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Install and Configure Vercel Speed Insights #2

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2 changes: 1 addition & 1 deletion .manus/db/db-query-1774834216959.json
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"stdout": "",
"stderr": "",
"execution_time_ms": 10273
}
}
16 changes: 11 additions & 5 deletions AI_CURRICULUM_DESIGN.md
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Expand Up @@ -8,12 +8,12 @@ This document outlines the theoretical framework and algorithmic logic for the A

SprintWork follows a research-backed 4-stage framework for career development:

| Stage | Goal | AI Feature |
|---|---|---|
| Stage | Goal | AI Feature |
| ----------- | ------------------------------------ | --------------------------------------- |
| **Explore** | Identify career paths and skill gaps | Smart Job Matching & Skill Gap Analysis |
| **Build** | Create professional assets | AI CV Tailoring & Resume Builder |
| **Connect** | Build professional network | Networking Hub & Recruiter Matching |
| **Refine** | Master interview and soft skills | AI Mock Interviews & Scoring |
| **Build** | Create professional assets | AI CV Tailoring & Resume Builder |
| **Connect** | Build professional network | Networking Hub & Recruiter Matching |
| **Refine** | Master interview and soft skills | AI Mock Interviews & Scoring |

---

Expand All @@ -22,6 +22,7 @@ SprintWork follows a research-backed 4-stage framework for career development:
The interview curriculum is divided into four specialized tracks, each with a structured progression:

### A. Behavioral Track (STAR Method)

- **Focus:** Soft skills, leadership, conflict resolution.
- **Curriculum:**
1. **Foundations:** Introduction to the STAR method.
Expand All @@ -31,6 +32,7 @@ The interview curriculum is divided into four specialized tracks, each with a st
- **Algorithm:** AI evaluates responses based on the presence of **Situation, Task, Action, and Result** components.

### B. Technical Track (DSA & System Design)

- **Focus:** Problem-solving, coding proficiency, architecture.
- **Curriculum:**
1. **Data Structures:** Arrays, Linked Lists, Trees, Graphs.
Expand All @@ -39,6 +41,7 @@ The interview curriculum is divided into four specialized tracks, each with a st
- **Algorithm:** AI checks for technical accuracy, time/space complexity analysis, and edge case handling.

### C. Case Study Track

- **Focus:** Analytical thinking, business logic.
- **Curriculum:**
1. **Market Entry:** Analyzing new business opportunities.
Expand All @@ -50,6 +53,7 @@ The interview curriculum is divided into four specialized tracks, each with a st
## 3. Core Algorithms

### A. Smart Job Matching Algorithm (Hybrid Approach)

The matching score ($S$) is calculated as a weighted sum of multiple factors:

$$S = w_1 \cdot S_{skills} + w_2 \cdot S_{experience} + w_3 \cdot S_{location} + w_4 \cdot S_{salary}$$
Expand All @@ -60,6 +64,7 @@ $$S = w_1 \cdot S_{skills} + w_2 \cdot S_{experience} + w_3 \cdot S_{location} +
- **$S_{salary}$:** Overlap between user expectations and job budget.

### B. AI CV Tailoring Algorithm

1. **Extraction:** Use LLM to extract key requirements (Skills, Keywords, Responsibilities) from a job description.
2. **Analysis:** Compare extracted keywords with the user's current resume.
3. **Optimization:**
Expand All @@ -68,6 +73,7 @@ $$S = w_1 \cdot S_{skills} + w_2 \cdot S_{experience} + w_3 \cdot S_{location} +
- **Quantification:** Prompt user to add metrics (e.g., "Increased sales by 20%").

### C. Interview Scoring Rubric (0-100)

- **Content (40%):** Accuracy, relevance, and depth of the answer.
- **Structure (30%):** Use of STAR method or logical flow.
- **Communication (20%):** Clarity, tone, and professional language.
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74 changes: 37 additions & 37 deletions CURRICULUM_DESIGN.md
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Expand Up @@ -8,76 +8,76 @@ This foundational stage focuses on helping users understand their intrinsic moti

### Core Modules:

* **Values & Motivations Identification:** Guided exercises to uncover personal values, work preferences, and career drivers.
* **Skills Inventory & Transferability:** Tools to list existing skills, identify transferable skills from past experiences, and map them to various job functions.
* **Career Interest Profiling:** AI-driven assessments to match user profiles with potential career clusters and industries.
* **Goal Setting:** Structured frameworks for defining short-term and long-term career objectives.
- **Values & Motivations Identification:** Guided exercises to uncover personal values, work preferences, and career drivers.
- **Skills Inventory & Transferability:** Tools to list existing skills, identify transferable skills from past experiences, and map them to various job functions.
- **Career Interest Profiling:** AI-driven assessments to match user profiles with potential career clusters and industries.
- **Goal Setting:** Structured frameworks for defining short-term and long-term career objectives.

