PCI Agent

Layer 2: Local AI agent for Personal Context Infrastructure.

Overview

The PCI Agent provides:

• Local AI Processing - Run language models on your device
• Context Retrieval - Query encrypted context store
• Policy Enforcement - Validate requests against S-PAL policies
• Decision Support - AI-powered assistance without data leakage

Installation

# Clone and install
git clone https://github.com/peteski22/pci-agent.git
cd pci-agent
uv sync

# With LLM support (llama-cpp-python)
uv sync --extra llm

Quick Start

from pci_agent import Agent, AgentConfig

# Initialize agent
agent = Agent(AgentConfig(
    model_path="models/phi-3-mini-q4.gguf",
))

# Process a request with policy enforcement
response = await agent.process(
    query="What are my upcoming appointments?",
    policy_id="calendar-access",
)

print(response.content)

Architecture

flowchart TB
    subgraph Agent["PCI Agent"]
        QH["Query Handler"]
        QH --> PC["Policy Checker"]
        QH --> CR["Context Retriever"]
        QH --> LLM["LLM Inference"]
    end

    PC --> SPAL["S-PAL Policy"]
    CR --> CS["Context Store"]

Supported Models

The agent works with GGUF-format models:

Environment Variables

Development

# Install with dev dependencies
uv sync --group dev

# Run tests
uv run pytest

# Type check
uv run mypy src/

# Lint
uv run ruff check src/

# Run the agent
uv run python -m pci_agent

Related Packages

• pci-spec - S-PAL schema and protocols
• pci-context-store - Layer 1: Context Store
• pci-contracts - Layer 3: Smart Contracts
• pci-zkp - Layer 4: Zero-Knowledge Proofs
• pci-identity - Layer 5: DID Management

License

Apache 2.0