OpenHire

AI-powered interview and candidate screening platform for high-volume hiring. OpenHire automates campus recruitment through structured voice interviews, resume parsing, and explainable multi-agent evaluations.

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Quickstart

You do not need an API key or database to run or develop OpenHire. The default setup runs offline in mock mode:

# 1. Clone and set up environment
git clone https://github.com/DevSidd2006/OpenHire.git
cd OpenHire
python -m venv .venv && source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt

# 2. Copy default environment (configured for mock mode)
cp .env.example .env

# 3. Start the server
python -m uvicorn api.app:app --reload

• Web App: http://localhost:8000/app
• API Docs: http://localhost:8000/docs
• Health Check: curl http://localhost:8000/api/v1/health

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How It Works

Recruiter Creates Job ──> Candidate Applies & Submits Resume
                               │
                               ▼
                   Adaptive Voice Interview (STT/TTS)
                               │
                               ▼
                   Multi-Agent Evaluation Pipeline
         (Technical · Behavioral · Resume Audit · Integrity · Bias)
                               │
                               ▼
                   Explainable Candidate Leaderboard

1. Job & Rubric Setup: Recruiters define job requirements and competencies. The system drafts an evidence-bound evaluation rubric.
2. Resume Matching: Candidate resumes (.pdf/.docx) are parsed via OCR/text extraction and scored against the approved rubric.
3. Adaptive Voice Interview: Shortlisted candidates take a conversational voice interview powered by an adaptive state machine.
4. Multi-Agent Evaluation: Sealed transcripts are scored across 12 specialized LLM agents, generating an evidence-backed candidate report.

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Multi-Agent System

Agent	Focus
JDAnalyzerAgent	Extracts skills, competencies, and requirements from job postings
ResumeParserAgent	Extracts candidate experience, education, and skills from resumes
ResumeMatcherAgent	Matches resumes to approved rubrics with grounded evidence spans
InterviewerAgent	Generates dynamic, non-repetitive interview questions and assesses answers
TechnicalEvaluatorAgent	Evaluates candidate technical proficiency from interview transcripts
BehavioralEvaluatorAgent	Assesses leadership, teamwork, and communication competencies
ResumeAuditorAgent	Cross-verifies verbal interview claims against resume entries
IntegrityAgent	Identifies inconsistencies, conversational contradictions, and red flags
BiasCheckerAgent	Audits evaluation rationales for demographic or scoring bias
ScoringAgent	Aggregates competency scores using configurable role weights
ReportGeneratorAgent	Compiles explainable, citation-backed candidate reports
LeaderboardAgent	Ranks candidates while surfacing incomplete profiles for human review

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Tech Stack

• Backend: Python 3.13, FastAPI, Uvicorn
• AI & Agents: LangGraph, Pydantic v2
• LLM Providers: NVIDIA NIM, Groq, OpenAI, Google Gemini, Mock Provider
• Speech (Voice): Edge-TTS, Azure Speech SDK, WebSockets
• Database: PostgreSQL (asyncpg) or zero-dependency In-Memory stubs
• Frontend: Vanilla HTML5, CSS3, ES6 JavaScript (served at /app)

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Running Tests

OpenHire includes a comprehensive test suite of 911 automated tests:

# Run all tests
pytest tests/ -v

# Run specific test suite
pytest tests/test_voice_layer.py -v

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Contributing & Community

Contributions are welcome! Please check:

• CONTRIBUTING.md — Workflow, test conventions, and PR guidelines.
• CODE_OF_CONDUCT.md — Community standards and candidate data protection.
• SECURITY.md — Vulnerability disclosure policy.
• OpenBox Bug Board — Platform-wide issue tracker.

Note: AI tools are welcome for contributing — just review and verify the output before submitting. Unreviewed AI-generated PR/issue spam will be closed. See CONTRIBUTING.md for details.

License

Distributed under the MIT License.