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Fixes #52\n\nSummary: Adds tests for and . The test file sets required env vars before importing modules that parse to avoid errors in test environment.

Copilot AI review requested due to automatic review settings January 3, 2026 18:05
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Summary of Changes

Hello @morningstarxcdcode, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request lays the groundwork for the LocalMind backend, a platform designed to offer flexible AI model interaction and data processing. It delivers a full-fledged user authentication system, integrates with various AI providers like Google Gemini, Groq, and Ollama, and provides a structured way for users to configure their AI agents. A key feature is the AI-powered processing of uploaded datasets for intelligent information extraction. The changes also include essential project setup, environment management, and a suite of tests to ensure the stability of these new functionalities.

Highlights

  • User Authentication and Management: Implemented a comprehensive user module including registration, login, profile management, and API key generation, complete with JWT token handling and password hashing using Argon2.
  • AI Model Integrations: Introduced integrations for multiple AI providers: Google Gemini, Groq, and Ollama. This includes dedicated controllers, services, and utilities for interacting with these models, supporting both cloud and on-premise deployments.
  • AI Model Configuration: Developed a new module allowing users to configure their AI agents, specifying providers, model types, and system prompts, which are stored in a MongoDB database.
  • Intelligent Dataset Processing: Added functionality to upload and process datasets (e.g., CSV files) using AI. The system leverages a prompt template to intelligently extract and validate question-answer pairs from the uploaded data.
  • Robust Testing Framework: Integrated Jest for unit and integration testing across critical components, including specific tests for UserUtils token generation/verification and OllamaService vector embeddings, ensuring reliability and correctness.
  • Infrastructure and Utilities: Established core backend infrastructure with Express.js, Mongoose for MongoDB connectivity, Zod for environment variable validation, and a Cloudflare tunnel setup script for local development exposure.

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Code Review

This pull request, titled "test(user): add unit tests for UserUtils token generation and verification", introduces a vast number of files, effectively creating the entire backend application. While the added tests for UserUtils are a good start, the scope of this PR is much larger than described, making it difficult to review thoroughly. In the future, please try to keep pull requests focused on a single feature or bug fix.

My review focuses on critical issues related to security, correctness, and maintainability. I've found several critical problems, including invalid package dependencies that will prevent the project from installing, use of hardcoded secrets, and significant bugs in business logic. Please address these high-priority issues.

Comment on lines 16 to 18
public async findAiModelConfigByUserId(id: string): Promise<IAiModelConfig | null> {
return await AiModelConfig.findById(id).exec()
}
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critical

The method findAiModelConfigByUserId is using findById, which searches by the document's _id. However, it's being called with a userId. This should be changed to findOne({ userId }) to correctly find the configuration document for a given user.

Suggested change
public async findAiModelConfigByUserId(id: string): Promise<IAiModelConfig | null> {
return await AiModelConfig.findById(id).exec()
}
public async findAiModelConfigByUserId(userId: string): Promise<IAiModelConfig | null> {
return await AiModelConfig.findOne({ userId }).exec()
}


ENCRYPTION_KEY: z.string(),

SERVER_HMAC_SECRET: z.string(),
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critical

The SERVER_HMAC_SECRET is a critical security variable and should be enforced to be present and have a minimum length to ensure strong keys are used. An empty string would be a security risk.

Suggested change
SERVER_HMAC_SECRET: z.string(),
SERVER_HMAC_SECRET: z.string().min(32, 'SERVER_HMAC_SECRET must be at least 32 characters long'),

.transform((v) => v === 'true')
.default(false),

JWT_SECRET: z.string(),
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critical

The JWT_SECRET is a critical security variable and should be enforced to be present and have a minimum length to ensure strong keys are used. An empty or short secret is a security risk.

Suggested change
JWT_SECRET: z.string(),
JWT_SECRET: z.string().min(32, 'JWT_SECRET must be at least 32 characters long'),

