■ ChatPromptTemplate 클래스의 from_messages 정적 메소드를 사용해 암시적으로 MessagesPlaceholder 객체를 만드는 방법을 보여준다.
▶ main.py
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from langchain_core.prompts import ChatPromptTemplate chatPromptTemplate = ChatPromptTemplate.from_messages( [ ("system" , "You are a helpful assistant. Answer all questions to the best of your ability."), ("placeholder", "{messages}") ] ) print(chatPromptTemplate) """ input_variables = [] optional_variables = ['messages'] input_types = { 'messages' : list[ typing.Annotated[ typing.Union[ typing.Annotated[langchain_core.messages.ai.AIMessage , Tag(tag = 'ai' )], typing.Annotated[langchain_core.messages.human.HumanMessage , Tag(tag = 'human' )], typing.Annotated[langchain_core.messages.chat.ChatMessage , Tag(tag = 'chat' )], typing.Annotated[langchain_core.messages.system.SystemMessage , Tag(tag = 'system' )], typing.Annotated[langchain_core.messages.function.FunctionMessage , Tag(tag = 'function' )], typing.Annotated[langchain_core.messages.tool.ToolMessage , Tag(tag = 'tool' )], typing.Annotated[langchain_core.messages.ai.AIMessageChunk , Tag(tag = 'AIMessageChunk' )], typing.Annotated[langchain_core.messages.human.HumanMessageChunk , Tag(tag = 'HumanMessageChunk' )], typing.Annotated[langchain_core.messages.chat.ChatMessageChunk , Tag(tag = 'ChatMessageChunk' )], typing.Annotated[langchain_core.messages.system.SystemMessageChunk , Tag(tag = 'SystemMessageChunk' )], typing.Annotated[langchain_core.messages.function.FunctionMessageChunk, Tag(tag = 'FunctionMessageChunk')], typing.Annotated[langchain_core.messages.tool.ToolMessageChunk , Tag(tag = 'ToolMessageChunk' )] ], FieldInfo( annotation = NoneType, required = True, discriminator = Discriminator( discriminator = <function _get_type at 0x0000024FD2ACA480>, custom_error_type = None, custom_error_message = None, custom_error_context = None ) ) ] ] } partial_variables = {'messages' : []} messages = [ SystemMessagePromptTemplate( prompt = PromptTemplate( input_variables = [], input_types = {}, partial_variables = {}, template = 'You are a helpful assistant. Answer all questions to the best of your ability.' ), additional_kwargs = {} ), MessagesPlaceholder(variable_name = 'messages', optional = True) ] """ |
▶ requirements.txt
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aiohappyeyeballs==2.4.4 aiohttp==3.11.10 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.7.0 attrs==24.2.0 certifi==2024.8.30 charset-normalizer==3.4.0 frozenlist==1.5.0 greenlet==3.1.1 h11==0.14.0 httpcore==1.0.7 httpx==0.28.1 idna==3.10 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.3.10 langchain-core==0.3.22 langchain-text-splitters==0.3.2 langsmith==0.1.147 multidict==6.1.0 numpy==2.2.0 orjson==3.10.12 packaging==24.2 propcache==0.2.1 pydantic==2.10.3 pydantic_core==2.27.1 PyYAML==6.0.2 requests==2.32.3 requests-toolbelt==1.0.0 sniffio==1.3.1 SQLAlchemy==2.0.36 tenacity==9.0.0 typing_extensions==4.12.2 urllib3==2.2.3 yarl==1.18.3 |
※ pip install langchain 명령을 실행했다.