编写代码 fromlangchain_core.output_parsersimportJsonOutputParserfromlangchain_openai.chat_modelsimportChatOpenAIasyncdefmain():model=ChatOpenAI(model="gpt-3.5-turbo",)chain=(model|JsonOutputParser())# Due to a bug in older versions of Langchain, JsonOutputParser did not stream results from some ...
model | JsonOutputParser() ) # Due to a bug in older versions of Langchain, JsonOutputParser did not stream results from some models async for text in chain.astream( 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer...
from langchain_core.output_parsers import JsonOutputParserfrom langchain_openai.chat_models import ChatOpenAIasync def main():model = ChatOpenAI(model="gpt-3.5-turbo",)chain = (model | JsonOutputParser()) # Due to a bug in older versions of Langchain, JsonOutputParser did not stream result...
import { z } from "zod"; import { StructuredOutputParser } from "langchain/output_parsers"; const parser = StructuredOutputParser.fromZodSchema( z.object({ answer: z.string().describe("answer to the user's question"), sources: z .array(z.string()) .describe("sources used to answer t...
from langchain_core.output_parsers import StrOutputParserfrom langchain_core.prompts import PromptTemplatefrom langchain_openai import ChatOpenAIllm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.5, max_tokens=200)summarizing_prompt_template = """输出为 JSON 格式,包含字段 content、summary。
python.langchain.com/docs/modules/model_io/output_parsers /\xe2\x80\xa6 (并处理嵌套此处解释... youtube.com/watch?v=yD_oDTeObJY)。\n 例如\n from langchain.output_parsers import PydanticOutputParser\nfrom pydantic import BaseModel, Field, validator\nfrom typing import List, Optional\n\n....
from langchain.output_parsers import ResponseSchema, StructuredOutputParser from langchain_community.llms.ollama import Ollama from langchain_core.pro
在LangChain中实现输出逻辑: 使用LangChain的ResponseSchema来定义输出结构,然后创建一个提示模板(PromptTemplate),该模板会包含我们期望的输出格式说明,并将这个说明传递给LLM。最后,使用StructuredOutputParser来解析LLM的输出,使其符合我们定义的JSON结构。 测试并验证JSON输出: 在实际应用中,我们需要测试生成的JSON输出是...
在langchian.js中,Structured output parser就是使用Zod来声明和校验JSON格式。 1.3.1 声明返回JSON格式 import { z } from"zod";import { StructuredOutputParser } from"langchain/output_parsers"; const parser = StructuredOutputParser.fromZodSchema(z.object({answer: z.string().describe("answer to the...
在Python 中,我们可以使用 JSON 格式来存储和传输数据。本文将介绍如何使用 Python 解析和输出成功的问答对 JSON 数据。我们将使用 langchain_core 库中的 ChatPromptTemplate 和StrOutputParser来实现这个过程,并提供了相应的示例代码。 第一部分:准备工作