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# MoE Prompt Refiner
<span class="category-badge pipeline">Pipeline</span>
<span class="version-badge">v1.0.0</span>
为 Mixture of ExpertsMoE汇总请求优化提示词生成高质量的综合报告。
---
## 概览
MoE Prompt Refiner 是一个高级 Pipeline会在将请求发送给多个专家模型前先优化提示词然后综合各模型回复输出结构化的高质量报告。
## 功能特性
- :material-view-module: **多模型**:同时利用多个 AI 模型
- :material-text-search: **提示词优化**:在发送前优化 prompt 获得更好结果
- :material-merge: **结果合成**:整合专家回复
- :material-file-document: **报告生成**:输出结构化报告
---
## 安装
1. 下载 Pipeline 文件:[`moe_prompt_refiner.py`](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/pipelines)
2. 上传到 OpenWebUI**Admin Panel** → **Settings****Functions**
3. 配置专家模型及相关参数
4. 启用该 Pipeline
---
## 工作流程
```mermaid
graph TD
A[User Prompt] --> B[Prompt Refiner]
B --> C[Expert Model 1]
B --> D[Expert Model 2]
B --> E[Expert Model N]
C --> F[Response Synthesizer]
D --> F
E --> F
F --> G[Comprehensive Report]
```
---
## 配置项
| 选项 | 类型 | 默认值 | 说明 |
|--------|------|---------|-------------|
| `expert_models` | list | `[]` | 需要咨询的模型列表 |
| `synthesis_model` | string | `"auto"` | 用于综合回复的模型 |
| `report_format` | string | `"markdown"` | 输出格式 |
---
## 适用场景
- **研究报告**:从多个 AI 视角收集洞见
- **综合分析**:多角度问题拆解
- **决策支持**:获得多模型的平衡建议
- **内容创作**:生成多视角的丰富内容
---
## 示例
**输入 Prompt**
```
Analyze the pros and cons of microservices architecture
```
**输出报告:**
```markdown
# Microservices Architecture Analysis
## Executive Summary
Based on analysis from multiple expert perspectives...
## Advantages
1. **Scalability** (Expert A)...
2. **Technology Flexibility** (Expert B)...
## Disadvantages
1. **Complexity** (Expert A)...
2. **Distributed System Challenges** (Expert C)...
## Recommendations
Synthesized recommendations based on expert consensus...
```
---
## 运行要求
!!! note "前置条件"
- OpenWebUI v0.3.0 及以上
- 可以访问多个 LLM 模型
- 有足够的 API 配额支撑多模型请求
!!! warning "资源消耗"
此 Pipeline 每次请求会进行多次 API 调用,请关注用量与成本。
---
## 源码
[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/pipelines){ .md-button }