Refactor/pure rust

[ProdByBuddha]

PR Description: Personal AI Infrastructure (PAI) Core - Rust Implementation

🎯 Overview

This PR introduces the pai-core crate, a high-performance, security-hardened Rust implementation of the Personal AI Infrastructure.
It transitions the core "Agency" logic into an adversarial-grade intelligence fabric, focusing on deterministic state management,
rigorous security validation, and modular "intelligence threads."

🏗️ Architectural Pillars

1. Deterministic Intelligence (algorithm.rs)

The heart of the crate is the Algorithm Engine, a deterministic state machine that drives the PAI lifecycle through 7 distinct
phases:

• Phases: Observe → Think → Plan → Build → Execute → Verify → Learn.
• ISC (Intelligent State Control): Implements requirement tracking with status management (Pending, Active, Looping, Blocked,
  Done).
• Thread Safety: Uses RwLock and AtomicU32 for high-concurrency "swarm" environments, eliminating global mutex bottlenecks.

2. Adversarial-Grade Security (safety.rs, oracle.rs, privacy.rs)

• SecurityValidator: A PAIHook that intercepts tool usage to block catastrophic commands (rm -rf /), reverse shells, and data
  exfiltration patterns.
• VerificationOracle: Restricts execution to a strict whitelist and implements SSRF Protection by enforcing HTTPS for external
  lookups and blocking internal IP probing.
• PrivacyGuard: Automated PII redaction for API keys, Bearer tokens, and internal IPs using pre-compiled regex patterns.

3. Modular Intelligence Fabric

• prosody.rs: A linguistic cleaning engine that detects emotional markers (e.g., [🚨 urgent], [✨ success]) to adjust speech
  synthesis parameters while stripping markdown for high-fidelity audio output.
• telos.rs: Deep context management that aligns agent actions with core user values, missions, and beliefs.
• swarm.rs: Aggregation logic for multi-agent consensus, utilizing Pareto-optimal selection to maximize quality while minimizing
  risk.

4. Memory & Observability (memory.rs, learning.rs, observability.rs)

• Tiered Memory: Implements Hot (active work), Warm (synthesis), and Cold (immutable history) storage tiers.
• Learning Engine: Captures "signals" (Failures, Anomalies, Ratings) to update performance stats and provide reinforcement context
  for future tasks.
• Structured Telemetry: Real-time event streaming formatted for dashboard integration with automatic phase tracing.

⚡ Technical Highlights

• Performance: Async I/O powered by tokio, global regex optimization via OnceLock, and zero-waste hooks that minimize memory
  cloning.
• Reliability: includes 83 integration tests covering edge cases like path traversal protection and lock contention.
• Extensibility: A robust HookManager allowing for Modify, Block, or Continue actions across the tool-use pipeline.

🧪 Testing State

• Unit Tests: 100% pass rate across all core modules.
• Integration Tests: tests/integration_tests.rs verifies the end-to-end pipeline, from security validation to memory persistence.
• Benchmarks: pai_bench.rs tracks performance for the Algorithm and Prosody engines.

📦 Dependencies

• tokio (Async runtime)
• serde / serde_json / serde_yaml (Serialization)
• handlebars (Template rendering for prompts)
• reqwest (Secure HTTP client)
• chrono (Temporal management)

---

Part of the Personal AI Infrastructure (PAI) Project.

[Daanvdplas]

Why refactor in rust? Don't get me wrong, I prefer Rust too, but is this an important refactor for now? The stuff works, many other things to work on that are more important imo.

[eccentricnode]

you could literally just have your preferred language be rust, and then all your core apps would run it.... No?

[ProdByBuddha]

Why refactor in rust? Don't get me wrong, I prefer Rust too, but is this an important refactor for now? The stuff works, many other things to work on that are more important imo.

It fit my needs, and I'm open to sharing what works for me, in case others need it too. Also, its importance is irrelevant against the fact that it's already been accomplished non-destructively. This code does no harm to the main branch, notice it's only additions.

[ProdByBuddha]

you could literally just have your preferred language be rust, and then all your core apps would run it.... No?

I don't understand this question, could you elaborate?

[ProdByBuddha]

Why refactor in rust? Don't get me wrong, I prefer Rust too, but is this an important refactor for now? The stuff works, many other things to work on that are more important imo.

https://github.com/prodbybuddha/agency is why I refactored to rust, fyi.

[eccentricnode]

you could literally just have your preferred language be rust, and then all your core apps would run it.... No?

I don't understand this question, could you elaborate?

in the core pai, system core skill defines your preferred languages, etc. Then, all of the apps can be built in your preferred language. You just tell your PAI to do so right?

[ProdByBuddha]

you could literally just have your preferred language be rust, and then all your core apps would run it.... No?

I don't understand this question, could you elaborate?

in the core pai, system core skill defines your preferred languages, etc. Then, all of the apps can be built in your preferred language. You just tell your PAI to do so right?

Ah, thank you for clarifying. Yes, I suppose that's an option. However, that's not my reasoning behind this refactor. It has everything to do with leveraging memory safety benefits, concurrency and the other tropes that come along with utilizing Rust, toward the semi-autonomous agent I've been building, which is native to this programming language. In effect, if I defined Rust to be my preferred skill to PAI, it simply would honor that preference, only running on Rust in this instance. https://github.com/prodbybuddha/agency