[JarvisLabs] Support RTX PRO 6000; update API endpoint; remove spot offers

src/gpuhunt/_internal/constraints.py

@@ -222,6 +222,7 @@ def is_nvidia_superchip(gpu_name: str) -> bool:
     NvidiaGPUInfo(name="RTX2000Ada", memory=16, compute_capability=(8, 9)),
     NvidiaGPUInfo(name="RTX4000Ada", memory=20, compute_capability=(8, 9)),
     NvidiaGPUInfo(name="RTX6000Ada", memory=48, compute_capability=(8, 9)),
+    NvidiaGPUInfo(name="RTXPRO6000", memory=96, compute_capability=(12, 0)),
     NvidiaGPUInfo(name="T4", memory=16, compute_capability=(7, 5)),
     NvidiaGPUInfo(name="V100", memory=16, compute_capability=(7, 0)),
     NvidiaGPUInfo(name="V100", memory=32, compute_capability=(7, 0)),

src/gpuhunt/providers/jarvislabs.py

@@ -1,15 +1,17 @@
 import logging
 import os
+from typing import cast
 
 import requests
 from requests import Response
+from typing_extensions import NotRequired, TypedDict
 
-from gpuhunt._internal.models import AcceleratorVendor, QueryFilter, RawCatalogItem
+from gpuhunt._internal.models import AcceleratorVendor, JSONObject, QueryFilter, RawCatalogItem
 from gpuhunt.providers import AbstractProvider
 
 logger = logging.getLogger(__name__)
 
-API_URL = "https://backendprod.jarvislabs.net"
+API_URL = "https://backendn.jarvislabs.net"
 SERVER_META_PATH = "/misc/server_meta"
 TIMEOUT = 30
 # JarvisLabs exposes offer regions in server_meta, but VM provisioning calls must be sent
@@ -18,17 +20,27 @@
 # unknown regions, otherwise dstack may select capacity it cannot create.
 JARVISLABS_REGION_URLS = {
     "india-01": "https://backendprod.jarvislabs.net",
+    "india-chennai-01": "https://backendc.jarvislabs.net",
     "india-noida-01": "https://backendn.jarvislabs.net",
     "europe-01": "https://backendeu.jarvislabs.net",
 }
-# dstack provisions JarvisLabs GPU VMs by passing a GPU type back to the API.
-# Keep ambiguous API names with spaces out of the catalog; otherwise the
-# normalized gpuhunt name cannot be converted back safely without provider_data.
+# Explicit mappings for human-reviewed JarvisLabs GPU tokens that differ from
+# gpuhunt canonical GPU names. Keep unmapped spaced names out of the catalog so
+# new provider tokens do not get normalized incorrectly and silently.
 JARVISLABS_GPU_NAME_OVERRIDES = {
     "A100-80GB": ("A100", 80.0),
+    "RTX-PRO6000": ("RTXPRO6000", 96.0),
+    "RTX PRO 6000": ("RTXPRO6000", 96.0),
 }
 
 
+class JarvisLabsCatalogItemProviderData(TypedDict):
+    # Original JarvisLabs API GPU type, set only when gpuhunt normalization loses
+    # the create-time token, e.g. A100-80GB -> A100 or RTX-PRO6000 -> RTXPRO6000.
+    # dstack uses this value for VM creation.
+    gpu_type: NotRequired[str]
+
+
 class JarvisLabsProvider(AbstractProvider):
     NAME = "jarvislabs"
 
@@ -97,7 +109,7 @@ def _make_gpu_catalog_items(gpu: dict) -> list[RawCatalogItem]:
 
     gpu_spec = _gpu_name_and_memory(gpu_type, gpu.get("vram"))
     if gpu_spec is None:
-        logger.warning("Skipping JarvisLabs GPU offer with ambiguous gpu_type: %s", gpu_type)
+        logger.warning("Skipping JarvisLabs GPU offer with unmapped gpu_type: %s", gpu_type)
         return []
     gpu_name, gpu_memory = gpu_spec
     if gpu_memory is None:
@@ -119,24 +131,12 @@ def _make_gpu_catalog_items(gpu: dict) -> list[RawCatalogItem]:
         ram_per_gpu=ram_per_gpu,
         available_devices=_available_devices(gpu),
         max_gpus_per_instance=_max_gpus_per_instance(gpu),
+        provider_data=_gpu_provider_data(gpu_type, gpu_name),
         spot=False,
     )
 
-    spot_price = _as_float(gpu.get("spot_price"))
-    if spot_price is not None:
-        items.extend(
-            _make_gpu_catalog_items_for_price(
-                region=region,
-                gpu_name=gpu_name,
-                gpu_memory=gpu_memory,
-                price=spot_price,
-                cpu_per_gpu=cpu_per_gpu,
-                ram_per_gpu=ram_per_gpu,
-                available_devices=_spot_available_devices(gpu),
-                max_gpus_per_instance=_max_gpus_per_instance(gpu),
-                spot=True,
-            )
-        )
+    # JarvisLabs supports spot for containers/templates, not VMs. This provider
+    # only publishes VM-capable offers because dstack provisions JarvisLabs VMs.
     return items
 
