Bools are failing to parse

hey, another small parsing issue.

My sample case:

from langchain.output_parsers import GuardrailsOutputParser
from langchain.chat_models import ChatOpenAI
from langchain import PromptTemplate, LLMChain

rail_spec = """
    <rail version="0.1">
        <output>
            <string
                name="message"
                description="the message the user wants to send"
            />
            <bool
                name="is_message_satisfactory"
                description="Whether indicated they are satisfied with the draft message."
            />
        </output>

        <prompt>
            Extract the message the user wants to send. If the message does not exist, enter an empty string.
            Determine if the user is satisfied with the message. If the user is satisfied, enter `true`. If the user is not satisfied, enter `false`. If the answer does not exist, enter `false`.

        {{transcript}}
        ```

        @xml_prefix_prompt

        {output_schema}

        @json_suffix_prompt
    </prompt>
    </rail>
"""

output_parser = GuardrailsOutputParser.from_rail_string(rail_spec)

transcript = """ Person: Hi, can you help me draft a business letter? AI Assistant: Of course, what type of letter are you looking to draft? Person: I need to send a formal email to a potential client to introduce my business. AI Assistant: Great. Can you give me some more details about your business and the purpose of the email? Person: Sure, my business provides marketing services and I want to introduce our services to the potential client and request a meeting to discuss potential collaboration. AI Assistant: Understood. Would you like me to provide you with a template to start with? Person: Yes, that would be helpful. AI Assistant: Okay, here's a draft you can start with: Dear [Client Name], I hope this email finds you well. My name is [Your Name], and I am reaching out from [Your Business Name], a marketing services company. We specialize in helping businesses like yours increase their brand awareness and drive sales through various marketing strategies. I would like to take this opportunity to introduce our services to you and discuss potential collaboration opportunities. I would like to request a meeting to discuss in more detail how we can help your business grow. Please let me know if this is something that interests you, and we can schedule a time that works best for you. Thank you for considering [Your Business Name]. I look forward to hearing back from you. Best regards, [Your Name] """

chat_prompt = PromptTemplate( template=output_parser.guard.base_prompt, input_variables=["transcript"] )

chain = LLMChain(llm=ChatOpenAI(temperature=0), prompt=chat_prompt)

output = chain.run(transcript=transcript)

output_parser.parse(output)


I get the following:

```py
  File "/usr/local/lib/python3.11/site-packages/guardrails/datatypes.py", line 123, in validate
    value = self.from_str(value)
            ^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/guardrails/datatypes.py", line 185, in from_str
    if s.lower() == "true":
       ^^^^^^^
AttributeError: 'bool' object has no attribute 'lower'

It's notable that the LLM is providing good output, this is what I see as the values within the last frame:

{'s': False, 'self': <class 'guardrails.datatypes.Boolean'>}

I'm not yet too familiar with the codebase but my hunch is that we don't need to parse bools, assuming the LLM produces valid JSON. Alternatively, if the goal is to support non-JSON formats down the line, it may be worthwhile to pattern match on the type of s to route to the right parsing logic.

guardrails-ai / guardrails

Bools are failing to parse #56