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2
litellm/constants.py
View file

@ -965,6 +965,7 @@ openai_compatible_endpoints: Final[list] = [
"https://api.cortecs.ai/v1",
"https://api.scx.ai/v1",
"https://api.prisminference.com/v1",
"https://api.code.umans.ai/v1",
"https://gigachat.devices.sberbank.ru/api/v1",
]
@ -1041,6 +1042,7 @@ openai_compatible_providers: Final[list] = [
"scx-ai",
"prism",
"sail",
"umans-ai",
]
OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS: Final = frozenset({"openai"} | frozenset(openai_compatible_providers))

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

@ -218,5 +218,11 @@
"api_key_env": "SAIL_API_KEY",
"api_base_env": "SAIL_API_BASE",
"supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/messages"]
},
"umans-ai": {
"base_url": "https://api.code.umans.ai/v1",
"api_key_env": "UMANS_AI_API_KEY",
"api_base_env": "UMANS_AI_API_BASE",
"supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/messages"]
}
}

166
litellm/model_prices_and_context_window_backup.json
View file

@ -80003,5 +80003,171 @@
"supports_tool_choice": true,
"supports_video_input": false,
"supports_vision": false
},
"umans-ai/umans-deepseek-v4-flash-0731": {
"cache_read_input_token_cost": 2.8e-08,
"input_cost_per_token": 1.4e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 393215,
"max_tokens": 393215,
"mode": "chat",
"output_cost_per_token": 2.8e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": false
},
"umans-ai/umans-deepseek-v4.1-flash": {
"cache_read_input_token_cost": 2.8e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 393215,
"max_tokens": 393215,
"mode": "chat",
"output_cost_per_token": 6e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-glm-5.3": {
"cache_read_input_token_cost": 2.6e-07,
"input_cost_per_token": 1.4e-06,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131071,
"max_tokens": 131071,
"mode": "chat",
"output_cost_per_token": 4.4e-06,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": false
},
"umans-ai/umans-glm-5.3-flash": {
"cache_read_input_token_cost": 3e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131071,
"max_tokens": 131071,
"mode": "chat",
"output_cost_per_token": 5e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-kimi-k3": {
"cache_read_input_token_cost": 3e-07,
"input_cost_per_token": 3e-06,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131072,
"max_tokens": 131072,
"mode": "chat",
"output_cost_per_token": 1.5e-05,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-flash": {
"cache_read_input_token_cost": 5e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 262144,
"max_output_tokens": 32768,
"max_tokens": 32768,
"mode": "chat",
"output_cost_per_token": 1e-06,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-coder": {
"cache_read_input_token_cost": 3e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131071,
"max_tokens": 131071,
"mode": "chat",
"output_cost_per_token": 5e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
}
}

18
litellm/provider_endpoints_support_backup.json
View file

@ -2262,6 +2262,24 @@
"interactions": true
}
},
"umans-ai": {
"display_name": "Umans AI (`umans-ai`)",
"url": "https://docs.litellm.ai/docs/providers/umans_ai",
"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
}
},
"v0": {
"display_name": "V0 (`v0`)",
"url": "https://docs.litellm.ai/docs/providers/v0",

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

@ -3291,6 +3291,34 @@
],
"default_model_placeholder": "gpt-3.5-turbo"
},
{
"provider": "UMANS_AI",
"provider_display_name": "Umans AI",
"litellm_provider": "umans-ai",
"credential_fields": [
{
"key": "api_base",
"label": "API Base",
"placeholder": "https://api.code.umans.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": "umans-ai/umans-deepseek-v4-flash-0731"
},
{
"provider": "V0",
"provider_display_name": "V0",

1
litellm/types/utils.py
View file

@ -4180,6 +4180,7 @@ class LlmProviders(str, Enum):
DARKBLOOM = "darkbloom"
META = "meta"
SAIL = "sail"
UMANS_AI = "umans-ai"
LITELLM_AGENT = "litellm_agent"
CURSOR = "cursor"
BEDROCK_MANTLE = "bedrock_mantle"

