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Merge pull request #1432 from guardrails-ai/repo-cleanup
[chore]: Post Docs Migration Repository Cleanup
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.github/ISSUE_TEMPLATE/config.yml

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blank_issues_enabled: false
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contact_links:
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- name: Guardrails Documentation
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url: https://www.guardrailsai.com/docs
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url: https://www.guardrailsai.com/guardrails/docs
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about: Check our documentation for answers to common questions and usage guides.
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- name: Guardrails Hub
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url: https://hub.guardrailsai.com/
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url: https://guardrailsai.com/hub
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about: Explore pre-built validators and guards for specific types of risks.
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- name: GitHub Discussions
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url: https://github.com/guardrails-ai/guardrails/discussions

.github/workflows/scripts/run_notebooks.sh

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rm -rf ./guardrails
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# Navigate to notebooks
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cd docs/src/examples
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cd docs/examples
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# Get the notebook name from the matrix variable
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notebook="$1"

.github/workflows/scripts/update_notebook_matrix.sh

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notebook_names="["
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# Compile list of file names
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for file in $(ls docs/src/examples/*.ipynb); do
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for file in $(ls docs/examples/*.ipynb); do
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# Add the full filename with extension
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filename=$(basename "$file")
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if ! [[ ${ignore[*]} =~ "$filename" ]]

.gitignore

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pyvenv.cfg
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mlruns
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mlartifacts
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/.guardrails
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/.guardrails
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.claude
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.idea
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.pytest_cache
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.ruff_cache
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.vscode

CONTRIBUTING.md

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1. Ensure tests pass: `make test`
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2. Format your code: `make autoformat`
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3. Run static analysis: `make type`
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4. Update documentation if needed. Docs are located in the `docs` directory. You can serve docs using `mkdocs serve`.
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4. Update documentation: `make docs-gen`
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### Optional: Pre-Commit Hooks
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4. Engage in the code review process and make any necessary changes.
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5. Celebrate when your pull request is merged! Your changes will be available in the next Guardrails release.
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Thank you for your contribution and happy coding!
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## Documentation
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Docs are served via docusaurus. To serve docs locally, run the following
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```bash
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# install dependencies
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pip install -e ".[dev]"
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# install npm dependencies
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npm i
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# serve the docs
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npm run start
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```
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then navigate to `localhost:3000` in your browser.
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Thank you for your contribution and happy coding!

DOCS.md

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Makefile

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.PHONY: autoformat type lint test test-basic test-cov view-test-cov view-test-cov-file docs-serve docs-deploy dev full install docs-gen self-install all precommit refresh update-lock
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MKDOCS_SERVE_ADDR ?= localhost:8000 # Default address for mkdocs serve, format: <host>:<port>, override with `make docs-serve MKDOCS_SERVE_ADDR=<host>:<port>`
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.PHONY: autoformat type lint test test-basic test-cov view-test-cov view-test-cov-file dev full install docs-gen self-install all precommit refresh update-lock
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autoformat:
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ruff check guardrails/ tests/ --fix
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view-test-cov-file:
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pytest tests/unit_tests/test_logger.py --cov=./guardrails/ --cov-report html && open htmlcov/index.html
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docs-serve:
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poetry run mkdocs serve -a $(MKDOCS_SERVE_ADDR)
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docs-deploy:
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poetry run mkdocs gh-deploy
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dev:
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poetry install --extras "dev"
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poetry run pre-commit install
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docs-gen:
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poetry run python ./docs/pydocs/generate_pydocs.py
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cp -r docs/src/* docs/dist
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poetry run nbdoc_build --force_all True --srcdir ./docs/dist
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self-install:
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pip install -e .
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all: autoformat type lint docs test
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all: autoformat type lint docs-gen test
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precommit:
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# pytest -x -q --no-summary

