Ollama Plugin

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Features

• Local execution - No API keys or internet required
• Multiple models - Support for Llama, Mistral, Gemma, and more
• Full model types - Text, embeddings, and objects
• Cost-free - No API charges

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Prerequisites

1. Install Ollama
2. Pull desired models:
   Copy

   Ask AI

   ollama pull llama3.1
   ollama pull nomic-embed-text
   

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Installation

elizaos plugins add @elizaos/plugin-ollama

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Configuration

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Environment Variables

# Required
OLLAMA_API_ENDPOINT=http://localhost:11434/api

# Model configuration
# You can use any model available in your Ollama installation
OLLAMA_SMALL_MODEL=llama3.2                # Default: llama3.2
OLLAMA_MEDIUM_MODEL=llama3.1               # Default: llama3.1
OLLAMA_LARGE_MODEL=llama3.1:70b            # Default: llama3.1:70b
OLLAMA_EMBEDDING_MODEL=nomic-embed-text    # Default: nomic-embed-text

# Examples of other available models:
# OLLAMA_SMALL_MODEL=mistral:7b
# OLLAMA_MEDIUM_MODEL=mixtral:8x7b
# OLLAMA_LARGE_MODEL=llama3.3:70b
# OLLAMA_EMBEDDING_MODEL=mxbai-embed-large
# OLLAMA_EMBEDDING_MODEL=all-minilm

# Optional parameters
OLLAMA_TEMPERATURE=0.7

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Character Configuration

{
  "name": "MyAgent",
  "plugins": ["@elizaos/plugin-ollama"]
}

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Supported Operations

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Model Configuration

The plugin uses three model tiers:

• SMALL_MODEL: Quick responses, lower resource usage
• MEDIUM_MODEL: Balanced performance
• LARGE_MODEL: Best quality, highest resource needs

You can use any model from Ollama’s library:

• Llama models (3, 3.1, 3.2, 3.3)
• Mistral/Mixtral models
• Gemma models
• Phi models
• Any custom models you’ve created

For embeddings, popular options include:

• nomic-embed-text - Balanced performance
• mxbai-embed-large - Higher quality
• all-minilm - Lightweight option

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Performance Tips

1. GPU Acceleration - Dramatically improves speed
2. Model Quantization - Use Q4/Q5 versions for better performance
3. Context Length - Limit context for faster responses

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Hardware Requirements

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Common Issues

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”Connection refused”

Ensure Ollama is running:

ollama serve

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Slow Performance

• Use smaller models or quantized versions
• Enable GPU acceleration
• Reduce context length

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External Resources

• Plugin Source
• Ollama Documentation
• Model Library