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darkolorin
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vibe_coding_router

MLX
routing
code
pid
cascade
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Upload three-tier cascaded coding router v3

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Files changed (7) hide show
  1. README.md +67 -0
  2. config.json +53 -0
  3. embedding_extractor.pkl +3 -0
  4. router_a.safetensors +3 -0
  5. router_b.safetensors +3 -0
  6. scaler.pkl +3 -0
  7. sweep_results.json +3516 -0
README.md ADDED
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1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - routing
5
+ - code
6
+ - mlx
7
+ - pid
8
+ - cascade
9
+ library_name: mlx
10
+ ---
11
+
12
+ # Vibe Coding Router
13
+
14
+ A three-tier cascaded router for coding tasks that routes prompts between:
15
+
16
+ - **Local**: Qwen3-Coder-Next (80B/3B active MoE, on-device via MLX)
17
+ - **Sonnet**: Claude Sonnet 4.6 (medium-complexity cloud)
18
+ - **Opus**: Claude Opus 4.6 (max-capability cloud)
19
+
20
+ ## Architecture
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+
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+ Two cascaded binary MLP routers trained with **Privileged Information Distillation (PID)**:
23
+
24
+ - **Router A** (local vs cloud): 70-dim input -> [128, 64] -> 1, dropout=0.2
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+ - **Router B** (sonnet vs opus): 70-dim input -> [64, 32] -> 1, dropout=0.2
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+
27
+ Features: 38 handcrafted code features + 32 PCA-reduced sentence embeddings (all-MiniLM-L6-v2).
28
+
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+ ## Training
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+
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+ - **Router A**: 100 samples with real (local, sonnet, opus) quality scores
32
+ - **Router B**: 1,729 samples (100 main + 1,644 cloud-only with sonnet+opus scores)
33
+ - **Judge**: GPT-5.4 scoring correctness, completeness, code quality, explanation
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+ - **Loss**: PID (reward-weighted CE + KL divergence)
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+ - **Label smoothing**: epsilon=0.05, cost-aware margin for Router B (cost_premium=0.03)
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+ - **HP sweep**: 108 configurations, 3-way split (train/val/test)
37
+
38
+ ## Routing Distribution
39
+
40
+ | Tier | Rate | Use Case |
41
+ |------|------|----------|
42
+ | Local | 46.7% | Simple tasks, explanations, basic code gen |
43
+ | Sonnet | 20.0% | Medium complexity, standard debugging |
44
+ | Opus | 33.3% | Architecture, complex multi-file tasks |
45
+
46
+ ## Thresholds
47
+
48
+ - Router A: 0.526 (p(cloud) >= threshold -> route to cloud)
49
+ - Router B: 0.474 (p(opus) >= threshold -> route to Opus, else Sonnet)
50
+
51
+ ## Files
52
+
53
+ - `router_a.safetensors` - Router A weights (128x64 MLP)
54
+ - `router_b.safetensors` - Router B weights (64x32 MLP)
55
+ - `config.json` - Model config, thresholds, training results
56
+ - `scaler.pkl` - StandardScaler for feature normalization
57
+ - `embedding_extractor.pkl` - PCA-reduced sentence-transformers extractor
58
+
59
+ ## Usage
60
+
61
+ ```python
62
+ from router.three_tier_inference import ThreeTierRouter
63
+
64
+ router = ThreeTierRouter("models/three_tier_v3")
65
+ tier, probs = router.route("Write a Python function to sort a list")
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+ # tier: "local", "sonnet", or "opus"
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+ ```
config.json ADDED
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+ "local_model": "Qwen/Qwen3-Coder-Next",
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+ "sonnet_model": "claude-sonnet-4-6",
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+ "opus_model": "claude-opus-4-6",
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+ "n_train": 69,
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+ "test_results": {
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+ "oracle_utility": 0.530666708946228,
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+ "regret": 0.07733333110809326
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+ }
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+ }
embedding_extractor.pkl ADDED
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+ size 51814
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+ size 71981
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+ size 28194
scaler.pkl ADDED
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