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5
litellm/__init__.py
View file

@ -681,6 +681,7 @@ publicai_models: Set = set()
darkbloom_models: Set = set()
openinfer_models: Final[Set[str]] = set()
v0_models: Set = set()
vispark_models: Set[str] = set()
morph_models: Set = set()
lambda_ai_models: Set = set()
inception_models: Set = set()
@ -968,6 +969,8 @@ def _populate_provider_model_sets(model_cost_map: Mapping[str, Mapping[str, obje
openinfer_models.add(key)
elif value.get("litellm_provider") == "v0":
v0_models.add(key)
elif value.get("litellm_provider") == "vispark":
vispark_models.add(key)
elif value.get("litellm_provider") == "morph":
morph_models.add(key)
elif value.get("litellm_provider") == "lambda_ai":
@ -1136,6 +1139,7 @@ model_list = list(
| darkbloom_models
| openinfer_models
| v0_models
| vispark_models
| morph_models
| lambda_ai_models
| inception_models
@ -1253,6 +1257,7 @@ def _build_models_by_provider() -> dict:
"darkbloom": darkbloom_models,
"openinfer": openinfer_models,
"v0": v0_models,
"vispark": vispark_models,
"morph": morph_models,
"lambda_ai": lambda_ai_models,
"inception": inception_models,

3
litellm/constants.py
View file

@ -1056,6 +1056,7 @@ openai_compatible_endpoints: Final[list[str]] = [
"https://inference.coralbricks.ai/v1",
"https://api.cortecs.ai/v1",
"https://api.scx.ai/v1",
"https://api.lab.vispark.in/v1",
"https://api.prisminference.com/v1",
"https://api.reka.ai/v1",
"https://gigachat.devices.sberbank.ru/api/v1",
@ -1130,6 +1131,7 @@ openai_compatible_providers: Final[list[str]] = [
"pinstripes", # Pinstripes - JSON-configured provider
"openinfer",
"darkbloom",
"vispark", # Vispark Lab - JSON-configured provider
"meta", # Meta Model API (Muse Spark) - JSON-configured provider
"cognition",
"coralbricks",
@ -1163,6 +1165,7 @@ openai_text_completion_compatible_providers: Final[list] = [ # providers that s
"poe",
"chutes",
"v0",
"vispark",
"lambda_ai",
"hyperbolic",
"wandb",

9
litellm/llms/openai_like/providers.json
View file

@ -249,5 +249,14 @@
"/v1/responses",
"/v1/messages"
]
},
"vispark": {
"base_url": "https://api.lab.vispark.in/v1",
"api_key_env": "VISPARK_LAB_API_KEY",
"api_base_env": "VISPARK_LAB_API_BASE",
"param_mappings": {
"max_completion_tokens": "max_tokens"
},
"supported_endpoints": ["/v1/chat/completions", "/v1/completions"]
}
}

96
litellm/model_prices_and_context_window_backup.json
View file

@ -49883,6 +49883,102 @@
"supports_tool_choice": true,
"supports_vision": true
},
"vispark/vision-small": {
"input_cost_per_token": 1.05e-06,
"litellm_provider": "vispark",
"max_input_tokens": 1000000,
"max_output_tokens": 65536,
"max_tokens": 65536,
"mode": "chat",
"output_cost_per_token": 3.16e-06,
"source": "https://api.lab.vispark.in/v1/models",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/completions"
],
"supported_modalities": [
"text",
"image",
"audio",
"video"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"vispark/vision-medium": {
"input_cost_per_token": 4.21e-06,
"litellm_provider": "vispark",
"max_input_tokens": 1000000,
"max_output_tokens": 65536,
"max_tokens": 65536,
"mode": "chat",
"output_cost_per_token": 1.263e-05,
"source": "https://api.lab.vispark.in/v1/models",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/completions"
],
"supported_modalities": [
"text",
"image",
"audio",
"video"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"vispark/vision-large": {
"input_cost_per_token": 7.37e-06,
"litellm_provider": "vispark",
"max_input_tokens": 1000000,
"max_output_tokens": 65536,
"max_tokens": 65536,
"mode": "chat",
"output_cost_per_token": 2.211e-05,
"source": "https://api.lab.vispark.in/v1/models",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/completions"
],
"supported_modalities": [
"text",
"image",
"audio",
"video"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"vercel_ai_gateway/alibaba/qwen-3-14b": {
"input_cost_per_token": 8e-08,
"litellm_provider": "vercel_ai_gateway",

