When I have this code first

from langchain_community.llms import HuggingFacePipeline
from transformers import AutoTokenizer
import transformers
import torch

model="meta-llama/Llama-2-7b-chat-hf"
tokenizer=AutoTokenizer.from_pretrained(model)

pipeline=transformers.pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
    device_map="auto",
    max_length=1000,
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id
    )

llm=HuggingFacePipeline(pipeline=pipeline, model_kwargs={'temperature':0})

from langchain.prompts import PromptTemplate
prompt_template=PromptTemplate(input_variables=["book_name"],
                               template="Provide me a concise summary of the book {book_name}")

and then I complete it with

from langchain.chains import LLMChain

chain = LLMChain(llm=llm, prompt=prompt_template, verbose=True)
response= chain.run("Alchemist")
print(response)

I get a response with the summary I wanted , but I get deprecation warnings.
So following the warnings I try to replace the second part with

chain = prompt | llm
response = chain.invoke("The name of the rose")
print(response)

but I get the error

TypeError: Expected a Runnable, callable or dict.Instead got an unsupported type: <class 'str'>

What am I doing wrong?

I have used something similar but with llm being a HuggingFaceEndPoint and in that case it worked, so I suspect that it has to do with llm being a HuggingFacePipeline but can someone tell me how to correct the code?