langchain 入门指南 - 如何做好 Prompt

from langchain.output_parsers import StructuredOutputParser, ResponseSchema
from langchain_core.prompts import PromptTemplate
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
    model_name="gpt-3.5-turbo",
    temperature=0.5,
    max_tokens=200
)
response_schemas = [
    ResponseSchema(name="content", description="The original content"),
    ResponseSchema(name="summary", description="The summary of the content"),
]
output_parser = StructuredOutputParser.from_response_schemas(response_schemas)
format_instructions = output_parser.get_format_instructions()
summarizing_prompt_template = """
{format_instructions}
总结以下文本为一个 20 字以内的句子:
---
{content}
"""
prompt = PromptTemplate.from_template(
    summarizing_prompt_template,
    partial_variables={'format_instructions': format_instructions}
)
summarizing_chain = prompt | llm | output_parser
print(summarizing_chain.invoke({"content": "这是一个测试。"}))

from langchain import PromptTemplate
template = """你是业务咨询顾问。你给一个销售{product}的电商公司，起一个好的名字。"""
prompt = PromptTemplate.from_template(template)
print(prompt.format(product="手机"))

from langchain import PromptTemplate
prompt = PromptTemplate(
    template="""你是业务咨询顾问。你给一个销售{product}的电商公司，起一个好的名字。""",
    input_variables=['product']
)
print(prompt.format(product="电脑"))

from openai import OpenAI
client = OpenAI()
client.chat.completions.create(
    model='gpt-3.5-turbo',
    messages=[
        {'role': 'system', 'content': 'You are a helpful assistant.'},
        {'role': 'user', 'content': 'What is the capital of France?'},
        {'role': 'assistant', 'content': 'The capital of France is Paris.'}
    ]
)

from langchain.prompts import (
    ChatPromptTemplate,
    SystemMessagePromptTemplate,
    HumanMessagePromptTemplate
)
template = "你是一位专业顾问，负责为专注于{product}的公司起名"
system_message_prompt = SystemMessagePromptTemplate.from_template(template)
human_template = "公司主打产品是{product_detail}"
human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
prompt_template = ChatPromptTemplate.from_messages([
    system_message_prompt,
    human_message_prompt
])
prompt = prompt_template.format_prompt(product="鲜花装饰", product_detail="创新的鲜花设计").to_messages()
from langchain.chat_models import ChatOpenAI
chat = ChatOpenAI()
result = chat(prompt)
print(result)

samples = [
    {
        "flower_type": "玫瑰",
        "occasion": "爱情",
        "ad_copy": "玫瑰，浪漫的象征，是你向心爱的人表达爱意的最佳选择。"
    },
    {
        "flower_type": "康乃馨",
        "occasion": "母亲节",
        "ad_copy": "康乃馨代表着母爱的纯洁与伟大，是母亲节赠送给母亲的完美礼物。"
    },
    {
        "flower_type": "百合",
        "occasion": "庆祝",
        "ad_copy": "百合象征着纯洁与高雅，是你庆祝特殊时刻的理想选择。"
    },
    {
        "flower_type": "向日葵",
        "occasion": "鼓励",
        "ad_copy": "向日葵代表着阳光与希望，是你鼓励朋友或家人的最佳礼物。"
    }
]
from langchain.prompts.prompt import PromptTemplate
template = "鲜花类型：{flower_type}\n适用场合：{occasion}\n广告文案：{ad_copy}"
prompt_sample = PromptTemplate(
    input_variables=["flower_type", "occasion", "ad_copy"],
    template=template
)
print(prompt_sample.format_prompt(**samples[0]))
from langchain.prompts.few_shot import FewShotPromptTemplate
prompt = FewShotPromptTemplate(
    examples=samples,
    example_prompt=prompt_sample,
    suffix="鲜花类型：{flower_type}\n适用场合：{occasion}",
    input_variables=["flower_type", "occasion"]
)
print(prompt.format(flower_type="野玫瑰", occasion="爱情"))
from langchain.chat_models import ChatOpenAI
llm = ChatOpenAI(
    model='gpt-3.5-turbo',
    temperature=0.5,
    max_tokens=200
)
res = llm.invoke(prompt.format(flower_type="野玫瑰", occasion="爱情"))
print(res)

from langchain.prompts.example_selector import SemanticSimilarityExampleSelector
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
example_selector = SemanticSimilarityExampleSelector.from_examples(
    samples,
    OpenAIEmbeddings(),
    Chroma,
    k=1
)
prompt = FewShotPromptTemplate(
    example_selector=example_selector,
    example_prompt=prompt_sample,
    suffix="鲜花类型：{flower_type}\n适用场合：{occasion}",
    input_variables=["flower_type", "occasion"]
)
print(prompt.format(flower_type="野玫瑰", occasion="爱情"))