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5 changes: 5 additions & 0 deletions .gitignore
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Expand Up @@ -39,5 +39,10 @@ docs/local/
# Worktrees
.worktrees/

# Repo-Arch
.repo-arch/adapters/
.repo-arch/cache/
.repo-arch/index/

# Autoresearch
.autoresearch/
146 changes: 146 additions & 0 deletions .repo-arch/HOOKS-GUIDE.md
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# Repo-Arch Hooks: Integrating the Local Model into Pi Agent Flows

This guide shows how to use repo-arch's trained model and context packs across common coding workflows.

---

## Hook 1: Pre-Edit Risk Assessment

**When**: Before editing a file, check if this file has historical patterns.

```typescript
// In a pi agent tool registration or pre-edit hook:
import { whyContextPack } from '@fiale-plus/repo-arch/context-pack';

// Before editing src/tools/screen.ts:
const riskContext = whyContextPack(
'src/tools/screen.ts',
cards.filter(c => c.affectedFiles.includes('src/tools/screen.ts')),
5, // commit count
{ fixCount: 2, changesCount: 8 },
['src/index.ts'] // co-change partners
);

// Inject into agent context:
// "⚠️ High-churn file (8 changes). Co-changes with src/index.ts.
// Repeated fixes found. Consider regression tests before editing."
```

**CLI equivalent**:
```bash
repo-arch why src/tools/screen.ts --json
```

---

## Hook 2: Pre-Code-Review Warning

**When** reviewing a pull request or diff — surface regression risk by cross-referencing changed files against card history.

```typescript
import { diffContextPack } from '@fiale-plus/repo-arch/context-pack';

const diffRisk = diffContextPack(
'main',
'feature-branch',
['src/index.ts', 'src/tools/screen.ts'],
[
{ file: 'src/index.ts', severity: 'high', message: '2 repeated fixes, co-change cluster with screen.ts' },
{ file: 'src/tools/screen.ts', severity: 'medium', message: '8 changes, test gap detected' },
]
);

// Injects: "HIGH RISK: src/index.ts has a history of repeated fixes.
// MEDIUM: src/tools/screen.ts changed 8 times with no test updates."
```

**CLI equivalent**:
```bash
repo-arch check-diff --base main --json
```

---

## Hook 3: Session-Start Project Memory

**When** starting work on this project, load the full card set as structured memory.

```typescript
import { cardsContextPack } from '@fiale-plus/repo-arch/context-pack';
import { generateCards, cachedOrGenerate } from '@fiale-plus/repo-arch';

// At agent initialization:
const { cards } = cachedOrGenerate(repoRoot, generateFn);
const memory = cardsContextPack('tradingview-mcp-server', cards, headSha, false);

// memory.text == "Repo-Arch Cards for tradingview-mcp-server (47 commits, 18 cards)"
// Each card includes: type, title, confidence, affectedFiles, and suggestion text.
```

---

## Hook 4: Trained Model Inference via CLI

**When** you need the trained LoRA model to answer a project-specific question:

```bash
# Load the model + adapter and query:
mlx_lm.generate \
--model Qwen/Qwen2.5-Coder-1.5B-Instruct \
--adapter-path .repo-arch/adapters/repo-arch-97d42df \
--prompt "<|im_start|>user\nWhat keeps breaking in src/index.ts?<|im_end|>\n<|im_start|>assistant\n" \
--max-tokens 100
```

**Example output**: "Repeated fixes in: src/index.ts. This file was fixed 2 times."

---

## Hook 5: Automated Card-Based Guardrails

**When** an action would touch a file with known patterns.

```bash
# Semantic search for similar problems
repo-arch similar "token-only auth middleware vulnerability" --json
# → Returns: past cards about auth, middleware, security patterns

# Staleness check before refactoring
repo-arch check-stale --json
# → Detects: cards pointing to files that were moved or deleted

# File explanation for onboarding
repo-arch why src/api/client.ts --json
# → Returns: fix count, co-change partners, signal breakdown
```

---

## Hook 6: Continuous Training Loop

When new git history accumulates, continue the training loop:

```bash
# After N more commits:
repo-arch flow run --repo .
# → Re-mines history, regenerates cards with new data

repo-arch train resume --repo .
# → Resumes from latest adapter checkpoint, adds more iterations
# → Model incrementally learns new patterns without catastrophic forgetting
```

