mirror of
https://github.com/hwchase17/langchain
synced 2024-10-29 17:07:25 +00:00
69 lines
2.1 KiB
Python
69 lines
2.1 KiB
Python
"""Experimental implementation of jsonformer wrapped LLM."""
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from __future__ import annotations
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import json
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from typing import TYPE_CHECKING, Any, List, Optional, cast
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from langchain.callbacks.manager import CallbackManagerForLLMRun
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from langchain.llms.huggingface_pipeline import HuggingFacePipeline
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from langchain_experimental.pydantic_v1 import Field, root_validator
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if TYPE_CHECKING:
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import jsonformer
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def import_jsonformer() -> jsonformer:
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"""Lazily import jsonformer."""
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try:
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import jsonformer
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except ImportError:
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raise ImportError(
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"Could not import jsonformer python package. "
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"Please install it with `pip install jsonformer`."
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)
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return jsonformer
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class JsonFormer(HuggingFacePipeline):
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"""Jsonformer wrapped LLM using HuggingFace Pipeline API.
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This pipeline is experimental and not yet stable.
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"""
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json_schema: dict = Field(..., description="The JSON Schema to complete.")
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max_new_tokens: int = Field(
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default=200, description="Maximum number of new tokens to generate."
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)
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debug: bool = Field(default=False, description="Debug mode.")
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# TODO: move away from `root_validator` since it is deprecated in pydantic v2
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# and causes mypy type-checking failures (hence the `type: ignore`)
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@root_validator # type: ignore[call-overload]
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def check_jsonformer_installation(cls, values: dict) -> dict:
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import_jsonformer()
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return values
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def _call(
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self,
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prompt: str,
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stop: Optional[List[str]] = None,
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run_manager: Optional[CallbackManagerForLLMRun] = None,
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**kwargs: Any,
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) -> str:
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jsonformer = import_jsonformer()
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from transformers import Text2TextGenerationPipeline
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pipeline = cast(Text2TextGenerationPipeline, self.pipeline)
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model = jsonformer.Jsonformer(
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model=pipeline.model,
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tokenizer=pipeline.tokenizer,
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json_schema=self.json_schema,
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prompt=prompt,
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max_number_tokens=self.max_new_tokens,
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debug=self.debug,
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)
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text = model()
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return json.dumps(text)
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