@ -23,7 +23,7 @@ from towhee import pipe, ops 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					p = ( 
			
		
	
		
			
				
					    pipe.input('messages') 
			
		
	
		
			
				
					        .map('messages', 'answer', ops.LLM.Ernie(api_key=ERNIE_API_KEY, secret_key=ERNIE_SECRET_KEY)) 
			
		
	
		
			
				
					        .map('messages', 'answer', ops.LLM.Ernie(api_key=ERNIE_API_KEY, secret_key=ERNIE_SECRET_KEY, temperature=0.5 )) 
			
		
	
		
			
				
					        .output('answer') 
			
		
	
		
			
				
					) 
			
		
	
		
			
				
					
 
			
		
	
	
		
			
				
					
						
						
						
							
								 
						
					 
				
				@ -34,6 +34,38 @@ messages=[ 
			
		
	
		
			
				
					answer = p(messages).get()[0] 
			
		
	
		
			
				
					``` 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					*Write a [retrieval-augmented generation pipeline ](https://towhee.io/tasks/detail/pipeline/retrieval-augmented-generation ) with explicit inputs/outputs name specifications:* 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					```python 
			
		
	
		
			
				
					from towhee import pipe, ops 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					temp = '''根据以下材料回答最末尾的问题: 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					{context} 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					问题:{question} 
			
		
	
		
			
				
					''' 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					docs = ['你可以通过`pip install towhee` 安装 Towhee。'] 
			
		
	
		
			
				
					history = [ 
			
		
	
		
			
				
					    ('什么是 Towhee?', 'Towhee 是一个开源项目,可以将非结构化数据转换为向量。') 
			
		
	
		
			
				
					] 
			
		
	
		
			
				
					question = '怎么安装它?' 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					p = ( 
			
		
	
		
			
				
					    pipe.input('question', 'docs', 'history') 
			
		
	
		
			
				
					        .map(('question', 'docs', 'history'), 'prompt', ops.prompt.template(temp, ['question', 'context'])) 
			
		
	
		
			
				
					        .map('prompt', 'answer', 
			
		
	
		
			
				
					             ops.LLM.Ernie(api_key=ERNIE_API_KEY, secret_key=ERNIE_SECRET_KEY) 
			
		
	
		
			
				
					             ) 
			
		
	
		
			
				
					        .output('answer') 
			
		
	
		
			
				
					) 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					answer = p(question, docs, history).get()[0] 
			
		
	
		
			
				
					``` 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					< br  / >  
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					## Factory Constructor 接口说明 
			
		
	
	
		
			
				
					
						
						
						
							
								 
						
					 
				
				@ -55,7 +87,7 @@ The Ernie Secret key in string, defaults to None. If None, it will use the envir 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					***\*\*kwargs*** 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					Other OpenAI  parameters such as temperature, etc. 
			
		
	
		
			
				
					Other Ernie  parameters such as temperature, etc. 
			
		
	
		
			
				
					
 
			
		
	
		
			
				
					< br  / >