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community[patch]: Fix error in LlamaCpp community LLM with Configurable Fields, 'grammar' custom type not available (#16995)

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- **Description:** Ensure the `LlamaGrammar` custom type is always
available when instantiating a `LlamaCpp` LLM
  - **Issue:** #16994 
  - **Dependencies:** None
  - **Twitter handle:** @fpaupier

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
François Paupier 2024-02-06 02:56:58 +01:00 committed by GitHub
parent 563f325034
commit 929f071513
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1 changed files with 2 additions and 5 deletions
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7
libs/community/langchain_community/llms/llamacpp.py
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@ -2,7 +2,7 @@ from __future__ import annotations
import logging
from pathlib import Path
from typing import TYPE_CHECKING, Any, Dict, Iterator, List, Optional, Union
from typing import Any, Dict, Iterator, List, Optional, Union
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
@ -11,9 +11,6 @@ from langchain_core.pydantic_v1 import Field, root_validator
from langchain_core.utils import get_pydantic_field_names
from langchain_core.utils.utils import build_extra_kwargs
if TYPE_CHECKING:
from llama_cpp import LlamaGrammar
logger = logging.getLogger(__name__)
@ -126,7 +123,7 @@ class LlamaCpp(LLM):
to force the model to generate valid JSON or to speak exclusively in emojis. At most
one of grammar_path and grammar should be passed in.
"""
grammar: Optional[Union[str, LlamaGrammar]] = None
grammar: Optional[Union[str, Any]] = None
"""
grammar: formal grammar for constraining model outputs. For instance, the grammar
can be used to force the model to generate valid JSON or to speak exclusively in