166
model_prices_and_context_window.json
View file

@ -80003,5 +80003,171 @@
"supports_tool_choice": true,
"supports_video_input": false,
"supports_vision": false
},
"umans-ai/umans-deepseek-v4-flash-0731": {
"cache_read_input_token_cost": 2.8e-08,
"input_cost_per_token": 1.4e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 393215,
"max_tokens": 393215,
"mode": "chat",
"output_cost_per_token": 2.8e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": false
},
"umans-ai/umans-deepseek-v4.1-flash": {
"cache_read_input_token_cost": 2.8e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 393215,
"max_tokens": 393215,
"mode": "chat",
"output_cost_per_token": 6e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-glm-5.3": {
"cache_read_input_token_cost": 2.6e-07,
"input_cost_per_token": 1.4e-06,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131071,
"max_tokens": 131071,
"mode": "chat",
"output_cost_per_token": 4.4e-06,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": false
},
"umans-ai/umans-glm-5.3-flash": {
"cache_read_input_token_cost": 3e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131071,
"max_tokens": 131071,
"mode": "chat",
"output_cost_per_token": 5e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-kimi-k3": {
"cache_read_input_token_cost": 3e-07,
"input_cost_per_token": 3e-06,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131072,
"max_tokens": 131072,
"mode": "chat",
"output_cost_per_token": 1.5e-05,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-flash": {
"cache_read_input_token_cost": 5e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 262144,
"max_output_tokens": 32768,
"max_tokens": 32768,
"mode": "chat",
"output_cost_per_token": 1e-06,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
},
"umans-ai/umans-coder": {
"cache_read_input_token_cost": 3e-08,
"input_cost_per_token": 1.5e-07,
"litellm_provider": "umans-ai",
"max_input_tokens": 1048576,
"max_output_tokens": 131071,
"max_tokens": 131071,
"mode": "chat",
"output_cost_per_token": 5e-07,
"source": "https://app.umans.ai/pricing",
"supported_modalities": [
"text",
"image"
],
"supported_output_modalities": [
"text"
],
"supports_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true
}
}

18
provider_endpoints_support.json
View file

@ -2637,6 +2637,24 @@
"interactions": true
}
},
"umans-ai": {
"display_name": "Umans AI (`umans-ai`)",
"url": "https://docs.litellm.ai/docs/providers/umans_ai",
"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
}
},
"v0": {
"display_name": "V0 (`v0`)",
"url": "https://docs.litellm.ai/docs/providers/v0",

