multi-llm

Multi-LLM intelligent switching. Use command 'multi llm' to activate local model selection based on task type. Default uses Claude Opus 4.5.

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Repository: duclm1x1/Dive-Ai
Last source activity: February 10, 2026 at 17:50
Detected SKILL.md language: English
Stars: 4
Forks: 2

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Help me write a Python function -> Uses Claude Opus 4.5
Analyze this code -> Uses Claude Opus 4.5

multi llm Help me write a Python function -> Selects qwen2.5-coder:32b
multi llm Analyze this math proof -> Selects deepseek-r1:70b
multi llm Translate to Chinese -> Selects glm4:9b

Command	Description
`multi llm`	Activate intelligent model selection
`multi llm coding`	Force coding model
`multi llm reasoning`	Force reasoning model
`multi llm chinese`	Force Chinese model
`multi llm general`	Force general model

Task Type	Model	Size	Best For
Coding	qwen2.5-coder:32b	19GB	Code generation, debugging, refactoring
Reasoning	deepseek-r1:70b	42GB	Math, logic, complex analysis
Chinese	glm4:9b	5.5GB	Translation, summaries, quick tasks
General	qwen3:32b	20GB	General purpose, fallback

Coding:    qwen2.5-coder:32b -> qwen2.5-coder:14b -> qwen3:32b
Reasoning: deepseek-r1:70b -> deepseek-r1:32b -> qwen3:32b
Chinese:   glm4:9b -> qwen3:8b -> qwen3:32b
General:   qwen3:32b -> qwen3:14b -> qwen3:8b

User Input
    |
    v
Contains "multi llm"?
    |
    +-- No -> Use Claude Opus 4.5 (default)
    |
    +-- Yes -> Task Type Detection
                |
        +-------+-------+-------+
        v       v       v       v
      Coding  Reasoning Chinese General
        |       |       |       |
        v       v       v       v
    qwen2.5  deepseek  glm4   qwen3
    coder    r1:70b    :9b    :32b

Category	Keywords (EN)	Keywords (CN)
Coding	code, debug, function, script, api, bug, refactor, python, java, javascript	代码, 编程, 函数, 调试, 重构
Reasoning	analysis, proof, logic, math, solve, algorithm, evaluate	推理, 分析, 证明, 逻辑, 数学, 计算, 算法
Chinese	translate, summary	翻译, 总结, 摘要, 简单, 快速

# Input
multi llm Write a Python function to calculate fibonacci

# Output
Selected: qwen2.5-coder:32b
Reason: Detected coding task (keywords: python, function)

# Input
multi llm reasoning Prove that sqrt(2) is irrational

# Output
Selected: deepseek-r1:70b
Reason: Force command 'reasoning' used

# Input
multi llm 把这段话翻译成英文

# Output
Selected: glm4:9b
Reason: Detected Chinese lightweight task (keywords: 翻译)

# Input
Write a REST API with authentication

# Output
Selected: claude-opus-4.5
Reason: Default model (no 'multi llm' trigger)

# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# Start Ollama service
ollama serve

# Pull required models
ollama pull qwen2.5-coder:32b
ollama pull deepseek-r1:70b
ollama pull glm4:9b
ollama pull qwen3:32b

ollama list

# Check if model exists
ollama list | grep "qwen2.5-coder"

# Pull missing model
ollama pull qwen2.5-coder:32b

# Check service status
curl -s http://localhost:11434/api/tags

# Start Ollama
ollama serve &

multi-llm/
├── SKILL.md              # This documentation
└── scripts/
    ├── select-model.sh   # Model selection logic
    └── fallback-demo.sh  # Interactive demo script

multi llm [your request here]

# Get recommended model for a task
./scripts/select-model.sh "multi llm write a sorting algorithm"
# Output: qwen2.5-coder:32b

# Demo with actual model call
./scripts/fallback-demo.sh --force-local "explain recursion"

name	multi-llm
description	Multi-LLM intelligent switching. Use command 'multi llm' to activate local model selection based on task type. Default uses Claude Opus 4.5.
trigger	multi llm
version	1.1.0
author	leohan123123
tags	llm, ollama, local-model, fallback, multi-model

name	multi-llm
description	Multi-LLM intelligent switching. Use command 'multi llm' to activate local model selection based on task type. Default uses Claude Opus 4.5.
trigger	multi llm
version	1.1.0
author	leohan123123
tags	llm, ollama, local-model, fallback, multi-model

multi-llm

Install options

Review the source files

Multi-LLM - Intelligent Model Switching

What's New in v1.1.0

Usage

Multi-LLM - Intelligent Model Switching

What's New in v1.1.0

Usage

Default Mode (without command)

Multi-Model Mode (with command)

Command Format

Model Mapping

Fallback Chain

Detection Logic

Task Detection Keywords

Examples

Example 1: Coding Task

Example 2: Math Analysis

Example 3: Quick Translation

Example 4: Default (No trigger)

Prerequisites

Troubleshooting

Model not found

Ollama not running

Slow response

Wrong model selected

Files in This Skill

Integration

With OpenCode/ClaudeCode

Programmatic Usage

Author

License

multi-llm

Source facts

Install options

Review the source files

More from this repository

More from this repository

Multi-LLM - Intelligent Model Switching

What's New in v1.1.0

Usage

Multi-LLM - Intelligent Model Switching

What's New in v1.1.0

Usage

Default Mode (without command)

Multi-Model Mode (with command)

Command Format

Model Mapping

Fallback Chain

Detection Logic

Task Detection Keywords

Examples

Example 1: Coding Task

Example 2: Math Analysis

Example 3: Quick Translation

Example 4: Default (No trigger)

Prerequisites

Troubleshooting

Model not found

Ollama not running

Slow response

Wrong model selected

Files in This Skill

Integration

With OpenCode/ClaudeCode

Programmatic Usage

Author

License