33 lines
1.4 KiB
Python
33 lines
1.4 KiB
Python
from dotenv import load_dotenv
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from langchain.output_parsers import StructuredOutputParser, ResponseSchema
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from langchain_core.prompts import PromptTemplate
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from langchain_openai import ChatOpenAI
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# 加载.env文件的环境变量
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load_dotenv()
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# 创建一个大语言模型，model指定了大语言模型的种类
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model = ChatOpenAI(model="qwen2.5-14b-instruct")
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# 想要接收的响应模式
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response_schemas = [
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ResponseSchema(name="brand_name", description="Brand name."),
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ResponseSchema(name="brand_slogan", description="Brand slogan."),
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ResponseSchema(name="brand_logo_prompt", description="prompt required for brand logo generation.")
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]
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output_parser = StructuredOutputParser.from_response_schemas(response_schemas)
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format_instructions = output_parser.get_format_instructions()
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prompt = PromptTemplate(
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template="你是一个时装品牌的设计师。根据用户输入提取出brand name，brand slogan,brand logo 描述。如果没有以上内容，需要你根据用户输入随意发挥。随后根据brand logo 描述生成一个prompt，这个prompt用于生成模型.\n{format_instructions}\n{question}",
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input_variables=["question"],
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partial_variables={"format_instructions": format_instructions}
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)
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_input = prompt.format_prompt(question="brand name: cat home")
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output = model(_input.to_messages())
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brand_data = output_parser.parse(output.content)
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def generate_logo(bucket_name, object_name, prompt):
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pass
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