Comment on lines 1 to 68
{
"name": "localmind-backend",
"version": "1.0.0",
"main": "index.js",
"scripts": {
"test": "jest",
"start-tunnel": "lt --port 5000",
"setup:backend": "ts-node src/script/project-setup.ts",
"format": "prettier --write .",
"build": "tsc",
"dev": "ts-node-dev --respawn --transpile-only src/server.ts"
},
"repository": {
"type": "git",
"url": "git+https://github.com/NexGenStudioDev/LocalMind-Backend.git"
},
"author": "",
"license": "ISC",
"bugs": {
"url": "https://github.com/NexGenStudioDev/LocalMind-Backend/issues"
},
"homepage": "https://github.com/NexGenStudioDev/LocalMind-Backend#readme",
"description": "",
"devDependencies": {
"@babel/preset-typescript": "^7.27.1",
"@types/argon2": "^0.15.4",
"@types/bcrypt": "^6.0.0",
"@types/express": "^5.0.3",
"@types/node": "^24.7.2",
"@types/nodemailer": "^7.0.3",
"jest": "^30.2.0",
"prettier": "3.6.2",
"ts-jest": "^29.4.5",
"ts-node": "^10.9.2",
"ts-node-dev": "^2.0.0",
"typescript": "^5.9.3"
},
"dependencies": {
"@jest/globals": "^30.2.0",
"@langchain/community": "^0.3.57",
"@langchain/core": "^0.3.78",
"@langchain/google-genai": "^0.2.18",
"@langchain/groq": "^0.2.4",
"@langchain/ollama": "^0.2.4",
"@types/cookie-parser": "^1.4.9",
"@types/jsonwebtoken": "^9.0.10",
"@types/mongoose": "^5.11.97",
"@types/morgan": "^1.9.10",
"argon2": "^0.44.0",
"axios": "^1.12.2",
"bcrypt": "^6.0.0",
"chalk": "^5.6.2",
"cloudflared-tunnel": "^1.0.3",
"cookie-parser": "^1.4.7",
"d3-dsv": "^2.0.0",
"dotenv": "^17.2.3",
"express": "^5.1.0",
"figlet": "^1.9.3",
"jsonwebtoken": "^9.0.2",
"langchain": "^0.3.36",
"mongoose": "^8.19.1",
"morgan": "^1.10.1",
"ngrok": "5.0.0-beta.2",
"nodemailer": "^7.0.10",
"ora": "^9.0.0",
"zod": "^4.1.12"
}
}
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critical

Many of the dependency versions listed in package.json do not exist on the npm registry (e.g., @types/express@^5.0.3, jest@^30.2.0, axios@^1.12.2, mongoose@^8.19.1, etc.). This will prevent the project from being installed and run. Please correct the versions to valid, existing ones. You can use npm view <package-name> versions to check for available versions, or npm install <package-name>@latest to get the latest stable version.

Comment on lines 31 to 37
if (!existingConfig) {
CreateConfig = await AiModelConfigService.setupAiModelConfig({
userId: String(FindUserByToken._id),
agents: [{} as IAgent],
system_prompt,
})
}
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critical

Creating a new AiModelConfig with agents: [{} as IAgent] is incorrect. The IAgent interface and AgentSchema have required fields like provider, type, and model. This will lead to a database validation error. If a new configuration is being created, it should be with the validated agents from the request body.


describe('UserUtils token helpers', () => {
test('generateToken and verifyToken roundtrip', () => {
const payload = { userId: 'abc123', email: 'a@b.com', role: 'user' }
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medium

To align with the suggested change to use _id in JwtPayload, the test payload should be updated.

Suggested change
const payload = { userId: 'abc123', email: 'a@b.com', role: 'user' }
const payload = { _id: 'abc123', email: 'a@b.com', role: 'user' }

Comment on lines 24 to 39
public static verifyToken(token: string): IUser | null {
try {
const decoded = jwt.verify(token, this.JWT_SECRET)

if (typeof decoded === 'object' && decoded !== null) {
return {
email: decoded.email as string,
_id: decoded.userId as string,
role: decoded.role as string,
}
}

return null
} catch {
return null
}
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medium

To align with the suggested change to use _id in JwtPayload, this method should be updated to use decoded._id. Also, casting decoded to JwtPayload provides better type safety and removes the need for individual property casting.

Suggested change
public static verifyToken(token: string): IUser | null {
try {
const decoded = jwt.verify(token, this.JWT_SECRET)
if (typeof decoded === 'object' && decoded !== null) {
return {
email: decoded.email as string,
_id: decoded.userId as string,
role: decoded.role as string,
}
}
return null
} catch {
return null
}
public static verifyToken(token: string): IUser | null {
try {
const decoded = jwt.verify(token, this.JWT_SECRET) as JwtPayload
if (typeof decoded === 'object' && decoded !== null) {
return {
email: decoded.email as string,
_id: decoded._id as string,
role: decoded.role as string,
}
}
return null
} catch {
return null
}
}

Comment on lines +15 to +19
console.log('Ai_Response', Ai_Response)

SendResponse.success(res, 'AI response generated successfully', Ai_Response, 200)
} catch (err: any) {
console.log('err', err)
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medium

Debug console.log statements should be removed from the code before merging. For logging, a dedicated logger library should be used, which can be configured per environment.

