■ merge_message_runs 함수를 사용해 동일한 유형의 메시지를 병합하는 방법을 보여준다.
▶ main.py
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from langchain_core.messages import SystemMessage from langchain_core.messages import HumanMessage from langchain_core.messages import AIMessage from langchain_core.messages import merge_message_runs sourceMessageList = [ SystemMessage("you're a good assistant."), SystemMessage("you always respond with a joke."), HumanMessage([{"type": "text", "text": "i wonder why it's called langchain"}]), HumanMessage("and who is harrison chasing anyways"), AIMessage('Well, I guess they thought "WordRope" and "SentenceString" just didn\'t have the same ring to it!'), AIMessage("Why, he's probably chasing after the last cup of coffee in the office!") ] targetMessageList = merge_message_runs(sourceMessageList) print("\n\n".join([repr(x) for x in targetMessageList])) """ SystemMessage(content="you're a good assistant.\nyou always respond with a joke.") HumanMessage(content=[{'type': 'text', 'text': "i wonder why it's called langchain"}, 'and who is harrison chasing anyways']) AIMessage(content='Well, I guess they thought "WordRope" and "SentenceString" just didn\'t have the same ring to it!\nWhy, he\'s probably chasing after the last cup of coffee in the office!') """ |
▶ requirements.txt
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aiohttp==3.9.5 aiosignal==1.3.1 annotated-types==0.7.0 async-timeout==4.0.3 attrs==23.2.0 certifi==2024.6.2 charset-normalizer==3.3.2 frozenlist==1.4.1 greenlet==3.0.3 idna==3.7 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.2.5 langchain-core==0.2.9 langchain-text-splitters==0.2.1 langsmith==0.1.82 multidict==6.0.5 numpy==1.26.4 orjson==3.10.5 packaging==24.1 pydantic==2.7.4 pydantic_core==2.18.4 PyYAML==6.0.1 requests==2.32.3 SQLAlchemy==2.0.31 tenacity==8.4.2 typing_extensions==4.12.2 urllib3==2.2.2 yarl==1.9.4 |
※ pip install langchain 명령을 실행했다.