 
@@ -150,6 +150,7 @@ def _make_gpu_catalog_items_for_price(
     ram_per_gpu: float,
     available_devices: int,
     max_gpus_per_instance: int,
+    provider_data: JSONObject,
     spot: bool,
 ) -> list[RawCatalogItem]:
     items = []
@@ -170,6 +171,7 @@ def _make_gpu_catalog_items_for_price(
                 gpu_memory=gpu_memory,
                 spot=spot,
                 disk_size=None,
+                provider_data=provider_data,
             )
         )
     return items
@@ -216,6 +218,12 @@ def _make_cpu_catalog_items(cpu_meta: dict) -> list[RawCatalogItem]:
     return offers
 
 
+def _gpu_provider_data(gpu_type: str, gpu_name: str) -> JSONObject:
+    if gpu_type == gpu_name:
+        return {}
+    return cast(JSONObject, JarvisLabsCatalogItemProviderData(gpu_type=gpu_type))
+
+
 def _supported_gpu_counts(*, available_devices: int, max_gpus_per_instance: int) -> list[int]:
     if available_devices <= 0 or max_gpus_per_instance <= 0:
         return []
@@ -228,18 +236,14 @@ def _available_devices(gpu: dict) -> int:
     )
 
 
-def _spot_available_devices(gpu: dict) -> int:
-    return _as_int(gpu.get("spot_num_free_devices")) or 0
-
-
 def _max_gpus_per_instance(gpu: dict) -> int:
     return _as_int(gpu.get("num_gpus")) or 1
 
 
 def _gpu_name_and_memory(gpu_type: str, vram: object) -> tuple[str, float | None] | None:
-    if any(c.isspace() for c in gpu_type):
-        return None
     gpu_name, default_memory = JARVISLABS_GPU_NAME_OVERRIDES.get(gpu_type, (gpu_type, None))
+    if gpu_name == gpu_type and any(c.isspace() for c in gpu_type):
+        return None
     return gpu_name, _as_float(vram) or default_memory
 
 

src/tests/_internal/test_constraints.py

@@ -4,6 +4,7 @@
 from gpuhunt._internal.constraints import (
     correct_gpu_memory_gib,
     find_accelerators,
+    get_compute_capability,
     get_gpu_vendor,
     matches,
 )
@@ -250,3 +251,14 @@ def test_tenstorrent_accelerators(gpu_name: str, expected_memories_gib: set[int]
     assert {accelerator.name for accelerator in accelerators} == {gpu_name}
     assert {accelerator.memory for accelerator in accelerators} == expected_memories_gib
     assert get_gpu_vendor(gpu_name.upper()) == AcceleratorVendor.TENSTORRENT
+
+
+def test_rtx_pro_6000_accelerator() -> None:
+    accelerators = find_accelerators(
+        names=["RTXPRO6000"],
+        vendors=[AcceleratorVendor.NVIDIA],
+    )
+
+    assert [accelerator.memory for accelerator in accelerators] == [96]
+    assert get_compute_capability("RTXPRO6000") == (12, 0)
+    assert get_gpu_vendor("RTXPRO6000") == AcceleratorVendor.NVIDIA

src/tests/providers/test_jarvislabs.py

@@ -50,6 +50,34 @@
             "workload_type": "vm",
             "num_gpus": "4",
         },
+        {
+            "gpu_type": "RTX-PRO6000",
+            "region": "india-chennai-01",
+            "num_free_devices": 2,
+            "effective_num_free_devices": 2,
+            "spot_num_free_devices": 1,
+            "price_per_hour": 1.89,
+            "spot_price": 1.19,
+            "vram": "96",
+            "cpus_per_gpu": 28,
+            "ram_per_gpu": 160,
+            "workload_type": "vm",
+            "num_gpus": "8",
+        },
+        {
+            "gpu_type": "RTX PRO 6000",
+            "region": "india-noida-01",
+            "num_free_devices": 1,
+            "effective_num_free_devices": 1,
+            "spot_num_free_devices": 0,
+            "price_per_hour": 1.89,
+            "spot_price": None,
+            "vram": "96",
+            "cpus_per_gpu": 28,
+            "ram_per_gpu": 160,
+            "workload_type": "vm",
+            "num_gpus": "8",
+        },
         {
             "gpu_type": "H100",
             "region": "europe-01",
@@ -98,28 +126,35 @@
 
 def test_convert_response_to_raw_catalog_items():
     offers = convert_response_to_raw_catalog_items(SERVER_META_RESPONSE)
-
-    assert all(o.provider_data == {} for o in offers)
+    assert not any(o.spot for o in offers)
 
