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Merge e5dc70bb06 into dddbaa803d

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1
README.md
View file

@ -411,6 +411,7 @@ Set `LITELLM_PROXY_API_BASE` and `LITELLM_PROXY_API_KEY` and every model call th
| [Sambanova (`sambanova`)](https://docs.litellm.ai/docs/providers/sambanova) | ✅ | ✅ | ✅ | | | | | | | |
| [ScaleDown (`scaledown`)](https://docs.litellm.ai/docs/providers/scaledown) | ✅ | | | | | | | | | |
| [Snowflake (`snowflake`)](https://docs.litellm.ai/docs/providers/snowflake) | ✅ | ✅ | ✅ | | | | | | | |
| [STACKIT (`stackit`)](https://docs.litellm.ai/docs/providers/stackit) | ✅ | ✅ | ✅ | | | | | | | |
| [Strands Decider (`strands_decider`)](https://docs.litellm.ai/docs/providers) | | | | | | | | | | |
| [Text Completion Codestral (`text-completion-codestral`)](https://docs.litellm.ai/docs/providers/codestral) | ✅ | ✅ | ✅ | | | | | | | |
| [Text Completion OpenAI (`text-completion-openai`)](https://docs.litellm.ai/docs/providers/text_completion_openai) | ✅ | ✅ | ✅ | | | ✅ | ✅ | ✅ | ✅ | |

2
litellm/constants.py
View file

@ -1060,6 +1060,7 @@ openai_compatible_endpoints: Final[list[str]] = [
"https://api.scx.ai/v1",
"https://api.prisminference.com/v1",
"https://api.reka.ai/v1",
"https://api.openai-compat.model-serving.eu01.onstackit.cloud/v1",
"https://gigachat.devices.sberbank.ru/api/v1",
"https://api.openinfer.ai/v1",
]
@ -1141,6 +1142,7 @@ openai_compatible_providers: Final[list[str]] = [
"prism",
"sail",
"reka",
"stackit",
]
OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS: Final = frozenset({"openai"} | frozenset(openai_compatible_providers))

6
litellm/llms/openai_like/providers.json
View file

@ -249,5 +249,11 @@
"/v1/responses",
"/v1/messages"
]
},
"stackit": {
"base_url": "https://api.openai-compat.model-serving.eu01.onstackit.cloud/v1",
"api_key_env": "STACKIT_API_KEY",
"api_base_env": "STACKIT_API_BASE",
"supported_endpoints": ["/v1/chat/completions"]
}
}

88
litellm/model_prices_and_context_window_backup.json
View file

@ -67899,6 +67899,94 @@
"supports_reasoning": true,
"supports_vision": false
},
"stackit/Qwen/Qwen3-VL-235B-A22B-Instruct-FP8": {
"input_cost_per_token": 1.5e-06,
"litellm_provider": "stackit",
"max_input_tokens": 200000,
"max_output_tokens": 16384,
"max_tokens": 16384,
"mode": "chat",
"output_cost_per_token": 1.75e-06,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_vision": true
},
"stackit/Qwen/Qwen3.8-27B": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 262144,
"max_output_tokens": 16384,
"max_tokens": 16384,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_vision": true
},
"stackit/Qwen/Qwen3.6-27B": {
"deprecation_date": "2026-12-08",
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 262144,
"max_output_tokens": 16384,
"max_tokens": 16384,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_vision": true
},
"stackit/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 131072,
"max_output_tokens": 4096,
"max_tokens": 4096,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true
},
"stackit/openai/gpt-oss-120b": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 131072,
"max_output_tokens": 8192,
"max_tokens": 8192,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_response_schema": true
},
"stackit/google/gemma-4-31B-it": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 262144,
"max_output_tokens": 4096,
"max_tokens": 4096,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_vision": true
},
"stackit/openai/gpt-oss-20b": {
"input_cost_per_token": 1.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 131072,
"max_output_tokens": 8192,
"max_tokens": 8192,
"mode": "chat",
"output_cost_per_token": 2.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true
},
"azure_ai/kimi-k2.7-code": {
"cache_read_input_token_cost": 1.9e-07,
"deprecation_date": "2027-04-16",

18
litellm/provider_endpoints_support_backup.json
View file

@ -2225,6 +2225,24 @@
"interactions": true
}
},
"stackit": {
"display_name": "STACKIT (`stackit`)",
"url": "https://docs.litellm.ai/docs/providers/stackit",
"endpoints": {
"chat_completions": true,
"messages": true,
"responses": true,
"embeddings": false,
"image_generations": false,
"audio_transcriptions": false,
"audio_speech": false,
"moderations": false,
"batches": false,
"rerank": false,
"a2a": false,
"interactions": false
}
},
"synthetic": {
"display_name": "Synthetic (`synthetic`)",
"endpoints": {

