■ ChatPromptTemplate 클래스의 partial 정적 메소드를 사용해 매개 변수를 템플리트에 전달하는 방법을 보여준다.
▶ main.py
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from typing import List from langchain_core.pydantic_v1 import BaseModel, Field from langchain_core.output_parsers import PydanticOutputParser from langchain_core.prompts import ChatPromptTemplate class Person(BaseModel): """Information about a person.""" name : str = Field(..., description = "The name of the person" ) height_in_meters : float = Field(..., description = "The height of the person expressed in meters.") class People(BaseModel): """Identifying information about all people in a text.""" people : List[Person] pydanticOutputParser = PydanticOutputParser(pydantic_object = People) instructionFormatString = pydanticOutputParser.get_format_instructions() chatPromptTemplate = ChatPromptTemplate.from_messages( [ ( "system", "Answer the user query. Wrap the output in `json` tags\n{format_instructions}", ), ("human", "{query}"), ] ).partial(format_instructions = instructionFormatString) query = "Anna is 23 years old and she is 6 feet tall" print(chatPromptTemplate.invoke(query).to_string()) """ System: Answer the user query. Wrap the output in `json` tags The output should be formatted as a JSON instance that conforms to the JSON schema below. As an example, for the schema {"properties": {"foo": {"title": "Foo", "description": "a list of strings", "type": "array", "items": {"type": "string"}}}, "required": ["foo"]} the object {"foo": ["bar", "baz"]} is a well-formatted instance of the schema. The object {"properties": {"foo": ["bar", "baz"]}} is not well-formatted. Here is the output schema: ``` {"description": "Identifying information about all people in a text.", "properties": {"people": {"title": "People", "type": "array", "items": {"$ref": "#/definitions/Person"}}}, "required": ["people"], "definitions": {"Person": {"title": "Person", "description": "Information about a person.", "type": "object", "properties": {"name": {"title": "Name", "description": "The name of the person", "type": "string"}, "height_in_meters": {"title": "Height In Meters", "description": "The height of the person expressed in meters.", "type": "number"}}, "required": ["name", "height_in_meters"]}}} ``` Human: Anna is 23 years old and she is 6 feet tall """ |
▶ 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==0.2.7 langchain-text-splitters==0.2.1 langsmith==0.1.77 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==2.0.30 tenacity==8.3.0 typing_extensions==4.12.2 urllib3==2.2.1 yarl==1.9.4 |
※ pip install langchain 명령을 실행했다.