Model Support

Model Support#

Overview#

The Open edX AI Extensions plugin supports multiple AI model providers across different processor types. While all listed providers are functional and tested, please note that prompts are optimized for OpenAI models. When using alternative providers, you may need to adjust prompts for optimal results.

Supported Providers#

The following providers have been tested and verified to work with the plugin:

OpenAI#

  • Provider: OpenAI

  • Status: ✅ Fully Supported & Optimized

  • Model Example: openai/gpt-4o-mini, openai/gpt-5-nano

Anthropic#

  • Provider: Anthropic (Claude)

  • Status: ✅ Supported

  • Model Example: anthropic/claude-3-haiku-20240307

  • Note: Prompts optimized for OpenAI; may require adjustment

Ollama#

  • Provider: Ollama (Local/Self-hosted)

  • Status: ✅ Supported

  • Model Example: ollama/llama3.2:1b

  • Note: Prompts optimized for OpenAI; may require adjustment

Deepseek#

  • Provider: Deepseek

  • Status: ✅ Supported

  • Model Example: huggingface/deepseek-ai/DeepSeek-V3.2:novita

  • Note: Prompts optimized for OpenAI; may require adjustment

Processor Compatibility Matrix#

The following table shows which processors have been tested with each provider:

Processor

OpenAI

Anthropic

Ollama

Deepseek

LLMProcessor(Threaded)

✅

✅

✅

✅

LLMProcessor

✅

✅

✅

✅

EducatorAssistantProcessor

✅

✅

✅

✅

Configuration#

Plugin Settings#

Configure AI providers in your Open edX settings using the AI_EXTENSIONS configuration:

AI_EXTENSIONS = {
    "my-openai": {
        "API_KEY": "sk-your-openai-api-key",
        "MODEL": "openai/gpt-4o-mini"
    },
    "my-anthropic": {
        "API_KEY": "sk-ant-your-anthropic-api-key",
        "MODEL": "anthropic/claude-3-haiku-20240307"
    },
    "my-ollama": {
        "API_BASE": "http://your-ollama-server:11434",
        "MODEL": "ollama/llama3.2:1b"
    },
    "my-deepseek": {
        "API_BASE": "https://router.huggingface.co/v1",
        "API_KEY": "hf_your-huggingface-token",
        "MODEL": "huggingface/deepseek-ai/DeepSeek-V3.2:novita"
    }
}

Configuration Parameters#

  • API_KEY: Authentication key for the provider (required for most providers)

  • API_BASE: Custom API endpoint (optional, required for self-hosted solutions like Ollama)

  • MODEL: Model identifier in the format provider/model-name

Workflow Configuration#

To specify which provider a processor should use, configure it in your workflow JSON configuration file:

{
  "orchestrator_class": "ThreadedLLMResponse",
  "processor_config": {
    "OpenEdXProcessor": {
      "function": "get_location_content",
      "char_limit": 300
    },
    "LLMProcessor(Threaded)": {
      "function": "chat_with_context",
      "config": "my-openai"
    },
    "SubmissionProcessor": {
      "function": "get_chat_history",
      "max_context_messages": 3
    }
  }
}

Key Configuration Elements#

  • config: Specifies which AI provider configuration to use (e.g., "my-openai", "my-anthropic")

  • This must match one of the keys defined in your AI_EXTENSIONS settings

Switching Providers#

To switch between providers, simply change the config value in your workflow configuration:

"LLMProcessor(Threaded)": {
  "function": "chat_with_context",
  "config": "my-anthropic"  // Changed from "my-openai"
}

Warning

When switching providers, be aware that:

  • Prompts are optimized for OpenAI’s models

  • Different models may interpret instructions differently

  • Response quality and format may vary

  • You may need to adjust system prompts for optimal results with non-OpenAI providers

Best Practices#

  1. Start with OpenAI: For the best out-of-the-box experience, start with OpenAI models as prompts are optimized for them.

  2. Test Thoroughly: When using alternative providers, thoroughly test your use cases to ensure acceptable response quality.

  3. Adjust Prompts: Consider customizing system prompts when using non-OpenAI providers for better results.

  4. Monitor Costs: Be aware that different providers have different pricing structures. Monitor your usage accordingly.

  5. Local Development: For local development and testing, Ollama provides a cost-effective option with self-hosted models.

  6. API Endpoints: Ensure your API endpoints are accessible from your Open edX installation, especially for self-hosted solutions like Ollama.

Troubleshooting#

Common Issues#

Provider Connection Errors

  • Verify API_BASE is correctly configured and accessible

  • Check that API keys are valid and have appropriate permissions

  • Ensure network connectivity to the provider’s endpoints

Unexpected Responses

  • Remember that prompts are optimized for OpenAI

  • Consider adjusting system prompts for your specific provider

  • Different models have different capabilities and limitations

Performance Issues

  • Smaller models (like llama3.2:1b) may have reduced capabilities

  • Consider using more powerful models for complex tasks

  • Self-hosted solutions depend on your hardware capabilities

For additional support, please refer to the project’s GitHub repository or contact the development team.

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