18
litellm/provider_endpoints_support_backup.json
View file

@ -2352,6 +2352,24 @@
"interactions": true
}
},
"vispark": {
"display_name": "Vispark (`vispark`)",
"url": "https://lab.vispark.in/#vision",
"endpoints": {
"chat_completions": true,
"messages": false,
"responses": false,
"embeddings": false,
"image_generations": false,
"audio_transcriptions": false,
"audio_speech": false,
"moderations": false,
"batches": false,
"rerank": false,
"a2a": false,
"interactions": false
}
},
"vercel_ai_gateway": {
"display_name": "Vercel AI Gateway (`vercel_ai_gateway`)",
"url": "https://docs.litellm.ai/docs/providers/vercel_ai_gateway",

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

@ -4070,5 +4070,33 @@
}
],
"default_model_placeholder": "cursor/claude-4-sonnet"
},
{
"provider": "VISPARK",
"provider_display_name": "Vispark",
"litellm_provider": "vispark",
"credential_fields": [
{
"key": "api_base",
"label": "API Base",
"placeholder": "https://api.lab.vispark.in/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": "vispark/vision-medium"
}
]

1
litellm/types/utils.py
View file

@ -4453,6 +4453,7 @@ class LlmProviders(str, Enum):
MOONSHOT = "moonshot"
PUBLICAI = "publicai"
V0 = "v0"
VISPARK = "vispark"
MORPH = "morph"
LAMBDA_AI = "lambda_ai"
INCEPTION = "inception"

96
model_prices_and_context_window.json
View file

@ -49883,6 +49883,102 @@
"supports_tool_choice": true,
"supports_vision": true
},
"vispark/vision-small": {
"input_cost_per_token": 1.05e-06,
"litellm_provider": "vispark",
"max_input_tokens": 1000000,
"max_output_tokens": 65536,
"max_tokens": 65536,
"mode": "chat",
"output_cost_per_token": 3.16e-06,
"source": "https://api.lab.vispark.in/v1/models",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/completions"
],
"supported_modalities": [
"text",
"image",
"audio",
"video"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"vispark/vision-medium": {
"input_cost_per_token": 4.21e-06,
"litellm_provider": "vispark",
"max_input_tokens": 1000000,
"max_output_tokens": 65536,
"max_tokens": 65536,
"mode": "chat",
"output_cost_per_token": 1.263e-05,
"source": "https://api.lab.vispark.in/v1/models",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/completions"
],
"supported_modalities": [
"text",
"image",
"audio",
"video"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"vispark/vision-large": {
"input_cost_per_token": 7.37e-06,
"litellm_provider": "vispark",
"max_input_tokens": 1000000,
"max_output_tokens": 65536,
"max_tokens": 65536,
"mode": "chat",
"output_cost_per_token": 2.211e-05,
"source": "https://api.lab.vispark.in/v1/models",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/completions"
],
"supported_modalities": [
"text",
"image",
"audio",
"video"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_pdf_input": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"vercel_ai_gateway/alibaba/qwen-3-14b": {
"input_cost_per_token": 8e-08,
"litellm_provider": "vercel_ai_gateway",

18
provider_endpoints_support.json
View file

@ -2722,6 +2722,24 @@
"interactions": true
}
},
"vispark": {
"display_name": "Vispark (`vispark`)",
"url": "https://lab.vispark.in/#vision",
"endpoints": {
"chat_completions": true,
"messages": false,
"responses": false,
"embeddings": false,
"image_generations": false,
"audio_transcriptions": false,
"audio_speech": false,
"moderations": false,
"batches": false,
"rerank": false,
"a2a": false,
"interactions": false
}
},
"vercel_ai_gateway": {
"display_name": "Vercel AI Gateway (`vercel_ai_gateway`)",
"url": "https://docs.litellm.ai/docs/providers/vercel_ai_gateway",

