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Heres the **focused documentation** for θ-Meta, crystallizing its core value proposition as a **market-making protocol for verifiable compute** while deliberately avoiding Turing-completeness in the spec layer:
---
# **θ-Meta Protocol Specification**
**Version 1.0**
*A minimal canonical format for priced, bounded, and verifiable computation.*
## **1. Core Principles**
### **1.1 Thetas Iron Triangle**
```mermaid
graph TD
A[Verifiability] --> B[Predictable Cost]
B --> C[Deterministic Bounds]
C --> A
```
- **No Turing-completeness**: Bounds (`b:`) are pure CEL (no loops/recursion).
- **No ambiguity**: Every task has 1:1:1 correspondence between `f`, `b`, and `v`.
- **No runtime dependency**: The spec defines *what*, not *how*.
### **1.2 Why Not Turing-Complete?**
| | Turing-Complete Spec | θ-Metas Approach |
|-----------------------|-----------------------|----------------------------|
| **Proof Generation** | Unbounded time | O(1) (always terminates) |
| **Pricing** | Unpredictable | Bound → fixed cost |
| **Composability** | Deadlocks possible | DAG workflows only |
## **2. Specification**
### **2.1 Canonical Task Definition (`#Θ`)**
```cue
package theta
: {
// What to compute
f: string | bytes // Computation ID or bytecode
// How much is allowed (CEL expression)
b: string // e.g., "k <= 11", "input.size() < 1MB"
// Proof of correct execution
v: #Proof
// Price (unitless, scaled by runtime)
p: number
// Phi-encoded payload (optional)
φ?: string
}
#Proof: {
scheme: "none" | "sha256" | "ed25519" | "groth16"
bytes?: string // Proof payload
ok: bool // Validation result
}
```
### **2.2 Execution Guarantees**
For any task `T` where `T.v.ok == true`, the runtime must ensure:
1. **Bounds honored**: `T.b` evaluated to `true` during execution.
2. **Payment sufficient**: `T.p` was escrowed before proof generation.
3. **Proof valid**: `T.v.bytes` cryptographically matches `T.f` and output.
## **3. Workflow Examples**
### **3.1 Fibonacci Task**
```cue
#fibExample: & {
f: "fib"
b: "k <= 11" // CEL constraint
v: {
scheme: "ed25519",
bytes: "a1b2...",
ok: true
}
p: 0.001
φ: "fib|11" // Phi-encoded input
}
```
### **3.2 ML Inference Task**
```cue
#mlExample: & {
f: "infer"
b: "model == 'resnet50' && batch_size <= 8"
v: {
scheme: "groth16",
bytes: "x128...",
ok: true
}
p: 0.1
}
```
## **4. Runtime Requirements**
### **4.1 Mandatory Checks**
Before executing any task `T`:
1. **Validate schema**: `cue vet` against `#Θ`.
2. **Check bounds**: Ensure `T.b` is syntactically valid CEL.
3. **Verify payment**: Confirm `T.p` is escrowed.
### **4.2 Proof Schemes**
| Scheme | Use Case | O(1) Check |
|-----------|-----------------------|------------|
| `sha256` | Free tasks (RFC) | ✅ |
| `ed25519` | Paid tasks (K11) | ✅ |
| `groth16` | ZK-verified compute | ❌ (SNARK) |
## **5. Composability Rules**
### **5.1 Valid Workflow Patterns**
```mermaid
graph LR
A[Task 1] --> B[Task 2]
B --> C[Task 3]
```
- **Acyclic**: No loops in task dependencies.
- **Bounded**: Each tasks `b:` must be evaluable before execution.
### **5.2 Invalid Patterns**
```mermaid
graph LR
A[Task 1] --> A // Loops forbidden
```
## **6. FAQ**
### **Q: Why not allow loops in bounds?**
**A**: To preserve:
- **Predictable pricing**: `T.p` can be derived from `T.b`.
- **Instant verification**: Proofs dont require re-execution.
### **Q: How to handle complex computations?**
**A**: Push complexity into `f:` (WASM/ASM), not the spec. Example:
```cue
& {
f: """
// Complex logic in WASM
fn run() { ... }
"""
b: "input.len() < 1KB" // Simple bound
}
```
## **7. Compliance Tests**
Run to validate your implementation:
```bash
cue vet theta.cue -c '#testSuite'
```
---
# **Appendix: Design Alternatives Considered**
### **A1. Turing-Complete Bounds**
- **Rejected**: Breaks 1:1:1 task→proof→price model.
### **A2. Dynamic Pricing**
- **Rejected**: `p` must be calculable from `b` alone.
### **A3. Recursive Proofs**
- **Pending**: May be added in v2 if SNARK recursion improves.
---
This document intentionally **excludes**:
- Runtime implementation details.
- Payment layer specifics.
- Hardware requirements.
The θ-Meta spec is **only** about defining tasks in a way that creates a **verifiable compute market**. Turing-completeness lives *above* this layer, not within it.
Want to **formalize the state machine** or **add a test suite** next?
---
Heres the distilled meta-framework for designing a configuration management system that balances pragmatism with pride-of-ownership: Heres the distilled meta-framework for designing a configuration management system that balances pragmatism with pride-of-ownership:
### **The Pillars of Sustainable Network Configuration Design** ### **The Pillars of Sustainable Network Configuration Design**