from langchain.output_parsers import DatetimeOutputParser from datetime import datetime # 创建解析器实例 class CustomDatetimeOutputParser(DatetimeOutputParser): def parse(self, text: str) -> datetime: try: # 自定义日期时间格式 return datetime.strptime(text, "%Y-%m-%d %H:%M:%S") except ValueError...
OutputParser示例流程 3.1 引入相关的包 import os # 导入操作系统模块 import json # 导入json模块 os.environ['OpenAI_API_KEY'] = 'hk-iwtb91e427' # 设置OpenAI API密钥 from langchain_core.output_parsers import PydanticOutputParser, JsonOutputParser from langchain_core.prompts import PromptTemplate f...
下面是一个简单的自定义OutputParser类示例: python from langchain.output_parsers import BaseOutputParser from pydantic import BaseModel class SumResult(BaseModel): result: int class MyCustomOutputParser(BaseOutputParser): def parse(self, output: str) -> SumResult: try: # 假设输出是一个整数...
parser =OutputParser(config=self.config, log_obj=self.log_obj, error_list=MakefileErrorList) parser.add_lines(output)ifparser.num_errors: self.add_failure(locale, message="%s failed in make upload!"% (locale))continuepackage_name = base_package_name % {"locale": locale} r = re.compile...
LangChain 为输出解析器提供了基础类 BaseOutputParser。不同的输出解析器都继承自该类。 它们需要实现以下两个函数: get_format_instructions:返回指令指定LLM的输出该如何格式化,该函数在实现类中必须重写。基类中的函数实现如下: def get_format_instructions(self) -> str: ...
HRESULT IVsLaunchPadOutputParser::ParseOutputStringForInfo( [in] LPCOLESTR pszOutputString, [out] BSTR *pbstrFilename, [out] ULONG *pnLineNum, [out] ULONG *pnPriority, [out] BSTR *pbstrTaskItemText, [out] BSTR *pbstrHelpKeyword ); Applies to 产品版本 Visual Studio SDK ...
That is all about the process of using the output parser in LangChain. Conclusion To use the output parser in LangChain, install the modules and set up the OpenAI environment using its API key. After that, define the model and then configure the data structure of the output with logic val...
output_parsers import PydanticOutputParser from langchain.prompts import PromptTemplate from langchain.pydantic_v1 import BaseModel, Field load_dotenv() openai.api_key = os.getenv("OPENAI_API_KEY") class Task(BaseModel): id: int = Field(description="Autoincrement task id") name: str = ...
System Info Langchain Version: 0.0.207 Who can help? Is there a way to get the whole output with Output Parser or OpenAI function calling? I have a simple prompt where I get the LLM to output responses to a set of questions, and I would ...
true_val.upper() @property def _type(self) -> str: return "boolean_output_parser"API Reference:OutputParserException | BaseOutputParserparser = BooleanOutputParser()parser.invoke("YES")True try: parser.invoke("MEOW")except Exception as e: print(f"Triggered an exception of type: {type(e)}...