AgentDoG Security Agent

An AI agent specifically trained for security-focused tasks, built on Llama 3.1 8B with enhanced safety and security capabilities. Runs locally using GGUF quantization for privacy and performance.

What This Agent Does

AgentDoG is designed to assist with:

Installation & Setup

Step 1: Choose Your Runtime

**Option A: llama.cpp**

```bash

Clone llama.cpp if not already installed

git clone https://github.com/ggerganov/llama.cpp

cd llama.cpp

make

```

**Option B: Ollama**

```bash

Install Ollama from https://ollama.ai

curl -fsSL https://ollama.ai/install.sh | sh

```

**Option C: LM Studio**

Download from https://lmstudio.ai

Step 2: Download the Model

Choose a quantization level based on your hardware:

**Recommended (balanced quality/speed):**

**Lower memory (reduced quality):**

**Best quality:**

Download from: https://huggingface.co/mradermacher/AgentDoG-Llama3.1-8B-i1-GGUF

Step 3: Load the Model

**llama.cpp:**

```bash

./llama-cli -m AgentDoG-Llama3.1-8B.i1-Q4_K_M.gguf -p "Your security prompt here" --temp 0.7

```

**Ollama:**

```bash

Create Modelfile

echo 'FROM ./AgentDoG-Llama3.1-8B.i1-Q4_K_M.gguf' > Modelfile

ollama create agentdog -f Modelfile

ollama run agentdog

```

**LM Studio:**

1. Open LM Studio

2. Navigate to "Local Models"

3. Click "Import" and select the GGUF file

4. Start chatting in the Chat tab

Usage Examples

Security Code Review

```

Analyze this Python function for security vulnerabilities:

def process_user_input(data):

query = f"SELECT * FROM users WHERE id = {data['user_id']}"

return db.execute(query)

```

Threat Assessment

```

Evaluate the security risks of this scenario:

Provide risk level and mitigation recommendations.

```

Safe Agent Operations

```

I'm designing an AI agent that will:

1. Read user emails

2. Classify them by priority

3. Auto-respond to routine requests

What safety guardrails should I implement?

```

Configuration Tips

Temperature Settings

Context Length

Performance Tuning

```bash

llama.cpp with GPU acceleration

./llama-cli -m model.gguf -ngl 35 --mlock

-ngl: number of layers to offload to GPU

--mlock: keep model in RAM

```

Important Notes

System Requirements

When to Use This vs Cloud APIs

Use AgentDoG when:

Use cloud APIs when:

Troubleshooting

**Model loads slowly:**

**Out of memory errors:**

**Low quality outputs:**