ipex-llm/python/llm/example/langchain/streamchat.py

71 lines
2.5 KiB
Python

#
# Copyright 2016 The BigDL Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# This would makes sure Python is aware there is more than one sub-package within bigdl,
# physically located elsewhere.
# Otherwise there would be module not found error in non-pip's setting as Python would
# only search the first bigdl package and end up finding only one sub-package.
import argparse
from bigdl.llm.langchain.llms import BigdlLLM
from langchain import PromptTemplate, LLMChain
from langchain.callbacks.manager import CallbackManager
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
def main(args):
question = args.question
model_path = args.model_path
model_family = args.model_family
n_threads = args.thread_num
template ="""{question}"""
prompt = PromptTemplate(template=template, input_variables=["question"])
# Callbacks support token-wise streaming
callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])
# Verbose is required to pass to the callback manager
llm = BigdlLLM(
model_path=model_path,
model_family=model_family,
n_threads=n_threads,
callback_manager=callback_manager,
verbose=True
)
llm_chain = LLMChain(prompt=prompt, llm=llm)
llm_chain.run(question)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='BigDL-LLM Langchain Streaming Chat Example')
parser.add_argument('-x','--model-family', type=str, required=True,
choices=["llama", "bloom", "gptneox"],
help='the model family')
parser.add_argument('-m','--model-path', type=str, required=True,
help='the path to the converted llm model')
parser.add_argument('-q', '--question', type=str, default='What is AI?',
help='qustion you want to ask.')
parser.add_argument('-t','--thread-num', type=int, default=2,
help='Number of threads to use for inference')
args = parser.parse_args()
main(args)