diff --git a/docker/.env.example b/docker/.env.example index ca3abde94..3397a8029 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -3,32 +3,31 @@ ## Base TZ=Asia/Shanghai -ENV_NAME=PLAYGROUND_OFFLINE # Tag shown in DingTalk notifications (e.g., PROD_ONLINE/TEST); no runtime effect unless ENABLE_DINGDING_BOT=true MOS_CUBE_PATH=/tmp/data_test # local data path MEMOS_BASE_PATH=. # CLI/SDK cache path MOS_ENABLE_DEFAULT_CUBE_CONFIG=true # enable default cube config MOS_ENABLE_REORGANIZE=false # enable memory reorg +# MOS Text Memory Type MOS_TEXT_MEM_TYPE=general_text # general_text | tree_text ASYNC_MODE=sync # async/sync, used in default cube config ## User/session defaults -MOS_USER_ID=root -MOS_SESSION_ID=default_session -MOS_MAX_TURNS_WINDOW=20 +# Top-K for LLM in the Product API（old version） MOS_TOP_K=50 ## Chat LLM (main dialogue) +# LLM model name for the Product API MOS_CHAT_MODEL=gpt-4o-mini +# Temperature for LLM in the Product API MOS_CHAT_TEMPERATURE=0.8 +# Max tokens for LLM in the Product API MOS_MAX_TOKENS=2048 +# Top-P for LLM in the Product API MOS_TOP_P=0.9 +# LLM for the Product API backend MOS_CHAT_MODEL_PROVIDER=openai # openai | huggingface | vllm -MOS_MODEL_SCHEMA=memos.configs.llm.VLLMLLMConfig # vllm only: config class path; keep default unless you extend it OPENAI_API_KEY=sk-xxx # [required] when provider=openai OPENAI_API_BASE=https://api.openai.com/v1 # [required] base for the key -OPENAI_BASE_URL= # compatibility for eval/scheduler -VLLM_API_KEY= # required when provider=vllm -VLLM_API_BASE=http://localhost:8088/v1 # required when provider=vllm ## MemReader / retrieval LLM MEMRADER_MODEL=gpt-4o-mini @@ -37,40 +36,60 @@ MEMRADER_API_BASE=http://localhost:3000/v1 # [required] base for the key MEMRADER_MAX_TOKENS=5000 ## Embedding & rerank +# embedding dim EMBEDDING_DIMENSION=1024 +# set default embedding backend MOS_EMBEDDER_BACKEND=universal_api # universal_api | ollama +# set openai style MOS_EMBEDDER_PROVIDER=openai # required when universal_api +# embedding model MOS_EMBEDDER_MODEL=bge-m3 # siliconflow → use BAAI/bge-m3 +# embedding url MOS_EMBEDDER_API_BASE=http://localhost:8000/v1 # required when universal_api +# embedding model key MOS_EMBEDDER_API_KEY=EMPTY # required when universal_api OLLAMA_API_BASE=http://localhost:11434 # required when backend=ollama +# reanker config MOS_RERANKER_BACKEND=http_bge # http_bge | http_bge_strategy | cosine_local +# reanker url MOS_RERANKER_URL=http://localhost:8001 # required when backend=http_bge* +# reranker model MOS_RERANKER_MODEL=bge-reranker-v2-m3 # siliconflow → use BAAI/bge-reranker-v2-m3 MOS_RERANKER_HEADERS_EXTRA= # extra headers, JSON string, e.g. {"Authorization":"Bearer your_token"} +# use source MOS_RERANKER_STRATEGY=single_turn -MOS_RERANK_SOURCE= # optional rerank scope, e.g., history/stream/custom # External Services (for evaluation scripts) +# API key for reproducting Zep(compertitor product) evaluation ZEP_API_KEY=your_zep_api_key_here +# API key for reproducting Mem0(compertitor product) evaluation MEM0_API_KEY=your_mem0_api_key_here +# API key for reproducting MemU(compertitor product) evaluation +MEMU_API_KEY=your_memu_api_key_here +# API key for reproducting MEMOBASE(compertitor product) evaluation +MEMOBASE_API_KEY=your_memobase_api_key_here +# Project url for reproducting MEMOBASE(compertitor product) evaluation +MEMOBASE_PROJECT_URL=your_memobase_project_url_here +# LLM for evaluation MODEL=gpt-4o-mini +# embedding model for evaluation EMBEDDING_MODEL=nomic-embed-text:latest ## Internet search & preference memory +# Enable web search ENABLE_INTERNET=false +# API key for BOCHA Search BOCHA_API_KEY= # required