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The python package that returns Response of Google Gemini through API.

Project description

Open Interview PyPI

$ pip install open-interview

https://github.com/dsdanielpark/open-interview/assets/81407603/22f9b991-33e8-40d2-a4f2-b80199415767

Transform your job interview preparation into an unparalleled journey with Open Interview, where the avant-garde artificial intelligence of OpenAI, Anthropic, and Google is meticulously tailored to forge your path to success. Here, every interaction is designed to sculpt your technical and personal narrative into perfection, mirroring the exigencies of your dream job.


Stellar Features ✨

  • 🌍 Universal Language Support: Emphasize the ability to accommodate all languages across the following features:
  • 🖋️ Dynamic Q&A Alchemy: Craft your arsenal with precision—generate nuanced technical interview Q&As distilled from the essence of your resume and the job description.
  • 📖 Document Genesis: Automate the creation of elegant Word documents (.docx), encapsulating your personalized interview Q&As for study and reflection.
  • 🎧 Sonic Refinement: Convert your Q&As into audio files, enabling auditory mastery and convenience for your preparatory rituals.
  • 🌐 Cosmos Customization: Navigate your preparation through customizable orbits—fine-tune preferences for job designation, interview cadence, lingua franca, and narrative complexity.

Commencing Voyage

Welcome to the nexus of your interview preparation odyssey.

[!IMPORTANT] Token usage for experimental projects can be high, possibly exhausting paid API tokens quickly. A long-response prompt is now active. Please see the document below to adjust system and user prompts accordingly.

Prerequisites

  • Python >= 3.7: Ensure your command module is updated to version 3.7 or beyond.
  • 🔑 API Keys - OpenAI, Anthropic, Google: Secure your access to the galaxies of OpenAI, Anthropic, and Google, embarking with the keys to unlock the full spectrum of your potential.

Installation 📦

pip install open-interview
git clone https://github.com/dsdanielpark/open-interview.git
pip install -r requirements.txt

Quick Start

Open In Colab

Generate interview content using Claude or GPT models with minimal setup:

Using Claude

from openinterview import InterviewManager

claudeToken = "<your_claude_token>"
claude_interview_manager = InterviewManager(api_key=claudeToken, engine="Claude")

claude_interview_manager.generate_interview(
    jd="This role demands a deep enthusiasm for AI development.",
    resume="path/resume.pdf or path/resume.txt or string",
    position= "AI Researcher",
    interview_type="techQAsFromResume",
    language="English", # Any language you want
    max_sentence=5,
    output_dir="save/dirs",
)

Using GPT

import openai
from openinterview import InterviewManager

openai.api_key = "<your_openai_token>"
gpt_interview_manager = InterviewManager(api_key=openai.api_key, engine="GPT")

gpt_interview_manager.generate_interview(
    jd="This role demands a deep enthusiasm for AI development.",
    resume="path/resume.pdf or path/resume.txt or string",
    position= "AI Researcher",
    interview_type="techQAsFromResume",
    language="English", # Any language you want
    max_sentence=5,
    output_dir="save/dirs",
)

Playing Random Question Audio

To randomly play question.mp3 files from a specified folder, create an instance of the RandomPlayer class with the folder path, and then invoke play_random_mp3:

player = RandomPlayer("path/to/output")  # Directory containing question.mp3 files
player.play_random_mp3()

Default plays randomly for 2 minutes. Press 'n' for next question, 'q' to quit.


Usage

For detailed examples, refer to the 📋Usage document for example code and prompting engineering or the 💻tutorial script.

  • OpenAI GPT: Use InterviewGPT for GPT-based content generation.
  • Anthropic Claude: Use InterviewClaude for Claude-based interviews.

FAQ & Support

For questions and support, visit our FAQ and Issues pages. Contributors are welcome! Submit issues, feature suggestions, or pull requests. Reach out to the core maintainer, Daniel Park, for direct contributions or queries.

License ©️

Apache 2.0 license, 2024.

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