Overview
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LlamaCloud supports multiple LLM models through different provider access methods to power its document parsing, extraction, and AI capabilities. This section provides guidance on configuring and choosing between different model providers for your self-hosted deployment.
Supported Models and Providers
Section titled âSupported Models and Providersâ| Model Family | Developer Direct (Simple Setup) | Enterprise Cloud (Advanced Features) |
|---|---|---|
| OpenAI GPT GPT-4o, GPT-4.1, GPT-5, GPT-3.5 | OpenAI API | Azure OpenAI |
| Anthropic Claude Claude 3.5 Sonnet, Claude 3.5 Haiku, Claude 3 Opus | Anthropic API | AWS Bedrock |
| Google Gemini Gemini 1.5 Pro, Gemini 1.5 Flash, Gemini 2.0 Flash | Google Gemini API | Google Vertex AI |
Configuration Methods
Section titled âConfiguration MethodsâExternal Secrets (Recommended)
Section titled âExternal Secrets (Recommended)âConfigure LLM credentials using Kubernetes secrets and reference them in your Helm values:
backend: externalSecrets: enabled: true secrets: - "your-llm-secret"
llamaParse: externalSecrets: enabled: true secrets: - "your-llm-secret"Helm Values Configuration (Legacy)
Some providers support direct configuration in Helm values (being deprecated):
backend: config: openAiApiKey: "your-api-key"Next Steps
Section titled âNext StepsâChoose your LLM provider and follow the detailed setup instructions:
- OpenAI Setup
- Azure OpenAI Setup
- Anthropic API Setup
- AWS Bedrock Setup
- Google Gemini API Setup
- Google Vertex AI Setup
Troubleshooting
Section titled âTroubleshootingâVerification Steps
Section titled âVerification StepsâAfter configuration, verify your setup by:
- Using the LlamaCloud admin UI to confirm available models
- Testing with a simple parsing or extraction task
Common Issues
Section titled âCommon Issuesâ- Model not available: Check provider documentation for model availability in your region
- Authentication failures: Verify API keys and permissions
- Rate limiting: Monitor usage and implement appropriate quotas