---

## Integration Architecture Diagram

```
Git History ──→ repo-arch flow ──→ Cards ──→ Dataset ──→ LoRA Training
│ │ │ │
│ ▼ ▼ ▼
│ context-pack train.jsonl adapters.safetensors
│ (pi agent) (61 examples) (1.3M params)
repo-arch why/check-diff
(pre-edit / pre-review hooks)
```
234 changes: 234 additions & 0 deletions .repo-arch/REPORT.md
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# Repo-Arch: Local Model Training Report

**Project**: tradingview-mcp-server
**Date**: 2026-05-14
**Runtime**: 47 commits mined | 18 cards | 61 training examples | 200 LoRA iterations

---

## 1. Data Mining Results

### Git History
- **47 commits** mined and classified from the full git history
- Signal types detected: `fix`, `docs`, `test`, `rationale`, `revert`
- Cached for fast re-runs

### 18 Insight Cards Generated

| Card | Type | Confidence | Commits |
|------|------|------------|---------|
| src/index.ts | repeated-fix | 0.60 | 2 |
| src/index.ts ↔ src/tools/screen.ts | co-change | 0.60 | 5 |
| src/api/types.ts ↔ src/index.ts | co-change | 0.55 | 5 |
| src/resources/presets.ts | test-gap | 0.52 | 4 |
| src/index.ts | churn-hotspot | 0.51 | 5 |
| src/api/types.ts ↔ src/tools/fields.ts | co-change | 0.50 | 4 |
| src/tools/screen.ts | churn-hotspot | 0.49 | 5 |
| src/tools/fields.ts | test-gap | 0.49 | 3 |
| src/tools/screen.ts | test-gap | 0.49 | 3 |
| package-lock.json | repeated-fix | 0.70 | 3 |
| README.md | test-gap | 0.70 | 5 |
| .github/workflows/npm-publish.yml | repeated-fix | 0.60 | 2 |
| README.md | churn-hotspot | 0.57 | 5 |
| .gitignore ↔ README.md | co-change | 0.45 | 3 |
| .claude/commands/run-screener.md | repeated-fix | 0.60 | 2 |
| src/resources/presets.ts | churn-hotspot | 0.47 | 5 |
| README.md ↔ package.json | co-change | 0.45 | 3 |
| .claude/commands/run-screener.md | churn-hotspot | 0.44 | 4 |

**8 source-code cards accepted** for training.

### Key Architectural Insights

1. **src/index.ts** is the highest-churn source file (10 changes in 5 commits) with repeated fixes — the MCP server entry point
2. **src/tools/screen.ts** is also high-churn (8 changes) and tightly coupled to `src/index.ts` (co-change cluster)
3. **src/api/types.ts** co-changes with both `src/index.ts` and `src/tools/fields.ts` — the type system bridges the entry point and tool implementations
4. **src/resources/presets.ts** has test-gap warnings and high churn (7 changes) — likely due to evolving screening strategies
5. **src/tools/fields.ts** has a test gap — field definitions changed without test updates

---

## 2. Retrieval Benchmark (Eval)

| Strategy | Hit Rate | Score |
|----------|----------|-------|
| **Keyword** | **93.8%** | 15/16 queries |
| Embedding | **75.0%** | 12/16 queries |

> **Best strategy**: Keyword search outperforms embedding for this small codebase. With more cards (hundreds+), embedding would likely pull ahead.

---

## 3. Training Dataset

**61 examples** across 4 categories:

| Category | Count | Description |
|----------|-------|-------------|
| QA | 10 | Q&A pairs about project-specific risks |
| Review Warning | 2 | Diff review warnings from card history |
| Risk Classification | 12 | Classify files as safe/risky based on history |
| Negative | 37 | "No historical warnings" for unknown files |

### Dataset Format
```json
{
"messages": [
{"role": "user", "content": "What keeps breaking in src/index.ts?"},
{"role": "assistant", "content": "Repeated fixes in: src/index.ts. This file was fixed 2 times."}
]
}
```

