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