Docker和Dify学习笔记
文章目录
- 1 docker学习
- 1.1 基本命令使用
- 1.1.1 docker ps查看当前正在运行的镜像
- 1.1.2 docker stop停止容器
- 1.1.3 docker compose容器编排
- 1.1.4 docker网络
- [1] 进入到容器里面敲命令
- [2] docker network ls
- [3] brige网络模式下容器访问宿主机的方式
- 2 Dify的安装和基础使用
- 2.1 下载dify的工程仓库
- 2.2 创建.env配置文件
- 2.3 修改Nginx的端口
- 2.4 启动Dify
- 2.5 添加一个本地模型
- 2.5.1 添加一个大语言模型
- 2.5.2 添加一个Embedding模型
- 3 基于Dify开发功能场景
- 3.1 Echarts绘图
- 3.2 让大模型能够解析Json
- 4 大模型或者Dify中常见的参数
- 4.1 Temperature
- 4 Dify使用过程中常见问题
- 4.1 json超长了，超过80000个字符了
- 参考资料
1 docker学习
1.1 基本命令使用
1.1.1 docker ps查看当前正在运行的镜像
PS E:\LargeModel\dify\docker> docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
5b2b8c1636e7 langgenius/dify-web:1.0.0 "/bin/sh ./entrypoin…" 6 minutes ago Up 6 minutes 3000/tcp thirsty_diffie
99740eb3c659 langgenius/dify-web:1.0.0 "/bin/sh ./entrypoin…" 6 minutes ago Up 6 minutes 3000/tcp upbeat_euclid
f8108bddcff7 nginx:latest "sh -c 'cp /docker-e…" 11 minutes ago Up 11 minutes 0.0.0.0:8001->80/tcp, 0.0.0.0:8443->443/tcp docker-nginx-1
2794a7f88a69 langgenius/dify-api:1.0.0 "/bin/bash /entrypoi…" 11 minutes ago Up 11 minutes 5001/tcp docker-api-1
d51ee39beb2c langgenius/dify-api:1.0.0 "/bin/bash /entrypoi…" 11 minutes ago Up 11 minutes 5001/tcp docker-worker-1
e008dc5e6386 ubuntu/squid:latest "sh -c 'cp /docker-e…" 11 minutes ago Up 11 minutes 3128/tcp docker-ssrf_proxy-1
8c966517876b langgenius/dify-sandbox:0.2.10 "/main" 11 minutes ago Up 11 minutes (healthy) docker-sandbox-1
a2d137e0f516 langgenius/dify-plugin-daemon:0.0.3-local "/bin/bash -c /app/e…" 11 minutes ago Up 11 minutes 0.0.0.0:5003->5003/tcp docker-plugin_daemon-1
56f97d78ab4c langgenius/dify-web:1.0.0 "/bin/sh ./entrypoin…" 11 minutes ago Up 11 minutes 3000/tcp docker-web-1
cfe29ccee8df postgres:15-alpine "docker-entrypoint.s…" 11 minutes ago Up 11 minutes (healthy) 0.0.0.0:5432->5432/tcp docker-db-1
edd0a6879ba7 semitechnologies/weaviate:1.19.0 "/bin/weaviate --hos…" 11 minutes ago Up 11 minutes docker-weaviate-1
191a080293e4 redis:6-alpine "docker-entrypoint.s…" 11 minutes ago Up 11 minutes (healthy) 6379/tcp docker-redis-1
PS E:\LargeModel\dify\docker>
1.1.2 docker stop停止容器
【停止指定名称的容器】
PS E:\LargeModel\dify\docker> docker stop thirsty_diffie
thirsty_diffie
【停止所有当前在运行的容器】
PS E:\LargeModel\dify\docker> docker stop $(docker ps -aq)
5b2b8c1636e7
99740eb3c659
f8108bddcff7
2794a7f88a69
d51ee39beb2c
e008dc5e6386
8c966517876b
a2d137e0f516
56f97d78ab4c
cfe29ccee8df
edd0a6879ba7
191a080293e4
fe75be867cd5
1.1.3 docker compose容器编排
1.1.4 docker网络
[1] 进入到容器里面敲命令
docker exec -it docker-api-1 /bin/bash
案例：安装ping命令和telnet命令
root@cb7f80d95b40:/app/api# apt-get update
Get:1 http://deb.debian.org/debian bookworm InRelease [151 kB]
Get:2 http://deb.debian.org/debian bookworm-updates InRelease [55.4 kB]
Get:3 http://deb.debian.org/debian-security bookworm-security InRelease [48.0 kB]
Get:4 http://deb.debian.org/debian bookworm/main amd64 Packages [8792 kB]
