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Ruijie 2026-10-06 21:25:19 -04:00 • committed by GitHub
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2
litellm/constants.py
View file

@ -965,6 +965,7 @@ openai_compatible_endpoints: Final[list] = [
"https://api.libertai.io/v1",
"https://pinstripes.io/v1",
"https://api.meta.ai/v1",
"https://api-inference.bitdeer.ai/v1",
"https://api.sailresearch.com/v1",
"https://api.cognition.ai/v1",
"https://api.cortecs.ai/v1",
@ -1042,6 +1043,7 @@ openai_compatible_providers: Final[list] = [
"pinstripes", # Pinstripes - JSON-configured provider
"darkbloom",
"meta", # Meta Model API (Muse Spark) - JSON-configured provider
"bitdeer-ai", # Bitdeer AI - JSON-configured provider
"cognition",
"cortecs",
"scx-ai",

8
litellm/litellm_core_utils/get_llm_provider_logic.py
View file

@ -371,6 +371,14 @@ def get_llm_provider(
elif endpoint == "https://llm.chutes.ai/v1/":
custom_llm_provider = "chutes"
dynamic_api_key = get_secret_str("CHUTES_API_KEY")
elif endpoint == "https://api-inference.bitdeer.ai/v1":
return _get_openai_compatible_provider_info(
model=f"bitdeer-ai/{model}",
api_base=api_base,
api_key=api_key,
dynamic_api_key=dynamic_api_key,
litellm_params=litellm_params,
)
elif endpoint == "https://api.v0.dev/v1":
custom_llm_provider = "v0"
dynamic_api_key = get_secret_str("V0_API_KEY")

7
litellm/llms/openai_like/dynamic_config.py
View file

@ -66,6 +66,13 @@ def create_config_class(provider: SimpleProviderConfig):
if not resolved_base:
resolved_base = provider.base_url
if (
provider.special_handling.get("require_api_key_for_custom_base")
and resolved_base.rstrip("/") != provider.base_url.rstrip("/")
and not api_key
):
raise ValueError(f"An explicit api_key is required for {provider.slug} when overriding api_base")
# Resolve API key
resolved_key: Final = api_key or get_secret_str(provider.api_key_env)

11
litellm/llms/openai_like/providers.json
View file

@ -1,4 +1,15 @@
{
"bitdeer-ai": {
"base_url": "https://api-inference.bitdeer.ai/v1",
"api_key_env": "BITDEER_API_KEY",
"param_mappings": {
"max_completion_tokens": "max_tokens"
},
"special_handling": {
"require_api_key_for_custom_base": true
},
"supported_endpoints": ["/v1/chat/completions"]
},
"publicai": {
"base_url": "https://api.publicai.co/v1",
"api_key_env": "PUBLICAI_API_KEY",

46
litellm/model_prices_and_context_window_backup.json
View file

@ -61225,6 +61225,52 @@
],
"supports_audio_output": true
},
"bitdeer-ai/moonshotai/Kimi-K3": {
"max_tokens": 131072,
"max_input_tokens": 1048576,
"max_output_tokens": 131072,
"input_cost_per_token": 3e-06,
"output_cost_per_token": 1.5e-05,
"cache_read_input_token_cost": 3e-07,
"litellm_provider": "bitdeer-ai",
"mode": "chat",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_vision": true,
"supports_prompt_caching": true,
"source": "https://www.bitdeer.ai/en/pricing/ai-models"
},
"bitdeer-ai/zai-org/GLM-5.2": {
"max_tokens": 131072,
"max_input_tokens": 1000000,
"max_output_tokens": 131072,
"input_cost_per_token": 1.4e-06,
"output_cost_per_token": 4.4e-06,
"cache_read_input_token_cost": 2.6e-07,
"litellm_provider": "bitdeer-ai",
"mode": "chat",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_prompt_caching": true,
"source": "https://www.bitdeer.ai/en/pricing/ai-models"
},
"bitdeer-ai/deepseek-ai/DeepSeek-V4-Flash": {
"max_tokens": 384000,
"max_input_tokens": 1000000,
"max_output_tokens": 384000,
"input_cost_per_token": 4e-08,
"output_cost_per_token": 8e-08,
"cache_read_input_token_cost": 1e-08,
"litellm_provider": "bitdeer-ai",
"mode": "chat",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_prompt_caching": true,
"source": "https://www.bitdeer.ai/en/pricing/ai-models"
},
"fallback_generalizations": {
"rules": [
{

17
litellm/provider_endpoints_support_backup.json
View file

@ -32,6 +32,23 @@
}
},
"providers": {
"bitdeer-ai": {
"display_name": "Bitdeer AI (`bitdeer-ai`)",
"url": "https://docs.litellm.ai/docs/providers/bitdeer",
"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
}
},
"a2a": {
"display_name": "A2A (Agent-to-Agent) (`a2a`)",
"url": "https://docs.litellm.ai/docs/providers/a2a",

