jupyter ai 结合local llm 实现思路

参考链接:

jupyter ai develop 开发文档

https://jupyter-ai.readthedocs.io/en/latest/developers/index.html

langchain custom LLM 开发文档

https://python.langchain.com/v0.1/docs/modules/model_io/llms/custom_llm/

stackoverflow :intergrate Local LLM with jupyter ai question

https://stackoverflow.com/questions/78989389/jupyterai-local-llm-integration/78989646#78989646

作者krassowski blog ,关于jupyter lab 有117个post

https://stackoverflow.com/users/6646912/krassowski

====================================

思路

1。Briefly, define the CustomLLM with something like:

python 复制代码
from typing import Any, Dict, Iterator, List, Mapping, Optional

from langchain_core.callbacks.manager import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
from langchain_core.outputs import GenerationChunk


class CustomLLM(LLM):

    def _call(
        self,
        prompt: str,
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> str:
        payload = ... # TODO: pass `prompt` to payload here
        # TODO: define `headers`
        response = requests.request(method="POST", url="10.1xx.1xx.50:8084/generate", headers=headers, data=payload)
        return response.text  # TODO: change it accordingly

    @property
    def _llm_type(self) -> str:
        return "custom"

2。 create MyProvider

python 复制代码
# my_package/my_provider.py
from jupyter_ai_magics import BaseProvider


class MyProvider(BaseProvider, CustomLLM):
    id = "my_provider"
    name = "My Provider"
    model_id_key = "model"
    models = [
        "your_model"
    ]
    def __init__(self, **kwargs):
        model_id = kwargs.get("model_id")
        # you can use `model_id` in `CustomLLM` to change models within provider
        super().__init__(**kwargs)

3。define an entrypoint 程序入口,配置pyproject.toml

python 复制代码
# my_package/pyproject.toml
[project]
name = "my_package"
version = "0.0.1"

[project.entry-points."jupyter_ai.model_providers"]
my-provider = "my_provider:MyProvider"

=================================

部署

bash 复制代码
cd mypackage/
pip install -e .
相关推荐
JNU freshman15 分钟前
计算机视觉 之 经典模型汇总
人工智能·计算机视觉
苏苏susuus19 分钟前
NLP:RNN文本生成案例分享
人工智能·rnn·自然语言处理
东方佑38 分钟前
仅27M参数!SamOutVX轻量级语言模型刷新认知,小身材也有大智慧
人工智能·语言模型·自然语言处理
东临碣石8239 分钟前
【AI论文】OmniPart:基于语义解耦与结构连贯性的部件感知三维生成
人工智能
啾啾Fun1 小时前
咨询导览,AI发展趋势
人工智能
向阳逐梦1 小时前
PID控制算法理论学习基础——单级PID控制
人工智能·算法
2zcode1 小时前
基于Matlab多特征融合的可视化指纹识别系统
人工智能·算法·matlab
Liudef061 小时前
三维点云Transformer局部感受野构建:理论、方法与挑战
人工智能·深度学习·transformer
说私域1 小时前
基于定制开发开源AI智能名片与S2B2C商城小程序的旅游日志创新应用研究
人工智能·小程序·旅游
DAWN_T172 小时前
Transforms
pytorch·python·机器学习·jupyter·pycharm