389
tests/unit/llms/openai_like/test_umans_ai_provider.py Normal file
View file

@ -0,0 +1,389 @@
import json
from collections.abc import Mapping
from pathlib import Path
from types import MappingProxyType
from typing import Final
import pytest
import respx
import litellm
from litellm.caching.llm_caching_handler import LLMClientCache
def test_umans_ai_provider_resolution(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("UMANS_AI_API_KEY", "umans-test-key")
model, provider, api_key, api_base = get_llm_provider(
model="umans-ai/umans-deepseek-v4-flash-0731",
custom_llm_provider=None,
api_base=None,
api_key=None,
)
assert model == "umans-deepseek-v4-flash-0731"
assert provider == "umans-ai"
assert api_key == "umans-test-key"
assert api_base == "https://api.code.umans.ai/v1"
def test_umans_ai_provider_keeps_explicit_credentials(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("UMANS_AI_API_KEY", "umans-env-key")
_, provider, api_key, api_base = get_llm_provider(
model="umans-ai/umans-deepseek-v4-flash-0731",
custom_llm_provider=None,
api_base="https://umans.internal.example/v1",
api_key="umans-explicit-key",
)
assert provider == "umans-ai"
assert api_key == "umans-explicit-key"
assert api_base == "https://umans.internal.example/v1"
def test_umans_ai_is_available_in_add_model_form():
fields_path: Final = Path(litellm.__file__).parent / "proxy" / "public_endpoints" / "provider_create_fields.json"
providers: Final = json.loads(fields_path.read_text())
umans: Final = next(provider for provider in providers if provider["litellm_provider"] == "umans-ai")
assert umans["provider"] == "UMANS_AI"
assert umans["provider_display_name"] == "Umans AI"
assert umans["default_model_placeholder"] == "umans-ai/umans-deepseek-v4-flash-0731"
assert {field["key"]: field["required"] for field in umans["credential_fields"]} == {
"api_base": False,
"api_key": True,
}
def test_umans_ai_supported_endpoints():
matrix_path: Final = Path(litellm.__file__).parent / "provider_endpoints_support_backup.json"
providers: Final = json.loads(matrix_path.read_text())["providers"]
assert providers["umans-ai"]["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,
}
def test_umans_ai_chat_completion_request():
with respx.mock() as upstream:
route: Final = upstream.post("https://api.code.umans.ai/v1/chat/completions").respond(
200,
json={
"id": "chatcmpl_umans",
"object": "chat.completion",
"created": 1_789_550_000,
"model": "umans-deepseek-v4-flash-0731",
"choices": [
{
"index": 0,
"message": {"role": "assistant", "content": "Hello from Umans AI"},
"finish_reason": "stop",
}
],
"usage": {"prompt_tokens": 4, "completion_tokens": 3, "total_tokens": 7},
},
)
response: Final = litellm.completion(
model="umans-ai/umans-deepseek-v4-flash-0731",
messages=[{"role": "user", "content": "Say hello"}],
api_key="umans-test-key",
)
request: Final = route.calls.last.request
body: Final = json.loads(request.content)
assert route.call_count == 1
assert str(request.url) == "https://api.code.umans.ai/v1/chat/completions"
assert request.headers["authorization"] == "Bearer umans-test-key"
assert body["model"] == "umans-deepseek-v4-flash-0731"
assert body["messages"] == [{"role": "user", "content": "Say hello"}]
assert response.choices[0].message.content == "Hello from Umans AI"
def test_umans_ai_responses_request():
with respx.mock() as upstream:
route: Final = upstream.post("https://api.code.umans.ai/v1/responses").respond(
200,
json={
"id": "resp_umans",
"object": "response",
"created_at": 1_789_550_000,
"model": "umans-deepseek-v4-flash-0731",
"status": "completed",
"output": [
{
"id": "msg_umans",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [{"type": "output_text", "text": "Hello from Umans AI", "annotations": []}],
}
],
"usage": {"input_tokens": 4, "output_tokens": 3, "total_tokens": 7},
},
)
response: Final = litellm.responses(
model="umans-ai/umans-deepseek-v4-flash-0731",
input="Say hello",
api_key="umans-test-key",
)
request: Final = route.calls.last.request
body: Final = json.loads(request.content)
assert route.call_count == 1
