"""A prompt template string to put after the examples.""" input_variables: List[str] """A list of the names of the variables the prompt template expects.""" example_separator: str = "\n\n" """String separator used to join the prefix, the examples, and suffix.""" prefix: str =...
prompt += "1. 这种疾病的主要症状是什么?\n2. 推荐的治疗方法有哪些?" return PromptTemplate(input_variables=["disease_info"], template=prompt) # 假设我们从用户输入或API调用中获得了疾病信息 disease_info = {"disease": "流感", "symptoms": "发热、咳嗽", "treatment": "抗病毒药物、休息"} #...
your suggestion is: """ prompt_template = PromptTemplate(input_variables=["role", "information", "Job_Duty"], template=template) chain_Agent = LLMChain(llm=llm, prompt=prompt_template) Controller Agent 实现,以 IntentAgent 为例: from typing import List, Tuple, Any, Union from langchain.sch...
" """ #Adding new parameter to prompt QA_CHAIN_PROMPT = PromptTemplate(input_variables=["context", "question", "name", "answer"], template=template) #Passing values along with value for new parameter prompt = QA_CHAIN_PROMPT(context="Some context here", question="What is the purpose of...
Human:{input} Assistant:{desired_output} """ prompt = PromptTemplate(input_variables=["input", "desired_output"], template=template) few_shot_prompt = FewShotPromptTemplate( examples=examples, example_prompt=prompt, input_variables=["input"], ...
Gets or sets the collection of input variables used by the prompt template. C# [System.Text.Json.Serialization.JsonPropertyName("input_variables")]publicSystem.Collections.Generic.List<Microsoft.SemanticKernel.InputVariable> InputVariables {get;set; } ...
Issue with current documentation: Modules -> prompt templates This set code which is there in documentation is throwing error from langchain import PromptTemplate invalid_prompt = PromptTemplate( input_variables=["adjective"], template="...
input_variables=["input"], example_selector=example_selector, example_prompt=ChatPromptTemplate.from_messages( [("human", "{input}"), ("ai", "{output}")] ), ) Step 8: Testing the Template Simply test the few-shot on the data using the input from the dataset: ...
def validate_input_variables(cls, v): """Validate that the input variables are correct.""" iflen(v)!=1or"function_name"notinv: raise ValueError("function_name must be the only input_variable") returnv def format(self,**kwargs)->str: ...
在自己练习的时候,我想知道为什么我们不能使用 ChatPromptTemplate 而不是 PromptTemplate 来获取路由器提示。 Router_temp = MULTI_PROMPT_ROUTER_TEMPLATE.format(destinations = destination_str) router_prompt = ChatPromptTemplate(template = Router_temp, input_variables=["input"], output_parser= RouterOutput...