mirror of
https://github.com/hwchase17/langchain.git
synced 2025-06-03 13:43:24 +00:00
a487ec47f4
### Description: This PR sets a default value of `output_token_limit = 4000` for the `PowerBIToolkit` to fix the unintentionally validation error. ### Problem: When attempting to run a code snippet from [Langchain's PowerBI toolkit documentation](https://python.langchain.com/v0.1/docs/integrations/toolkits/powerbi/) to interact with a `PowerBIDataset`, the following error occurs: ``` pydantic.v1.error_wrappers.ValidationError: 1 validation error for QueryPowerBITool output_token_limit none is not an allowed value (type=type_error.none.not_allowed) ``` ### Root Cause: The issue arises because when creating a `QueryPowerBITool`, the `output_token_limit` parameter is unintentionally set to `None`, which is the current default for `PowerBIToolkit`. However, `QueryPowerBITool` expects a default value of `4000` for `output_token_limit`. This unintended override causes the error.17659ca2cd/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py (L63)17659ca2cd/libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py (L72-L79)17659ca2cd/libs/community/langchain_community/tools/powerbi/tool.py (L39)### Solution: To resolve this, the default value of `output_token_limit` is now explicitly set to `4000` in `PowerBIToolkit` to prevent the accidental assignment of `None`. Co-authored-by: ccurme <chester.curme@gmail.com>
118 lines
4.1 KiB
Python
118 lines
4.1 KiB
Python
"""Toolkit for interacting with a Power BI dataset."""
|
|
|
|
from __future__ import annotations
|
|
|
|
from typing import TYPE_CHECKING, List, Optional, Union
|
|
|
|
from langchain_core.callbacks import BaseCallbackManager
|
|
from langchain_core.language_models import BaseLanguageModel
|
|
from langchain_core.language_models.chat_models import BaseChatModel
|
|
from langchain_core.prompts import PromptTemplate
|
|
from langchain_core.prompts.chat import (
|
|
ChatPromptTemplate,
|
|
HumanMessagePromptTemplate,
|
|
SystemMessagePromptTemplate,
|
|
)
|
|
from langchain_core.tools import BaseTool
|
|
from langchain_core.tools.base import BaseToolkit
|
|
from pydantic import ConfigDict, Field
|
|
|
|
from langchain_community.tools.powerbi.prompt import (
|
|
QUESTION_TO_QUERY_BASE,
|
|
SINGLE_QUESTION_TO_QUERY,
|
|
USER_INPUT,
|
|
)
|
|
from langchain_community.tools.powerbi.tool import (
|
|
InfoPowerBITool,
|
|
ListPowerBITool,
|
|
QueryPowerBITool,
|
|
)
|
|
from langchain_community.utilities.powerbi import PowerBIDataset
|
|
|
|
if TYPE_CHECKING:
|
|
from langchain.chains.llm import LLMChain
|
|
|
|
|
|
class PowerBIToolkit(BaseToolkit):
|
|
"""Toolkit for interacting with Power BI dataset.
|
|
|
|
*Security Note*: This toolkit interacts with an external service.
|
|
|
|
Control access to who can use this toolkit.
|
|
|
|
Make sure that the capabilities given by this toolkit to the calling
|
|
code are appropriately scoped to the application.
|
|
|
|
See https://python.langchain.com/docs/security for more information.
|
|
|
|
Parameters:
|
|
powerbi: The Power BI dataset.
|
|
llm: The language model to use.
|
|
examples: Optional. The examples for the prompt. Default is None.
|
|
max_iterations: Optional. The maximum iterations to run. Default is 5.
|
|
callback_manager: Optional. The callback manager. Default is None.
|
|
output_token_limit: The output token limit. Default is 4000.
|
|
tiktoken_model_name: Optional. The TikToken model name. Default is None.
|
|
"""
|
|
|
|
powerbi: PowerBIDataset = Field(exclude=True)
|
|
llm: Union[BaseLanguageModel, BaseChatModel] = Field(exclude=True)
|
|
examples: Optional[str] = None
|
|
max_iterations: int = 5
|
|
callback_manager: Optional[BaseCallbackManager] = None
|
|
output_token_limit: int = 4000
|
|
tiktoken_model_name: Optional[str] = None
|
|
|
|
model_config = ConfigDict(
|
|
arbitrary_types_allowed=True,
|
|
)
|
|
|
|
def get_tools(self) -> List[BaseTool]:
|
|
"""Get the tools in the toolkit."""
|
|
return [
|
|
QueryPowerBITool(
|
|
llm_chain=self._get_chain(),
|
|
powerbi=self.powerbi,
|
|
examples=self.examples,
|
|
max_iterations=self.max_iterations,
|
|
output_token_limit=self.output_token_limit, # type: ignore[arg-type]
|
|
tiktoken_model_name=self.tiktoken_model_name,
|
|
),
|
|
InfoPowerBITool(powerbi=self.powerbi),
|
|
ListPowerBITool(powerbi=self.powerbi),
|
|
]
|
|
|
|
def _get_chain(self) -> LLMChain:
|
|
"""Construct the chain based on the callback manager and model type."""
|
|
from langchain.chains.llm import LLMChain
|
|
|
|
if isinstance(self.llm, BaseLanguageModel):
|
|
return LLMChain(
|
|
llm=self.llm,
|
|
callback_manager=self.callback_manager
|
|
if self.callback_manager
|
|
else None,
|
|
prompt=PromptTemplate(
|
|
template=SINGLE_QUESTION_TO_QUERY,
|
|
input_variables=["tool_input", "tables", "schemas", "examples"],
|
|
),
|
|
)
|
|
|
|
system_prompt = SystemMessagePromptTemplate(
|
|
prompt=PromptTemplate(
|
|
template=QUESTION_TO_QUERY_BASE,
|
|
input_variables=["tables", "schemas", "examples"],
|
|
)
|
|
)
|
|
human_prompt = HumanMessagePromptTemplate(
|
|
prompt=PromptTemplate(
|
|
template=USER_INPUT,
|
|
input_variables=["tool_input"],
|
|
)
|
|
)
|
|
return LLMChain(
|
|
llm=self.llm,
|
|
callback_manager=self.callback_manager if self.callback_manager else None,
|
|
prompt=ChatPromptTemplate.from_messages([system_prompt, human_prompt]),
|
|
)
|