Spaces:
Sleeping
Sleeping
Sync TECHNICAL_ARCHITECTURE.md with public WandB Report URL
Browse files
TECHNICAL_ARCHITECTURE.md
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@@ -39,7 +39,7 @@ flowchart TB
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end
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subgraph WandB["π WandB"]
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Run["openenv-contract-guardian
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end
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subgraph Inference["π LLM Providers"]
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@@ -118,7 +118,7 @@ Every dependency, what it does, and why we chose it.
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| **HuggingFace Hub** | Hosts trained adapter + training artifacts (reward_curve.png, training_state.json, trained_scores.json) | Free for public models; `HfApi.upload_file` from inside the training job |
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| **HuggingFace Jobs** | On-demand cloud GPU runtime (used L4 24 GB at $0.80/hr) | Faster + more reliable than Colab Free; doesn't time out; supports inline PEP-723 dependency declarations via `hf jobs uv run` |
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| **HF Inference Providers (router)** | Serverless inference for Qwen2.5-72B / 7B baselines | Free tier covers ~9 tasks of ~10 calls each; no GPU needed for baselines |
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| **WandB** | Public, immutable experiment tracking | Free; satisfies "experimental tracking turned on" requirement
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| **Docker** | Containerization for the OpenEnv server | Required by HF Spaces (`sdk: docker` in README frontmatter); reproducible build |
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| **GitHub** | Source-of-truth + the URL the HF Job clones from | Public, free; supports raw-content URLs for plot embeds |
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| **`uv` (PyPI installer used in HF Jobs)** | Fast Python dep installer (~500 ms for 177 packages) | Default tool for `hf jobs uv run`; PEP-723 inline deps make our launcher self-contained |
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### Verify the WandB run is real
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Open https://wandb.ai/pushpamsubscriptions-inn/openenv-contract-guardian/
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### Re-run inference
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end
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subgraph WandB["π WandB"]
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Run["openenv-contract-guardian (public WandB Report)<br/>300 steps Β· immutable Β· timestamped"]
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end
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subgraph Inference["π LLM Providers"]
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| **HuggingFace Hub** | Hosts trained adapter + training artifacts (reward_curve.png, training_state.json, trained_scores.json) | Free for public models; `HfApi.upload_file` from inside the training job |
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| 119 |
| **HuggingFace Jobs** | On-demand cloud GPU runtime (used L4 24 GB at $0.80/hr) | Faster + more reliable than Colab Free; doesn't time out; supports inline PEP-723 dependency declarations via `hf jobs uv run` |
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| **HF Inference Providers (router)** | Serverless inference for Qwen2.5-72B / 7B baselines | Free tier covers ~9 tasks of ~10 calls each; no GPU needed for baselines |
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| **WandB** | Public, immutable experiment tracking | Free; satisfies "experimental tracking turned on" requirement. Public report (share-via-link): see [WandB Report URL in README](README.md#links) |
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| **Docker** | Containerization for the OpenEnv server | Required by HF Spaces (`sdk: docker` in README frontmatter); reproducible build |
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| 123 |
| **GitHub** | Source-of-truth + the URL the HF Job clones from | Public, free; supports raw-content URLs for plot embeds |
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| **`uv` (PyPI installer used in HF Jobs)** | Fast Python dep installer (~500 ms for 177 packages) | Default tool for `hf jobs uv run`; PEP-723 inline deps make our launcher self-contained |
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### Verify the WandB run is real
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Open https://wandb.ai/pushpamsubscriptions-inn/openenv-contract-guardian/reports/Enterprise-Contract-Guardian-GRPO-training-Qwen-7B-LoRA-300-steps---VmlldzoxNjY3MTAxMA?accessToken=3dhumexjta1umyk04rq6dx47iww4t25utt3j0x7063b7pvzzibp8jah29grhlwpb β should show 300-step reward / loss / grad_norm / kl curves with timestamps from 2026-04-25 18:57.
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### Re-run inference
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