2.3.55 Satellite Resume Matcher

Resume Matcher

Handle: resume-matcher
URL: http://localhost:34561

Resume Matcher is an AI-powered tool for comparing resumes against job descriptions. It analyzes resumes in PDF/DOCX format, extracts keywords, compares them with job descriptions, and provides improvement suggestions using local LLMs via Ollama.

Key Features:

• Resume Analysis: Upload resumes in PDF or DOCX format for automated parsing
• Keyword Extraction: Identifies key skills and qualifications from resumes and job descriptions
• Match Scoring: Compares resume content against job requirements
• AI Suggestions: Provides improvement recommendations using local LLMs
• Local Processing: All data stays on your machine with Ollama-powered inference

Architecture:

• FastAPI backend (Python 3.12, uv package manager) on port 34562
• Next.js frontend (Node.js 18) on port 34561
• SQLite database for persistent storage
• Ollama integration for LLM and embeddings

Starting

# Start Resume Matcher with Ollama
harbor up resume-matcher ollama

# Open in browser
harbor open resume-matcher

The first startup will:

1. Build both frontend and backend containers
2. Pull the required Ollama models (gemma3:4b for LLM, bge-m3 for embeddings)

See troubleshooting guide if you encounter any issues.

Configuration

Environment Variables

Following options can be set via harbor config:

# Frontend UI port
HARBOR_RESUME_MATCHER_HOST_PORT            34561

# Backend API port
HARBOR_RESUME_MATCHER_BACKEND_HOST_PORT    34562

# Git reference for building
HARBOR_RESUME_MATCHER_GIT_REF              "https://github.com/srbhr/Resume-Matcher.git#main"

# Workspace directory for data persistence
HARBOR_RESUME_MATCHER_WORKSPACE            "./resume-matcher"

# Session secret (change in production)
HARBOR_RESUME_MATCHER_SESSION_SECRET       "harbor_resume_matcher_secret_change_me"

# LLM configuration
HARBOR_RESUME_MATCHER_LLM_PROVIDER         "ollama"
HARBOR_RESUME_MATCHER_LLM_MODEL            "gemma3:4b"

# Embedding configuration
HARBOR_RESUME_MATCHER_EMBEDDING_PROVIDER   "ollama"
HARBOR_RESUME_MATCHER_EMBEDDING_MODEL      "bge-m3:latest"

Volumes

Resume Matcher persists data in the following directories:

• resume-matcher/data/ - Uploaded resumes, job descriptions, and SQLite database

Ollama Integration

When running with Ollama, Harbor automatically configures the connection between Resume Matcher and Ollama. Ensure the required models are available:

# Pull the LLM model
harbor pull gemma3:4b
harbor ollama pull gemma3:4b

# Pull the embedding model
harbor ollama pull bge-m3:latest

You can customize the models via configuration:

# Use a different LLM
harbor config set resume-matcher.llm.model llama3.2:3b

# Use a different embedding model
harbor config set resume-matcher.embedding.model nomic-embed-text:latest