This commit is contained in:
aruo
2026-05-31 21:45:14 +08:00
parent d4b5015beb
commit ac08345369
67 changed files with 11120 additions and 387 deletions
+54 -33
View File
@@ -18,63 +18,84 @@ milvus:
password: ""
database: db_4a578da0f27ce9d
timeout: 10000
token: ${MILVUS_TOKEN:}
token: d246a77f43a109685596e3c68ecfd359e1cd8b29d35c41d708160f02b97ae623d2ab392738df740d0c77b58ca1bbadfa7c412140
secure: true
vector-dim: 1024 # BGE-M3 = 1024,换模型时同步改
# =====================================================
# 模型路由配置
# =====================================================
# 通过关键字匹配 Bean,切换模型只改这里 + 对应 api-key
# Chat: deepseek | openai | ollama | ...
# Embedding: siliconflow | openai | ollama | dashscope | ...
# =====================================================
model-routing:
chat: deepseek
embedding: siliconflow
# Spring AI Alibaba DashScope 配置
spring:
ai:
dashscope:
api-key: ${DASHSCOPE_API_KEY:your-api-key-here} # 从环境变量读取或使用默认值
# --- Chat: DeepSeek (原生) ---
deepseek:
api-key: sk-1f44696abe644bd684f09cc43f12c557
base-url: https://api.deepseek.com
chat:
options:
timeout: 180000 # 超时时间180秒(3分钟)
retry:
max-attempts: 3 # 最大重试次数
backoff:
initial-interval: 2000 # 初始重试间隔2秒
multiplier: 2 # 重试间隔倍数
max-interval: 10000 # 最大重试间隔10秒
model: deepseek-v4-flash
# --- OpenAI 模块供 SiliconFlow Embedding 复用 ---
openai:
api-key: unused
# Spring AI MCP 客户端配置
# 如果使用mock数据,请注释这部分内容
mcp:
client:
enabled: true
name: tencent-mcp-server
version: 1.0.0
request-timeout: 60s
type: ASYNC
sse:
connections:
tencent-cls:
url: https://mcp-api.tencent-cloud.com
sse-endpoint: /sse/92XXXXXXXXb4 # 完整的SSE端点路径
enabled: false
# 阿里云 DashScope Embedding API 配置
dashscope:
api:
key: ${DASHSCOPE_API_KEY:your-api-key-here} # 从环境变量读取或使用默认值(用于自定义配置)
# --- Embedding: SiliconFlow BGE-M3 ---
siliconflow:
api-key: sk-rlxqcnlohjqwkzoffollthmzzfiohngdrabrmmqhcgtewnzx
base-url: https://api.siliconflow.cn
embedding:
model: text-embedding-v4 # 阿里云文本向量化模型
model: BAAI/bge-m3
# 文档分片配置
document:
chunk:
max-size: 800 # 每个分片最大字符数
overlap: 100 # 分片之间的重叠字符数
max-size: 800
overlap: 100
# RAG 配置
rag:
top-k: 3 # 检索返回的最相似文档数量
model: "qwen3-max" # 大语言模型名称
# Prometheus 配置
prometheus:
base-url: http://localhost:9090
timeout: 10 # 超时时间(秒)
mock-enabled: false # 是否启用 Mock 模式(用于测试)
mock-enabled: true # 是否启用 Mock 模式(用于测试)
# CLS 云日志服务配置
cls:
mock-enabled: false # 是否启用 Mock 模式(用于测试,设为 true 返回与告警关联的模拟日志数据)
mock-enabled: true # 是否启用 Mock 模式(用于测试,设为 true 返回与告警关联的模拟日志数据)
# =====================================================
# 日志配置
# =====================================================
logging:
file:
name: logs/application.log # 日志文件路径
pattern:
console: "%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
file: "%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
level:
root: INFO
org.example: DEBUG # 本项目包日志级别设为 DEBUG
org.springframework.ai: DEBUG # Spring AI 日志
com.alibaba.cloud: INFO
logback:
rollingpolicy:
max-file-size: 10MB # 单个日志文件最大 10MB
max-history: 30 # 保留 30 天
total-size-cap: 1GB # 所有日志文件总大小上限 1GB