28
litellm/proxy/public_endpoints/provider_create_fields.json
View file

@ -3481,6 +3481,34 @@
],
"default_model_placeholder": "soniox/stt-async-v5"
},
{
"provider": "STACKIT",
"provider_display_name": "STACKIT",
"litellm_provider": "stackit",
"credential_fields": [
{
"key": "api_base",
"label": "API Base",
"placeholder": "https://api.openai-compat.model-serving.eu01.onstackit.cloud/v1",
"tooltip": null,
"required": false,
"field_type": "text",
"options": null,
"default_value": null
},
{
"key": "api_key",
"label": "API Key",
"placeholder": null,
"tooltip": null,
"required": true,
"field_type": "password",
"options": null,
"default_value": null
}
],
"default_model_placeholder": "stackit/openai/gpt-oss-120b"
},
{
"provider": "StrandsDecider",
"provider_display_name": "Strands Decider",

1
litellm/types/utils.py
View file

@ -4586,6 +4586,7 @@ class LlmProviders(str, Enum):
META = "meta"
SAIL = "sail"
REKA = "reka"
STACKIT = "stackit"
LITELLM_AGENT = "litellm_agent"
CURSOR = "cursor"
BEDROCK_MANTLE = "bedrock_mantle"

88
model_prices_and_context_window.json
View file

@ -67899,6 +67899,94 @@
"supports_reasoning": true,
"supports_vision": false
},
"stackit/Qwen/Qwen3-VL-235B-A22B-Instruct-FP8": {
"input_cost_per_token": 1.5e-06,
"litellm_provider": "stackit",
"max_input_tokens": 200000,
"max_output_tokens": 16384,
"max_tokens": 16384,
"mode": "chat",
"output_cost_per_token": 1.75e-06,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_vision": true
},
"stackit/Qwen/Qwen3.8-27B": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 262144,
"max_output_tokens": 16384,
"max_tokens": 16384,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_vision": true
},
"stackit/Qwen/Qwen3.6-27B": {
"deprecation_date": "2026-12-08",
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 262144,
"max_output_tokens": 16384,
"max_tokens": 16384,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_vision": true
},
"stackit/cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 131072,
"max_output_tokens": 4096,
"max_tokens": 4096,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true
},
"stackit/openai/gpt-oss-120b": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 131072,
"max_output_tokens": 8192,
"max_tokens": 8192,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_response_schema": true
},
"stackit/google/gemma-4-31B-it": {
"input_cost_per_token": 4.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 262144,
"max_output_tokens": 4096,
"max_tokens": 4096,
"mode": "chat",
"output_cost_per_token": 6.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true,
"supports_vision": true
},
"stackit/openai/gpt-oss-20b": {
"input_cost_per_token": 1.5e-07,
"litellm_provider": "stackit",
"max_input_tokens": 131072,
"max_output_tokens": 8192,
"max_tokens": 8192,
"mode": "chat",
"output_cost_per_token": 2.5e-07,
"source": "https://docs.stackit.cloud/products/data-and-ai/ai-model-serving/basics/available-shared-models/",
"supports_function_calling": true,
"supports_reasoning": true
},
"azure_ai/kimi-k2.7-code": {
"cache_read_input_token_cost": 1.9e-07,
"deprecation_date": "2027-04-16",

18
provider_endpoints_support.json
View file

@ -2513,6 +2513,24 @@
"rerank": false
}
},
"stackit": {
"display_name": "STACKIT (`stackit`)",
"url": "https://docs.litellm.ai/docs/providers/stackit",
"endpoints": {
"chat_completions": true,
"messages": true,
"responses": true,
"embeddings": false,
"image_generations": false,
"audio_transcriptions": false,
"audio_speech": false,
"moderations": false,
"batches": false,
"rerank": false,
"a2a": false,
"interactions": false
}
},
"synthetic": {
"display_name": "Synthetic (`synthetic`)",
"endpoints": {

