Instructions to use realitisoft/ai-bot-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use realitisoft/ai-bot-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="realitisoft/ai-bot-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("realitisoft/ai-bot-test") model = AutoModelForSpeechSeq2Seq.from_pretrained("realitisoft/ai-bot-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ai-bot-test / venv /lib /python3.11 /site-packages /prompt_toolkit /contrib /regular_languages /validation.py
Download venv/lib/python3.11/site-packages/prompt_toolkit/contrib/regular_languages/validation.py from realitisoft/ai-bot-test: direct link, hf CLI and curl.
- Browser
- Download file 2.06 kB
-
https://huggingface.co/realitisoft/ai-bot-test/resolve/main/venv/lib/python3.11/site-packages/prompt_toolkit/contrib/regular_languages/validation.py
- Command line
-
hf download hf://realitisoft/ai-bot-test/venv/lib/python3.11/site-packages/prompt_toolkit/contrib/regular_languages/validation.py
-
curl -L -o validation.py https://huggingface.co/realitisoft/ai-bot-test/resolve/main/venv/lib/python3.11/site-packages/prompt_toolkit/contrib/regular_languages/validation.py
2.06 kB
| """ | |
| Validator for a regular language. | |
| """ | |
| from __future__ import annotations | |
| from prompt_toolkit.document import Document | |
| from prompt_toolkit.validation import ValidationError, Validator | |
| from .compiler import _CompiledGrammar | |
| __all__ = [ | |
| "GrammarValidator", | |
| ] | |
| class GrammarValidator(Validator): | |
| """ | |
| Validator which can be used for validation according to variables in | |
| the grammar. Each variable can have its own validator. | |
| :param compiled_grammar: `GrammarCompleter` instance. | |
| :param validators: `dict` mapping variable names of the grammar to the | |
| `Validator` instances to be used for each variable. | |
| """ | |
| def __init__( | |
| self, compiled_grammar: _CompiledGrammar, validators: dict[str, Validator] | |
| ) -> None: | |
| self.compiled_grammar = compiled_grammar | |
| self.validators = validators | |
| def validate(self, document: Document) -> None: | |
| # Parse input document. | |
| # We use `match`, not `match_prefix`, because for validation, we want | |
| # the actual, unambiguous interpretation of the input. | |
| m = self.compiled_grammar.match(document.text) | |
| if m: | |
| for v in m.variables(): | |
| validator = self.validators.get(v.varname) | |
| if validator: | |
| # Unescape text. | |
| unwrapped_text = self.compiled_grammar.unescape(v.varname, v.value) | |
| # Create a document, for the completions API (text/cursor_position) | |
| inner_document = Document(unwrapped_text, len(unwrapped_text)) | |
| try: | |
| validator.validate(inner_document) | |
| except ValidationError as e: | |
| raise ValidationError( | |
| cursor_position=v.start + e.cursor_position, | |
| message=e.message, | |
| ) from e | |
| else: | |
| raise ValidationError( | |
| cursor_position=len(document.text), message="Invalid command" | |
| ) | |