env.template.0g.example

# =====================================================
# EverMemOS Configuration — 0G Storage Backend
# =====================================================
#
# SECURITY: Never commit this file to version control.
#
# ── How to use this file ─────────────────────────────
#
# STEP 1: Choose your deployment mode below (Scenario A / B / C).
#
# STEP 2: Fill in required keys based on your scenario:
#   Scenario A or B (running local service):
#     LLM_API_KEY        your LLM provider API key
#     VECTORIZE_API_KEY  your embedding provider API key
#     RERANK_API_KEY     your rerank provider API key (default: DeepInfra)
#     ZEROG_WALLET_KEY   your EVM wallet private key (see Appendix C in README.md)
#     MEMORY_USER_ID     (optional) your name in memory records; defaults to "default_user"
#   Scenario C (connecting to remote server):
#     MEMORY_REMOTE_URL  remote server URL
#     MEMORY_USER_ID     your username on that server (required, must be unique)
#     ZEROG_WALLET_KEY   your EVM wallet private key
#
# EVERYTHING ELSE: leave at defaults.
#   These are pre-configured internal settings that work correctly out of the box.
#   Changing them may break the backend and is intended only for advanced users
#   familiar with the underlying infrastructure.
#
# =====================================================


# =====================================================
# STEP 1 — Deployment mode
# Three deployment scenarios — choose one:
#
# Scenario A (default): Local single-user mode. No auth required.
#   SERVER_MODE=false, leave MEMORY_REMOTE_URL empty.
#   Run: ./install.sh && ./start_service.sh
#
# Scenario B: Shared server (admin side). You host the service for your team;
#   each user connects from their own machine using Scenario C.
#   SERVER_MODE=true, leave MEMORY_REMOTE_URL empty.
#   Run: ./install.sh && ./start_service.sh
#
# Scenario C: Remote client (user side). Connect to a server set up by your admin.
#   No local service needed — just run the installer and you are done.
#   Set MEMORY_REMOTE_URL and MEMORY_USER_ID below.
#   Run: ./install.sh only (no start_service.sh needed).
#   Registration, API key storage, and AI assistant config are fully automatic.
# =====================================================

SERVER_MODE=false

# --- User identity (all scenarios) ---
# Your name in memory records. Optional for Scenario A/B — defaults to
# "default_user" if not set. Required for Scenario C — must be unique on
# the remote server.
# Note: memory is always isolated between different AI assistants regardless
# of this value, so you can safely use the same name across all of them.
MEMORY_USER_ID=

# --- Remote EverMemOS server (Scenario C only) ---
# Leave empty for local deployment (Scenario A or B).
# When set, ./install.sh will auto-register, store credentials in
# .evermemos_remote_secrets, and configure your AI assistant to use this server.
# No local memory service will be started.
#
# Remote server URL (e.g. http://123.45.67.89:1995)
MEMORY_REMOTE_URL=


# =====================================================
# STEP 2 — Required keys
# Scenario A / B (local service): all four keys below are required.
# Scenario C (remote client): only ZEROG_WALLET_KEY is required
#   (LLM_API_KEY, VECTORIZE_API_KEY, RERANK_API_KEY are not used on the client).
# =====================================================

# Your LLM provider API key (OpenAI, OpenRouter, DeepSeek, xAI, etc.)
# Not needed for Scenario C.
LLM_API_KEY=sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

# Embedding service API key.
# If using OpenAI (default), set this to the same value as LLM_API_KEY above.
# Not needed for Scenario C.
VECTORIZE_API_KEY=sk-proj-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

# Rerank service API key. Default provider is DeepInfra (deepinfra.com).
# OpenAI does not offer a reranking API, so a separate key is needed here.
# Not needed for Scenario C.
RERANK_API_KEY=xxxxx

# EVM wallet private key for writing memories to the 0G decentralized storage network.
# Required for all scenarios (A, B, and C).
# In Scenario C, this key is sent to the remote server during registration and used
# for 0G storage writes on your behalf — each user owns their own 0G stream.
# See Appendix C in README.md for how to create a wallet and get free testnet tokens.
# KEEP THIS SECURE — never share it or commit it to version control.
ZEROG_WALLET_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx


# =====================================================
# OPTIONAL — change only if switching providers or languages
# =====================================================

# LLM model and endpoint.
# Defaults to OpenAI gpt-4o-mini. To use a different OpenAI-compatible provider
# (OpenRouter, DeepSeek, xAI, etc.), update LLM_BASE_URL, LLM_MODEL, and LLM_API_KEY.
LLM_MODEL=gpt-4o-mini
LLM_BASE_URL=https://api.openai.com/v1

# Embedding model and endpoint.
# Defaults to OpenAI text-embedding-3-small.
# To use a different provider, update VECTORIZE_BASE_URL and VECTORIZE_MODEL.
#   DeepInfra: https://api.deepinfra.com/v1/openai  /  Qwen/Qwen3-Embedding-4B
#   vLLM:      http://localhost:8000/v1              /  Qwen3-Embedding-4B
VECTORIZE_BASE_URL=https://api.openai.com/v1
VECTORIZE_MODEL=text-embedding-3-small

