MoE Prompt Refiner¶

Pipeline v1.0.0

Refines prompts for Mixture of Experts (MoE) summary requests to generate high-quality comprehensive reports.

Overview¶

The MoE Prompt Refiner is an advanced pipeline that optimizes prompts before sending them to multiple expert models, then synthesizes the responses into comprehensive, high-quality reports.

Features¶

Multi-Model: Leverages multiple AI models
Prompt Optimization: Refines prompts for best results
Response Synthesis: Combines expert responses
Report Generation: Creates structured reports

Installation¶

Download the pipeline file: moe_prompt_refiner.py
Upload to OpenWebUI: Admin Panel → Settings → Functions
Configure expert models and settings
Enable the pipeline

How It Works¶

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]

Configuration¶

Option	Type	Default	Description
`expert_models`	list	`[]`	List of models to consult
`synthesis_model`	string	`"auto"`	Model for synthesizing responses
`report_format`	string	`"markdown"`	Output format

Use Cases¶

Research Reports: Gather insights from multiple AI perspectives
Comprehensive Analysis: Multi-faceted problem analysis
Decision Support: Balanced recommendations from diverse models
Content Creation: Rich, multi-perspective content

Example¶

Input Prompt:

Analyze the pros and cons of microservices architecture

Output Report:

# 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...

Requirements¶

Prerequisites

OpenWebUI v0.3.0 or later
Access to multiple LLM models
Sufficient API quotas for multi-model queries

Resource Usage

This pipeline makes multiple API calls per request. Monitor your usage and costs.

Source Code¶

View on GitHub