243
tests/unit/llms/openai_like/test_stackit_provider.py Normal file
View file

@ -0,0 +1,243 @@
import json
from pathlib import Path
from typing import Final
import pytest
import respx
import litellm
from litellm.caching.llm_caching_handler import LLMClientCache
_BASE_URL: Final = "https://api.openai-compat.model-serving.eu01.onstackit.cloud/v1"
_REPO_ROOT: Final = Path(litellm.__file__).parent.parent
_CHAT_COMPLETION: Final = {
"id": "chatcmpl_stackit",
"object": "chat.completion",
"created": 1_790_000_000,
"model": "openai/gpt-oss-120b",
"choices": [
{
"index": 0,
"message": {"role": "assistant", "content": "Hello from STACKIT"},
"finish_reason": "stop",
}
],
"usage": {"prompt_tokens": 4, "completion_tokens": 3, "total_tokens": 7},
}
def test_stackit_is_a_registered_provider():
assert litellm.LlmProviders.STACKIT.value == "stackit"
assert "stackit" in litellm.provider_list
assert "stackit" in litellm.constants.openai_compatible_providers
assert _BASE_URL in litellm.constants.openai_compatible_endpoints
def test_stackit_provider_resolution(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("STACKIT_API_KEY", "stackit-test-key")
monkeypatch.delenv("STACKIT_API_BASE", raising=False)
model, provider, api_key, api_base = get_llm_provider(
model="stackit/openai/gpt-oss-120b",
custom_llm_provider=None,
api_base=None,
api_key=None,
)
assert model == "openai/gpt-oss-120b"
assert provider == "stackit"
assert api_key == "stackit-test-key"
assert api_base == _BASE_URL
def test_stackit_provider_keeps_explicit_credentials(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("STACKIT_API_KEY", "stackit-env-key")
monkeypatch.setenv("STACKIT_API_BASE", "https://stackit.env.example/v1")
_, provider, api_key, api_base = get_llm_provider(
model="stackit/openai/gpt-oss-120b",
custom_llm_provider=None,
api_base="https://stackit.internal.example/v1",
api_key="stackit-explicit-key",
)
assert provider == "stackit"
assert api_key == "stackit-explicit-key"
assert api_base == "https://stackit.internal.example/v1"
def test_stackit_api_base_env_overrides_default(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("STACKIT_API_KEY", "stackit-env-key")
monkeypatch.setenv("STACKIT_API_BASE", "https://stackit.env.example/v1")
_, provider, _, api_base = get_llm_provider(
model="stackit/openai/gpt-oss-120b",
custom_llm_provider=None,
api_base=None,
api_key=None,
)
assert provider == "stackit"
assert api_base == "https://stackit.env.example/v1"
def test_stackit_api_base_autodetects_provider(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("STACKIT_API_KEY", "stackit-env-key")
# STACKIT model ids carry their own org prefix (openai/, google/, Qwen/, ...). "openai/..." on its own
# would be routed to OpenAI, so autodetection is only meaningful for ids without a provider-like prefix.
model, provider, api_key, api_base = get_llm_provider(
model="Qwen/Qwen3.8-27B",
custom_llm_provider=None,
api_base=_BASE_URL,
api_key=None,
)
assert model == "Qwen/Qwen3.8-27B"
assert provider == "stackit"
assert api_key == "stackit-env-key"
assert api_base == _BASE_URL
def test_stackit_is_available_in_add_model_form():
fields_path = Path(litellm.__file__).parent / "proxy" / "public_endpoints" / "provider_create_fields.json"
providers = json.loads(fields_path.read_text())
stackit = next(provider for provider in providers if provider["litellm_provider"] == "stackit")
assert stackit["provider"] == "STACKIT"
assert stackit["provider_display_name"] == "STACKIT"
assert stackit["default_model_placeholder"] == "stackit/openai/gpt-oss-120b"
assert {field["key"]: field["required"] for field in stackit["credential_fields"]} == {
"api_base": False,
"api_key": True,
}
def test_stackit_supported_endpoints():
expected: Final = {
"chat_completions": True,
"messages": True,
"responses": True,
"embeddings": False,
"image_generations": False,
"audio_transcriptions": False,
"audio_speech": False,
"moderations": False,
"batches": False,
"rerank": False,
"a2a": False,
"interactions": False,
}
backup_path = Path(litellm.__file__).parent / "provider_endpoints_support_backup.json"
root_path = _REPO_ROOT / "provider_endpoints_support.json"
assert json.loads(backup_path.read_text())["providers"]["stackit"]["endpoints"] == expected
