| # Riprap runtime dependencies (deployment). |
| # Offline-only deps (py3dep, terratorch, whitebox-workflows) are NOT here |
| # — they only run for the one-time fixture pre-compute in scripts/. |
|
|
| # Web + streaming |
| fastapi>=0.115 |
| uvicorn>=0.32 |
| httpx>=0.27 |
| pydantic>=2.9 |
|
|
| # Geo |
| geopandas>=1.0 |
| shapely>=2.0 |
| pyproj>=3.6 |
| fiona>=1.10 |
| rasterio>=1.4 |
|
|
| # Data |
| pandas>=2.2 |
| pyarrow>=18.0 |
| numpy>=1.26 |
|
|
| # pyarrow.PyExtensionType was removed in pyarrow 17 and older `datasets` |
| # (transitive dep of sentence-transformers / gliner / terratorch) crashes |
| # on import against pyarrow 18+. datasets >= 3.0 uses pa.ExtensionType |
| # instead. Without this pin, HF Spaces' resolver picks an older datasets |
| # and FastAPI startup dies before the first request. |
| datasets>=3.0 |
|
|
| # RAG: Granite Embedding 278M (CPU torch is sufficient on HF Spaces). |
| # sentence-transformers 3.x's model_card.py does |
| # `from transformers.integrations import CodeCarbonCallback` at import |
| # time. transformers's lazy-import surface raises if `codecarbon` isn't |
| # present; on HF Space (Python 3.10) the lazy-import resolution fails |
| # even on import-only paths. Two options: |
| # (1) pin sentence-transformers to a version that didn't have model_card |
| # (2) install codecarbon so the lazy-import resolves |
| # We tried (1) at <3.4 and <4 — both failed because 3.3.x also imports |
| # CodeCarbonCallback. Going with (2): codecarbon is a small ~7MB pure- |
| # Python package; we don't enable its tracking, just satisfy the import. |
| sentence-transformers>=3.3,<4 |
| codecarbon>=2.5,<4 |
| pypdf>=5.0 |
|
|
| # Tight coexistence pins: granite-tsfm 0.3.x calls transformers.utils |
| # .download_url which was removed in transformers 5.x; mellea 0.3.x is |
| # happy with the older hf_hub. Keep BOTH older to avoid the conflict |
| # (transformers >=4.55,<5 + huggingface_hub >=0.34,<1). |
| transformers>=4.55,<5 |
| huggingface_hub>=0.34,<1 |
|
|
| # Granite 4.1 reconciliation via Ollama (local fallback) |
| ollama>=0.4 |
|
|
| # LiteLLM Router: unifies vLLM (AMD GPU, OpenAI-compatible) and Ollama |
| # behind one chat() call surface, with automatic primary->fallback |
| # routing when RIPRAP_LLM_PRIMARY=vllm is unreachable. See app/llm.py. |
| litellm>=1.52 |
|
|
| # GLiNER specialist (Phase 2): typed entity extraction over RAG output. |
| # Apache-2.0 model is `urchade/gliner_medium-v2.1` — NOT the gliner_base |
| # variant which is CC-BY-NC-4.0. See app/context/gliner_extract.py. |
| gliner>=0.2.13 |
|
|
| # Phase 1 (Prithvi live) + Phase 4 (TerraMind) + earth-observation deps. |
| # |
| # These deps live in `requirements-experiments.txt` (local + AMD), NOT |
| # in production. Two attempts at bringing them into the HF image (the |
| # floor at 1.0.x then the pin at 1.1rc6) both failed pip resolution |
| # against our Py3.10 constraints (transformers<5, hf_hub<1, |
| # granite-tsfm<0.3.4, mellea<0.4). `terratorch>=1.2` pins numpy>=2.2 |
| # which breaks the rest of the stack; `1.1rc6` and earlier had |
| # transitive cone conflicts the resolver couldn't satisfy in the |
| # 30-second pip budget. |
| # |
| # On HF Spaces the lazy-import path returns clean `skipped: deps |
| # unavailable on this deployment` for both prithvi_live and |
| # terramind_synthesis steps; the other 14 specialists run normally. |
| # - terratorch / torchgeo / pystac-client / planetary-computer |
| # - rioxarray / xarray / einops |
|
|
| # Burr FSM |
| burr>=0.40 |
|
|
| # Granite TimeSeries TTM r2 — short-horizon residual nowcast (Ekambaram et al. |
| # 2024, NeurIPS). The PyPI package name is granite-tsfm; importable as |
| # tsfm_public. Brings in transformers + accelerate; torch is already in the |
| # CUDA base image. |
| # Pinned to 0.3.3 because >=0.3.4 dropped Python 3.10 support and the |
| # CUDA-runtime base image ships Ubuntu 22.04 / Python 3.10. The |
| # tsfm_public.toolkit.get_model API is stable across this minor range. |
| granite-tsfm>=0.3.0,<0.3.4 |
|
|
| # IBM Research's Mellea — instruct/validate/repair framework. Powers the |
| # default reconciler: Granite output + programmatic post-conditions |
| # + rejection sampling. |
| # Pinned to <0.4 because 0.4+ requires Python>=3.11 and the |
| # nvidia/cuda:12.4.1-cudnn-runtime-ubuntu22.04 base image ships Python 3.10. |
| # 0.3.2 has the same instruct/req/RejectionSamplingStrategy API surface |
| # we use; if it doesn't, the validator falls through to the standard |
| # reconciler (graceful degradation). |
| mellea>=0.3.0,<0.4 |
|
|
| # Misc |
| tqdm>=4.66 |
|
|
