cai/docs/cai_list_of_models.md

32 lines
1.8 KiB
Markdown
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

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.
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:
- **Anthropic**: Claude 3.7, Claude 3.5, Claude 3, Claude 3 Opus
- **OpenAI**: O1, O1 Mini, O3 Mini, GPT-4o, GPT-4.5 Preview
- **DeepSeek**: DeepSeek V3, DeepSeek R1
- **Ollama**: Qwen2.5 72B, Qwen2.5 14B, and more
CAI is also compatibile with other platforms like OpenRouter and Ollama. Below youll find some configurations to help you get started.
#### [OpenRouter Integration](https://openrouter.ai/)
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. Heres how you can configure it:
```bash
CAI_MODEL=openrouter/meta-llama/llama-4-maverick
OPENROUTER_API_KEY=<sk-your-key> # note, add yours
OPENROUTER_API_BASE=https://openrouter.ai/api/v1
```
#### [Ollama Integration](https://ollama.com/)
For local models using Ollama, add the following to your .env:
```bash
CAI_MODEL=qwen2.5:72b
OLLAMA_API_BASE=http://localhost:8000/v1 # note, maybe you have a different endpoint
```
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.