Get:5 http://deb.debian.org/debian bookworm-updates/main amd64 Packages [13.5 kB]
Get:6 http://deb.debian.org/debian-security bookworm-security/main amd64 Packages [246 kB]
Fetched 9306 kB in 8min 19s (18.6 kB/s)
Reading package lists... Done
root@cb7f80d95b40:/app/api# apt-get install -y iputils-ping
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
The following additional packages will be installed:libcap2-bin libpam-cap
The following NEW packages will be installed:
[2] docker network ls
PS D:\LargeModel> docker network ls
NETWORK ID NAME DRIVER SCOPE
35353aad5d22 bridge bridge local
6e02ea3b25c6 docker_default bridge local
5973270d4a91 docker_ssrf_proxy_network bridge local
503869a64910 host host local
a0056c2c396d none null local
[3] brige网络模式下容器访问宿主机的方式
容器内可以使用host.docker.internal来代替主机的ip
2 Dify的安装和基础使用
2.1 下载dify的工程仓库
git clone https://github.com/langgenius/dify.git
# 国内镜像站
https://gitee.com/dify_ai/dify
2.2 创建.env配置文件
我们进入dify目录下的docker目录中,
# 以示例创建一个.env的文件，执行下面命令
cp .\.env.example .env
2.3 修改Nginx的端口
默认占用的是80和443端口，如果你本机已经部署了其他的应用，占了该端口，修改.env文件中的下面两个变量
EXPOSE_NGINX_PORT=8001
EXPOSE_NGINX_SSL_PORT=8443
2.4 启动Dify
docker compose up -d
2.5 添加一个本地模型
2.5.1 添加一个大语言模型
这里需要注意， 我的ollama是直接安装在宿主机的。 但是Dify是通过docker启动起来的，这里涉及到docker和宿主机之间的通信。 如果docker访问宿主机，可以使用host.docker.internal域名，Docker的DNS可以解析这个域名。
2.5.2 添加一个Embedding模型
（1）安装bge-m3模型
ollama pull bge-m3
（2）Dify中配置embedding模型
3 基于Dify开发功能场景
3.1 Echarts绘图
思路就是利用Dify的echarts渲染的能力(即使是Dify自带的Echarts图表生成工具也是输出了一串echarts的配置字符串，甚至还没有直接写python代码生成来的直接)。 但是只能在工作流和chatflow里面使用。如果将绘图的工作流集成到Agent里面的话，会导致大模型解析不了json，输出不了内容了。
import json
import requests
from datetime import datetime, timedelta
import statistics"""这是一个try参数的机制
"""
def getValidResponse(url, headers, params):response = Nonefor resourceFlag in ['sw', 'lk', 'wlw']:params["resource_flag"] = resourceFlagresponse = requests.get(url= url, headers= headers, params= params, timeout= 10)# 检查请求是否成功if response.status_code == 200:try:json_data = response.json()print(json_data)if (not "data" in json_data) or json_data["data"] is None or len(json_data["data"]) <= 0:continueelse:return responseexcept ValueError:continue else:continue """获取某一个水库某一段时间内的的水情数据。（主要是水位）参数：startDate: start_dt=2025-03-16+10:00:00endDate: end_dt=2025-03-17+11:00:00
"""
def getWaterStatus(guid: str, stcd: str, startDate: str, endDate: str) -> dict:url = "https://sk.hubeishuiyi.cn/services/1234567890ABCDEFGHIJKLMN/res_z_detail/param"headers = {"Apikey": "F1DBECD719108635189480CF60E6553ADB3109616426BD537F25A430DFC613B491A025C4A51E77FD08C6E5B7CBE05917A461286E7B6D69F1AB1B14F946149D2065B0C675F8FEDF4B9B05C1496881BC5A"}params = {"is_tb": "n","pageNo": 1,"pageSize":10000,"st_cd": stcd,"resource_flag":"sw","flag": 1,"start_dt": startDate,"end_dt": endDate,"res_cd": guid}response = getValidResponse(url, headers, params)# 检查请求是否成功if response is not None and response.status_code == 200:try:json_data = response.json()# # 转为双引号的标准json字符串# json_data = json.dumps(json_data)# json_data = json.loads(json_data)print(json_data)if (not "data" in json_data) or json_data["data"] is None or len(json_data["data"]) <= 0:return {"result" : []} # 以时间作为横坐标timeList = []# 水位数据waterLevelList = []# 蓄水量waterStorageList = []for dataObject in json_data["data"]:timeStr = dataObject["tm"]timeList.append(timeStr)waterLevel = dataObject["rz"]waterLevelList.append(waterLevel)waterStorage = dataObject["w"]waterStorageList.append(waterStorage)statisticData = {"time": timeList,"waterLevel": waterLevelList,"waterStorage": waterStorageList}return {"result": statisticData}except ValueError:return {"result" : "Failed to parse JSON response"}else:statisticData = {"failMsg": f"Request failed. url = {url}, params = {params}"}return {"result" : statisticData}def calcYAxisMinMax(nums: list):minValue = min(nums) - 8if minValue < 0:minValue = 0maxValue = max(nums) + 8return minValue, maxValue"""参数：data： tuple的列表。
"""
def create_dynamic_table_str(headers: list, data):table = "|"for header in headers:table += f" {header} |"table += "\n|"for _ in headers:table += " ------- |"for row in data:table += "\n|"for item in row:table += f" {item} |"return tabledef constructTableString(timeList: list, waterLevelList: list) -> str:timeList = timeList[-10:]waterLevelList = waterLevelList[-10:]headers = ['时间', '水位(m)']data = list(zip(timeList, waterLevelList))return create_dynamic_table_str(headers, data)def constructStatisticString(waterLevelList: list) -> str:headers = ['统计项', '统计值']data = []minValue = min(waterLevelList)data.append(("最小值", f"{minValue:.2f}"))maxValue = max(waterLevelList)data.append(("最大值", f"{maxValue:.2f}"))meanValue = sum(waterLevelList) / len(waterLevelList)data.append(("平均值", f"{meanValue:.2f}"))# 计算列表的中位数medianValue = statistics.median(waterLevelList)data.append(("中位数", f"{medianValue:.2f}"))# 标准差devValue = statistics.stdev(waterLevelList)data.append(("标准差", f"{devValue:.2f}"))return create_dynamic_table_str(headers, data=data)def drawEcharts(data: dict) -> dict:if data is None or len(data) <= 0:return {"result": ""}if "time" not in data or "waterLevel" not in data or "waterStorage" not in data:return {"result": ""}waterStatusData = data# 提取时间和对应的数据timeList = list(reversed(waterStatusData["time"]))waterLevelList = waterStatusData["waterLevel"]waterStorageList = waterStatusData["waterStorage"]if timeList is None or len(timeList) < 2:return {"result": ""}# 绘图准备工作UTC_FORMAT = "%Y-%m-%d %H:%M:%S"startTime = datetime.strptime(timeList[0], UTC_FORMAT)endTime = datetime.strptime(timeList[-1], UTC_FORMAT)walterLevelMin, walterLevelMax = calcYAxisMinMax(waterLevelList)# 生成echarts配置echarts_config = {"color": ['#eb6877', '#0f91c4', '#46cbd4'],"title": {"subtext": f"{startTime.strftime('%m')}月{startTime.strftime('%d')}日-{endTime.strftime('%m')}月{endTime.strftime('%d')}日水位情况","left": 