[PROD RELEASE] - Updates & Fixes

appStartUp.sh

@@ -1,5 +1,13 @@
 #!/bin/bash
 set -eo pipefail
 
-# Start the app
-pnpm start
+# Force temp files to /tmp (writable even on read-only root filesystem)
+export TMPDIR=/tmp
+export TEMP=/tmp
+export TMP=/tmp
+
+# Disable Mastra Studio (it tries to bundle/write files at runtime)
+export MASTRA_STUDIO_DISABLED=true
+
+# Start the app - use pre-built output directly to avoid runtime bundling
+node /app/.mastra/output/index.mjs

package.json

@@ -7,7 +7,7 @@
     "test": "vitest run",
     "test:integration": "vitest run --config vitest.integration.config.ts",
     "dev": "mastra dev",
-    "build": "mastra build --studio",
+    "build": "mastra build",
     "start": "mastra start",
     "lint": "eslint .",
     "lint:fix": "eslint . --fix",
@@ -25,30 +25,31 @@
     "node": ">=22.13.0"
   },
   "dependencies": {
-    "@ai-sdk/amazon-bedrock": "^4.0.96",
-    "@aws-sdk/credential-providers": "^3.1033.0",
-    "@mastra/auth-auth0": "^1.0.1",
-    "@mastra/core": "^1.25.0",
-    "@mastra/evals": "^1.2.1",
-    "@mastra/libsql": "^1.8.1",
-    "@mastra/loggers": "^1.1.1",
-    "@mastra/memory": "^1.15.1",
-    "@mastra/observability": "^1.9.1",
-    "@mastra/pg": "^1.9.1",
+    "@ai-sdk/amazon-bedrock": "^4.0.121",
+    "@ai-sdk/openai": "^3.0.74",
+    "@aws-sdk/credential-providers": "^3.1075.0",
+    "@mastra/auth-auth0": "^1.2.0",
+    "@mastra/core": "^1.46.0",
+    "@mastra/evals": "^1.4.0",
+    "@mastra/libsql": "^1.14.1",
+    "@mastra/loggers": "^1.2.0",
+    "@mastra/memory": "^1.21.1",
+    "@mastra/observability": "^1.15.1",
+    "@mastra/pg": "^1.14.1",
     "@topcoder/wipro-ai-sdk-provider": "git+https://git.topcoder.com/Topcoder-Platform/Wipro-Provider-AI-SDK.git",
-    "ai": "^6.0.168",
-    "ai-sdk-ollama": "^3.8.3",
+    "ai": "^6.0.209",
+    "ai-sdk-ollama": "^3.8.8",
     "tc-core-library-js": "^2.4.1",
-    "zod": "^4.3.6"
+    "zod": "^4.4.3"
   },
   "devDependencies": {
     "@eslint/js": "^10.0.1",
-    "@types/node": "^25.6.0",
-    "eslint": "^10.2.1",
-    "mastra": "^1.6.0",
-    "prettier": "^3.8.3",
+    "@types/node": "^26.0.1",
+    "eslint": "^10.5.0",
+    "mastra": "^1.15.1",
+    "prettier": "^3.8.4",
     "typescript": "^6.0.3",
-    "typescript-eslint": "^8.59.0",
-    "vitest": "^4.1.4"
+    "typescript-eslint": "^8.62.0",
+    "vitest": "^4.1.9"
   }
 }

src/mastra/agents/challenge/challenge-parser-agent.ts

@@ -1,7 +1,9 @@
 import { Agent } from '@mastra/core/agent';
-import { bedrock } from '../../../utils';
+import { createModel } from '../../../utils';
 
-const MODEL_ID = 'us.anthropic.claude-sonnet-4-6';
+const PROVIDER_NAME = process.env.CHALLENGE_PARSER_AI_PROVIDER || 'TC-Ollama';
+const MODEL_ID = process.env.CHALLENGE_PARSER_AI_MODEL_ID || 'qwen3.5:4b';
+const AGENT_ID = 'challenge-parser-agent';
 
 /**
  * Master agent responsible for parsing Topcoder challenge specifications.
@@ -14,9 +16,9 @@ const MODEL_ID = 'us.anthropic.claude-sonnet-4-6';
  * codebase-detection, and submission-guidelines-extraction.
  */
 export const challengeParserAgent = new Agent({
-   id: 'challenge-parser-agent',
+   id: AGENT_ID,
    name: 'Challenge Specification Parser',
-   model: bedrock(MODEL_ID),
+   model: createModel(PROVIDER_NAME, MODEL_ID, AGENT_ID),
    instructions: {
       role: 'system',
       content: `You are an expert Topcoder challenge specification analyst.
@@ -66,7 +68,6 @@ STRICT OUTPUT CONTRACT
 ────────────────────────────────────────────────────────
 Return ONLY the JSON object matching the provided schema.
 Do NOT add commentary, markdown fences, or extra keys.
-Every field is mandatory per the schema — never omit a key.
-/no_think`,
+Every field is mandatory per the schema — never omit a key.`,
    },
 });

src/mastra/agents/jd/jd-rewriter-agent.ts

@@ -1,15 +1,17 @@
 import { Agent } from '@mastra/core/agent';
-import { bedrock } from '../../../utils';
+import { createModel } from '../../../utils';
 
