docker-compose安装anythingLLM

1、anythingLLM的docker-compose文件

version: '3.8'
services:anythingllm:image: mintplexlabs/anythingllm:latestcontainer_name: anythingllmports:- "23001:3001"cap_add:- SYS_ADMINenvironment:# Adjust for your environment- STORAGE_DIR=/app/server/storage- JWT_SECRET="admin123456"- PASSWORDMINCHAR=8volumes:- anythingllm_storage:/app/server/storagerestart: alwaysnetworks:- anythingllmnetworks:anythingllm:driver: bridgevolumes:anythingllm_storage:driver: localdriver_opts:type: noneo: bind# 宿主机文件夹device: /opt/st

anything 的environment 文件

SERVER_PORT=3001
STORAGE_DIR="/app/server/storage"
UID='1000'
GID='1000'
# SIG_KEY='passphrase' # Please generate random string at least 32 chars long.
# SIG_SALT='salt' # Please generate random string at least 32 chars long.
# JWT_SECRET="my-random-string-for-seeding" # Only needed if AUTH_TOKEN is set. Please generate random string at least 12 chars long.###########################################
######## LLM API SElECTION ################
###########################################
# LLM_PROVIDER='openai'
# OPEN_AI_KEY=
# OPEN_MODEL_PREF='gpt-4o'# LLM_PROVIDER='gemini'
# GEMINI_API_KEY=
# GEMINI_LLM_MODEL_PREF='gemini-pro'# LLM_PROVIDER='azure'
# AZURE_OPENAI_ENDPOINT=
# AZURE_OPENAI_KEY=
# OPEN_MODEL_PREF='my-gpt35-deployment' # This is the "deployment" on Azure you want to use. Not the base model.
# EMBEDDING_MODEL_PREF='embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002# LLM_PROVIDER='anthropic'
# ANTHROPIC_API_KEY=sk-ant-xxxx
# ANTHROPIC_MODEL_PREF='claude-2'# LLM_PROVIDER='lmstudio'
# LMSTUDIO_BASE_PATH='http://your-server:1234/v1'
# LMSTUDIO_MODEL_PREF='Loaded from Chat UI' # this is a bug in LMStudio 0.2.17
# LMSTUDIO_MODEL_TOKEN_LIMIT=4096# LLM_PROVIDER='localai'
# LOCAL_AI_BASE_PATH='http://host.docker.internal:8080/v1'
# LOCAL_AI_MODEL_PREF='luna-ai-llama2'
# LOCAL_AI_MODEL_TOKEN_LIMIT=4096
# LOCAL_AI_API_KEY="sk-123abc"# LLM_PROVIDER='ollama'
# OLLAMA_BASE_PATH='http://host.docker.internal:11434'
# OLLAMA_MODEL_PREF='llama2'
# OLLAMA_MODEL_TOKEN_LIMIT=4096
# OLLAMA_AUTH_TOKEN='your-ollama-auth-token-here (optional, only for ollama running behind auth - Bearer token)'# LLM_PROVIDER='togetherai'
# TOGETHER_AI_API_KEY='my-together-ai-key'
# TOGETHER_AI_MODEL_PREF='mistralai/Mixtral-8x7B-Instruct-v0.1'# LLM_PROVIDER='mistral'
# MISTRAL_API_KEY='example-mistral-ai-api-key'
# MISTRAL_MODEL_PREF='mistral-tiny'# LLM_PROVIDER='perplexity'
# PERPLEXITY_API_KEY='my-perplexity-key'
# PERPLEXITY_MODEL_PREF='codellama-34b-instruct'# LLM_PROVIDER='openrouter'
# OPENROUTER_API_KEY='my-openrouter-key'
# OPENROUTER_MODEL_PREF='openrouter/auto'# LLM_PROVIDER='huggingface'
# HUGGING_FACE_LLM_ENDPOINT=https://uuid-here.us-east-1.aws.endpoints.huggingface.cloud
# HUGGING_FACE_LLM_API_KEY=hf_xxxxxx
# HUGGING_FACE_LLM_TOKEN_LIMIT=8000# LLM_PROVIDER='groq'
# GROQ_API_KEY=gsk_abcxyz
# GROQ_MODEL_PREF=llama3-8b-8192# LLM_PROVIDER='koboldcpp'
# KOBOLD_CPP_BASE_PATH='http://127.0.0.1:5000/v1'
