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
Yeats_Liao2 分钟前
评估体系构建:基于自动化指标与人工打分的双重验证
运维·人工智能·深度学习·算法·机器学习·自动化
深圳市恒星物联科技有限公司6 分钟前
水质流量监测仪:复合指标监测的管网智能感知设备
大数据·网络·人工智能
断眉的派大星18 分钟前
均值为0,方差为1:数据的“标准校服”
人工智能·机器学习·均值算法
A尘埃27 分钟前
电子厂PCB板焊点缺陷检测(卷积神经网络CNN)
人工智能·神经网络·cnn
Tadas-Gao28 分钟前
缸中之脑:大模型架构的智能幻象与演进困局
人工智能·深度学习·机器学习·架构·大模型·llm
中金快讯30 分钟前
新视野混合净值波动有几何?贝莱德基金回撤控制策略是否命中关键?
人工智能
楚兴33 分钟前
MacBook M1 安装 OpenClaw 完整指南
人工智能·后端
23遇见38 分钟前
探索CANN:开源AI计算底座的关键组件与技术思想
人工智能
jl486382144 分钟前
变比测试仪显示屏的“标杆“配置!如何兼顾30000小时寿命与六角矢量图精准显示?
人工智能·经验分享·嵌入式硬件·物联网·人机交互
2301_818730561 小时前
transformer(上)
人工智能·深度学习·transformer