if ENABLE_INTERNET=true -XINYU_API_KEY= -XINYU_SEARCH_ENGINE_ID= +# default search mode SEARCH_MODE=fast # fast | fine | mixture -FAST_GRAPH=false -BM25_CALL=false -VEC_COT_CALL=false +# Slow retrieval strategy configuration, rewrite is the rewrite strategy FINE_STRATEGY=rewrite # rewrite | recreate | deep_search -ENABLE_ACTIVATION_MEMORY=false +# Whether to enable preference memory ENABLE_PREFERENCE_MEMORY=true +# Preference Memory Add Mode PREFERENCE_ADDER_MODE=fast # fast | safe +# Whether to deduplicate explicit preferences based on factual memory DEDUP_PREF_EXP_BY_TEXTUAL=false ## Reader chunking @@ -81,64 +100,71 @@ MEM_READER_CHAT_CHUNK_SESS_SIZE=10 # sessions per chunk (default mode) MEM_READER_CHAT_CHUNK_OVERLAP=2 # overlap between chunks ## Scheduler (MemScheduler / API) +# Enable or disable the main switch for configuring the memory scheduler during MemOS class initialization MOS_ENABLE_SCHEDULER=false +# Determine the number of most relevant memory entries that the scheduler retrieves or processes during runtime (such as reordering or updating working memory) MOS_SCHEDULER_TOP_K=10 +# The time interval (in seconds) for updating "Activation Memory" (usually referring to caching or short-term memory mechanisms) MOS_SCHEDULER_ACT_MEM_UPDATE_INTERVAL=300 +# The size of the context window considered by the scheduler when processing tasks (such as the number of recent messages or conversation rounds) MOS_SCHEDULER_CONTEXT_WINDOW_SIZE=5 +# The maximum number of working threads allowed in the scheduler thread pool for concurrent task execution MOS_SCHEDULER_THREAD_POOL_MAX_WORKERS=10000 +# The polling interval (in seconds) for the scheduler to consume new messages/tasks from the queue. The smaller the value, the faster the response, but the CPU usage may be higher MOS_SCHEDULER_CONSUME_INTERVAL_SECONDS=0.01 +# Whether to enable the parallel distribution function of the scheduler to improve the throughput of concurrent operations MOS_SCHEDULER_ENABLE_PARALLEL_DISPATCH=true +# The specific switch to enable or disable the "Activate Memory" function in the scheduler logic MOS_SCHEDULER_ENABLE_ACTIVATION_MEMORY=false +# Control whether the scheduler instance is actually started during server initialization. If false, the scheduler object may be created but its background loop will not be started API_SCHEDULER_ON=true +# Specifically define the window size for API search operations in OptimizedScheduler. It is passed to the ScherderrAPIModule to control the scope of the search context API_SEARCH_WINDOW_SIZE=5 +# Specify how many rounds of previous conversations (history) to retrieve and consider during the 'hybrid search' (fast search+asynchronous fine search). This helps provide context aware search results API_SEARCH_HISTORY_TURNS=5 ## Graph / vector stores +# Neo4j database selection mode NEO4J_BACKEND=neo4j-community # neo4j-community | neo4j | nebular | polardb +# Neo4j database url NEO4J_URI=bolt://localhost:7687 # required when backend=neo4j* +# Neo4j database user NEO4J_USER=neo4j # required when backend=neo4j* +# Neo4j database password NEO4J_PASSWORD=12345678 # required when backend=neo4j* +# Neo4j database name NEO4J_DB_NAME=neo4j # required for shared-db mode +# Neo4j database data sharing with Memos MOS_NEO4J_SHARED_DB=false QDRANT_HOST=localhost QDRANT_PORT=6333 # For Qdrant Cloud / remote endpoint (takes priority if set): QDRANT_URL=your_qdrant_url QDRANT_API_KEY=your_qdrant_key +# milvus server uri MILVUS_URI=http://localhost:19530 # required when ENABLE_PREFERENCE_MEMORY=true MILVUS_USER_NAME=root # same as above MILVUS_PASSWORD=12345678 # same as above -NEBULAR_HOSTS=["localhost"] -NEBULAR_USER=root -NEBULAR_PASSWORD=xxxxxx -NEBULAR_SPACE=shared-tree-textual-memory -NEBULAR_WORKING_MEMORY=20 -NEBULAR_LONGTERM_MEMORY=1000000 -NEBULAR_USER_MEMORY=1000000 - -## Relational DB (user manager / PolarDB) -MOS_USER_MANAGER_BACKEND=sqlite # sqlite | mysql -MYSQL_HOST=localhost # required when backend=mysql -MYSQL_PORT=3306 -MYSQL_USERNAME=root -MYSQL_PASSWORD=12345678 -MYSQL_DATABASE=memos_users -MYSQL_CHARSET=utf8mb4 + +# PolarDB endpoint/host POLAR_DB_HOST=localhost +# PolarDB port POLAR_DB_PORT=5432 +# PolarDB username POLAR_DB_USER=root +# PolarDB password POLAR_DB_PASSWORD=123456 +# PolarDB database name POLAR_DB_DB_NAME=shared_memos_db +# PolarDB Server Mode: +# If set to true, use Multi-Database Mode where each user has their own independent database (physical isolation). +# If set to false (default), use Shared Database Mode where all users share one database with logical isolation via username. POLAR_DB_USE_MULTI_DB=false +# PolarDB connection pool size POLARDB_POOL_MAX_CONN=100 -## Redis (scheduler queue) — fill only if you want scheduler queues in Redis; otherwise in-memory queue is used -REDIS_HOST=localhost # global Redis endpoint (preferred over MEMSCHEDULER_*) -REDIS_PORT=6379 -REDIS_DB=0 -REDIS_PASSWORD= -REDIS_SOCKET_TIMEOUT= -REDIS_SOCKET_CONNECT_TIMEOUT= +## Related configurations of Redis +# Reddimq sends scheduling information and synchronization information for some variables MEMSCHEDULER_REDIS_HOST= # fallback keys if not using the global ones MEMSCHEDULER_REDIS_PORT= MEMSCHEDULER_REDIS_DB= @@ -146,41 +172,26 @@ MEMSCHEDULER_REDIS_PASSWORD= MEMSCHEDULER_REDIS_TIMEOUT= MEMSCHEDULER_REDIS_CONNECT_TIMEOUT= -## MemScheduler LLM -MEMSCHEDULER_OPENAI_API_KEY= # LLM key for scheduler’s own calls (OpenAI-compatible); leave empty if scheduler not using LLM -MEMSCHEDULER_OPENAI_BASE_URL= # Base URL for the above; can reuse OPENAI_API_BASE -MEMSCHEDULER_OPENAI_DEFAULT_MODEL=gpt-4o-mini ## Nacos (optional config center) +# Nacos turns off long polling listening, defaults to true NACOS_ENABLE_WATCH=false +# The monitoring interval for long rotation training is 60 seconds, and the default 30 seconds can be left unconfigured NACOS_WATCH_INTERVAL=60 +# nacos server address NACOS_SERVER_ADDR= +# nacos dataid NACOS_DATA_ID= +# nacos group NACOS_GROUP=DEFAULT_GROUP +# nacos namespace NACOS_NAMESPACE= +# nacos ak AK= +# nacos sk SK= -## DingTalk bot & OSS upload -ENABLE_DINGDING_BOT=false # set true -> fields below required -DINGDING_ACCESS_TOKEN_USER= -DINGDING_SECRET_USER= -DINGDING_ACCESS_TOKEN_ERROR= -DINGDING_SECRET_ERROR= -DINGDING_ROBOT_CODE= -DINGDING_APP_KEY= -DINGDING_APP_SECRET= -OSS_ENDPOINT= # bot image upload depends on OSS -OSS_REGION= -OSS_BUCKET_NAME= -OSS_ACCESS_KEY_ID= -OSS_ACCESS_KEY_SECRET= -OSS_PUBLIC_BASE_URL= - -## SDK / external client -MEMOS_API_KEY= -MEMOS_BASE_URL=https://memos.memtensor.cn/api/openmem/v1 - +# chat model for chat api CHAT_MODEL_LIST='[{ "backend": "deepseek", "api_base": "http://localhost:1234", @@ -188,3 +199,16 @@ CHAT_MODEL_LIST='[{ "model_name_or_path": "deepseek-r1", "support_models": ["deepseek-r1"] }]' + +# RabbitMQ host name for message-log pipeline +MEMSCHEDULER_RABBITMQ_HOST_NAME= +# RabbitMQ user name for message-log pipeline +MEMSCHEDULER_RABBITMQ_USER_NAME= +# RabbitMQ password for message-log pipeline +MEMSCHEDULER_RABBITMQ_PASSWORD= +# RabbitMQ virtual host for message-log pipeline +MEMSCHEDULER_RABBITMQ_VIRTUAL_HOST=memos +# Erase connection state on connect for message-log pipeline +MEMSCHEDULER_RABBITMQ_ERASE_ON_CONNECT=true +# RabbitMQ port for message-log pipeline +MEMSCHEDULER_RABBITMQ_PORT=5672 \ No newline at end of file