### AI Integration:

| AI Feature | Description | Algorithm/Methodology |
|:---|:---|:---|
| **Career Path Suggestion** | Analyzes user's skills, interests, and values to recommend relevant career paths and industries. | Natural Language Processing (NLP) for interest extraction, skill-to-job mapping databases, clustering algorithms for career similarity. |
| **Skill Gap Identification** | Compares user's current skills against target roles to highlight areas for development. | Skill taxonomy matching, keyword extraction, similarity scoring. |
| AI Feature | Description | Algorithm/Methodology |
| :--------------------------- | :----------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------- |
| **Career Path Suggestion** | Analyzes user's skills, interests, and values to recommend relevant career paths and industries. | Natural Language Processing (NLP) for interest extraction, skill-to-job mapping databases, clustering algorithms for career similarity. |
| **Skill Gap Identification** | Compares user's current skills against target roles to highlight areas for development. | Skill taxonomy matching, keyword extraction, similarity scoring. |

## 2. Build: Resume & Cover Letter Tailoring

This stage equips users with the ability to create compelling application materials optimized for Applicant Tracking Systems (ATS) and human recruiters. AI provides real-time feedback and tailoring suggestions.

### Core Modules:

* **Resume Building:** Step-by-step guidance on structuring resumes, selecting appropriate formats, and content creation.
* **Cover Letter Crafting:** Techniques for writing persuasive cover letters that highlight relevant experiences and motivations.
* **ATS Optimization:** Strategies for incorporating keywords and formatting resumes to pass ATS scans.
* **Portfolio Development:** Guidance for creating online portfolios for creative and technical roles.
- **Resume Building:** Step-by-step guidance on structuring resumes, selecting appropriate formats, and content creation.
- **Cover Letter Crafting:** Techniques for writing persuasive cover letters that highlight relevant experiences and motivations.
- **ATS Optimization:** Strategies for incorporating keywords and formatting resumes to pass ATS scans.
- **Portfolio Development:** Guidance for creating online portfolios for creative and technical roles.

### AI Integration:

| AI Feature | Description | Algorithm/Methodology |
|:---|:---|:---|
| **ATS Optimization Score** | Evaluates resume against a job description for keyword density, formatting, and overall ATS compatibility. | Keyword extraction, semantic similarity (BERT embeddings), rule-based scoring for formatting. |
| **Content Enhancement** | Suggests stronger action verbs, quantifies achievements, and refines bullet points for impact. | NLP for verb identification, sentiment analysis, pattern recognition for quantifiable metrics. |
| **Tailored Content Generation** | Generates customized resume sections or cover letter paragraphs based on job description and user's profile. | Generative AI (LLM) with prompt engineering, contextual understanding. |
| AI Feature | Description | Algorithm/Methodology |
| :------------------------------ | :----------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------- |
| **ATS Optimization Score** | Evaluates resume against a job description for keyword density, formatting, and overall ATS compatibility. | Keyword extraction, semantic similarity (BERT embeddings), rule-based scoring for formatting. |
| **Content Enhancement** | Suggests stronger action verbs, quantifies achievements, and refines bullet points for impact. | NLP for verb identification, sentiment analysis, pattern recognition for quantifiable metrics. |
| **Tailored Content Generation** | Generates customized resume sections or cover letter paragraphs based on job description and user's profile. | Generative AI (LLM) with prompt engineering, contextual understanding. |

## 3. Connect: Job Search & Networking

This stage focuses on effective job search strategies, networking, and leveraging professional connections. AI assists in identifying suitable job opportunities and optimizing outreach efforts.

