# ════════════════════════════════════════════════════════════
# {{DOMAIN}} — TODO: 一句话描述
# ════════════════════════════════════════════════════════════
# 部署后访问 http://1.95.125.250:{{PORT}}/
# ════════════════════════════════════════════════════════════

agent: qaagent67lambda            # agent 模板（位于 /home/67/agentexample/）
name: {{DOMAIN}}问答
description: >
  TODO: 多行领域描述

# ═══ 路径覆盖 (instance 数据目录) ═══
knowledge:
  baseDir:      /home/67/knowledge/{{DOMAIN}}
  rawDir:       /home/67/knowledge/{{DOMAIN}}/raw
  processedDir: /home/67/knowledge/{{DOMAIN}}/processed
  indexFile:    /home/67/knowledge/{{DOMAIN}}/rag_index.json
  keywordFile:  /home/67/knowledge/{{DOMAIN}}/rag_index.keywords.json
  vectorIndex:  /home/67/knowledge/{{DOMAIN}}/rag_vectors_v2.npy
  vectorMeta:   /home/67/knowledge/{{DOMAIN}}/rag_vectors_meta_v2.pkl

wiki:
  dir:           /home/67/knowledge/{{DOMAIN}}/wiki
  relationsFile: /home/67/knowledge/{{DOMAIN}}/wiki/relations.json

# ═══ 模型 ═══
model:
  provider: ollama
  name: qwen2.5-32b
  baseUrl: http://127.0.0.1:8000/v1

# ═══ 检索权重 (按需调整) ═══
retrieval:
  skills:
    embedding:
      baseUrl: http://127.0.0.1:11435/api/embed
  weights:
    fact:      {bm25: 1.0, vector: 0.5, graph: 0.1, wiki: 0.1}
    process:   {bm25: 0.7, vector: 0.5, graph: 0.3, wiki: 0.6}
    person:    {bm25: 0.8, vector: 0.5, graph: 0.3, wiki: 0.5}
    compare:   {bm25: 0.5, vector: 0.8, graph: 0.4, wiki: 0.7}
    relation:  {bm25: 0.5, vector: 0.3, graph: 0.7, wiki: 0.8}
    synthesis: {bm25: 0.6, vector: 0.5, graph: 0.5, wiki: 0.6}
    temporal:  {bm25: 1.0, vector: 0.2, graph: 0.05, wiki: 0.2}

# ═══ 领域 system prompt ═══
systemPrompt: |
  你是 {{DOMAIN}} 知识库问答助手。
  ## 工作原则
  - TODO: 仅使用检索到的知识库内容回答，不得编造
  - TODO: 标明信息来源
  - TODO: 如知识库无相关信息，明确告知

# ═══ Demo UI 配置 (deploy_domain.sh 读取) ═══
demo:
  title:       {{DOMAIN}} QA Demo                 # 网页标题/H1
  tagline:     RAG vs Wiki | TODO 多少文档 | Qwen2.5:32B
  placeholder: 请输入 {{DOMAIN}} 相关问题...
  domain:      {{DOMAIN}}                         # BM25 baseline 提示词中使用
  port:        {{PORT}}                           # 必填，唯一端口号
  examples:                                       # 5 个示例问题
    - { q: "TODO 示例问题 1?", label: "短标签 1" }
    - { q: "TODO 示例问题 2?", label: "短标签 2" }
    - { q: "TODO 示例问题 3?", label: "短标签 3" }
    - { q: "TODO 示例问题 4?", label: "短标签 4" }
    - { q: "TODO 示例问题 5?", label: "短标签 5" }
