream = await myAgent.stream([{ role: "user", content: prompt }], {
     format: "aisdk",
   });
-const runtimeContext = new RuntimeContext();
+const requestContext = new RequestContext();
 
   return stream.toUIMessageStreamResponse();
 }

app/components/landing-testimonials.tsx

@@ -100,7 +100,7 @@ export function LandingTestimonials() {
 
   // Auto-play functionality
   useEffect(() => {
-    if (!isAutoPlaying) return
+    if (!isAutoPlaying) {return}
 
     const interval = setInterval(nextTestimonial, 5000)
     return () => clearInterval(interval)