assert json.loads(root_path.read_text())["providers"]["stackit"]["endpoints"] == expected
def test_stackit_cost_map_entries():
root = json.loads((_REPO_ROOT / "model_prices_and_context_window.json").read_text())
backup = json.loads((Path(litellm.__file__).parent / "model_prices_and_context_window_backup.json").read_text())
for cost_map in (root, backup):
stackit = {k: v for k, v in cost_map.items() if v.get("litellm_provider") == "stackit"}
assert stackit, "no stackit entries in cost map"
assert all(key.startswith("stackit/") for key in stackit)
assert {v["mode"] for v in stackit.values()} == {"chat"}
# STACKIT price tiers (EUR per 1M tokens): standard 0.15/0.25, plus 0.45/0.65, premium 1.50/1.75
gpt_oss_20b = stackit["stackit/openai/gpt-oss-20b"]
assert gpt_oss_20b["input_cost_per_token"] == pytest.approx(0.15e-6)
assert gpt_oss_20b["output_cost_per_token"] == pytest.approx(0.25e-6)
gpt_oss_120b = stackit["stackit/openai/gpt-oss-120b"]
assert gpt_oss_120b["input_cost_per_token"] == pytest.approx(0.45e-6)
assert gpt_oss_120b["output_cost_per_token"] == pytest.approx(0.65e-6)
assert gpt_oss_120b["supports_reasoning"] is True
assert gpt_oss_120b["supports_function_calling"] is True
qwen_vl = stackit["stackit/Qwen/Qwen3-VL-235B-A22B-Instruct-FP8"]
assert qwen_vl["input_cost_per_token"] == pytest.approx(1.50e-6)
assert qwen_vl["output_cost_per_token"] == pytest.approx(1.75e-6)
assert qwen_vl["supports_vision"] is True
def test_stackit_chat_completion_request():
with respx.mock() as upstream:
route: Final = upstream.post(f"{_BASE_URL}/chat/completions").respond(200, json=_CHAT_COMPLETION)
response: Final = litellm.completion(
model="stackit/openai/gpt-oss-120b",
messages=[{"role": "user", "content": "Say hello"}],
api_key="stackit-test-key",
)
request: Final = route.calls.last.request
body: Final = json.loads(request.content)
assert route.call_count == 1
assert str(request.url) == f"{_BASE_URL}/chat/completions"
assert request.headers["authorization"] == "Bearer stackit-test-key"
assert body["model"] == "openai/gpt-oss-120b"
assert body["messages"] == [{"role": "user", "content": "Say hello"}]
assert response.choices[0].message.content == "Hello from STACKIT"
def test_stackit_chat_completion_cost_uses_cost_map():
with respx.mock() as upstream:
upstream.post(f"{_BASE_URL}/chat/completions").respond(200, json=_CHAT_COMPLETION)
response: Final = litellm.completion(
model="stackit/openai/gpt-oss-120b",
messages=[{"role": "user", "content": "Say hello"}],
api_key="stackit-test-key",
)
# 4 prompt tokens * 0.45e-6 + 3 completion tokens * 0.65e-6
assert response._hidden_params["response_cost"] == pytest.approx(4 * 0.45e-6 + 3 * 0.65e-6)
def test_stackit_responses_request_is_bridged_to_chat_completions():
with respx.mock() as upstream:
route: Final = upstream.post(f"{_BASE_URL}/chat/completions").respond(200, json=_CHAT_COMPLETION)
response: Final = litellm.responses(
model="stackit/openai/gpt-oss-120b",
input="Say hello",
api_key="stackit-test-key",
)
request: Final = route.calls.last.request
body: Final = json.loads(request.content)
assert route.call_count == 1
assert request.headers["authorization"] == "Bearer stackit-test-key"
assert body["model"] == "openai/gpt-oss-120b"
assert body["messages"] == [{"role": "user", "content": "Say hello"}]
assert response.output[0].content[0].text == "Hello from STACKIT"
@pytest.mark.asyncio
async def test_stackit_anthropic_messages_request_is_bridged_to_chat_completions(monkeypatch: pytest.MonkeyPatch):
monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
monkeypatch.setattr(litellm, "in_memory_llm_clients_cache", LLMClientCache())
with respx.mock() as upstream:
route: Final = upstream.post(f"{_BASE_URL}/chat/completions").respond(200, json=_CHAT_COMPLETION)
response: Final = await litellm.anthropic.messages.acreate(
model="stackit/openai/gpt-oss-120b",
messages=[{"role": "user", "content": "Say hello"}],
max_tokens=32,
api_key="stackit-test-key",
)
request: Final = route.calls.last.request
body: Final = json.loads(request.content)
assert route.call_count == 1
assert request.headers["authorization"] == "Bearer stackit-test-key"
assert body["model"] == "openai/gpt-oss-120b"
assert body["max_tokens"] == 32
assert response["content"][0]["text"] == "Hello from STACKIT"