langchain+gpt+agent

一.agent+Conversation

通过用户问题，来选择

import json
import os
import refrom langchain import FAISS, PromptTemplate, LLMChain
from langchain.agents import initialize_agent, Tool, AgentType
from langchain.chains import RetrievalQA
from langchain.chat_models import ChatOpenAI
from langchain.document_loaders import TextLoader
from langchain.embeddings import OpenAIEmbeddings
from langchain.memory import ConversationBufferMemory
from langchain.text_splitter import SpacyTextSplitter
from langchain.tools import tool"""
pip install spacy
python -m spacy download zh_core_web_sm
"""os.environ["OPENAI_API_KEY"] = ''llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-16k", max_tokens=10240)  # type: ignorefile_path = "faq.txt"loader = TextLoader(file_path, encoding="utf-8")
documents = loader.load()
text_splitter = SpacyTextSplitter(chunk_size=500, chunk_overlap=0, pipeline="zh_core_web_sm", separator="\n\n")
texts = text_splitter.split_documents(documents)
embeddings = OpenAIEmbeddings()docsearch = FAISS.from_documents(texts, embeddings)
faq_chain = RetrievalQA.from_chain_type(llm=llm, retriever=docsearch.as_retriever(), verbose=True)order_1_num = "20230926001"order_2_num = "20230927002"order_1 = {"order_number": order_1_num,"statu": "已发货","shipping_date": "2023-09-26","estimated_delivered_date": "2023-09-31"
}order_2 = {"order_number": order_2_num,"statu": "未发货","shipping_date": None,"estimated_delivered_date": None}answer_order_info = PromptTemplate(template="请把下面的订单信息回复给用户:\n{order}?", input_variables=["order"])answer_order_llm = LLMChain(llm=ChatOpenAI(temperature=0), prompt=answer_order_info)# 模拟订单
@tool("searchOrder", return_direct=True)
def search_order(input: str) -> str:"""userful for when you need to answer questions about customers orders"""pattern = r"\d{11}"match = re.search(pattern, input)order_number = inputif match:order_number = match.group(0)else:return f"""请提供订单号"""if order_number == order_1_num:return answer_order_llm.run(json.dumps(order_1))elif order_number == order_2_num:return answer_order_llm.run(json.dumps(order_2))else:return f"""根据{input}没有找到订单"""# 模拟推荐商品
def recommend_product(input: str) -> str:if "male".lower() == input.lower():return "红色衣服,衣服的商品编号为999"elif "female".lower() == input.lower():return "黄色衣服,衣服的商品编号为888"else:return "蓝色衣服,衣服的商品编号为777"# 模拟推荐商品
@tool("productPrice", return_direct=True)
def product_price(input: str) -> str:"""userful for when you need to answer questions about product price.the user needs to provide the item number to query product priceAnswer users' questions in Chinese"""print(str)pattern = r"\d{3}"match = re.search(pattern, input)product_number = inputif match:product_number = match.group(0)else:return f"""请提供商品编号"""if "999" == product_number:return "价格为1080"elif "888" == product_number:return "价格为2080"elif "777" == product_number:return "价格为3080"else:return "价格不知道"# 模拟问电商faq
@tool("FAQ", return_direct=True)
def faq(input: str) -> str:"""userful for when you need to answer questions about shopping policies,like return policyAnswer users' questions in Chinese"""return faq_chain.run(input)tools = [Tool(name="recommend product", func=recommend_product,description="""userful for when you need to answer questions about product recommendations,"if question about male ,input value is male,    if question about female ,input value is female""",return_direct=True),faq,search_order,product_price
]memory = ConversationBufferMemory(memory_key="chat_history", return_message=True)
# 当没有相关答案，不需要一直重试，最大次数max_iterations=2
agent = initialize_agent(tools, llm, agent=AgentType.CONVERSATIONAL_REACT_DESCRIPTION, memory=memory, verbose=True)# question = "我有一个订单20230926002的购买日期是多久？一直没有收到，啥时候发货,帮我查下"
# print(agent.run(question))def query_answer(question: str) -> str:# question = "我要查询一个订单啥时候送到？"res = agent.run(question)print(res)return resif __name__ == '__main__':query_answer("我的订单到哪了？")

faq.txt

Q:如果更改收获地址？
A:在订单发货前，登录账号，进行修改，如果已经发货，联系客服协助处理Q:如何查询发票？
A:进入"我的发票"页面，在此页面上查看详细信息Q:为什么我的订单被取消？
A:订单可能因为库存不足，支付异常，用户要求等原因被取消，联系客服Q:如何使用优惠券？
A:在购物车页面，输入优惠券代码后，点击"应用"。优惠券折扣将自动应用你的订单Q:物流时效是多久？
A:一般情况下，大部分城市的订单在2-3个工作日，偏远地区是5-7个工作日，具体的配货时间可能因为订单的商品，物流公司而异