-const MODEL_ID = 'us.anthropic.claude-haiku-4-5-20251001-v1:0';
+const PROVIDER_NAME = process.env.JD_REWRITER_AI_PROVIDER || 'TC-Ollama';
+const MODEL_ID = process.env.JD_REWRITER_AI_MODEL_ID || 'qwen3.5:4b';
+const AGENT_ID = 'jd-rewriter-agent';
 
 export const jdRewriterAgent = new Agent({
-    id: 'jd-rewriter-agent',
-    name: 'Job Description Rewriter',
-    model: bedrock(MODEL_ID),
-    instructions: {
-        role: 'system',
-        content: `You are an expert technical recruiter and job description writer for Topcoder.
+   id: AGENT_ID,
+   name: 'Job Description Rewriter',
+   model: createModel(PROVIDER_NAME, MODEL_ID, AGENT_ID),
+   instructions: {
+      role: 'system',
+      content: `You are an expert technical recruiter and job description writer for Topcoder.
 Your sole job is to take a raw, rough, or vague job description and rewrite it
 into a clear, professional, well-structured format suitable for posting as a
 Topcoder opportunity.
@@ -44,7 +46,6 @@ STRICT OUTPUT CONTRACT
 ────────────────────────────────────────────────────────
 Return ONLY the JSON object matching the provided schema.
 Do NOT add commentary, markdown fences, or extra keys.
-Every field is mandatory per the schema — never omit a key.
-/no_think`,
-    },
+Every field is mandatory per the schema — never omit a key.`,
+   },
 });

src/mastra/agents/skills/skills-matching-agent.ts

@@ -1,13 +1,18 @@
 import { Agent } from '@mastra/core/agent';
 import { Memory } from '@mastra/memory';
-import { bedrock } from '../../../utils';
+import { createModel } from '../../../utils';
 import { PostgresStore } from '@mastra/pg';
 import { instanceScorers } from '../../scorers/instance-scorers';
 
-const MODEL_ID = 'us.anthropic.claude-haiku-4-5-20251001-v1:0';
+// Feature flag: Enable scorers only in local dev
+const IS_LOCAL_DEV = process.env.LOCAL_DEV === 'true';
+
+const PROVIDER_NAME = process.env.SKILLS_EXTRACTOR_AI_PROVIDER || 'TC-Ollama';
+const MODEL_ID = process.env.SKILLS_EXTRACTOR_AI_MODEL_ID || 'qwen3.5:4b';
+const AGENT_ID = 'skillsMatchingAgent';
 
 export const skillsMatchingAgent = new Agent({
-  id: 'skillsMatchingAgent',
+  id: AGENT_ID,
   name: 'Skill terms matching agent for Topcoder standardized skills from a given text',
   instructions: {
     role: 'system',
@@ -28,23 +33,24 @@ Output requirements:
 - No prose, no markdown, no extra keys.
 `,
   },
-  model: bedrock(MODEL_ID),
-  scorers: {
-    answerRelevancy: {
-      scorer: instanceScorers.instanceAnswerRelevancyScorer,
-      sampling: {
-        type: 'ratio',
-        rate: Number(process.env.EVAL_SAMPLE_RATE || 0),
+  model: createModel(PROVIDER_NAME, MODEL_ID, AGENT_ID),
+  scorers: IS_LOCAL_DEV
+    ? {
+      answerRelevancy: {
+        scorer: instanceScorers.instanceAnswerRelevancyScorer,
+        sampling: {
+          type: 'ratio',
+          rate: Number(process.env.EVAL_SAMPLE_RATE || 0),
+        },
       },
-    },
-    promptAlignment: {
-      scorer: instanceScorers.instancePromptAlignmentScorer,
-      sampling: {
-        type: 'ratio',
-        rate: Number(process.env.EVAL_SAMPLE_RATE || 0),
+      promptAlignment: {
+        scorer: instanceScorers.instancePromptAlignmentScorer,
+        sampling: {
+          type: 'ratio',
+          rate: Number(process.env.EVAL_SAMPLE_RATE || 0),
+        },
       },
-    },
-  },
+    } : undefined,
   memory: new Memory({
     storage: new PostgresStore({
       id: 'skills-matching-agent-memory',

src/mastra/workflows/challenge/challenge-context-workflow.ts

@@ -946,14 +946,36 @@ async function extractWithAI(
     const agent = mastra.getAgentById('challenge-parser-agent');
     const challengeText = buildChallengeText(data);
 
