本地化部署AI常见问题总结
满满的坑
去网上学习了如何部署AI，视频大约20分钟，但是搞了2天还是没有搞定。下载了docker,ollama，ollama里面的模型，根据RAGFLOW的文档进行配置，可是不是这里问题就是那里问题。一开始是docker的镜像源不对，好不容易镜像源搞好了，最后还是在配置模型的时候出错了。
错误如下：
基础URL:host.docker.internal:11434
后来看了官方文档，如何去修改内存，最后搞不定。真的耗费心力啊！
后续的麻烦事
折腾了将近一个星期，还是没有搞出来。把和自己电脑配置的相关内容记录一下：
1 电脑配置
2wsl配置
3比较重要的命令行
docker compose -f docker-compose.yml up -d #从docker仓库拉取RAGFLOW的各种容器
docker logs -f ragflow-server #启动ragflow服务
4如何快速进入网页版配置页面
http://localhost:8880/ 主要用作打开RAGFLOW的配置页面
5RAGFLOW/docker文件下.env文件的配置
注意：这个文件特别重要，里面的每个选项都要看懂，哪些需要注释，哪些不需要注释要根据自己的实际情况确定。
# The type of doc engine to use.
# Available options:
# - `elasticsearch` (default)
# - `infinity` (https://github.com/infiniflow/infinity)
# - `opensearch` (https://github.com/opensearch-project/OpenSearch)
#DOC_ENGINE=${DOC_ENGINE:-elasticsearch}
DOC_ENGINE=${DOC_ENGINE:-infinity}
# ------------------------------
# docker env var for specifying vector db type at startup
# (based on the vector db type, the corresponding docker
# compose profile will be used)
# ------------------------------
COMPOSE_PROFILES=${DOC_ENGINE}
# The version of Elasticsearch.
STACK_VERSION=8.11.3
# The hostname where the Elasticsearch service is exposed
ES_HOST=es01
# The port used to expose the Elasticsearch service to the host machine,
# allowing EXTERNAL access to the service running inside the Docker container.
ES_PORT=1200
# The password for Elasticsearch.
ELASTIC_PASSWORD=infini_rag_flow
# the hostname where OpenSearch service is exposed, set it not the same as elasticsearch
OS_PORT=1201
# The hostname where the OpenSearch service is exposed
OS_HOST=opensearch01
# The password for OpenSearch.
# At least one uppercase letter, one lowercase letter, one digit, and one special character
OPENSEARCH_PASSWORD=infini_rag_flow_OS_01
# The port used to expose the Kibana service to the host machine,
# allowing EXTERNAL access to the service running inside the Docker container.
KIBANA_PORT=6601
KIBANA_USER=rag_flow
KIBANA_PASSWORD=infini_rag_flow
# The maximum amount of the memory, in bytes, that a specific Docker container can use while running.
# Update it according to the available memory in the host machine.
MEM_LIMIT=8073741824
# The hostname where the Infinity service is exposed
INFINITY_HOST=infinity
# Port to expose Infinity API to the host
INFINITY_THRIFT_PORT=23817
INFINITY_HTTP_PORT=23820
INFINITY_PSQL_PORT=5432
#MYSQL_USER=ragflow
MYSQL_USER=root
# The password for MySQL.
MYSQL_PASSWORD=infini_rag_flow
#MYSQL_PASSWORD=YES
# The hostname where the MySQL service is exposed
MYSQL_HOST=mysql
# The database of the MySQL service to use
MYSQL_DBNAME=rag_flow
# The port used to expose the MySQL service to the host machine,
# allowing EXTERNAL access to the MySQL database running inside the Docker container.
MYSQL_PORT=5455
# The maximum size of communication packets sent to the MySQL server
MYSQL_MAX_PACKET=1073741824
# The hostname where the MinIO service is exposed
MINIO_HOST=minio
# The port used to expose the MinIO console interface to the host machine,
# allowing EXTERNAL access to the web-based console running inside the Docker container.
MINIO_CONSOLE_PORT=9001
# The port used to expose the MinIO API service to the host machine,
# allowing EXTERNAL access to the MinIO object storage service running inside the Docker container.
MINIO_PORT=9000
# The username for MinIO.
# When updated, you must revise the `minio.user` entry in service_conf.yaml accordingly.
MINIO_USER=rag_flow
# The password for MinIO.
# When updated, you must revise the `minio.password` entry in service_conf.yaml accordingly.
MINIO_PASSWORD=infini_rag_flow
# The hostname where the Redis service is exposed
REDIS_HOST=redis
# The port used to expose the Redis service to the host machine,
# allowing EXTERNAL access to the Redis service running inside the Docker container.
REDIS_PORT=6379
# The password for Redis.
REDIS_PASSWORD=infini_rag_flow
# The port used to expose RAGFlow's HTTP API service to the host machine,
# allowing EXTERNAL access to the service running inside the Docker container.
SVR_HTTP_PORT=9380
# The RAGFlow Docker image to download.
# Defaults to the v0.20.1-slim edition, which is the RAGFlow Docker image without embedding models.
#RAGFLOW_IMAGE=infiniflow/ragflow:v0.20.3-slim
#RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow #20250828注释掉了，因为没有embedding
#
# To download the RAGFlow Docker image with embedding models, uncomment the following line instead:
RAGFLOW_IMAGE=infiniflow/ragflow:v0.20.4
#RAGFLOW_IMAGE=infiniflow/ragflow:v0.20.1
#RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow
#RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow
#RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/infiniflow/ragflow:latest
#
# The Docker image of the v0.20.1 edition includes built-in embedding models:
# - BAAI/bge-large-zh-v1.5
# - maidalun1020/bce-embedding-base_v1
#
# If you cannot download the RAGFlow Docker image:
#
# - For the `nightly-slim` edition, uncomment either of the following:
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly-slim
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly-slim
#
# - For the `nightly` edition, uncomment either of the following:
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly
# The local time zone.
TIMEZONE='Asia/Shanghai'
# Uncomment the following line if you have limited access to huggingface.co:
# HF_ENDPOINT=https://hf-mirror.com
# Optimizations for MacOS
# Uncomment the following line if your operating system is MacOS:
# MACOS=1
# The maximum file size limit (in bytes) for each upload to your knowledge base or File Management.
# To change the 1GB file size limit, uncomment the line below and update as needed.
# MAX_CONTENT_LENGTH=1073741824
# After updating, ensure `client_max_body_size` in nginx/nginx.conf is updated accordingly.
# Note that neither `MAX_CONTENT_LENGTH` nor `client_max_body_size` sets the maximum size for files uploaded to an agent.
