85 lines
2.0 KiB
Markdown
85 lines
2.0 KiB
Markdown
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# 大模型环境配置说明
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## 需要修改的文件列表
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切换大模型环境时，需要修改以下文件：
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| 文件路径 | 说明 |
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|----------|------|
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| `ry-xinli-admin/src/main/resources/application.yml` | Java后端配置，ollama.enabled和openai.enabled |
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| `xinli-ui/src/views/psychology/report/comprehensive.vue` | 综合评估页面，API_URL和MODEL |
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| `xinli-ui/src/views/psychology/report/detail.vue` | 报告详情页面，API_URL和MODEL |
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| `xinli-ui/src/views/psychology/report/index.vue` | 报告列表页面，API_URL和MODEL |
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## 服务器环境
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- **Python**: 3.8.6 (Windows)
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- **Ollama 模型**:
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- `nomic-embed-text:latest` (274 MB) - 向量嵌入
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- `deepseek-r1:32b` (19 GB) - 文本生成
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## 配置方案
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### 本地开发环境
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| 用途 | 模型 | 来源 |
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|------|------|------|
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| 向量嵌入 | `nomic-embed-text` | 本地 Ollama |
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| 文本生成 | `moonshot-v1-32k` | Kimi API (远程) |
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### 服务器部署环境
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| 用途 | 模型 | 来源 |
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|------|------|------|
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| 向量嵌入 | `nomic-embed-text` | 本地 Ollama |
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| 文本生成 | `deepseek-r1:32b` | 本地 Ollama |
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## 配置文件
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### Python RAG 服务 (rag-python/config.py)
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本地和服务器配置相同：
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```python
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OLLAMA_URL = "http://localhost:11434"
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OLLAMA_EMBED_MODEL = "nomic-embed-text"
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```
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### Java 后端 (application.yml)
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**本地开发** - 使用 Kimi API:
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```yaml
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rag:
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mode: disabled
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python:
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url: http://localhost:5000
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enabled: true
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openai:
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base-url: https://api.moonshot.cn/v1
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api-key: sk-xxx
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generate-model: moonshot-v1-32k
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```
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**服务器部署** - 使用本地 Ollama:
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```yaml
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rag:
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mode: disabled
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python:
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url: http://localhost:5000
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enabled: true
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ollama:
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url: http://localhost:11434
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generate-model: deepseek-r1:32b
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enabled: true
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```
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## 启动顺序
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1. `ollama serve` - 启动 Ollama 服务
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2. `rag-python/start.bat` - 启动 Python RAG 服务
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3. `java -jar xinli-admin.jar` - 启动 Java 后端
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## 服务端口
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| 服务 | 端口 |
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|------|------|
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| Ollama | 11434 |
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| Python RAG | 5000 |
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| Java 后端 | 30081 |
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