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from smolagents import CodeAgent, LiteLLMModel, tool
from pypdf import PdfReader
import google.generativeai as genai
import os
from typing import List
from utils import CURRENT_RESUME_LATEX
import os
import json
config = json.load(open("config.json"))
os.environ["GOOGLE_API_KEY"] = config["GOOGLE_API_KEY"]
@tool
def header_details(name: str, mobile_number: str, email_id: str, linkedin_profile_link : str, github_link: str) -> str:
"""
Generates header details of the person. It will display the name, mobile_number, email_id, linkedin profile and github profile
Args:
name(str): Name of the candidate
mobile_number(str): Mobile number of the candidate
email_id(str): email_id
linkedin_profile_link(str): Linkedin profile link of the candidate.
github_link(str): github link of the candidate.
Returns:
str: Instruction for the next steps
"""
header_latex = r"""
\begin{center}
\textbf{\Huge \scshape """
header_latex+= name + r"""} \\ \vspace{1pt}
\small""" + mobile_number + r""" $|$ \href{mailto:[email protected]}{\underline{"""
header_latex+= email_id + r"""}} $|$
\href{https://linkedin.com/in/...}{\underline{"""
header_latex+=linkedin_profile_link + r"""}} $|$
\href{https://github.com/...}{\underline{"""
header_latex+=github_link + r"""}}
\end{center}
"""
global CURRENT_RESUME_LATEX
CURRENT_RESUME_LATEX += header_latex
response_message = "Now call professional_summary_tool"
return response_message
@tool
def professional_summary(summary: str) -> str:
"""
Creates a Professional Experience summary section of the candidate.
Args:
summary (str): The generated summary should be in less than 4 lines. It should follow the STAR method while generating the summary. It should speak about the experience and the role he is applying for.
(e.g: Accomplished Gen AI Specialist with expertise in machine learning (ML), deep learning (DL), generative AI, and AI Agents, proficient in end-to end development from design to deployment. Skilled in problem-solving, data structures and algorithms (DSA), strong analytical abilities, and debugging complex systems. Passionate about optimizing ML model performance to deliver efficient, high-impact AI solutions. Adept at leveraging the full AI stack to drive innovation and achieve business objectives in fast-paced, technology-focused environments)
Returns:
str: Instruction for the next steps
"""
summary_latex = """
\section{Professional Summary}
"""
summary_latex += rf"""
{{{summary}}}
"""
summary_latex = summary_latex.replace("%","\%")
global CURRENT_RESUME_LATEX
CURRENT_RESUME_LATEX += summary_latex
response_message = "Now call the professional_experience_tool"
return response_message
@tool
def professional_experience(experiences: List[dict]) -> str:
"""
Creates an Experience section for a user.Processes the user work experiences across different companies and generates a string in latex form which will be used in further steps
Args:
experiences (list of dict): A list where each dict contains:
- company_name (required) (str): Name of the company.
- place (Optional) (str): Location of the company. If not mentioned in the resume then keep it as empty string "".
- period (required) (str): Employment duration (e.g., "Jan 2020 - Dec 2022").
- role (required) (str): Title or designation.
- bullet_points (required) (list of str): Key achievements/responsibilities. These points must be in ATS friendly format, quantifying things and following the STAR method(situation, task , action and result)(eg. reduced latency by 5ms, improved accuracy by 50%).
Returns:
str: Instruction for the next steps
"""
Experience_latex = r"""
\section{Professional Experience}
\resumeSubHeadingListStart
"""
for exp in experiences:
company = exp['company_name']
period = exp['period']
place = exp['place']
role = exp['role']
bullet_points = exp['bullet_points']
Experience_latex += rf"""
\resumeSubheading
{{{role}}}{{{period}}}
{{{company}}}{{{place}}}
\resumeItemListStart
"""
for item in bullet_points:
Experience_latex += rf"""
\resumeItem{{{item}}}
"""
Experience_latex += r"""
\resumeItemListEnd
\resumeSubHeadingListEnd
"""
Experience_latex = Experience_latex.replace("%","\%")
global CURRENT_RESUME_LATEX
CURRENT_RESUME_LATEX += Experience_latex
response_message = "Now call the projects tool"
return response_message
@tool
def projects(projects: List[dict]) -> str :
"""
Creates an projects section for a user. Processes the projects and generates a string in latex form which will be used in further steps
Args:
projects (list of dict): A list where each dict contains:
- project_name (required) (str): Name of the project.