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

@ -748,6 +748,34 @@
],
"default_model_placeholder": "gpt-3.5-turbo"
},
{
"provider": "BITDEER_AI",
"provider_display_name": "Bitdeer AI",
"litellm_provider": "bitdeer-ai",
"credential_fields": [
{
"key": "api_base",
"label": "API Base",
"placeholder": "https://api-inference.bitdeer.ai/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": "bitdeer-ai/moonshotai/Kimi-K3"
},
{
"provider": "BYTEZ",
"provider_display_name": "Bytez",

1
litellm/types/utils.py
View file

@ -4200,6 +4200,7 @@ class LlmProviders(str, Enum):
XIAOMI_MIMO = "xiaomi_mimo"
TENSORMESH = "tensormesh"
LIBERTAI = "libertai"
BITDEER_AI = "bitdeer-ai"
PINSTRIPES = "pinstripes"
COGNITION = "cognition"
CORTECS = "cortecs"

46
model_prices_and_context_window.json
View file

@ -61225,6 +61225,52 @@
],
"supports_audio_output": true
},
"bitdeer-ai/moonshotai/Kimi-K3": {
"max_tokens": 131072,
"max_input_tokens": 1048576,
"max_output_tokens": 131072,
"input_cost_per_token": 3e-06,
"output_cost_per_token": 1.5e-05,
"cache_read_input_token_cost": 3e-07,
"litellm_provider": "bitdeer-ai",
"mode": "chat",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_vision": true,
"supports_prompt_caching": true,
"source": "https://www.bitdeer.ai/en/pricing/ai-models"
},
"bitdeer-ai/zai-org/GLM-5.2": {
"max_tokens": 131072,
"max_input_tokens": 1000000,
"max_output_tokens": 131072,
"input_cost_per_token": 1.4e-06,
"output_cost_per_token": 4.4e-06,
"cache_read_input_token_cost": 2.6e-07,
"litellm_provider": "bitdeer-ai",
"mode": "chat",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_prompt_caching": true,
"source": "https://www.bitdeer.ai/en/pricing/ai-models"
},
"bitdeer-ai/deepseek-ai/DeepSeek-V4-Flash": {
"max_tokens": 384000,
"max_input_tokens": 1000000,
"max_output_tokens": 384000,
"input_cost_per_token": 4e-08,
"output_cost_per_token": 8e-08,
"cache_read_input_token_cost": 1e-08,
"litellm_provider": "bitdeer-ai",
"mode": "chat",
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_reasoning": true,
"supports_prompt_caching": true,
"source": "https://www.bitdeer.ai/en/pricing/ai-models"
},
"fallback_generalizations": {
"rules": [
{

17
provider_endpoints_support.json
View file

@ -33,6 +33,23 @@
}
},
"providers": {
"bitdeer-ai": {
"display_name": "Bitdeer AI (`bitdeer-ai`)",
"url": "https://docs.litellm.ai/docs/providers/bitdeer",
"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
}
},
"a2a": {
"display_name": "A2A (Agent-to-Agent) (`a2a`)",
"url": "https://docs.litellm.ai/docs/providers/a2a",