# KOBOLD_CPP_MODEL_PREF='koboldcpp/codellama-7b-instruct.Q4_K_S'
# KOBOLD_CPP_MODEL_TOKEN_LIMIT=4096# LLM_PROVIDER='textgenwebui'
# TEXT_GEN_WEB_UI_BASE_PATH='http://127.0.0.1:5000/v1'
# TEXT_GEN_WEB_UI_TOKEN_LIMIT=4096
# TEXT_GEN_WEB_UI_API_KEY='sk-123abc'# LLM_PROVIDER='generic-openai'
# GENERIC_OPEN_AI_BASE_PATH='http://proxy.url.openai.com/v1'
# GENERIC_OPEN_AI_MODEL_PREF='gpt-3.5-turbo'
# GENERIC_OPEN_AI_MODEL_TOKEN_LIMIT=4096
# GENERIC_OPEN_AI_API_KEY=sk-123abc# LLM_PROVIDER='litellm'
# LITE_LLM_MODEL_PREF='gpt-3.5-turbo'
# LITE_LLM_MODEL_TOKEN_LIMIT=4096
# LITE_LLM_BASE_PATH='http://127.0.0.1:4000'
# LITE_LLM_API_KEY='sk-123abc'# LLM_PROVIDER='novita'
# NOVITA_LLM_API_KEY='your-novita-api-key-here' check on https://novita.ai/settings/key-management
# NOVITA_LLM_MODEL_PREF='deepseek/deepseek-r1'# LLM_PROVIDER='cohere'
# COHERE_API_KEY=
# COHERE_MODEL_PREF='command-r'# LLM_PROVIDER='bedrock'
# AWS_BEDROCK_LLM_ACCESS_KEY_ID=
# AWS_BEDROCK_LLM_ACCESS_KEY=
# AWS_BEDROCK_LLM_REGION=us-west-2
# AWS_BEDROCK_LLM_MODEL_PREFERENCE=meta.llama3-1-8b-instruct-v1:0
# AWS_BEDROCK_LLM_MODEL_TOKEN_LIMIT=8191# LLM_PROVIDER='fireworksai'
# FIREWORKS_AI_LLM_API_KEY='my-fireworks-ai-key'
# FIREWORKS_AI_LLM_MODEL_PREF='accounts/fireworks/models/llama-v3p1-8b-instruct'# LLM_PROVIDER='apipie'
# APIPIE_LLM_API_KEY='sk-123abc'
# APIPIE_LLM_MODEL_PREF='openrouter/llama-3.1-8b-instruct'# LLM_PROVIDER='xai'
# XAI_LLM_API_KEY='xai-your-api-key-here'
# XAI_LLM_MODEL_PREF='grok-beta'# LLM_PROVIDER='nvidia-nim'
# NVIDIA_NIM_LLM_BASE_PATH='http://127.0.0.1:8000'
# NVIDIA_NIM_LLM_MODEL_PREF='meta/llama-3.2-3b-instruct'# LLM_PROVIDER='deepseek'
# DEEPSEEK_API_KEY='your-deepseek-api-key-here'
# DEEPSEEK_MODEL_PREF='deepseek-chat'# LLM_PROVIDER='ppio'
# PPIO_API_KEY='your-ppio-api-key-here'
# PPIO_MODEL_PREF=deepseek/deepseek-v3/community###########################################
######## Embedding API SElECTION ##########
###########################################
# Only used if you are using an LLM that does not natively support embedding (openai or Azure)
# EMBEDDING_ENGINE='openai'
# OPEN_AI_KEY=sk-xxxx
# EMBEDDING_MODEL_PREF='text-embedding-ada-002'# EMBEDDING_ENGINE='azure'
# AZURE_OPENAI_ENDPOINT=
# AZURE_OPENAI_KEY=
# EMBEDDING_MODEL_PREF='my-embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002# EMBEDDING_ENGINE='localai'
# EMBEDDING_BASE_PATH='http://localhost:8080/v1'
# EMBEDDING_MODEL_PREF='text-embedding-ada-002'
# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=1000 # The max chunk size in chars a string to embed can be# EMBEDDING_ENGINE='ollama'
# EMBEDDING_BASE_PATH='http://host.docker.internal:11434'
# EMBEDDING_MODEL_PREF='nomic-embed-text:latest'
# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192# EMBEDDING_ENGINE='lmstudio'
# EMBEDDING_BASE_PATH='https://host.docker.internal:1234/v1'
# EMBEDDING_MODEL_PREF='nomic-ai/nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.Q4_0.gguf'
# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192# EMBEDDING_ENGINE='cohere'