# See https://ragflow.io/docs/dev/begin_component for details.
# Controls how many documents are processed in a single batch.
# Defaults to 4 if DOC_BULK_SIZE is not explicitly set.
DOC_BULK_SIZE=${DOC_BULK_SIZE:-4}
# Defines the number of items to process per batch when generating embeddings.
# Defaults to 16 if EMBEDDING_BATCH_SIZE is not set in the environment.
EMBEDDING_BATCH_SIZE=${EMBEDDING_BATCH_SIZE:-16}
# Log level for the RAGFlow's own and imported packages.
# Available levels:
# - `DEBUG`
# - `INFO` (default)
# - `WARNING`
# - `ERROR`
# For example, the following line changes the log level of `ragflow.es_conn` to `DEBUG`:
# LOG_LEVELS=ragflow.es_conn=DEBUG
# aliyun OSS configuration
# STORAGE_IMPL=OSS
# ACCESS_KEY=xxx
# SECRET_KEY=eee
# ENDPOINT=http://oss-cn-hangzhou.aliyuncs.com
# REGION=cn-hangzhou
# BUCKET=ragflow65536
# A user registration switch:
# - Enable registration: 1
# - Disable registration: 0
REGISTER_ENABLED=1
# Sandbox settings
# Important: To enable sandbox, you must re-declare the compose profiles. See hints at the end of file.
# Double check if you add `sandbox-executor-manager` to your `/etc/hosts`
# Pull the required base images before running:
# docker pull infiniflow/sandbox-base-nodejs:latest
# docker pull infiniflow/sandbox-base-python:latest
# Our default sandbox environments include:
# - Node.js base image: includes axios
# - Python base image: includes requests, numpy, and pandas
# Specify custom executor images below if you're using non-default environments.
# SANDBOX_ENABLED=1
# SANDBOX_HOST=sandbox-executor-manager
# SANDBOX_EXECUTOR_MANAGER_IMAGE=infiniflow/sandbox-executor-manager:latest
# SANDBOX_EXECUTOR_MANAGER_POOL_SIZE=3
# SANDBOX_BASE_PYTHON_IMAGE=infiniflow/sandbox-base-python:latest
# SANDBOX_BASE_NODEJS_IMAGE=infiniflow/sandbox-base-nodejs:latest
# SANDBOX_EXECUTOR_MANAGER_PORT=9385
# SANDBOX_ENABLE_SECCOMP=false
# SANDBOX_MAX_MEMORY=256m # b, k, m, g
# SANDBOX_TIMEOUT=10s # s, m, 1m30s
# Important: To enable sandbox, you must re-declare the compose profiles.
# 1. Comment out the COMPOSE_PROFILES line above.
# 2. Uncomment one of the following based on your chosen document engine:
# - For Elasticsearch:
# COMPOSE_PROFILES=elasticsearch,sandbox
# - For Infinity:
# COMPOSE_PROFILES=infinity,sandbox
# - For OpenSearch:
# COMPOSE_PROFILES=opensearch,sandbox
HF_ENDPOINT=https://hf-mirror.com
MACOS=true
6docker-compose.yml文件配置
include:
- ./docker-compose-base.yml
# To ensure that the container processes the locally modified `service_conf.yaml.template` instead of the one included in its image, you need to mount the local `service_conf.yaml.template` to the container.为了确保容器处理本地修改的 service_conf.yaml.template, 而不是其映像中包含的那个，你需要将本地的 service_conf.yaml.template 挂载到容器中。
services:
ragflow:
depends_on:
mysql:
condition: service_healthy
