Source code for langchain_experimental.llms.jsonformer_decoder

"""Experimental implementation of jsonformer wrapped LLM."""
from __future__ import annotations

import json
from typing import TYPE_CHECKING, Any, List, Optional, cast

from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline
from langchain_core.callbacks.manager import CallbackManagerForLLMRun

from langchain_experimental.pydantic_v1 import Field, root_validator

if TYPE_CHECKING:
    import jsonformer


[docs]def import_jsonformer() -> jsonformer: """Lazily import of the jsonformer package.""" try: import jsonformer except ImportError: raise ImportError( "Could not import jsonformer python package. " "Please install it with `pip install jsonformer`." ) return jsonformer
[docs]class JsonFormer(HuggingFacePipeline): """Jsonformer wrapped LLM using HuggingFace Pipeline API. This pipeline is experimental and not yet stable. """ json_schema: dict = Field(..., description="The JSON Schema to complete.") max_new_tokens: int = Field( default=200, description="Maximum number of new tokens to generate." ) debug: bool = Field(default=False, description="Debug mode.") # TODO: move away from `root_validator` since it is deprecated in pydantic v2 # and causes mypy type-checking failures (hence the `type: ignore`) @root_validator # type: ignore[call-overload] def check_jsonformer_installation(cls, values: dict) -> dict: import_jsonformer() return values def _call( self, prompt: str, stop: Optional[List[str]] = None, run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> str: jsonformer = import_jsonformer() from transformers import Text2TextGenerationPipeline pipeline = cast(Text2TextGenerationPipeline, self.pipeline) model = jsonformer.Jsonformer( model=pipeline.model, tokenizer=pipeline.tokenizer, json_schema=self.json_schema, prompt=prompt, max_number_tokens=self.max_new_tokens, debug=self.debug, ) text = model() return json.dumps(text)