20},"tooltip": {"trigger": "axis","axisPointer": {"type": "cross"}},"legend": {# "data": ["水位", "最低气温", "降水"],"data": ["水位"],"right": 20},"xAxis": {"data": timeList,"axisLine": {"onZero": False}},"yAxis": [{"type": "value","name": "水位","position": "left","min": walterLevelMin,"max": walterLevelMax,"axisLabel": {"formatter": "{value} m"}},# {# "type": "value",# "name": "蓄水量",# "position": "right",# "axisLabel": {# "formatter": "{value} m"# }# }],"series": [{"name": "水位","type": "line","data": waterLevelList,"yAxisIndex": 0,"itemStyle": {"color": "#eae213"},"markPoint": {"data": [{"type": 'max'},{"type": 'min'},],# 设置为点"symbol": 'circle', # 调整点的大小"symbolSize": 8, "label": {"position": 'right',# 标签字体加粗"fontWeight": 'bold', # 标签字体大小"fontSize": 12 }},},# {# "name": "蓄水量",# "type": "bar",# "smooth": True,# "data": waterStorageList,# "yAxisIndex": 0,# "itemStyle": {# "color": "#4bb2fa"# }# },# {# "name": "降水",# "type": "bar",# "smooth": True,# "data": rainfall,# "yAxisIndex": 1,# "itemStyle": {# "color": "#31e84f"# }# }]}echartString = "```echarts\n" + json.dumps(echarts_config, indent=2, ensure_ascii=False) + "\n```"tableString = constructTableString(timeList, waterLevelList)statisticString = constructStatisticString(waterLevelList)# 生成输出文件output = echartString + "\n\n" \+ "最近十条数据展示：\n" + tableString + "\n\n" \+ "常用统计数据展示：\n" + statisticStringreturn {"result":output}def main(guid: str, stcdList: list) -> dict:if guid is None or stcdList is None or len(guid) <= 0 or len(stcdList) <= 0:return {"result" : ""}endDate = datetime.now()endDateStr = endDate.strftime("%Y-%m-%d %H:%M:%S")startDate = endDate - timedelta(days=15)startDateStr = startDate.strftime("%Y-%m-%d %H:%M:%S")result = getWaterStatus(guid=guid, stcd=stcdList[0], startDate=startDateStr, endDate=endDateStr)print(f"main.result = {result['result']}")markdownScript = drawEcharts(result["result"])print(markdownScript)return markdownScriptif __name__ == "__main__":# print(main('42022220001', ['61608180']))# print(main('42130330004', ["61608180"]))# print(main('42122350024', ['90021804']))print(main('42058340006', [ "90006379"]))
3.2 让大模型能够解析Json
4 大模型或者Dify中常见的参数
4.1 Temperature
LLM 生成是具有随机性的，在模型的顶层通过选取不同预测概率的预测结果来生成最后的结果。我们一般可以通过控制 temperature 参数来控制 LLM 生成结果的随机性与创造性。
Temperature 一般取值在 0~1 之间，当取值较低接近 0 时，预测的随机性会较低，产生更保守、可预测的文本，不太可能生成意想不到或不寻常的词。当取值较高接近 1 时，预测的随机性会较高，所有词被选择的可能性更大，会产生更有创意、多样化的文本，更有可能生成不寻常或意想不到的词。
4 Dify使用过程中常见问题
4.1 json超长了，超过80000个字符了
这是因为Dify限制了默认的长度。本地部署的情况下可以修改.env配置文件中的相关变量数值。 修改之后重启整个服务。
常见的参数和含义入下图所示：
重启服务所需要使用的命令：
docker compose down
docker compose up -d
参考资料
[1] https://mp.weixin.qq.com/s/n5GrGZ9hZmdhzt4avs1XSw
[2] https://wiki.eryajf.net/pages/674f53/
[3] https://zhuanlan.zhihu.com/p/20939683190
[4] https://dify.flowus.cn/haojixing/share/943044ea-005e-4e57-9e74-450700df71c2
[5] https://blog.csdn.net/luckcxy/article/details/144900399