rail_parser: Allow creation from pydantic (#6832)

<!-- Thank you for contributing to LangChain!

Replace this comment with:
  - Description: a description of the change, 
  - Issue: the issue # it fixes (if applicable),
  - Dependencies: any dependencies required for this change,
- Tag maintainer: for a quicker response, tag the relevant maintainer
(see below),
- Twitter handle: we announce bigger features on Twitter. If your PR
gets announced and you'd like a mention, we'll gladly shout you out!

If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
  2. an example notebook showing its use.

Maintainer responsibilities:
  - General / Misc / if you don't know who to tag: @dev2049
  - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
  - Models / Prompts: @hwchase17, @dev2049
  - Memory: @hwchase17
  - Agents / Tools / Toolkits: @vowelparrot
  - Tracing / Callbacks: @agola11
  - Async: @agola11

If no one reviews your PR within a few days, feel free to @-mention the
same people again.

See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md
 -->

Adds a way to create the guardrails output parser from a pydantic model.

langchain/output_parsers/rail_parser.py

@@ -61,6 +61,29 @@ def from_rail_string(
             kwargs=kwargs,
         )
 
+    @classmethod
+    def from_pydantic(
+        cls,
+        output_class: Any,
+        num_reasks: int = 1,
+        api: Optional[Callable] = None,
+        *args: Any,
+        **kwargs: Any,
+    ) -> GuardrailsOutputParser:
+        try:
+            from guardrails import Guard
+        except ImportError:
+            raise ValueError(
+                "guardrails-ai package not installed. "
+                "Install it by running `pip install guardrails-ai`."
+            )
+        return cls(
+            guard=Guard.from_pydantic(output_class, "", num_reasks=num_reasks),
+            api=api,
+            args=args,
+            kwargs=kwargs,
+        )
+
     def get_format_instructions(self) -> str:
         return self.guard.raw_prompt.format_instructions