# COHERE_API_KEY=
# EMBEDDING_MODEL_PREF='embed-english-v3.0'# EMBEDDING_ENGINE='voyageai'
# VOYAGEAI_API_KEY=
# EMBEDDING_MODEL_PREF='voyage-large-2-instruct'# EMBEDDING_ENGINE='litellm'
# EMBEDDING_MODEL_PREF='text-embedding-ada-002'
# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192
# LITE_LLM_BASE_PATH='http://127.0.0.1:4000'
# LITE_LLM_API_KEY='sk-123abc'# EMBEDDING_ENGINE='generic-openai'
# EMBEDDING_MODEL_PREF='text-embedding-ada-002'
# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192
# EMBEDDING_BASE_PATH='http://127.0.0.1:4000'
# GENERIC_OPEN_AI_EMBEDDING_API_KEY='sk-123abc'
# GENERIC_OPEN_AI_EMBEDDING_MAX_CONCURRENT_CHUNKS=500# EMBEDDING_ENGINE='gemini'
# GEMINI_EMBEDDING_API_KEY=
# EMBEDDING_MODEL_PREF='text-embedding-004'###########################################
######## Vector Database Selection ########
###########################################
# Enable all below if you are using vector database: Chroma.
# VECTOR_DB="chroma"
# CHROMA_ENDPOINT='http://host.docker.internal:8000'
# CHROMA_API_HEADER="X-Api-Key"
# CHROMA_API_KEY="sk-123abc"# Enable all below if you are using vector database: Pinecone.
# VECTOR_DB="pinecone"
# PINECONE_API_KEY=
# PINECONE_INDEX=# Enable all below if you are using vector database: LanceDB.
# VECTOR_DB="lancedb"# Enable all below if you are using vector database: Weaviate.
# VECTOR_DB="weaviate"
# WEAVIATE_ENDPOINT="http://localhost:8080"
# WEAVIATE_API_KEY=# Enable all below if you are using vector database: Qdrant.
# VECTOR_DB="qdrant"
# QDRANT_ENDPOINT="http://localhost:6333"
# QDRANT_API_KEY=# Enable all below if you are using vector database: Milvus.
# VECTOR_DB="milvus"
# MILVUS_ADDRESS="http://localhost:19530"
# MILVUS_USERNAME=
# MILVUS_PASSWORD=# Enable all below if you are using vector database: Zilliz Cloud.
# VECTOR_DB="zilliz"
# ZILLIZ_ENDPOINT="https://sample.api.gcp-us-west1.zillizcloud.com"
# ZILLIZ_API_TOKEN=api-token-here# Enable all below if you are using vector database: Astra DB.
# VECTOR_DB="astra"
# ASTRA_DB_APPLICATION_TOKEN=
# ASTRA_DB_ENDPOINT=###########################################
######## Audio Model Selection ############
###########################################
# (default) use built-in whisper-small model.
# WHISPER_PROVIDER="local"# use openai hosted whisper model.
# WHISPER_PROVIDER="openai"
# OPEN_AI_KEY=sk-xxxxxxxx###########################################
######## TTS/STT Model Selection ##########
###########################################
# TTS_PROVIDER="native"# TTS_PROVIDER="openai"
# TTS_OPEN_AI_KEY=sk-example
# TTS_OPEN_AI_VOICE_MODEL=nova# TTS_PROVIDER="generic-openai"
# TTS_OPEN_AI_COMPATIBLE_KEY=sk-example
# TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL=nova
# TTS_OPEN_AI_COMPATIBLE_ENDPOINT="https://api.openai.com/v1"# TTS_PROVIDER="elevenlabs"
# TTS_ELEVEN_LABS_KEY=
# TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel# CLOUD DEPLOYMENT VARIRABLES ONLY
# AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
# DISABLE_TELEMETRY="false"###########################################
######## PASSWORD COMPLEXITY ##############