164
tests/unit/llms/openai_like/test_bitdeer_provider.py Normal file
View file

@ -0,0 +1,164 @@
import json
from pathlib import Path
from typing import Final
import pytest
import respx
import litellm
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
from litellm.llms.openai_like.dynamic_config import create_config_class
from litellm.llms.openai_like.json_loader import JSONProviderRegistry
BASE_URL: Final = "https://api-inference.bitdeer.ai/v1"
MODEL: Final = "moonshotai/Kimi-K3"
MODELS: Final = (MODEL, "zai-org/GLM-5.2", "deepseek-ai/DeepSeek-V4-Flash")
@pytest.mark.parametrize("api_key", (None, "explicit-key"))
@pytest.mark.parametrize("api_base", (BASE_URL, BASE_URL + "/"))
@pytest.mark.parametrize("routing", ("prefix", "provider", "url"))
def test_bitdeer_credentials(
monkeypatch: pytest.MonkeyPatch, api_key: str | None, api_base: str, routing: str
) -> None:
monkeypatch.setenv("BITDEER_API_KEY", "environment-key")
result: Final = get_llm_provider(
model=f"bitdeer-ai/{MODEL}" if routing == "prefix" else MODEL,
custom_llm_provider="bitdeer-ai" if routing == "provider" else None,
api_base=api_base,
api_key=api_key,
)
assert result == (MODEL, "bitdeer-ai", api_key or "environment-key", api_base)
def test_bitdeer_default_base_and_missing_credentials(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.delenv("BITDEER_API_KEY", raising=False)
assert get_llm_provider(model=f"bitdeer-ai/{MODEL}") == (MODEL, "bitdeer-ai", None, BASE_URL)
monkeypatch.setenv("BITDEER_API_KEY", "environment-key")
assert get_llm_provider(model=f"bitdeer-ai/{MODEL}") == (MODEL, "bitdeer-ai", "environment-key", BASE_URL)
@pytest.mark.parametrize("api_key", (None, ""))
@pytest.mark.parametrize(
"api_base",
(
"https://custom.example/v1",
"http://api-inference.bitdeer.ai/v1",
"https://api-inference.bitdeer.ai:8443/v1",
"https://api-inference.bitdeer.ai.evil.example/v1",
"https://api-inference.bitdeer.ai@evil.example/v1",
"https://evil.example/https://api-inference.bitdeer.ai/v1",
BASE_URL + "/other",
BASE_URL + "?redirect=https://evil.example",
),
)
def test_bitdeer_custom_base_requires_explicit_key(
monkeypatch: pytest.MonkeyPatch, api_base: str, api_key: str | None
) -> None:
monkeypatch.setenv("BITDEER_API_KEY", "server-secret")
with pytest.raises(litellm.BadRequestError, match="explicit api_key is required") as error:
get_llm_provider(model=f"bitdeer-ai/{MODEL}", api_base=api_base, api_key=api_key)
assert "server-secret" not in str(error.value)
@pytest.mark.parametrize(
"api_base", ("http://api-inference.bitdeer.ai/v1", "https://api-inference.bitdeer.ai:8443/v1", BASE_URL + "/other")
)
def test_bitdeer_url_autodetection_rejects_unsafe_key_fallback(
monkeypatch: pytest.MonkeyPatch, api_base: str
) -> None:
monkeypatch.setenv("BITDEER_API_KEY", "server-secret")
with pytest.raises(litellm.BadRequestError, match="explicit api_key is required"):
get_llm_provider(model=MODEL, api_base=api_base)
def test_bitdeer_dynamic_config_checks_custom_base(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("BITDEER_API_KEY", "server-secret")
provider: Final = JSONProviderRegistry.get("bitdeer-ai")
assert provider is not None
config: Final = create_config_class(provider)()
with pytest.raises(ValueError, match="explicit api_key is required"):
config._get_openai_compatible_provider_info("https://custom.example/v1", None)
assert config._get_openai_compatible_provider_info("https://custom.example/v1", "explicit-key") == (
"https://custom.example/v1", "explicit-key"
)
@pytest.mark.parametrize("model", (MODEL, f"bitdeer-ai/{MODEL}"))
@pytest.mark.parametrize("api_key", (None, "explicit-key"))
def test_bitdeer_completion_sends_selected_key(
monkeypatch: pytest.MonkeyPatch, model: str, api_key: str | None
) -> None:
monkeypatch.setenv("BITDEER_API_KEY", "environment-key")
with respx.mock() as upstream:
route: Final = upstream.post(BASE_URL + "/chat/completions").respond(
200,
json={
"id": "chatcmpl-bitdeer",
"object": "chat.completion",
"created": 0,
"model": MODEL,
"choices": [{"index": 0, "message": {"role": "assistant", "content": "Hello"}, "finish_reason": "stop"}],
"usage": {"prompt_tokens": 10, "completion_tokens": 2, "total_tokens": 12},
},
)
response: Final = litellm.completion(
model=model,
api_base=BASE_URL,
api_key=api_key,
messages=[{"role": "user", "content": "Hi"}],
max_completion_tokens=32,
)
request: Final = route.calls.last.request
payload: Final = json.loads(request.content)
assert route.call_count == 1
assert request.headers["authorization"] == f"Bearer {api_key or 'environment-key'}"
assert payload["model"] == MODEL
assert payload["max_tokens"] == 32
assert "max_completion_tokens" not in payload
assert response.choices[0].message.content == "Hello"
assert response._hidden_params["response_cost"] == pytest.approx(
10 * litellm.model_cost[f"bitdeer-ai/{MODEL}"]["input_cost_per_token"]
+ 2 * litellm.model_cost[f"bitdeer-ai/{MODEL}"]["output_cost_per_token"]
)
def test_bitdeer_completion_rejects_custom_base_before_sending(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("BITDEER_API_KEY", "server-secret")
with respx.mock() as upstream:
with pytest.raises(litellm.BadRequestError, match="explicit api_key is required"):
litellm.completion(
model=f"bitdeer-ai/{MODEL}",
api_base="https://custom.example/v1",
messages=[{"role": "user", "content": "Hi"}],
)
assert len(upstream.calls) == 0
def _unique_entries(pairs: list[tuple[str, object]]) -> dict[str, object]:
keys: Final = tuple(key for key, _ in pairs)
assert len(keys) == len(set(keys)), "Duplicate JSON key"
return dict(pairs)
def test_bitdeer_pricing_and_packaged_registry() -> None:
root: Final = Path(litellm.__file__).parent.parent
prices: Final = json.loads((root / "model_prices_and_context_window.json").read_text(), object_pairs_hook=_unique_entries)
backup: Final = json.loads((root / "litellm/model_prices_and_context_window_backup.json").read_text())
for model in MODELS:
name: Final = f"bitdeer-ai/{model}"
entry: Final = prices[name]
assert entry == backup[name] == litellm.model_cost[name]
assert entry["max_tokens"] == entry["max_output_tokens"] <= entry["max_input_tokens"]
assert entry["litellm_provider"] == "bitdeer-ai"
prompt_cost, output_cost = litellm.cost_per_token(model=name, prompt_tokens=100, completion_tokens=10)
assert prompt_cost == pytest.approx(100 * entry["input_cost_per_token"])
assert output_cost == pytest.approx(10 * entry["output_cost_per_token"])