README.md

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<div align="center">
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/dist/img/Guardrails-ai-logo-for-dark-bg.svg#gh-dark-mode-only" alt="Guardrails AI Logo" width="600px">
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/dist/img/Guardrails-ai-logo-for-white-bg.svg#gh-light-mode-only" alt="Guardrails AI Logo" width="600px">
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/assets/Guardrails-ai-logo-for-dark-bg.svg#gh-dark-mode-only" alt="Guardrails AI Logo" width="600px">
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/assets/Guardrails-ai-logo-for-white-bg.svg#gh-light-mode-only" alt="Guardrails AI Logo" width="600px">
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<hr>
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[![Checked with pyright](https://microsoft.github.io/pyright/img/pyright_badge.svg)](https://microsoft.github.io/pyright/)
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[![X (formerly Twitter) Follow](https://img.shields.io/twitter/follow/guardrails_ai)](https://x.com/guardrails_ai)
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[![Discord](https://img.shields.io/discord/1085077079697150023?logo=discord&label=support&link=https%3A%2F%2Fdiscord.gg%2Fgw4cR9QvYE)](https://discord.gg/U9RKkZSBgx)
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[![Static Badge](https://img.shields.io/badge/Docs-blue?link=https%3A%2F%2Fwww.guardrailsai.com%2Fdocs)](https://www.guardrailsai.com/docs)
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[![Static Badge](https://img.shields.io/badge/Docs-blue?link=https%3A%2F%2Fwww.guardrailsai.com%2Fdocs)](https://guardrailsai.com/guardrails/docs)
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[![Static Badge](https://img.shields.io/badge/Blog-blue?link=https%3A%2F%2Fwww.guardrailsai.com%2Fblog)](https://www.guardrailsai.com/blog)
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[![Gurubase](https://img.shields.io/badge/Gurubase-Ask%20Guardrails%20Guru-006BFF)](https://gurubase.io/g/guardrails)
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## What is Guardrails?
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Guardrails is a Python framework that helps build reliable AI applications by performing two key functions:
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1. Guardrails runs Input/Output Guards in your application that detect, quantify and mitigate the presence of specific types of risks. To look at the full suite of risks, check out [Guardrails Hub](https://hub.guardrailsai.com/).
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1. Guardrails runs Input/Output Guards in your application that detect, quantify and mitigate the presence of specific types of risks. To look at the full suite of risks, check out [Guardrails Hub](https://guardrailsai.com/hub/).
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2. Guardrails help you generate structured data from LLMs.
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<div align="center">
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/dist/img/with_and_without_guardrails.svg" alt="Guardrails in your application" width="1500px">
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/assets/with_and_without_guardrails.svg" alt="Guardrails in your application" width="1500px">
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</div>
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### Guardrails Hub
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Guardrails Hub is a collection of pre-built measures of specific types of risks (called 'validators'). Multiple validators can be combined together into Input and Output Guards that intercept the inputs and outputs of LLMs. Visit [Guardrails Hub](https://hub.guardrailsai.com/) to see the full list of validators and their documentation.
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Guardrails Hub is a collection of pre-built measures of specific types of risks (called 'validators'). Multiple validators can be combined together into Input and Output Guards that intercept the inputs and outputs of LLMs. Visit [Guardrails Hub](https://guardrailsai.com/hub/) to see the full list of validators and their documentation.
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/dist/img/guardrails_hub.gif" alt="Guardrails Hub gif" width="600px">
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<img src="https://raw.githubusercontent.com/guardrails-ai/guardrails/main/docs/assets/guardrails_hub.gif" alt="Guardrails Hub gif" width="600px">
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</div>
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#### Can I use Guardrails with any LLM?
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Yes, Guardrails can be used with proprietary and open-source LLMs. Check out this guide on [how to use Guardrails with any LLM](https://www.guardrailsai.com/docs/how_to_guides/llm_api_wrappers).
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Yes, Guardrails can be used with proprietary and open-source LLMs. Check out this guide on [how to use Guardrails with any LLM](https://guardrailsai.com/guardrails/docs/how-to-guides/using_llms).
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#### Can I create my own validators?
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Yes, you can create your own validators and contribute them to Guardrails Hub. Check out this guide on [how to create your own validators](https://www.guardrailsai.com/docs/hub/how_to_guides/custom_validator).
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Yes, you can create your own validators and contribute them to Guardrails Hub. Check out this guide on [how to create your own validators](https://guardrailsai.com/guardrails/docs/hub/how_to_guides/custom_validator).
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#### Does Guardrails support other languages?
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docs-graveyard/cli.md

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docs-graveyard/concepts/prompts_instructions.md

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