image: ${RAGFLOW_IMAGE}
# Example configuration to set up an MCP server:
# command:
# - --enable-mcpserver
# - --mcp-host=0.0.0.0
# - --mcp-port=9382
# - --mcp-base-url=http://127.0.0.1:9380
# - --mcp-script-path=/ragflow/mcp/server/server.py
# - --mcp-mode=self-host
# - --mcp-host-api-key=ragflow-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# Optional transport flags for MCP (customize if needed).
# Host mode need to combined with --no-transport-streamable-http-enabled flag, namely, host+streamable-http is not supported yet.
# The following are enabled by default unless explicitly disabled with --no-<flag>.
# - --no-transport-sse-enabled # Disable legacy SSE endpoints (/sse and /messages/)
# - --no-transport-streamable-http-enabled # Disable Streamable HTTP transport (/mcp endpoint)
# - --no-json-response # Disable JSON response mode in Streamable HTTP transport (instead of SSE over HTTP)
container_name: ragflow-server
ports:
- ${SVR_HTTP_PORT}:9380
- 8880:80
- 4443:443
- 5678:5678
- 5679:5679
- 9382:9382 #entry for MCP (host_port:docker_port). The docker_port must match the value you set for `mcp-port` above.
volumes:
- ./ragflow-logs:/ragflow/logs
- ./nginx/ragflow.conf:/etc/nginx/conf.d/ragflow.conf
- ./nginx/proxy.conf:/etc/nginx/proxy.conf
- ./nginx/nginx.conf:/etc/nginx/nginx.conf
- ../history_data_agent:/ragflow/history_data_agent
- ./service_conf.yaml.template:/ragflow/conf/service_conf.yaml.template
- ./entrypoint.sh:/ragflow/entrypoint.sh
env_file: .env
environment:
- TZ=${TIMEZONE}
- HF_ENDPOINT=${HF_ENDPOINT-}
- MACOS=${MACOS-}
networks:
- ragflow
restart: on-failure
# https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
# If you use Docker Desktop, the --add-host flag is optional. This flag ensures that the host's internal IP is exposed to the Prometheus container.
extra_hosts:
- "host.docker.internal:host-gateway"
# executor:
# depends_on:
# mysql:
# condition: service_healthy
# image: ${RAGFLOW_IMAGE}
# container_name: ragflow-executor
# volumes:
# - ./ragflow-logs:/ragflow/logs
# - ./nginx/ragflow.conf:/etc/nginx/conf.d/ragflow.conf
# env_file: .env
# environment:
# - TZ=${TIMEZONE}
# - HF_ENDPOINT=${HF_ENDPOINT}
# - MACOS=${MACOS}
# entrypoint: "/ragflow/entrypoint_task_executor.sh 1 3"
# networks:
# - ragflow
# restart: on-failure
# # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
# # If you're using Docker Desktop, the --add-host flag is optional. This flag makes sure that the host's internal IP gets exposed to the Prometheus container.
# extra_hosts:
# - "host.docker.internal:host-gateway"
7 ollmama中下载好的大模型
D:\软件下载\ragflow-main\docker>ollama list
NAME ID SIZE MODIFIED
qwen:4b d53d04290064 2.3 GB 7 days ago
8需要下载的软件
801 OLLAMA
802 dockerdesktop
803 wsl
804 OLLAMA
805 迅雷
参考链接
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