     l4_vm = [o for o in offers if o.gpu_name == "L4" and not o.spot]
     assert [o.gpu_count for o in l4_vm] == [1, 2, 3]
     assert [o.price for o in l4_vm] == [0.44, 0.88, 1.32]
     assert [o.instance_name for o in l4_vm] == ["L4-1x", "L4-2x", "L4-3x"]
-
-    l4_spot = [o for o in offers if o.gpu_name == "L4" and o.spot]
-    assert [o.gpu_count for o in l4_spot] == [1, 2]
-    assert [o.price for o in l4_spot] == [0.29, 0.58]
-    assert [o.instance_name for o in l4_spot] == ["L4-1x", "L4-2x"]
+    assert all(o.provider_data == {} for o in l4_vm)
 
     a100 = next(o for o in offers if o.instance_name == "A100-1x" and not o.spot)
     assert a100.gpu_name == "A100"
     assert a100.gpu_memory == 80
     assert a100.location == "india-noida-01"
     assert a100.disk_size is None
-    assert a100.provider_data == {}
+    assert a100.provider_data == {"gpu_type": "A100-80GB"}
 
-    a100_spot = next(o for o in offers if o.instance_name == "A100-1x" and o.spot)
-    assert a100_spot.price == 0.89
+    rtx_pro_6000 = [o for o in offers if o.gpu_name == "RTXPRO6000" and not o.spot]
+    assert [o.gpu_count for o in rtx_pro_6000] == [1, 2, 1]
+    assert [o.instance_name for o in rtx_pro_6000] == [
+        "RTXPRO6000-1x",
+        "RTXPRO6000-2x",
+        "RTXPRO6000-1x",
+    ]
+    assert [o.provider_data for o in rtx_pro_6000] == [
+        {"gpu_type": "RTX-PRO6000"},
+        {"gpu_type": "RTX-PRO6000"},
+        {"gpu_type": "RTX PRO 6000"},
+    ]
+    assert rtx_pro_6000[0].location == "india-chennai-01"
+    assert all(o.gpu_memory == 96 for o in rtx_pro_6000)
 
     h100 = next(o for o in offers if o.gpu_name == "H100")
     assert h100.gpu_count == 1
@@ -145,24 +180,24 @@ def test_convert_response_warns_and_skips_unsupported_regions(caplog):
     assert "Skipping JarvisLabs CPU VM offer in unsupported region unknown-region" in caplog.text
 
 
-def test_convert_response_skips_ambiguous_gpu_types_with_spaces(caplog):
+def test_convert_response_skips_unmapped_gpu_types_with_spaces(caplog):
     response = {
         "server_meta": [
             {
-                "gpu_type": "H100 NVL",
+                "gpu_type": "RTX A6000",
                 "region": "india-noida-01",
                 "num_free_devices": 1,
-                "price_per_hour": 2.99,
-                "vram": "94",
+                "price_per_hour": 0.79,
+                "vram": "48",
                 "cpus_per_gpu": 16,
-                "ram_per_gpu": 200,
+                "ram_per_gpu": 100,
                 "workload_type": "vm",
             },
         ],
     }
 
     assert convert_response_to_raw_catalog_items(response) == []
-    assert "Skipping JarvisLabs GPU offer with ambiguous gpu_type: H100 NVL" in caplog.text
+    assert "Skipping JarvisLabs GPU offer with unmapped gpu_type: RTX A6000" in caplog.text
 
 
 def test_convert_response_skips_malformed_specs(caplog):
@@ -239,10 +274,11 @@ def test_catalog_query(requests_mock, monkeypatch):
         JarvisLabsProvider(api_key="test-token", api_url="https://api.jarvislabs.test")
     )
 
-    assert len(catalog.query(provider=["jarvislabs"], min_gpu_count=2, gpu_name="L4")) == 3
-    assert len(catalog.query(provider=["jarvislabs"], gpu_name="A100", min_gpu_memory=80)) == 2
+    assert len(catalog.query(provider=["jarvislabs"], min_gpu_count=2, gpu_name="L4")) == 2
+    assert len(catalog.query(provider=["jarvislabs"], gpu_name="A100", min_gpu_memory=80)) == 1
+    assert len(catalog.query(provider=["jarvislabs"], gpu_name="RTXPRO6000")) == 3
     assert len(catalog.query(provider=["jarvislabs"], max_gpu_count=0)) == 1
     assert len(catalog.query(provider=["jarvislabs"], min_disk_size=250)) == 9
     assert len(catalog.query(provider=["jarvislabs"], max_disk_size=50)) == 9
     assert len(catalog.query(provider=["jarvislabs"], gpu_name="L4", spot=False)) == 3
-    assert len(catalog.query(provider=["jarvislabs"], gpu_name="L4", spot=True)) == 2
+    assert len(catalog.query(provider=["jarvislabs"], gpu_name="L4", spot=True)) == 0