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 Dify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 = None
for resourceFlag in ['sw', 'lk', 'wlw']:
params["resource_flag"] = resourceFlag
response = 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:
continue
else:
return response
except 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+10:00:00
endDate: 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) - 8
if minValue < 0:
minValue = 0
maxValue = max(nums) + 8
return 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 table
def 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" + statisticString
return {"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 markdownScript
if __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 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