MicroFish/.env.example

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# LLM API配置支持 OpenAI SDK 格式的任意 LLM API
# 推荐使用阿里百炼平台qwen-plus模型https://bailian.console.aliyun.com/
# 注意消耗较大可先进行小于40轮的模拟尝试
LLM_API_KEY=your_api_key_here
LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
LLM_MODEL_NAME=qwen-plus
LLM_CONTEXT_WINDOW=8192
LLM_MAX_CONCURRENCY=1
LLM_JSON_MAX_RETRIES=2
ONTOLOGY_MAX_OUTPUT_TOKENS=2048
ONTOLOGY_PROMPT_MARGIN_TOKENS=512
ONTOLOGY_MAX_CHUNKS=8
LOCAL_ZEP_EXTRACT_MAX_OUTPUT_TOKENS=2048
LOCAL_ZEP_EXTRACT_MAX_RETRIES=2
# ===== Local Zep / Embeddings 配置 =====
# 使用 OpenAI-compatible embeddings 接口vLLM 可作为首选后端
EMBEDDING_API_KEY=local-embedding-key
EMBEDDING_BASE_URL=http://localhost:8001/v1
EMBEDDING_MODEL_NAME=your_embedding_model_here
# 可选cross_encoder reranker 接口;不配置时本地图谱会自动回退到 RRF
RERANKER_API_KEY=local-reranker-key
RERANKER_BASE_URL=http://localhost:8002/v1
RERANKER_MODEL_NAME=your_reranker_model_here
LOCAL_ZEP_RERANK_TOP_K=50
# 本地图谱 SQLite 路径(可选)
LOCAL_ZEP_DB_PATH=backend/data/local_zep.sqlite3
# Optional: Python executable for the original OASIS/CAMEL simulation runner.
# Use this when the backend runs on Python 3.13 but OASIS is installed in a Python 3.11 venv.
# OASIS_PYTHON=/absolute/path/to/oasis-venv/bin/python
# ===== Tailscale / Remote Access可选=====
# 前端开发模式默认会通过 /api 代理访问后端,适合直接用 Tailscale 访问 http://<tailnet-host>:3000
VITE_API_BASE_URL=
VITE_DEV_HOST=0.0.0.0
VITE_DEV_PORT=3000
VITE_DEV_PROXY_TARGET=http://127.0.0.1:5001
VITE_ALLOWED_HOSTS=localhost,127.0.0.1,.ts.net,.beta.tailscale.net
# 如果通过 MagicDNS 访问时 HMR 需要显式指定,可取消注释
# VITE_HMR_HOST=your-machine.your-tailnet.ts.net
# VITE_HMR_CLIENT_PORT=3000
FLASK_HOST=0.0.0.0
FLASK_PORT=5001
ENABLE_PROXY_FIX=false
PUBLIC_BASE_URL=
TAILSCALE_URL=
# ===== 加速 LLM 配置(可选)=====
# 注意如果不使用加速配置env文件中就不要出现下面的配置项
LLM_BOOST_API_KEY=your_api_key_here
LLM_BOOST_BASE_URL=your_base_url_here
LLM_BOOST_MODEL_NAME=your_model_name_here