### Core Modules:

* **Job Search Strategy:** Techniques for identifying target companies, roles, and industries.
* **Networking & Outreach:** Best practices for informational interviews, LinkedIn networking, and professional event engagement.
* **Online Presence Management:** Optimizing LinkedIn profiles and other professional social media.
* **Application Tracking:** Tools for managing job applications and follow-ups.
- **Job Search Strategy:** Techniques for identifying target companies, roles, and industries.
- **Networking & Outreach:** Best practices for informational interviews, LinkedIn networking, and professional event engagement.
- **Online Presence Management:** Optimizing LinkedIn profiles and other professional social media.
- **Application Tracking:** Tools for managing job applications and follow-ups.

### AI Integration:

| AI Feature | Description | Algorithm/Methodology |
|:---|:---|:---|
| **Smart Job Matching** | Recommends job openings based on user's profile, skills, experience, and preferences. | Weighted sum algorithm (as defined in `mlService.ts`), collaborative filtering, content-based filtering, location-based services. |
| **Networking Message Drafts** | Generates personalized outreach messages for informational interviews or connection requests. | Generative AI (LLM) with user context and recipient information. |
| **Company Insights** | Provides AI-summarized information about target companies, culture, and recent news. | Web scraping, NLP for summarization, sentiment analysis. |
| AI Feature | Description | Algorithm/Methodology |
| :---------------------------- | :-------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------- |
| **Smart Job Matching** | Recommends job openings based on user's profile, skills, experience, and preferences. | Weighted sum algorithm (as defined in `mlService.ts`), collaborative filtering, content-based filtering, location-based services. |
| **Networking Message Drafts** | Generates personalized outreach messages for informational interviews or connection requests. | Generative AI (LLM) with user context and recipient information. |
| **Company Insights** | Provides AI-summarized information about target companies, culture, and recent news. | Web scraping, NLP for summarization, sentiment analysis. |

## 4. Refine: Interview Preparation & Skill Development

This final stage prepares users for interviews through practice, feedback, and continuous skill development. AI powers mock interviews and provides detailed performance analytics.

### Core Modules:

* **Behavioral Interview Practice:** Focus on the STAR method (Situation, Task, Action, Result) for answering common behavioral questions.
* **Technical Interview Practice:** Modules for Data Structures & Algorithms, System Design, and role-specific technical questions.
* **Case Study Interview Practice:** Frameworks and practice scenarios for analytical problem-solving.
* **Feedback & Iteration:** Tools for self-reflection and incorporating feedback into interview responses.
* **Skill Development Pathways:** Personalized learning recommendations to address identified skill gaps.
- **Behavioral Interview Practice:** Focus on the STAR method (Situation, Task, Action, Result) for answering common behavioral questions.
- **Technical Interview Practice:** Modules for Data Structures & Algorithms, System Design, and role-specific technical questions.
- **Case Study Interview Practice:** Frameworks and practice scenarios for analytical problem-solving.
- **Feedback & Iteration:** Tools for self-reflection and incorporating feedback into interview responses.
- **Skill Development Pathways:** Personalized learning recommendations to address identified skill gaps.

### AI Integration:

| AI Feature | Description | Algorithm/Methodology |
|:---|:---|:---|
| **Dynamic Question Generation** | Creates realistic behavioral, technical, and case study interview questions based on job roles and user profiles. | Generative AI (LLM) with question templates and contextual parameters. |
| **Interview Answer Evaluation** | Analyzes user responses for content, structure, communication, and confidence, providing a detailed score and actionable feedback. | NLP for semantic analysis, keyword matching, sentiment analysis, speech-to-text (for verbal responses), predefined scoring rubrics. |
| **STAR Method Adherence Check** | Specifically assesses if behavioral answers follow the STAR framework. | Pattern recognition, NLP for structural analysis. |
| **Personalized Skill Recommendations** | Suggests courses, tutorials, or projects to improve skills identified during mock interviews or skill gap analysis. | Collaborative filtering, content-based recommendations, knowledge graph traversal. |
| AI Feature | Description | Algorithm/Methodology |
| :------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------- | :---------------------------------------------------------------------------------------------------------------------------------- |
| **Dynamic Question Generation** | Creates realistic behavioral, technical, and case study interview questions based on job roles and user profiles. | Generative AI (LLM) with question templates and contextual parameters. |
| **Interview Answer Evaluation** | Analyzes user responses for content, structure, communication, and confidence, providing a detailed score and actionable feedback. | NLP for semantic analysis, keyword matching, sentiment analysis, speech-to-text (for verbal responses), predefined scoring rubrics. |
| **STAR Method Adherence Check** | Specifically assesses if behavioral answers follow the STAR framework. | Pattern recognition, NLP for structural analysis. |
| **Personalized Skill Recommendations** | Suggests courses, tutorials, or projects to improve skills identified during mock interviews or skill gap analysis. | Collaborative filtering, content-based recommendations, knowledge graph traversal. |