177
tests/unit/llms/openai_like/test_vispark_provider.py Normal file
View file

@ -0,0 +1,177 @@
import json
from pathlib import Path
from typing import Final
import pytest
import respx
import litellm
_CHAT_COMPLETION: Final = {
"id": "chatcmpl_vispark",
"object": "chat.completion",
"created": 1_790_000_000,
"model": "vision-medium",
"choices": [
{
"index": 0,
"message": {"role": "assistant", "content": "Hello from Vispark"},
"finish_reason": "stop",
}
],
"usage": {"prompt_tokens": 4, "completion_tokens": 3, "total_tokens": 7},
}
_TEXT_COMPLETION: Final = {
"id": "cmpl_vispark",
"object": "text_completion",
"created": 1_790_000_000,
"model": "vision-small",
"choices": [{"index": 0, "text": "Hello from Vispark", "finish_reason": "stop", "logprobs": None}],
"usage": {"prompt_tokens": 4, "completion_tokens": 3, "total_tokens": 7},
}
def test_vispark_provider_resolution(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("VISPARK_LAB_API_KEY", "vispark-env-key")
monkeypatch.delenv("VISPARK_LAB_API_BASE", raising=False)
model, provider, api_key, api_base = get_llm_provider(
model="vispark/vision-medium",
custom_llm_provider=None,
api_base=None,
api_key=None,
)
assert model == "vision-medium"
assert provider == "vispark"
assert api_key == "vispark-env-key"
assert api_base == "https://api.lab.vispark.in/v1"
def test_vispark_provider_keeps_explicit_credentials(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("VISPARK_LAB_API_KEY", "vispark-env-key")
monkeypatch.setenv("VISPARK_LAB_API_BASE", "https://vispark.env.example/v1")
_, provider, api_key, api_base = get_llm_provider(
model="vispark/vision-medium",
custom_llm_provider=None,
api_base="https://vispark.internal.example/v1",
api_key="vispark-explicit-key",
)
assert provider == "vispark"
assert api_key == "vispark-explicit-key"
assert api_base == "https://vispark.internal.example/v1"
def test_vispark_api_base_env_overrides_default(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("VISPARK_LAB_API_KEY", "vispark-env-key")
monkeypatch.setenv("VISPARK_LAB_API_BASE", "https://vispark.env.example/v1")
_, provider, _, api_base = get_llm_provider(
model="vispark/vision-medium",
custom_llm_provider=None,
api_base=None,
api_key=None,
)
assert provider == "vispark"
assert api_base == "https://vispark.env.example/v1"
def test_vispark_api_base_autodetects_provider(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("VISPARK_LAB_API_KEY", "vispark-env-key")
model, provider, api_key, api_base = get_llm_provider(
model="vision-medium",
custom_llm_provider=None,
api_base="https://api.lab.vispark.in/v1",
api_key=None,
)
assert model == "vision-medium"
assert provider == "vispark"
assert api_key == "vispark-env-key"
assert api_base == "https://api.lab.vispark.in/v1"
def test_vispark_chat_completion_request_maps_max_completion_tokens():
with respx.mock() as upstream:
route: Final = upstream.post("https://api.lab.vispark.in/v1/chat/completions").respond(
200, json=_CHAT_COMPLETION
)
response: Final = litellm.completion(
model="vispark/vision-medium",
messages=[{"role": "user", "content": "Say hello"}],
max_completion_tokens=64,
api_key="vispark-test-key",
)
request: Final = route.calls.last.request
body: Final = json.loads(request.content)
assert route.call_count == 1
assert request.headers["authorization"] == "Bearer vispark-test-key"
assert body["model"] == "vision-medium"
assert body["max_tokens"] == 64
assert "max_completion_tokens" not in body
assert response.choices[0].message.content == "Hello from Vispark"
def test_vispark_text_completion_request():
with respx.mock() as upstream:
route: Final = upstream.post("https://api.lab.vispark.in/v1/completions").respond(200, json=_TEXT_COMPLETION)
response: Final = litellm.text_completion(
model="vispark/vision-small",
prompt="Say hello",
api_key="vispark-test-key",
)
body: Final = json.loads(route.calls.last.request.content)
assert route.call_count == 1
assert body["model"] == "vision-small"
assert body["prompt"] == "Say hello"
assert response.choices[0].text == "Hello from Vispark"
def test_vispark_cost_follows_the_cost_map():
cost_entry: Final = litellm.model_cost["vispark/vision-large"]
prompt_cost, completion_cost = litellm.cost_per_token(
model="vision-large",
custom_llm_provider="vispark",
prompt_tokens=1_000,
completion_tokens=500,
)
assert prompt_cost == pytest.approx(1_000 * cost_entry["input_cost_per_token"])
assert completion_cost == pytest.approx(500 * cost_entry["output_cost_per_token"])
def test_vispark_models_are_listed_for_the_provider():
from litellm.utils import get_valid_models
expected: Final = {name for name, entry in litellm.model_cost.items() if entry.get("litellm_provider") == "vispark"}
assert expected
assert set(litellm.models_by_provider["vispark"]) == expected
assert expected <= set(get_valid_models(custom_llm_provider="vispark"))
def test_vispark_endpoint_matrix_matches_between_root_and_backup():
backup_path: Final = Path(litellm.__file__).parent / "provider_endpoints_support_backup.json"
root_path: Final = Path(litellm.__file__).parent.parent / "provider_endpoints_support.json"
backup_entry: Final = json.loads(backup_path.read_text())["providers"]["vispark"]
root_entry: Final = json.loads(root_path.read_text())["providers"]["vispark"]
assert backup_entry == root_entry
assert root_entry["endpoints"]["chat_completions"] is True