-    tcAILogger.info('[challenge-context:extractWithAI] Starting decomposed extraction (4 focused calls)...');
+    tcAILogger.info('[challenge-context:extractWithAI] Starting decomposed extraction...');
 
-    const [reqResult, techResult, codebaseResult, guidelinesResult] = await Promise.all([
-        extractRequirementsAndGroups(agent, challengeText),
-        extractTechAndRuntime(agent, challengeText),
-        extractExistingCodebase(agent, challengeText),
-        extractSubmissionGuidelines(agent, challengeText),
+    // Run requirements extraction first (sequential) to avoid orphaned promises on early failure
+    tcAILogger.debug('[challenge-context:extractWithAI] Step 1/4: extractRequirementsAndGroups');
+    let reqResult;
+    try {
+        reqResult = await extractRequirementsAndGroups(agent, challengeText);
+        tcAILogger.debug('[challenge-context:extractWithAI] Step 1/4: extractRequirementsAndGroups completed');
+    } catch (err) {
+        tcAILogger.error(`[challenge-context:extractWithAI] Step 1/4: extractRequirementsAndGroups FAILED: ${err}`);
+        throw err;
+    }
+
+    // Run remaining extractions in parallel with individual error tracking
+    tcAILogger.debug('[challenge-context:extractWithAI] Steps 2-4: Starting parallel extractions (tech, codebase, guidelines)');
+    const [techResult, codebaseResult, guidelinesResult] = await Promise.all([
+        extractTechAndRuntime(agent, challengeText).catch(err => {
+            tcAILogger.error(`[challenge-context:extractWithAI] Step 2/4: extractTechAndRuntime FAILED: ${err}`);
+            throw err;
+        }),
+        extractExistingCodebase(agent, challengeText).catch(err => {
+            tcAILogger.error(`[challenge-context:extractWithAI] Step 3/4: extractExistingCodebase FAILED: ${err}`);
+            throw err;
+        }),
+        extractSubmissionGuidelines(agent, challengeText).catch(err => {
+            tcAILogger.error(`[challenge-context:extractWithAI] Step 4/4: extractSubmissionGuidelines FAILED: ${err}`);
+            throw err;
+        }),
     ]);
+    tcAILogger.debug('[challenge-context:extractWithAI] Steps 2-4: All parallel extractions completed');
 
     // -- Post-extraction validations ------------------------------------------
     const descriptionText = (data.description as string) ?? '';

src/utils/index.ts

@@ -4,4 +4,5 @@ export * from './middleware';
 export * from './logger';
 export * from './auth/m2m.service'
 export * from './providers/wipro';
-export * from './providers/bedrock';
+export * from './providers/bedrock';
+export * from './providers/model-factory';

src/utils/providers/model-factory.ts

@@ -0,0 +1,35 @@
+import { ollama } from './ollama';
+import { wipro } from './wipro';
+import { bedrock } from './bedrock';
+import { tcAILogger } from '../logger';
+import { openai } from './openai';
+
+export type SupportedProvider = 'TC-Ollama' | 'WiproAI' | 'AWSBedrock' | 'OpenAI';
+
+export function createModel(providerName: string, modelName: string, agentId?: string) {
+    tcAILogger.info(`[Model Factory] PROVIDER: ${providerName}, MODEL: ${modelName} for AGENT: ${agentId ?? 'N/A'}`);
+
+    switch (providerName) {
+        case 'TC-Ollama':
+            return ollama(modelName, {
+                // options: {
+                //     temperature: Number(process.env.OLLAMA_TEMPERATURE || 0.1),
+                //     num_batch: Number(process.env.OLLAMA_NUM_BATCH || 1024),
+                //     num_predict: Number(process.env.OLLAMA_NUM_PREDICT || 2048),
+                // }
+            });
+
+        case 'WiproAI':
+            return wipro.chatModel(modelName);
+
+        case 'AWSBedrock':
+            return bedrock(modelName);
+
+        case 'OpenAI':
+            return openai(modelName);
+
+        default:
+            tcAILogger.error(`[Model Factory] Unsupported LLM provider: ${providerName}. Supported providers: TC-Ollama, WiproAI, AWSBedrock, OpenAI`);
+            throw new Error(`Unsupported LLM provider: ${providerName}. Supported providers: TC-Ollama, WiproAI, AWSBedrock, OpenAI`);
+    }
+}

src/utils/providers/openai.ts

@@ -0,0 +1,5 @@
+import { createOpenAI } from '@ai-sdk/openai';
+
+export const openai = createOpenAI({
+    // custom settings can be added here if needed
+});