assert str(request.url) == "https://api.code.umans.ai/v1/responses"
assert request.headers["authorization"] == "Bearer umans-test-key"
assert body["model"] == "umans-deepseek-v4-flash-0731"
assert body["input"] == "Say hello"
assert response.output[0].content[0].text == "Hello from Umans AI"
@pytest.mark.asyncio
async def test_umans_ai_anthropic_messages_request(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("https://api.code.umans.ai/v1/messages").respond(
200,
json={
"id": "msg_umans",
"type": "message",
"role": "assistant",
"model": "umans-deepseek-v4-flash-0731",
"content": [{"type": "text", "text": "Hello from Umans AI"}],
"stop_reason": "end_turn",
"stop_sequence": None,
"usage": {"input_tokens": 4, "output_tokens": 3},
},
)
response: Final = await litellm.anthropic.messages.acreate(
model="umans-ai/umans-deepseek-v4-flash-0731",
messages=[{"role": "user", "content": "Say hello"}],
max_tokens=32,
api_key="umans-test-key",
)
request: Final = route.calls.last.request
body: Final = json.loads(request.content)
assert route.call_count == 1
assert str(request.url) == "https://api.code.umans.ai/v1/messages"
assert request.headers["authorization"] == "Bearer umans-test-key"
assert request.headers["anthropic-version"] == "2023-06-01"
assert body["model"] == "umans-deepseek-v4-flash-0731"
assert body["messages"] == [{"role": "user", "content": "Say hello"}]
assert response["content"][0]["text"] == "Hello from Umans AI"
COST_FIELDS: Final = ("input_cost_per_token", "output_cost_per_token", "cache_read_input_token_cost")
def _umans_cost_entries(filename: str = "model_prices_and_context_window.json") -> Mapping[str, Mapping[str, object]]:
cost_map: Final = json.loads((Path(__file__).parents[4] / filename).read_text())
return MappingProxyType({model: entry for model, entry in cost_map.items() if model.startswith("umans-ai/")})
def test_umans_ai_cost_map_entries_match_backup_and_are_priced():
entries: Final = _umans_cost_entries()
assert entries
assert entries == _umans_cost_entries("litellm/model_prices_and_context_window_backup.json")
for entry in entries.values():
assert entry["litellm_provider"] == "umans-ai"
assert entry["mode"] == "chat"
assert entry["max_tokens"] == entry["max_output_tokens"]
assert all(isinstance(cost, float) and cost > 0 for cost in (entry[field] for field in COST_FIELDS))
def test_umans_ai_default_model_is_priced():
fields_path: Final = Path(litellm.__file__).parent / "proxy" / "public_endpoints" / "provider_create_fields.json"
umans: Final = next(
provider for provider in json.loads(fields_path.read_text()) if provider["litellm_provider"] == "umans-ai"
)
assert umans["default_model_placeholder"] in _umans_cost_entries()
def test_umans_ai_usage_is_billed_at_cost_map_rates():
model: Final = "umans-ai/umans-deepseek-v4-flash-0731"
entry: Final = _umans_cost_entries()[model]
input_cost: Final = entry["input_cost_per_token"]
output_cost: Final = entry["output_cost_per_token"]
cache_read_cost: Final = entry["cache_read_input_token_cost"]
assert isinstance(input_cost, float)
assert isinstance(output_cost, float)
assert isinstance(cache_read_cost, float)
prompt_cost, completion_cost = litellm.cost_per_token(
model=model, prompt_tokens=1_000, completion_tokens=2_000, cache_read_input_tokens=800
)
assert prompt_cost == pytest.approx(200 * input_cost + 800 * cache_read_cost)
assert completion_cost == pytest.approx(2_000 * output_cost)
def _sse(*events: Mapping[str, object]) -> bytes:
return b"".join(f"data: {json.dumps(event)}\n\n".encode() for event in events) + b"data: [DONE]\n\n"
def _typed_sse(*events: Mapping[str, object]) -> bytes:
return b"".join(f"event: {event['type']}\ndata: {json.dumps(event)}\n\n".encode() for event in events)
def test_umans_ai_chat_completion_streaming_request():
chunk: Final = {
"id": "chatcmpl_umans",
"object": "chat.completion.chunk",
"created": 1_789_550_000,
"model": "umans-deepseek-v4-flash-0731",
}
stream_body: Final = _sse(
{
**chunk,
"choices": [{"index": 0, "delta": {"role": "assistant", "content": "Hello from "}, "finish_reason": None}],
},