# Rerank model and endpoint.
# Defaults to DeepInfra Qwen3-Reranker-4B.
# To use a self-hosted vLLM instance, update RERANK_BASE_URL and RERANK_MODEL.
#   vLLM: http://localhost:12000/score  /  Qwen3-Reranker-4B
RERANK_BASE_URL=https://api.deepinfra.com/v1/inference
RERANK_MODEL=Qwen/Qwen3-Reranker-4B

# Language for memory extraction and summarization.
# Supported values: "en" (English) or "zh" (Chinese). Defaults to "en" if unrecognized.
MEMORY_LANGUAGE=en


# =====================================================
# INTERNAL DEFAULTS — advanced use only
# Pre-configured settings that work correctly out of the box.
# Modifying them may break the backend. Only change if you are familiar
# with the underlying infrastructure.
# =====================================================

# --- LLM internals ---
LLM_PROVIDER=openai
LLM_TEMPERATURE=0.3
LLM_MAX_TOKENS=16384
# Maximum concurrent requests to the LLM endpoint. 0 = unlimited (default, suitable for OpenAI/OpenRouter).
# Set to a positive integer when using a self-hosted endpoint with a low concurrency limit.
LLM_MAX_CONCURRENT=0
# When using Qwen3 via OpenRouter, "cerebras" routing is recommended.
# LLM_OPENROUTER_PROVIDER=cerebras

# --- Embedding internals ---
# "deepinfra" here denotes the OpenAI-compatible API format, not the DeepInfra service.
# This adapter works with any OpenAI-compatible endpoint, including OpenAI itself.
VECTORIZE_PROVIDER=deepinfra
VECTORIZE_TIMEOUT=30
VECTORIZE_MAX_RETRIES=3
VECTORIZE_BATCH_SIZE=10
VECTORIZE_MAX_CONCURRENT=5
VECTORIZE_ENCODING_FORMAT=float
# Set to 0 to disable the dimensions parameter (required for some vLLM models).
VECTORIZE_DIMENSIONS=1024

# --- Rerank internals ---
RERANK_PROVIDER=deepinfra
RERANK_TIMEOUT=30
RERANK_MAX_RETRIES=3
RERANK_BATCH_SIZE=10
RERANK_MAX_CONCURRENT=5

# --- Redis (managed by Docker — do not change) ---
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_DB=8
REDIS_SSL=false

# --- MongoDB (managed by Docker — do not change) ---
MONGODB_HOST=localhost
MONGODB_PORT=27017
MONGODB_USERNAME=admin
MONGODB_PASSWORD=memsys123
MONGODB_DATABASE=memsys
MONGODB_URI_PARAMS=socketTimeoutMS=15000&authSource=admin

# --- Elasticsearch (managed by Docker — do not change) ---
ES_HOSTS=http://localhost:19200
ES_USERNAME=
ES_PASSWORD=
ES_VERIFY_CERTS=false
SELF_ES_INDEX_NS=memsys

# --- Milvus (managed by Docker — do not change) ---
MILVUS_HOST=localhost
MILVUS_PORT=19530
SELF_MILVUS_COLLECTION_NS=memsys

# --- KV storage backend ---
KV_STORAGE_TYPE=zerog

# --- 0G network constants (fixed values for the Galileo Testnet — do not change) ---
# ZEROG_READ_NODE points to the local kv-server started by start_service.sh.
ZEROG_READ_NODE=http://127.0.0.1:6789      # local node
ZEROG_RPC_URL=https://evmrpc-testnet.0g.ai
ZEROG_INDEXER_URL=https://indexer-storage-testnet-turbo.0g.ai
# On-chain contract address for the 0G storage flow — do not change.
ZEROG_FLOW_ADDRESS=0x22E03a6A89B950F1c82ec5e74F8eCa321a105296
# Stream ID and encryption key are auto-generated on first startup and stored in
# .0g_secrets (project root). No manual configuration needed.

# --- API server ---
# Must match the port Claude Code hooks use to reach the backend.
API_BASE_URL=http://localhost:1995

# --- Startup data sync ---
# Validates and re-syncs Milvus/Elasticsearch against MongoDB on each backend start.
# Master switch — set to false to skip the entire sync process on startup.
STARTUP_SYNC_ENABLED=true
# Whether to validate Milvus (vector database) against MongoDB and re-sync missing docs.
STARTUP_SYNC_MILVUS=true
# Whether to validate Elasticsearch (full-text search) against MongoDB and re-sync missing docs.
STARTUP_SYNC_ES=true
# Days to validate: 0 = full database (slower), positive N = last N days only (faster).
STARTUP_SYNC_DAYS=0
STARTUP_SYNC_BATCH_SIZE=500
STARTUP_SYNC_MAX_DOCS=10000

# --- Logging and runtime ---
LOG_LEVEL=INFO
# ENV and PYTHONASYNCIODEBUG are internal runtime flags — leave as-is.
ENV=dev
PYTHONASYNCIODEBUG=1