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Pull request overview

This PR adds unit tests for UserUtils token generation and verification methods, along with a comprehensive backend setup including user authentication, AI model integration, and configuration management. The tests ensure JWT token operations work correctly by testing roundtrip token generation/verification and invalid token handling.

  • Unit tests for generateToken and verifyToken in UserUtils
  • Integration tests for user registration with database interaction
  • Complete backend infrastructure including user management, AI model services (Ollama, Groq, Google Gemini), and dataset processing

Reviewed changes

Copilot reviewed 59 out of 67 changed files in this pull request and generated 23 comments.

Show a summary per file
File Description
src/api/v1/user/__test__/user.utils.test.ts Adds unit tests for token generation and verification with proper env setup
src/api/v1/user/__test__/user.test.ts Adds integration tests for user registration endpoints
src/api/v1/user/user.utils.ts Implements JWT token helpers and user authentication utilities
src/api/v1/user/user.validator.ts Defines Zod schemas for user registration and login validation
src/api/v1/user/user.controller.ts Implements user authentication endpoints (register, login, profile)
src/api/v1/user/user.service.ts Provides user creation and API key generation services
src/api/v1/user/user.routes.ts Defines authentication routes with middleware protection
src/api/v1/user/user.model.ts Mongoose schema for User model with authentication fields
src/api/v1/user/user.type.ts TypeScript interface for User entity
src/api/v1/user/user.constant.ts Centralized user-related message constants
src/api/v1/user/user.middleware.ts JWT authentication middleware for protected routes
src/validator/env.ts Zod schema for environment variable validation
src/constant/env.constant.ts Exports validated environment configuration
src/utils/safeJson.util.ts Safe JSON parsing utility with fallback
src/utils/__test__/safeJson.util.test.ts Unit tests for safe JSON parsing
src/utils/SendResponse.utils.ts Standardized API response formatting
src/api/v1/AiModelConfig/* AI model configuration management (models, services, validators)
src/api/v1/Ai-model/Ollama/* Ollama AI integration with embeddings and text generation
src/api/v1/Ai-model/Groq/* Groq AI service integration
src/api/v1/Ai-model/Google/* Google Gemini AI integration utilities
src/api/v1/DataSet/v1/* Dataset processing and validation services
src/Template/v1/* AI prompt templates and formatters
tsconfig.json TypeScript compiler configuration
package.json Project dependencies and scripts
jest.config.ts Jest test framework configuration
.env.example Environment variable template

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see now

… user controller error handling and token usage; security: enforce env secrets min length; update Ollama and DataSet utilities; fix AiModelConfig agent handling and service
@morningstarxcdcode
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Thanks @gemini-code-assist and @copilot for the detailed review — I addressed the critical/high comments and pushed fixes:

  • Aligned JWT payload to use (updated , , and all token usage) and updated tests accordingly (test(user): add unit tests for UserUtils token generation and verification #53).
  • Added Zod validation error handling in user endpoints (register/login) to return 400 Bad Request.
  • Removed redundant auth token checks on routes protected by and use instead.
  • Enforced minimum length requirements for and in .
  • Removed insecure fallback for and use validated env value.
  • Replaced sync with async in DataSet utils.
  • Made Ollama base URL configurable via env var and fixed grammar in messages.
  • Fixed AiModelConfig controller/service logic (avoid creating empty agents; de-duplicate agents using ; implemented using ).
  • Cleaned up and hardened tests (updated endpoints, response assertions, and removed brittle assertions).
  • Fixed package.json dependency versions that would block installs.
  • Added to .

If I missed anything else called out by the bots, please point me to the exact comment and I'll iterate further. Ready for re-review — I can also run CI locally if you want (need to install dependencies first).

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Thanks for the detailed update, @morningstarxcdcode! It's great to see that you've addressed the critical and high-priority feedback. Your proactive approach to improving the codebase is much appreciated.

I'll initiate a re-review of the pull request to ensure all changes are thoroughly checked and to identify any further areas for improvement. I'll provide specific comments if I find anything that needs attention.

Looking forward to seeing the updated code!

@NishantRana07
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@morningstarxcdcode please be active for the project

configure ecwoc sentinel and Merge PRs with ECWoC label

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🧪 Add unit tests for UserUtils token generation and verification

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