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Browse files- .gitignore +160 -0
- README.md +1 -13
- app.py +149 -0
- requirements.txt +5 -0
.gitignore
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# Byte-compiled / optimized / DLL files
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__pycache__/
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+
*.py[cod]
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*$py.class
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+
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# C extensions
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+
*.so
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+
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# Distribution / packaging
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+
.Python
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build/
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+
develop-eggs/
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+
dist/
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+
downloads/
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+
eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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+
MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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+
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# Installer logs
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+
pip-log.txt
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+
pip-delete-this-directory.txt
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+
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+
# Unit test / coverage reports
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+
htmlcov/
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+
.tox/
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+
.nox/
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+
.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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+
cover/
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+
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# Translations
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+
*.mo
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+
*.pot
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+
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+
# Django stuff:
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+
*.log
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+
local_settings.py
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+
db.sqlite3
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+
db.sqlite3-journal
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+
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# Flask stuff:
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+
instance/
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66 |
+
.webassets-cache
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+
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# Scrapy stuff:
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+
.scrapy
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+
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# Sphinx documentation
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72 |
+
docs/_build/
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+
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# PyBuilder
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+
.pybuilder/
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target/
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+
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# Jupyter Notebook
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+
.ipynb_checkpoints
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+
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# IPython
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+
profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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README.md
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title: HTF2024
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emoji: 🐠
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colorFrom: gray
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colorTo: gray
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sdk: streamlit
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sdk_version: 1.31.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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# Resume-ATS-Tracking
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app.py
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from dotenv import load_dotenv
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load_dotenv()
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import streamlit as st
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import os
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import io
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import base64
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from PIL import Image
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import pdf2image
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import google.generativeai as genai
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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os.environ["PATH"] += os.pathsep + "/usr/bin"
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def get_gemini_response(input, pdf_content, prompt):
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model = genai.GenerativeModel('gemini-pro-vision')
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response = model.generate_content([input, pdf_content[0], prompt])
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return response.text
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def input_pdf_setup(uploaded_file):
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# Converting the PDF to Image
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if uploaded_file is not None:
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images = pdf2image.convert_from_bytes(uploaded_file.read(), poppler_path="/usr/bin")
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first_page = images[0]
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# Convert into Bytes
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img_byte_arr = io.BytesIO()
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first_page.save(img_byte_arr, format='JPEG')
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img_byte_arr = img_byte_arr.getvalue()
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pdf_parts = [
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{
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"mime_type": "image/jpeg",
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"data": base64.b64encode(img_byte_arr).decode() # encode to base 64
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}
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]
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return pdf_parts
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else:
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raise FileNotFoundError("No file uploaded")
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## StreamLit App
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st.set_page_config(page_title="ATS Resume Expert")
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st.header("ATS Tracking System")
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input_text = st.text_area("Job Description: ", key="input")
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uploaded_file = st.file_uploader("Upload a Resume (PDF)", type="pdf")
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if uploaded_file is not None:
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st.write("PDF uploaded successfully")
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## THE 4 BUTTONS OF THE APPLICATION:
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submit1 = st.button("Review My Resume")
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submit2 = st.button("How can I improvise my skills")
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submit3 = st.button("Percentage Match")
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submit4 = st.button("What are the Keywords that are Missing?")
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submit5 = st.button("Technical Skills")
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# for the above buttons, we have an example input prompt:
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input_prompt1 = """
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You are an experienced HR with Tech Experience in the field of Data Science, Full Stack Web Development,
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Devops, Data Analyst, your task is to review the provided resume
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against the job description for these profiles. Please share your professional evaluation on
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whether the candidate's profile aligns with the role.
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Highlight the strengths and weaknesses of the applicant in relation to the specified job requirements.
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"""
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input_prompt2 = """
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You are an experienced and skilled ATS (Application Tracking System) scanner with a deep understanding of
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data science, full stack web development, devops, data analyst, and deep ATS functionality. Your task is
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to evaluate the resume and then provide the candidate with insights on how they can improvise
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their skills according to the job description provided. Jot down bullet points on how the candidate can
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improvise their skills so that they can align with the job description.
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"""
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input_prompt3 = """
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You are a skilled ATS (Applicant Tracking System) scanner with a deep understanding of Data Science,
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Full Stack Web Development, Devops, Data Analyst, and deep ATS functionality, your task is to
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evaluate the resume against the provided job description. Give me the percentage of match if the resume
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matches the job description. First the output should come as percentage and then keywords missing and
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last final thoughts.
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"""
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input_prompt4 = """
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You are a skilled ATS (Applicant Tracking System) scanner with a deep understanding of Data Science,
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Full Stack Web Development, DevOps, and Data Analyst roles. The job description has several keywords
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that are important for the role. Your task is to evaluate the resume against the provided job description
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and then provide the candidate with insights on the keywords that are missing in the resume.
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Provide the candidate with the missing keywords and how they can improvise their resume to
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align with the job description.
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Jot down the missing keywords along with reasons why they are important for the role in a list manner."""
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+
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input_prompt5 = """
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You are a skilled ATS (Applicant Tracking System) scanner with a deep understanding of Data Science and
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Full Stack Web Development roles. Your task is to filter out the technical skills from the resume and
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then mention them in bullet points in the output. There should be no other information in the output.
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"""
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if submit1:
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if uploaded_file is not None:
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pdf_content = input_pdf_setup(uploaded_file)
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response = get_gemini_response(input_prompt1, pdf_content, input_text)
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st.subheader("Recommendation by the A.I.")
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st.write(response)
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else:
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st.write("Please upload the Resume PDF")
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elif submit2:
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if uploaded_file is not None:
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pdf_content = input_pdf_setup(uploaded_file)
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response = get_gemini_response(input_prompt2, pdf_content, input_text)
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st.subheader("Recommendation by the A.I.")
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st.write(response)
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else:
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st.write("Please upload the Resume PDF")
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+
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elif submit3:
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if uploaded_file is not None:
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pdf_content = input_pdf_setup(uploaded_file)
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response = get_gemini_response(input_prompt3, pdf_content, input_text)
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st.subheader("Recommendation by the A.I.")
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st.write(response)
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else:
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st.write("Please upload the Resume PDF")
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elif submit4:
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if uploaded_file is not None:
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pdf_content = input_pdf_setup(uploaded_file)
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response = get_gemini_response(input_prompt4, pdf_content, input_text)
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st.subheader("Recommendation by the A.I.")
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st.write(response)
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else:
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st.write("Please upload the Resume PDF")
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elif submit5:
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if uploaded_file is not None:
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pdf_content = input_pdf_setup(uploaded_file)
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response = get_gemini_response(input_prompt5, pdf_content, input_text)
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st.subheader("Here is a list of your Technical Skills")
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st.write(response)
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else:
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st.write("Please upload the Resume PDF")
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requirements.txt
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1 |
+
streamlit
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2 |
+
google-generativeai
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3 |
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python-dotenv
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4 |
+
pdf2image
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5 |
+
PyPDF2
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