## Conclusion

Expand Down
16 changes: 16 additions & 0 deletions DEPLOYMENT_GUIDE.md
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@@ -1,9 +1,11 @@
# SprintWork Deployment Guide

## Overview

SprintWork is a full-stack TypeScript application with **Manus-integrated AI**, **TiDB Cloud database**, and **OAuth authentication**. This guide covers deployment to Vercel with all features enabled.

## Prerequisites

- GitHub account (repository already set up)
- Vercel account (free tier available)
- TiDB Cloud account (free tier available)
Expand All @@ -12,19 +14,22 @@ SprintWork is a full-stack TypeScript application with **Manus-integrated AI**,
## Database Setup (TiDB Cloud)

Your database is already configured:

- **Connection String**: `mysql://a2xXqbP1YKYZnPR.root:Ml8MTBkj61gN8MAS@gateway01.eu-central-1.prod.aws.tidbcloud.com:4000/sprintwork`
- **Schema**: Automatically migrated via Drizzle ORM
- **Free Tier**: 5GB storage, sufficient for MVP

## Deployment to Vercel

### Step 1: Connect GitHub Repository

1. Go to [Vercel Dashboard](https://vercel.com/dashboard)
2. Click "Add New" → "Project"
3. Select "Import Git Repository"
4. Find and select `Samkele05/SprintWork`

### Step 2: Configure Environment Variables

In Vercel project settings, add these environment variables:

```
Expand All @@ -42,6 +47,7 @@ VITE_APP_ID=sprintwork
```

### Step 3: Optional - Add OAuth Credentials

For third-party login (Google, GitHub, LinkedIn):

```
Expand All @@ -53,34 +59,40 @@ GITHUB_CLIENT_SECRET=[Your GitHub Client Secret]
```

### Step 4: Deploy

Click "Deploy" and Vercel will automatically build and deploy your app.

## Features Included

### ✅ AI-Powered Career Tools

- **CV Tailoring**: AI-powered resume optimization for job descriptions
- **Mock Interviews**: STAR-method-based interview practice with AI scoring
- **Job Matching**: Intelligent job recommendations based on skills and experience
- **Curriculum**: Personalized learning paths for skill development

### ✅ Authentication

- Manus OAuth (built-in)
- Google OAuth (optional)
- GitHub OAuth (optional)
- LinkedIn OAuth (optional)

### ✅ Database

- TiDB Cloud MySQL (free tier)
- Drizzle ORM for type-safe queries
- Automatic schema migrations

### ✅ Frontend

- React with TypeScript
- Vite for fast development
- TailwindCSS for styling
- Responsive design

### ✅ Backend

- tRPC for type-safe APIs
- Manus LLM integration for AI features
- Express.js server
Expand Down Expand Up @@ -114,23 +126,27 @@ pnpm dev
## Troubleshooting

### Database Connection Issues

- Verify `DATABASE_URL` is correctly set
- Check TiDB Cloud IP whitelist includes Vercel's IP ranges
- Ensure SSL mode is set to `REQUIRED`

### OAuth Not Working

- Verify redirect URIs match your deployment URL
- Check client IDs and secrets are correct
- Ensure OAuth credentials are added to Vercel environment

### AI Features Not Working

- Verify `BUILT_IN_FORGE_API_KEY` is set
- Check Manus API endpoint is reachable
- Review server logs for API errors

## Support

For issues or questions:

1. Check the GitHub repository: https://github.com/Samkele05/SprintWork
2. Review the AI_CURRICULUM_DESIGN.md for feature details
3. Contact Manus support for API issues
Expand Down
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