SETUP.md

Setup Instructions for ClarityGuard Space

Required Secrets

Set these secrets in your HuggingFace Space settings:

1. Go to: https://huggingface.co/spaces/CharlieBonito/ClarityGuardAgent/settings
2. Add these secrets:
   • JINA_API_KEY: Your Jina API key (optional, enables RAG)
   • HF_TOKEN: Not needed for inference, only for model upload

Upload Steps

Step 1: Create a Write Token

1. Go to https://huggingface.co/settings/tokens
2. Create a new token with Write permissions
3. Copy the token

Step 2: Upload the Space Files

cd /home/charlie/charlielinux/hugginclarity/ClarityGuardAgent

# Login with write token
huggingface-cli login --token YOUR_WRITE_TOKEN --add-to-git-credential

# Push to Space
git add .
git commit -m "Add ClarityGuard implementation with RAG"
git push

Step 3: Upload the Model

# Create model repository
python3 << 'EOF'
from huggingface_hub import HfApi
api = HfApi()
api.create_repo("CharlieBonito/clarity-guard-gemma4-7b", repo_type="model", exist_ok=True)
EOF

# Upload active ClarityGuard v2 model files (this will take ~30-60 minutes for 5GB)
huggingface-cli upload CharlieBonito/clarity-guard-gemma4-7b \
    /home/charlie/charlielinux/finalversion/models/ClarityGuard-v2.gguf \
    ClarityGuard-v2.gguf

huggingface-cli upload CharlieBonito/clarity-guard-gemma4-7b \
    /home/charlie/charlielinux/finalversion/models/mmproj-ClarityGuard-v2.gguf \
    mmproj-ClarityGuard-v2.gguf

Step 4: Enable ZeroGPU

1. Go to Space settings
2. Enable ZeroGPU
3. The Space will automatically use GPU when available

Architecture

User Input
    ↓
Gradio Interface
    ↓
ClarityGuard Prompt + RAG Context
    ↓
ClarityGuard v2 / Gemma 4 E4B IT checkpoint 750 (GPU Space)
    ↓
Structured Analysis (C.F.R.V.A.)
    ↓
User Response

Competition Categories

• Digital Equity & Inclusivity ($10,000)
• Safety & Trust ($10,000)
• Unsloth Track ($10,000)
• llama.cpp Track ($10,000)