HireMe

Automated outreach and job-application platform focused on LinkedIn-style messaging, cold email, and multi-platform applications. The AI model runs locally via Ollama to keep data on-device.

Overview

HireMe orchestrates:

• Discovery of roles and companies.
• Personalized message and email drafting.
• Multi-channel outreach (LinkedIn, X, Gmail).
• Application submissions on platforms like Unstop and others.
• Local LLM inference with Ollama.

The goal is to streamline high-volume, compliant outreach while preserving personalization and user control.

Key Features

• Multi-platform outreach queue with per-channel rate limits.
• Draft-first workflow (review, edit, approve before sending).
• Local LLM via Ollama for personalization and privacy.
• Contact and campaign management.
• Application tracking and status updates.
• Template library with A/B variants.
• Audit log for every send and submission.

Tech Stack

• Next.js (App Router)
• TypeScript
• HeroUI
• Tailwind CSS
• Ollama (local inference)

Architecture (Planned)

• Web app for workflow, approvals, and status dashboards.
• Background worker for queue processing and platform automations.
• Data store for contacts, campaigns, and activity logs.
• Provider adapters for each platform (LinkedIn, X, Gmail, Unstop, etc.).

Local Development

npm install
npm run dev

Deploy (local-first)

Deploy on a single machine with data and LLM on localhost: no cloud database, no external API for AI. Everything runs in Docker on your host.

# Build and run app + Ollama; data in Docker volumes
docker compose up -d

# Pull an Ollama model (one-time)
docker compose exec ollama ollama pull llama3.2

The first docker compose up -d (or docker compose build) needs network access to install dependencies and pull images.

• App: http://localhost:3000
• Ollama: inside the ollama service (app uses OLLAMA_BASE_URL=http://ollama:11434)
• Data: bot config, uploads, and logs are in Docker volumes (bot_config, bot_uploads, bot_logs); no data leaves the host.

Config is created via the Onboarding UI and stored in the bot_config volume. Optional: copy env.docker.example to .env and override variables (e.g. OLLAMA_BASE_URL if Ollama runs on the host: http://host.docker.internal:11434).

Local Bot Wiring

HireMe connects the Next.js UI to the Python automation bot via /api/bot. Copy .env.example to .env.local and adjust paths if needed:

cp .env.example .env.local

Key environment variables:

• OLLAMA_BASE_URL - local Ollama server URL
• BOT_WORKDIR - path to the Python bot folder
• BOT_PYTHON_PATH - Python executable
• BOT_CONFIG_PATH - bot config file path

Configuration (Draft)

This project will use environment variables for provider credentials and feature flags.

# Example only
OLLAMA_BASE_URL=http://localhost:11434

Usage (Planned)

1. Import contacts and target roles.
2. Configure outreach templates and approval rules.
3. Generate drafts with Ollama and review.
4. Send approved messages and emails.
5. Track responses and application status.

Safety, Compliance, and Ethics

This project is intended for responsible outreach. You are responsible for compliance with platform terms, spam laws, and privacy regulations. Use opt-in, rate limits, and human review where required.

Roadmap

• Provider adapters and secure credential storage.
• Campaign scheduling with throttling.
• Auto follow-up sequences with guardrails.
• Analytics dashboard for response rates.
• Import/export for CRM tools.

License

MIT