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Strix uses LiteLLM to support a wide range of LLM providers. You can use cloud-based models, local models, or the Strix Router for unified access. For best results, we recommend using one of these frontier models:
  • OpenAI GPT-5 - openai/gpt-5
  • Anthropic Claude Sonnet 4.6 - anthropic/claude-sonnet-4-6
  • Google Gemini 3 Pro Preview - vertex_ai/gemini-3-pro-preview

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Strix Router

Strix Router provides a single API key for accessing multiple LLM providers with intelligent routing and $10 free credit on signup. 
export STRIX_LLM="strix/gpt-5"
export LLM_API_KEY="your-strix-router-key"
Available models via Strix Router:
  • strix/gpt-5
  • strix/claude-sonnet-4-6
  • strix/gemini-3-pro-preview
When using the strix/ prefix, the API base URL is automatically set to https://models.strix.ai/api/v1. You don’t need to configure LLM_API_BASE.

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Cloud Providers

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OpenAI

export STRIX_LLM="openai/gpt-5"
export LLM_API_KEY="sk-..."
Supported models:
  • openai/gpt-5
  • openai/gpt-4o
  • openai/o1
  • openai/o3-mini
Get your API key at platform.openai.com.

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Anthropic

export STRIX_LLM="anthropic/claude-sonnet-4-6"
export LLM_API_KEY="sk-ant-..."
Supported models:
  • anthropic/claude-sonnet-4-6
  • anthropic/claude-opus-4
  • anthropic/claude-3.5-sonnet
Get your API key at console.anthropic.com.

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Google Cloud (Vertex AI)

export STRIX_LLM="vertex_ai/gemini-3-pro-preview"
# Authentication via gcloud CLI or service account
Supported models:
  • vertex_ai/gemini-3-pro-preview
  • vertex_ai/gemini-2.0-flash-exp
  • vertex_ai/gemini-1.5-pro
Vertex AI uses Google Cloud authentication. You need to authenticate via gcloud auth application-default login or set GOOGLE_APPLICATION_CREDENTIALS to your service account JSON file.

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AWS Bedrock

export STRIX_LLM="bedrock/anthropic.claude-sonnet-4-6-v1:0"
# Authentication via AWS credentials
Supported models:
  • bedrock/anthropic.claude-sonnet-4-6-v1:0
  • bedrock/anthropic.claude-opus-4-v1:0
  • bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0
AWS Bedrock uses AWS credentials. Configure your credentials via AWS CLI (aws configure) or environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION).

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Azure OpenAI

export STRIX_LLM="azure/your-deployment-name"
export LLM_API_KEY="your-azure-api-key"
export LLM_API_BASE="https://your-resource.openai.azure.com"
You can also use Azure-specific environment variables: 
export AZURE_API_KEY="your-azure-api-key"
export AZURE_API_BASE="https://your-resource.openai.azure.com"
export AZURE_API_VERSION="2024-02-15-preview"

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Local Models

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Ollama

Ollama lets you run LLMs locally on your machine. 
export STRIX_LLM="ollama/llama3.1:70b"
export LLM_API_BASE="http://localhost:11434"
You don’t need to set LLM_API_KEY when using Ollama. Make sure Ollama is running (ollama serve) before starting Strix.
Recommended models for security testing:
  • ollama/llama3.1:70b
  • ollama/qwen2.5:72b
  • ollama/deepseek-v3

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LM Studio

LM Studio provides a local server for running LLMs with an OpenAI-compatible API. 
export STRIX_LLM="openai/model-name"
export LLM_API_BASE="http://localhost:1234/v1"
When using LM Studio, the model name should match the model loaded in LM Studio, or use a generic name like openai/local-model.

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Other Local Providers

Strix works with any OpenAI-compatible API endpoint: 
export STRIX_LLM="openai/your-model"
export LLM_API_BASE="http://your-server:port/v1"

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Advanced Configuration

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Custom Timeouts

Adjust LLM request timeouts for slower models or connections: 
export LLM_TIMEOUT="600"  # 10 minutes

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Retry Configuration

Control how many times Strix retries failed LLM requests: 
export STRIX_LLM_MAX_RETRIES="10"

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Reasoning Effort

Control the reasoning effort level for better or faster responses: 
# For thorough analysis (slower)
export STRIX_REASONING_EFFORT="xhigh"

# For quick scans (faster)
export STRIX_REASONING_EFFORT="medium"

# For minimal overhead
export STRIX_REASONING_EFFORT="low"

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Provider-Specific Notes

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Using Multiple Providers

You can use different models for different purposes by switching STRIX_LLM: 
# Quick scan with smaller model
export STRIX_LLM="openai/gpt-4o"
strix --target ./app --scan-mode quick

# Deep analysis with larger model
export STRIX_LLM="openai/gpt-5"
strix --target ./app --scan-mode deep

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Authentication Priority

Strix checks for credentials in this order:
  1. LLM_API_KEY environment variable
  2. Provider-specific environment variables (e.g., OPENAI_API_KEY, ANTHROPIC_API_KEY)
  3. Provider-specific authentication mechanisms (e.g., gcloud, AWS credentials)

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Base URL Priority

Strix checks for base URLs in this order:
  1. Automatic detection for strix/ models
  2. LLM_API_BASE environment variable
  3. OPENAI_API_BASE environment variable
  4. LITELLM_BASE_URL environment variable
  5. OLLAMA_API_BASE environment variable
  6. Provider default URLs

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Troubleshooting

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Connection Failed

If you see “LLM CONNECTION FAILED”, verify:
  1. Your API key is correct and has the necessary permissions
  2. Your model name is correct (e.g., openai/gpt-5, not gpt-5)
  3. Your API base URL is correct (for local models)
  4. Your network can reach the API endpoint
  5. Your model/deployment exists and is accessible

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Model Not Found

Ensure you’re using the correct provider prefix:
  • ✅ openai/gpt-5
  • ❌ gpt-5

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Rate Limiting

If you hit rate limits, you can:
  1. Reduce STRIX_REASONING_EFFORT to make fewer requests
  2. Use a different model with higher rate limits
  3. Increase your API plan limits

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Local Model Performance

For best results with local models:
  1. Use models with at least 70B parameters
  2. Ensure you have sufficient RAM/VRAM
  3. Use GPU acceleration when possible
  4. Consider using --scan-mode quick for faster scans

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See Also

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