- tools_used (required)(list[str]): Tools and technologies used in the project (eg Python, Flask, React, PostgreSQL, Docker). It is a list of strings.
- period (required)(str): Employment duration (e.g., "Jan 2020 - Dec 2022").
- bullet_points (required) (list of str): Key achievements/responsibilities.These points must be in ATS friendly format, quantifying things and following the STAR method(situation, task , action and result)(eg. reduced latency by 5ms, improved accuracy by 50%).
Returns:
str: Instruction for the next steps
"""
Projects_latex = r"""
\section{Projects}
\resumeSubHeadingListStart
"""
for project in projects:
project_name = project['project_name']
period = project['period']
tools = ", ".join(project['tools_used'])
bullet_points = project['bullet_points']
Projects_latex += rf"""
\resumeProjectHeading
{{\textbf{{{project_name}}} \textit{{| {tools}}}}}{{}}
\resumeItemListStart"""
for item in bullet_points:
Projects_latex += rf"""\resumeItem{{{item}}}"""
Projects_latex += r"""\resumeItemListEnd"""
Projects_latex += r"""\resumeSubHeadingListEnd"""
Projects_latex = Projects_latex.replace("%","\%")
global CURRENT_RESUME_LATEX
CURRENT_RESUME_LATEX += Projects_latex
response_message = "Now call the skills tool"
return response_message
@tool
def Education(education : List[dict]) -> str:
"""
Generates an Education section for the candidate. It generates a string which will be processed in the further steps.
Args:
education (list of dict): A list where each dict contains:
- Institute (required) (str): Name of the Institute.
- place (required)(str): Location of the Institute.
- period (required)(str): Education duration (e.g., "Jan 2020 - Dec 2022").
- specialization (required) (str): Specialization of education (e.g., "Bachelors in computer science", "Intermediate", "High School")
Returns:
str: Instruction for the next steps
"""
Education_latex = r"""
\section{Education}
\resumeSubHeadingListStart
"""
for edu in education:
institute_name = edu["Institute"]
place = edu["place"]
period = edu["period"]
specialization = edu["specialization"]
studies = rf"""
\resumeSubheading
{{{institute_name}}}{{{place}}}
{{{specialization}}}{{{period}}}
"""
Education_latex+=studies
Education_latex = Education_latex.replace("%","\%")
global CURRENT_RESUME_LATEX
CURRENT_RESUME_LATEX += Education_latex
response_message = "Now call the achievements tool"
return response_message
@tool
def achievements(achievements : List[str]) -> str:
"""
Generates an achievements section for the candidate's resume in LaTeX format.
Args:
achievements (List[str]): List of achievement strings to be included in the resume
Returns:
str: Instruction for the next steps
"""
achievements_latex = r"""
\section{Achievements}
\resumeItemListStart"""
for achievement in achievements:
achievements_latex += rf"""
\resumeItem{{{achievement}}}"""
achievements_latex += r"""
\resumeItemListEnd
\end{document}
"""
achievements_latex = achievements_latex.replace("%","\%")
global CURRENT_RESUME_LATEX
CURRENT_RESUME_LATEX += achievements_latex
response_message = "Created a file in your pc"
return response_message
def create_resume_agent(prompt: str):
try:
model = LiteLLMModel(model_id="gemini/gemini-2.0-flash-exp",
api_key=os.getenv("GOOGLE_API_KEY"))
resume_agent =CodeAgent(
tools = [header_details,professional_summary,professional_experience,projects,skills,Education,achievements],
model = model
)
print(resume_agent)
resume_agent.run(prompt)
global CURRENT_RESUME_LATEX
print(CURRENT_RESUME_LATEX)
return CURRENT_RESUME_LATEX
except Exception as e:
return e |