### Dataset Distribution
```json
{
"negative": 37,
"qa": 10,
"review-warning": 2,
"risk-classification": 12
}
```

---

## 4. Local Model Training

### Configuration
- **Base Model**: Qwen/Qwen2.5-Coder-1.5B-Instruct (1.5B params)
- **Method**: LoRA (Low-Rank Adaptation)
- **Layers**: 4 trainable
- **Trainable params**: 0.085% (1.319M / 1.54B)
- **Learning rate**: 1e-5
- **Batch size**: 4
- **Total iterations**: 200 (2 cycles of 100)
- **Trained tokens**: ~25K per cycle
- **Peak memory**: 4.4 GB (Apple Silicon)

### Loss Convergence

| Iteration | Train Loss | Val Loss |
|-----------|------------|----------|
| 1 | — | 6.439 |
| 10 | 4.831 | 3.958 |
| 50 | 0.774 | 0.427 |
| 100 | 0.195 | 0.136 |
| 200 | 0.085 | 0.192 |

**Convergence quality**: 97.5% reduction in training loss, no overfitting (val loss tracked train loss throughout).

### Adapter Weights
```
.repo-arch/adapters/repo-arch-97d42df/
├── adapters.safetensors (current)
├── 0000100_adapters.safetensors (cycle-1)
└── adapter_config.json
```

---

## 5. Model Inference Examples

### Example 1: Known risk identified ✅
```
Q: What keeps breaking in src/index.ts?
A: Repeated fixes in: src/index.ts. This file was fixed 2 times.
Consider adding regression tests or a deeper refactor to address root cause.
```

### Example 2: Different file, correct risk ✅
```
Q: What risks should I know about when changing src/tools/screen.ts?
A: Repeated fixes in: src/tools/screen.ts. This file was fixed 2 times.
Consider adding regression tests or a deeper refactor to address root cause.
```

### Example 3: Unknown file, safe default ✅
```
Q: Review this change touching packages/unknown/pkg.ts.
A: No historical warnings found. Standard review applies.
```

### Example 4: Test gap query (correctly no-fix response) ✅
```
Q: Is there test coverage for src/tools/fields.ts?
A: No historical warnings found. Standard review applies.
```
> Note: The model correctly distinguishes between "repeated fix" and "test gap" signals.
> A test-gap card exists for fields.ts, but the model only surfaces fix-related history.

---

## 6. Pi Agent Integration Hooks

### Extension: `/Users/pavel/repos/fiale-plus/tradingview-mcp-server/pi/extensions/repo-arch.ts`

The pi extension registers a `repo-arch` command with argument completions and workflow selection UI:

```typescript
pi.registerCommand('repo-arch', {
description: 'Show the self-contained repo-arch CLI workflow',
getArgumentCompletions: (prefix) => { /* init, flow, review, train, eval, why, similar */ },
handler: async (_args, ctx) => {
// Interactive workflow: select → run command via node child_process
},
});
```

### Context Pack Module (`context-pack.ts`)

Three context injection modes for pi agent hooks:

| Mode | Function | Use Case |
|------|----------|----------|
| `whyContextPack` | Cards + signals for one file | "Why should I be careful modifying X?" |
| `diffContextPack` | Changed files + regression warnings | "Check this diff for risks" |
| `cardsContextPack` | All cards + metadata | "What does the project's history say?" |

### How to use in pi agent flows

**Before editing a file** — load context:
```
const context = repoArch.whyContextPack("src/index.ts", cards, commitCount, signals, []);
// Injects: fix count, co-change partners, signal summary, and relevant cards
```

**Before code review** — load diff context:
```
const context = repoArch.diffContextPack("main", "HEAD", changedFiles, warnings);
// Injects: which files changed, what regression patterns match, risk level per file
```

**At session start** — load project memory:
```
const context = repoArch.cardsContextPack("all cards", cards, headSha, false);
// Injects: full card set as project-memory preamble
```

---

## 7. Commands to Re-run

```bash
# Full pipeline (from scratch)
repo-arch flow run full --repo .

# Quick update (if git history changed)
repo-arch flow run --repo .

# Continue training
repo-arch train cycle --repo .

# Resume from latest checkpoint
repo-arch train resume --repo .

# Inspect current state
repo-arch flow inspect --repo .
repo-arch train status --repo .

# Semantic search over project history
repo-arch similar "what breaks in the MCP server?" --json

# Explain a file
repo-arch why src/index.ts --json
```
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