mirror of https://github.com/aliasrobotics/cai.git
32 lines
1.8 KiB
Markdown
32 lines
1.8 KiB
Markdown
The **Cybersecurity AI (CAI)** platform provides seamless integration with multiple Large Language Models (LLMs). This functionality allows users to leverage state-of-the-art AI capabilities for various cybersecurity tasks. CAI acts as a bridge between your security workflows and a wide range of LLMs, enhancing both flexibility and performance of AI agents.
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CAI supports **over 300 models**, thanks to its integration with [LiteLLM](https://github.com/BerriAI/litellm). You can choose from a wide variety of providers and models, including:
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- **Anthropic**: Claude 3.7, Claude 3.5, Claude 3, Claude 3 Opus
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- **OpenAI**: O1, O1 Mini, O3 Mini, GPT-4o, GPT-4.5 Preview
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- **DeepSeek**: DeepSeek V3, DeepSeek R1
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- **Ollama**: Qwen2.5 72B, Qwen2.5 14B, and more
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CAI is also compatibile with other platforms like OpenRouter and Ollama. Below you’ll find some configurations to help you get started.
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#### [OpenRouter Integration](https://openrouter.ai/)
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To enable OpenRouter support in CAI, you need to configure your environment by adding specific entries to your `.env` file. This setup ensures that CAI can interact with the OpenRouter API, facilitating the use of sophisticated models like Meta-LLaMA. Here’s how you can configure it:
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```bash
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CAI_MODEL=openrouter/meta-llama/llama-4-maverick
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OPENROUTER_API_KEY=<sk-your-key> # note, add yours
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OPENROUTER_API_BASE=https://openrouter.ai/api/v1
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```
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#### [Ollama Integration](https://ollama.com/)
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For local models using Ollama, add the following to your .env:
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```bash
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CAI_MODEL=qwen2.5:72b
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OLLAMA_API_BASE=http://localhost:8000/v1 # note, maybe you have a different endpoint
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```
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Make sure that the Ollama server is running and accessible at the specified base URL. You can swap the model with any other supported by your local Ollama instance.
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