Added Resume Coach Pack

llama-index-packs/llama-index-packs-resume-coach-pack/.gitignore

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+llama_index/_static
+.DS_Store
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+bin/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+etc/
+include/
+lib/
+lib64/
+parts/
+sdist/
+share/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+.ruff_cache
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+notebooks/
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+pyvenv.cfg
+
+# Spyder project settings
+.spyderproject
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+# Rope project settings
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+# mkdocs documentation
+/site
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+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
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+
+# Jetbrains
+.idea
+modules/
+*.swp
+
+# VsCode
+.vscode
+
+# pipenv
+Pipfile
+Pipfile.lock
+
+# pyright
+pyrightconfig.json

llama-index-packs/llama-index-packs-resume-coach-pack/BUILD

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+python_sources()

llama-index-packs/llama-index-packs-resume-coach-pack/Makefile

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+GIT_ROOT ?= $(shell git rev-parse --show-toplevel)
+
+help:	## Show all Makefile targets.
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}'
+
+format:	## Run code autoformatters (black).
+	pre-commit install
+	git ls-files | xargs pre-commit run black --files
+
+lint:	## Run linters: pre-commit (black, ruff, codespell) and mypy
+	pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files
+
+test:	## Run tests via pytest.
+	pytest tests
+
+watch-docs:	## Build and watch documentation.
+	sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/

llama-index-packs/llama-index-packs-resume-coach-pack/README.md

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+# LlamaIndex Packs Integration: Resume Coach Pack
+
+This LLamaIndex pack takes a resume, a job description, a LLM, an embedding model, and optionally a Reader and a list of queries and returns the answer for each query by using the job description, job criterions and job keywords to evaluate the resume.
+
+The purpose of this pack is to help job candidates match and improve their resumes to reach the job requirements with the default queries or anything else by passing custom queries.
+
+## Code Usage
+
+You can download the pack to a `./resume_coach_pack` directory:
+
+```python
+from llama_index.core.llama_pack import download_llama_pack
+
+# download and install dependencies
+ResumeCoachPack = download_llama_pack(
+    "ResumeCoachPack", "./resume_coach_pack"
+)
+```
+
+From here, you can use the pack, or inspect and modify the pack in `./resume_coach_pack`.
+
+Then, you can set up the pack like so:
+
+```python
+# create the pack
+resume_coach = ResumeCoachPack(
+    job_description_path='job_description.txt', 
+    resume_path='CV.pdf', 
+    embed_model=embed_model, 
+    llm=llm
+)
+```
+
+In this example, `embed_model` has the type BaseEmbedding and `llm` has the type LLM.
+
+Two additional parameters can be passed to the pack:
+* reader: a Reader object that has the 'load_data' method
+* queries: a Dictionary containing a key that describes each query and a value that contains the query itself
+
+
+
+You can get the response from the pack by running the following code:
+
+```python
+response = resume_match_pack.run()
+```
+
+
+```python
+response = resume_screener.run(resume_path="resume.pdf")
+print(response.overall_decision)
+```
+
+The `response` will be dictionary that can be displayed as follows:
+
+```python
+for key, value in response.items():
+    display(Markdown(f"<b>{key}</b>"))
+    display(Markdown(f"{value}"))
+    display(Markdown(f"---"))
+```