What Programming Language Is Hiring Agent Written In? Complete Python Source Analysis

The InterviewStreet Hiring Agent repository is written entirely in Python, utilizing standard .py file extensions and Python-specific dependency management via requirements.txt.

When examining the interviewstreet/hiring-agent codebase to determine what programming language powers this automated hiring tool, the evidence points exclusively to Python. Every module—from configuration loading to LLM integration—uses Python's syntax and ecosystem, with no evidence of compiled languages or JavaScript components.

Source File Extensions Confirm Python Implementation

A comprehensive review of the repository structure reveals that all source files use the .py extension, confirming Python as the sole implementation language. The codebase contains no JavaScript, TypeScript, Go, or Rust files, establishing a pure Python environment.

Key files that demonstrate this include:

• config.py: Loads and validates configuration settings using pathlib and json
• prompt.py: Handles Jinja2-based prompt generation for LLMs
• models.py: Defines data models used throughout the application
• evaluator.py: Contains core logic for evaluating resumes with LLM calls
• github.py: Provides utilities for interacting with the GitHub API
• requirements.txt: Lists Python package dependencies including jinja2 and requests

Python Dependency Management

The presence of requirements.txt in the repository root provides additional confirmation that Hiring Agent is a Python project. This file manages the project's external dependencies, including web frameworks and templating engines essential for LLM operations.

Core Python Implementation Examples

The Hiring Agent architecture follows Pythonic principles with modular separation of concerns. Below are practical implementations from key modules.

Configuration Loading in config.py

The configuration module uses Python's pathlib for cross-platform path handling:

# src: config.py

from pathlib import Path
import json

def load_config() -> dict:
    config_path = Path(__file__).with_name("config.json")
    with config_path.open() as f:
        return json.load(f)

LLM Prompt Generation in prompt.py

Template rendering leverages the Jinja2 library, a Python-specific templating engine:

# src: prompt.py

from jinja2 import Environment, FileSystemLoader

env = Environment(loader=FileSystemLoader("prompts/templates"))
template = env.get_template("basics.jinja")
prompt = template.render(name="Alice", experience=5)

Resume Evaluation in evaluator.py

The core evaluation logic interfaces with LLM utilities using standard Python typing:

# src: evaluator.py

from llm_utils import call_llm

def evaluate_resume(resume_text: str) -> dict:
    response = call_llm(prompt=resume_text)
    return response.json()

GitHub API Integration in github.py

External API calls utilize Python's requests library:

# src: github.py

import requests

def fetch_repo_issues(owner: str, repo: str) -> list:
    url = f"https://api.github.com/repos/{owner}/{repo}/issues"
    resp = requests.get(url, headers={"Accept": "application/vnd.github.v3+json"})
    return resp.json()

Architectural Patterns

The codebase demonstrates typical Pythonic patterns: duck typing, modular imports, and clear separation between data models, business logic, and external integrations. This structure confirms that when asking what programming language Hiring Agent is written in, the answer is definitively Python 3, leveraging modern features like type hints and pathlib.

Summary

• Hiring Agent is 100% Python: Every source file uses the .py extension with no other languages present.
• Python ecosystem dependencies: The requirements.txt file manages packages like jinja2 and requests.
• Modular architecture: Code is organized into logical units (config.py, evaluator.py, github.py) following Python best practices.
• Modern Python features: Uses type hints, pathlib, and f-strings throughout the codebase.
• LLM integration: Python's rich ecosystem supports the Jinja2 templating required for prompt engineering.

Frequently Asked Questions

Is Hiring Agent written in Python or JavaScript?

Hiring Agent is written exclusively in Python. The repository contains no JavaScript or TypeScript files; all logic—including frontend-facing components and API integrations—is implemented in Python modules. Every file in the source tree uses the .py extension.

What Python version does Hiring Agent require?

While the repository does not specify a minimum Python version explicitly, the syntax indicates Python 3.6+ based on the use of type hints, f-strings, and pathlib functionality. The type annotation syntax (-> dict) and pathlib with context managers require modern Python versions.

Does Hiring Agent use any compiled languages like C or Rust?

No, Hiring Agent uses pure Python. While Python packages like requests may rely on compiled extensions internally, the application code itself contains no C, C++, Rust, or Go source files. All core functionality is implemented in interpreted Python code located in the repository's .py files.

Where can I find the Python package requirements for Hiring Agent?

The requirements.txt file in the repository root lists all Python dependencies. According to the source analysis, this includes essential packages like jinja2 for template rendering and requests for HTTP API communications with GitHub and LLM endpoints.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}