###########################################
# Enforce a password schema for your organization users.
# Documentation on how to use https://github.com/kamronbatman/joi-password-complexity
# Default is only 8 char minimum
# PASSWORDMINCHAR=8
# PASSWORDMAXCHAR=250
# PASSWORDLOWERCASE=1
# PASSWORDUPPERCASE=1
# PASSWORDNUMERIC=1
# PASSWORDSYMBOL=1
# PASSWORDREQUIREMENTS=4###########################################
######## ENABLE HTTPS SERVER ##############
###########################################
# By enabling this and providing the path/filename for the key and cert,
# the server will use HTTPS instead of HTTP.
#ENABLE_HTTPS="true"
#HTTPS_CERT_PATH="sslcert/cert.pem"
#HTTPS_KEY_PATH="sslcert/key.pem"###########################################
######## AGENT SERVICE KEYS ###############
############################################------ SEARCH ENGINES -------
#=============================
#------ Google Search -------- https://programmablesearchengine.google.com/controlpanel/create
# AGENT_GSE_KEY=
# AGENT_GSE_CTX=#------ SearchApi.io ----------- https://www.searchapi.io/
# AGENT_SEARCHAPI_API_KEY=
# AGENT_SEARCHAPI_ENGINE=google#------ Serper.dev ----------- https://serper.dev/
# AGENT_SERPER_DEV_KEY=#------ Bing Search ----------- https://portal.azure.com/
# AGENT_BING_SEARCH_API_KEY=#------ Serply.io ----------- https://serply.io/
# AGENT_SERPLY_API_KEY=#------ SearXNG ----------- https://github.com/searxng/searxng
# AGENT_SEARXNG_API_URL=#------ Tavily ----------- https://www.tavily.com/
# AGENT_TAVILY_API_KEY=###########################################
######## Other Configurations ############
############################################ Disable viewing chat history from the UI and frontend APIs.
# See https://docs.anythingllm.com/configuration#disable-view-chat-history for more information.
# DISABLE_VIEW_CHAT_HISTORY=1# Enable simple SSO passthrough to pre-authenticate users from a third party service.
# See https://docs.anythingllm.com/configuration#simple-sso-passthrough for more information.
# SIMPLE_SSO_ENABLED=1# Specify the target languages for when using OCR to parse images and PDFs.
# This is a comma separated list of language codes as a string. Unsupported languages will be ignored.
# Default is English. See https://tesseract-ocr.github.io/tessdoc/Data-Files-in-different-versions.html for a list of valid language codes.
# TARGET_OCR_LANG=eng,deu,ita,spa,fra,por,rus,nld,tur,hun,pol,ita

访问地址

http://172.16.50.25:23001/onboarding/llm-preference