resume_builder.py

### READ ME:
# use the fake_resume.md to run this code

from crewai import Agent, Task, Crew

import os
from utils import get_openai_api_key, get_serper_api_key

openai_api_key = get_openai_api_key()
os.environ["OPENAI_MODEL_NAME"] = 'gpt-3.5-turbo'
os.environ["SERPER_API_KEY"] = get_serper_api_key()

from crewai_tools import (
  FileReadTool,
  ScrapeWebsiteTool,
  MDXSearchTool,
  SerperDevTool
)

search_tool = SerperDevTool()
scrape_tool = ScrapeWebsiteTool()
read_resume = FileReadTool(file_path='./fake_resume.md')
semantic_search_resume = MDXSearchTool(mdx='./fake_resume.md')

# Agent 1: Researcher
researcher = Agent(
    role="Tech Job Researcher",
    goal="Make sure to do amazing analysis on "
         "job posting to help job applicants",
    tools = [scrape_tool, search_tool],
    verbose=True,
    backstory=(
        "As a Job Researcher, your prowess in "
        "navigating and extracting critical "
        "information from job postings is unmatched."
        "Your skills help pinpoint the necessary "
        "qualifications and skills sought "
        "by employers, forming the foundation for "
        "effective application tailoring."
    )
)

# Agent 2: Profiler
profiler = Agent(
    role="Personal Profiler for Engineers",
    goal="Do increditble research on job applicants "
         "to help them stand out in the job market",
    tools = [scrape_tool, search_tool,
             read_resume, semantic_search_resume],
    verbose=True,
    backstory=(
        "Equipped with analytical prowess, you dissect "
        "and synthesize information "
        "from diverse sources to craft comprehensive "
        "personal and professional profiles, laying the "
        "groundwork for personalized resume enhancements."
    )
)

# Agent 3: Resume Strategist
resume_strategist = Agent(
    role="Resume Strategist for Engineers",
    goal="Find all the best ways to make a "
         "resume stand out in the job market.",
    tools = [scrape_tool, search_tool,
             read_resume, semantic_search_resume],
    verbose=True,
    backstory=(
        "With a strategic mind and an eye for detail, you "
        "excel at refining resumes to highlight the most "
        "relevant skills and experiences, ensuring they "
        "resonate perfectly with the job's requirements."
    )
)

# Agent 4: Interview Preparer
interview_preparer = Agent(
    role="Engineering Interview Preparer",
    goal="Create interview questions and talking points "
         "based on the resume and job requirements",
    tools = [scrape_tool, search_tool,
             read_resume, semantic_search_resume],
    verbose=True,
    backstory=(
        "Your role is crucial in anticipating the dynamics of "
        "interviews. With your ability to formulate key questions "
        "and talking points, you prepare candidates for success, "
        "ensuring they can confidently address all aspects of the "
        "job they are applying for."
    )
)

# Task for Researcher Agent: Extract Job Requirements
research_task = Task(
    description=(
        "Analyze the job posting URL provided ({job_posting_url}) "
        "to extract key skills, experiences, and qualifications "
        "required. Use the tools to gather content and identify "
        "and categorize the requirements."
    ),
    expected_output=(
        "A structured list of job requirements, including necessary "
        "skills, qualifications, and experiences."
    ),
    agent=researcher,
    async_execution=True
)

# Task for Profiler Agent: Compile Comprehensive Profile
profile_task = Task(
    description=(
        "Compile a detailed personal and professional profile "
        "using the GitHub ({github_url}) URLs, and personal write-up "
        "({personal_writeup}). Utilize tools to extract and "
        "synthesize information from these sources."
    ),
    expected_output=(
        "A comprehensive profile document that includes skills, "
        "project experiences, contributions, interests, and "
        "communication style."
    ),
    agent=profiler,
    async_execution=True
)

# Task for Resume Strategist Agent: Align Resume with Job Requirements
resume_strategy_task = Task(
    description=(
        "Using the profile and job requirements obtained from "
        "previous tasks, tailor the resume to highlight the most "
        "relevant areas. Employ tools to adjust and enhance the "
        "resume content. Make sure this is the best resume even but "
        "don't make up any information. Update every section, "
        "inlcuding the initial summary, work experience, skills, "
        "and education. All to better reflrect the candidates "
        "abilities and how it matches the job posting."
    ),
    expected_output=(
        "An updated resume that effectively highlights the candidate's "
        "qualifications and experiences relevant to the job."
    ),
    output_file="tailored_resume.md",
    context=[research_task, profile_task],
    agent=resume_strategist
)

# Task for Interview Preparer Agent: Develop Interview Materials
interview_preparation_task = Task(
    description=(
        "Create a set of potential interview questions and talking "
        "points based on the tailored resume and job requirements. "
        "Utilize tools to generate relevant questions and discussion "
        "points. Make sure to use these question and talking points to "
        "help the candiadte highlight the main points of the resume "
        "and how it matches the job posting."
    ),
    expected_output=(
        "A document containing key questions and talking points "
        "that the candidate should prepare for the initial interview."
    ),
    output_file="interview_materials.md",
    context=[research_task, profile_task, resume_strategy_task],
    agent=interview_preparer
)


job_application_crew = Crew(
    agents=[researcher,
            profiler,
            resume_strategist,
            interview_preparer],

    tasks=[research_task,
           profile_task,
           resume_strategy_task,
           interview_preparation_task],

    verbose=True
)

job_application_inputs = {
    'job_posting_url': 'https://jobs.lever.co/AIFund/6c82e23e-d954-4dd8-a734-c0c2c5ee00f1?lever-origin=applied&lever-source%5B%5D=AI+Fund',
    'github_url': 'https://github.com/joaomdmoura',
    'personal_writeup': """Noah is an accomplished Software
    Engineering Leader with 18 years of experience, specializing in
    managing remote and in-office teams, and expert in multiple
    programming languages and frameworks. He holds an MBA and a strong
    background in AI and data science. Noah has successfully led
    major tech initiatives and startups, proving his ability to drive
    innovation and growth in the tech industry. Ideal for leadership
    roles that require a strategic and innovative approach."""
}

### this execution will take a few minutes to run
result = job_application_crew.kickoff(inputs=job_application_inputs)

from IPython.display import Markdown, display
display(Markdown("./tailored_resume.md"))

display(Markdown("./interview_materials.md"))