{**chunk, "choices": [{"index": 0, "delta": {"content": "Umans AI"}, "finish_reason": None}]},
{**chunk, "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]},
)
with respx.mock() as upstream:
route: Final = upstream.post("https://api.code.umans.ai/v1/chat/completions").respond(
200, content=stream_body, headers={"content-type": "text/event-stream"}
)
chunks: Final = list(
litellm.completion(
model="umans-ai/umans-deepseek-v4-flash-0731",
messages=[{"role": "user", "content": "Say hello"}],
api_key="umans-test-key",
stream=True,
)
)
body: Final = json.loads(route.calls.last.request.content)
assert route.call_count == 1
assert str(route.calls.last.request.url) == "https://api.code.umans.ai/v1/chat/completions"
assert body["stream"] is True
assert "".join(chunk.choices[0].delta.content or "" for chunk in chunks) == "Hello from Umans AI"
def test_umans_ai_responses_streaming_request():
response: Final = {
"id": "resp_umans",
"object": "response",
"created_at": 1_789_550_000,
"model": "umans-deepseek-v4-flash-0731",
"status": "in_progress",
"output": [],
}
message: Final = {
"id": "msg_umans",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [{"type": "output_text", "text": "Hello from Umans AI", "annotations": []}],
}
stream_body: Final = _typed_sse(
{"type": "response.created", "sequence_number": 0, "response": response},
{
"type": "response.output_text.delta",
"sequence_number": 1,
"item_id": "msg_umans",
"output_index": 0,
"content_index": 0,
"delta": "Hello from Umans AI",
},
{
"type": "response.completed",
"sequence_number": 2,
"response": {
**response,
"status": "completed",
"output": [message],
"usage": {"input_tokens": 4, "output_tokens": 3, "total_tokens": 7},
},
},
)
with respx.mock() as upstream:
route: Final = upstream.post("https://api.code.umans.ai/v1/responses").respond(
200, content=stream_body, headers={"content-type": "text/event-stream"}
)
events: Final = list(
litellm.responses(
model="umans-ai/umans-deepseek-v4-flash-0731",
input="Say hello",
api_key="umans-test-key",
stream=True,
)
)
body: Final = json.loads(route.calls.last.request.content)
assert route.call_count == 1
assert str(route.calls.last.request.url) == "https://api.code.umans.ai/v1/responses"
assert body["stream"] is True
assert "".join(event.delta for event in events if event.type == "response.output_text.delta") == (
"Hello from Umans AI"
)
assert events[-1].type == "response.completed"
@pytest.mark.asyncio
async def test_umans_ai_anthropic_messages_streaming_request(monkeypatch: pytest.MonkeyPatch):
monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
monkeypatch.setattr(litellm, "in_memory_llm_clients_cache", LLMClientCache())
stream_body: Final = _typed_sse(
{
"type": "message_start",
"message": {
"id": "msg_umans",
"type": "message",
"role": "assistant",
"model": "umans-deepseek-v4-flash-0731",
"content": [],
"stop_reason": None,
"stop_sequence": None,
"usage": {"input_tokens": 4, "output_tokens": 0},
},
},
{"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}},
{"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "Hello from Umans AI"}},
{"type": "content_block_stop", "index": 0},
{
"type": "message_delta",
"delta": {"stop_reason": "end_turn", "stop_sequence": None},
"usage": {"output_tokens": 3},
},
{"type": "message_stop"},
)
with respx.mock() as upstream:
route: Final = upstream.post("https://api.code.umans.ai/v1/messages").respond(
200, content=stream_body, headers={"content-type": "text/event-stream"}
)
stream: Final = await litellm.anthropic.messages.acreate(
model="umans-ai/umans-deepseek-v4-flash-0731",
messages=[{"role": "user", "content": "Say hello"}],
max_tokens=32,
api_key="umans-test-key",
stream=True,
)
streamed: Final = b"".join([chunk async for chunk in stream]).decode()
body: Final = json.loads(route.calls.last.request.content)
assert route.call_count == 1
assert str(route.calls.last.request.url) == "https://api.code.umans.ai/v1/messages"
assert body["stream"] is True
assert "event: message_start" in streamed
assert "Hello from Umans AI" in streamed
assert "event: message_stop" in streamed