contributing and readme swap

CONTRIBUTING.md

@@ -0,0 +1,38 @@
+# Guardrails Validator Template
+
+## How to create a Guardrails Validator
+- On the top right of the page, click "Use this template", select "create a new repository"  and set a name for the package.  See [Naming Conventions](#naming-conventions) below.
+- Clone down the new repository.
+- Modify the class in [validator/main.py](validator/main.py) with source code for the new validator
+    - Make sure that the class still inherits from `Validator` and has the `register_validator` annotation.
+    - Set the `name` in the `register_validator` to the name of the repo prefixed with your org as a namespace and set the appropriate data type.
+- Change [validator/__init__.py](validator/__init__.py) to your new Validator classname instead of ValidatorTemplate
+- Perform a self install with `make dev` or `pip install -e ".[dev]"`
+- Locally test the validator with the [test instructions below](#testing-and-using-your-validator)
+- Modify the README and follow the Validator Card format; you can find an example [here](https://github.com/guardrails-ai/lowercase/blob/main/README.md)
+
+* Note: This package uses a pyproject.toml file, on first run, run `make dev` to pull down and install all dependencies
+
+### Naming Conventions
+1. Avoid using `is` and `bug`
+2. Use snake_case: i.e. `_` to separate words. e.g. valid_address
+3. For the description of the repo, write one sentence that says what the validator does; should be the same as the description in the pydoc string.
+4. When annotating the class use the `{namespace}/{validator_name}` pattern: e.g. `@register_validator(name=“guardrails/valid_address”)`
+
+### Testing and using your validator
+- Open [test/test-validator.py](test/test-validator.py) to test your new validator 
+- Import your new validator and modify `ValidatorTestObject` accordingly
+- Modify the TEST_OUTPUT and TEST_FAIL_OUTPUT accordingly
+- Run `python test/test-validator.py` via terminal, make sure the returned output reflects the input object 
+- Write advanced tests for failures, etc.
+
+## Upload your validator to the validator hub
+- Update the [pyproject.toml](pyproject.toml) file and make necessary changes as follows:
+    - Update the `name` field to the name of your validator
+    - Update the `description` field to a short description of your validator
+    - Update the `authors` field to your name and email
+    - Add/update the `dependencies` field to include all dependencies your validator needs.
+- If there are are any post-installation steps such as downloading tokenizers, logging into huggingface etc., update the [post-install.py](validator/post-install.py) file accordingly.
+- You can add additional files to the [validator](validator) directory, but don't rename any existing files/directories.
+    - e.g. Add any environment variables (without the values, just the keys) to the [.env](.env) file.
+- Ensure that there are no other dependencies or any additional steps required to run your validator.

README.md

@@ -1,38 +1,77 @@
-# Guardrails Validator Template
-
-## How to create a Guardrails Validator
-- On the top right of the page, click "Use this template", select "create a new repository"  and set a name for the package.  See [Naming Conventions](#naming-conventions) below.
-- Clone down the new repository.
-- Modify the class in [validator/main.py](validator/main.py) with source code for the new validator
-    - Make sure that the class still inherits from `Validator` and has the `register_validator` annotation.
-    - Set the `name` in the `register_validator` to the name of the repo prefixed with your org as a namespace and set the appropriate data type.
-- Change [validator/__init__.py](validator/__init__.py) to your new Validator classname instead of ValidatorTemplate
-- Perform a self install with `make dev` or `pip install -e ".[dev]"`
-- Locally test the validator with the [test instructions below](#testing-and-using-your-validator)
-- Update this README to follow the Validator Card format; you can find an example [here](https://github.com/guardrails-ai/lowercase/blob/main/README.md)
-
-* Note: This package uses a pyproject.toml file, on first run, run `make dev` to pull down and install all dependencies
-
-### Naming Conventions
-1. Avoid using `is` and `bug`
-2. Use snake_case: i.e. `_` to separate words. e.g. valid_address
-3. For the description of the repo, write one sentence that says what the validator does; should be the same as the description in the pydoc string.
-4. When annotating the class use the `{namespace}/{validator_name}` pattern: e.g. `@register_validator(name=“guardrails/valid_address”)`
-
-### Testing and using your validator
-- Open [test/test-validator.py](test/test-validator.py) to test your new validator 
-- Import your new validator and modify `ValidatorTestObject` accordingly
-- Modify the TEST_OUTPUT and TEST_FAIL_OUTPUT accordingly
-- Run `python test/test-validator.py` via terminal, make sure the returned output reflects the input object 
-- Write advanced tests for failures, etc.
-
-## Upload your validator to the validator hub
-- Update the [pyproject.toml](pyproject.toml) file and make necessary changes as follows:
-    - Update the `name` field to the name of your validator
-    - Update the `description` field to a short description of your validator
-    - Update the `authors` field to your name and email
-    - Add/update the `dependencies` field to include all dependencies your validator needs.
-- If there are are any post-installation steps such as downloading tokenizers, logging into huggingface etc., update the [post-install.py](validator/post-install.py) file accordingly.
-- You can add additional files to the [validator](validator) directory, but don't rename any existing files/directories.
-    - e.g. Add any environment variables (without the values, just the keys) to the [.env](.env) file.
-- Ensure that there are no other dependencies or any additional steps required to run your validator.
+# Overview
+
+| Developed by | Guardrails AI |
+| Date of development | Feb 15, 2024 |
+| Validator type | Format |
+| Blog |  |
+| License | Apache 2 |
+| Input/Output | Output |
+
+# Description
+
+This validator ensures that a generated output is the literal "pass".
+
+# Installation
+
+```bash
+$ guardrails hub install hub://guardrails/validator_template
+```
+
+# Usage Examples
+
+## Validating string output via Python
+
+In this example, we’ll test that a generated word is `pass`.
+
+```python
+# Import Guard and Validator
+from guardrails.hub import ValidatorTemplate
+from guardrails import Guard
+
+# Initialize Validator
+val = ValidatorTemplate()
+
+# Setup Guard
+guard = Guard.from_string(
+    validators=[val, ...],
+)
+
+guard.parse("pass")  # Validator passes
+guard.parse("fail")  # Validator fails
+```
+
+## Validating JSON output via Python
+
+In this example, we verify that a processes’s status is specified as `pass`.
+
+```python
+# Import Guard and Validator
+from pydantic import BaseModel
+from guardrails.hub import ValidatorTemplate
+from guardrails import Guard
+
+val = ValidatorTemplate()
+
+# Create Pydantic BaseModel
+class Process(BaseModel):
+		process_name: str
+		status: str = Field(validators=[val])
+
+# Create a Guard to check for valid Pydantic output
+guard = Guard.from_pydantic(output_class=Process)
+
+# Run LLM output generating JSON through guard
+guard.parse("""
+{
+		"process_name": "tempalting",
+		"status": "pass"
+}
+""")
+```
+
+# API Reference
+
+`__init__`
+- `arg_1`: A placeholder argument to demonstrate how to use init arguments.
+- `arg_2`: Another placeholder argument to demonstrate how to use init arguments.
+- `on_fail`: The policy to enact when a validator fails.