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feat(providers): add Prism provider (internal copy of #40914) (#41961)

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* feat(providers): add Prism provider

* fix(providers): complete Prism registration

* feat(providers): expose Prism responses and messages

* feat(providers): add DeepSeek V4.1 Flash to Prism

* test(providers): exercise Prism endpoint requests

* fix(providers): align Prism pricing and limits with the live catalog

deepseek-v4.1-flash bills 0.17/0.63 USD per 1M input/output tokens and takes image input;
deepseek-v4-flash bills 0.17/0.21 and caps output at 384000 tokens, per GET /v1/models

* test(prism): assert cost-map invariants instead of pinning catalog facts

* test(prism): derive the asserted model list from the cost map instead of pinning it

* test(prism): capture requests through respx instead of appending to a list and swapping the client transport

---------

Co-authored-by: rajitkhanna <rajitskhanna@gmail.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: ryan <ryan@berri.ai>
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devin-ai-integration[bot] 2026-09-28 16:07:09 -07:00 • committed by GitHub
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2
litellm/constants.py
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@ -949,6 +949,7 @@ openai_compatible_endpoints: Final[list] = [
"https://api.sailresearch.com/v1",
"https://api.cognition.ai/v1",
"https://api.scx.ai/v1",
"https://api.prisminference.com/v1",
"https://gigachat.devices.sberbank.ru/api/v1",
]
@ -1022,6 +1023,7 @@ openai_compatible_providers: Final[list] = [
"meta", # Meta Model API (Muse Spark) - JSON-configured provider
"cognition",
"scx-ai",
"prism",
"sail",
]

6
litellm/llms/openai_like/providers.json
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@ -201,6 +201,12 @@
},
"supported_endpoints": ["/v1/chat/completions"]
},
"prism": {
"base_url": "https://api.prisminference.com/v1",
"api_key_env": "PRISM_API_KEY",
"api_base_env": "PRISM_API_BASE",
"supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/messages"]
},
"sail": {
"base_url": "https://api.sailresearch.com/v1",
"api_key_env": "SAIL_API_KEY",

50
litellm/model_prices_and_context_window_backup.json
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@ -78485,5 +78485,55 @@
"thinking_always_on": true,
"prompt_cache_min_tokens": 512,
"source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing"
},
"prism/deepseek-v4.1-flash": {
"cache_read_input_token_cost": 7e-08,
"input_cost_per_token": 1.7e-07,
"litellm_provider": "prism",
"max_input_tokens": 1000000,
"max_output_tokens": 384000,
"max_tokens": 384000,
"mode": "chat",
"output_cost_per_token": 6.3e-07,
"source": "https://prisminference.com/pricing",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses",
"/v1/messages"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"prism/deepseek-v4-flash": {
"cache_read_input_token_cost": 7e-08,
"input_cost_per_token": 1.7e-07,
"litellm_provider": "prism",
"max_input_tokens": 1000000,
"max_output_tokens": 384000,
"max_tokens": 384000,
"mode": "chat",
"output_cost_per_token": 2.1e-07,
"source": "https://prisminference.com/pricing",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses",
"/v1/messages"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": false
}
}

17
litellm/provider_endpoints_support_backup.json
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@ -1943,6 +1943,23 @@
"interactions": true
}
},
"prism": {
"display_name": "Prism (`prism`)",
"url": "https://docs.litellm.ai/docs/providers/prism",
"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
}
},
"recraft": {
"display_name": "Recraft (`recraft`)",
"url": "https://docs.litellm.ai/docs/providers/recraft",

28
litellm/proxy/public_endpoints/provider_create_fields.json
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@ -2855,6 +2855,34 @@
],
"default_model_placeholder": "gpt-3.5-turbo"
},
{
"provider": "PRISM",
"provider_display_name": "Prism",
"litellm_provider": "prism",
"credential_fields": [
{
"key": "api_base",
"label": "API Base",
"placeholder": "https://api.prisminference.com/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": "prism/deepseek-v4.1-flash"
},
{
"provider": "RECRAFT",
"provider_display_name": "Recraft",

1
litellm/types/utils.py
View file

@ -4139,6 +4139,7 @@ class LlmProviders(str, Enum):
PINSTRIPES = "pinstripes"
COGNITION = "cognition"
SCX_AI = "scx-ai"
PRISM = "prism"
DARKBLOOM = "darkbloom"
META = "meta"
SAIL = "sail"

50
model_prices_and_context_window.json
View file

@ -78485,5 +78485,55 @@
"thinking_always_on": true,
"prompt_cache_min_tokens": 512,
"source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing"
},
"prism/deepseek-v4.1-flash": {
"cache_read_input_token_cost": 7e-08,
"input_cost_per_token": 1.7e-07,
"litellm_provider": "prism",
"max_input_tokens": 1000000,
"max_output_tokens": 384000,
"max_tokens": 384000,
"mode": "chat",
"output_cost_per_token": 6.3e-07,
"source": "https://prisminference.com/pricing",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses",
"/v1/messages"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": true
},
"prism/deepseek-v4-flash": {
"cache_read_input_token_cost": 7e-08,
"input_cost_per_token": 1.7e-07,
"litellm_provider": "prism",
"max_input_tokens": 1000000,
"max_output_tokens": 384000,
"max_tokens": 384000,
"mode": "chat",
"output_cost_per_token": 2.1e-07,
"source": "https://prisminference.com/pricing",
"supported_endpoints": [
"/v1/chat/completions",
"/v1/responses",
"/v1/messages"
],
"supports_function_calling": true,
"supports_native_streaming": true,
"supports_parallel_function_calling": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_system_messages": true,
"supports_tool_choice": true,
"supports_vision": false
}
}

17
provider_endpoints_support.json
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@ -2195,6 +2195,23 @@
"interactions": true
}
},
"prism": {
"display_name": "Prism (`prism`)",
"url": "https://docs.litellm.ai/docs/providers/prism",
"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
}
},
"recraft": {
"display_name": "Recraft (`recraft`)",
"url": "https://docs.litellm.ai/docs/providers/recraft",

192
tests/unit/llms/openai_like/test_prism_provider.py Normal file
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@ -0,0 +1,192 @@
import json
from pathlib import Path
from typing import Final
import pytest
import respx
import litellm
from litellm.caching.llm_caching_handler import LLMClientCache
def test_prism_provider_resolution(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("PRISM_API_KEY", "prism-test-key")
model, provider, api_key, api_base = get_llm_provider(
model="prism/deepseek-v4-flash",
custom_llm_provider=None,
api_base=None,
api_key=None,
)
assert model == "deepseek-v4-flash"
assert provider == "prism"
assert api_key == "prism-test-key"
assert api_base == "https://api.prisminference.com/v1"
def test_prism_provider_keeps_explicit_credentials(monkeypatch: pytest.MonkeyPatch):
from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
monkeypatch.setenv("PRISM_API_KEY", "prism-env-key")
_, provider, api_key, api_base = get_llm_provider(
model="prism/deepseek-v4-flash",
custom_llm_provider=None,
api_base="https://prism.internal.example/v1",
api_key="prism-explicit-key",
)
assert provider == "prism"
assert api_key == "prism-explicit-key"
assert api_base == "https://prism.internal.example/v1"
PRISM_MODELS = tuple(sorted(name for name in litellm.model_cost if name.startswith("prism/")))
@pytest.mark.parametrize("model", PRISM_MODELS)
def test_prism_model_cost_and_capabilities(model: str):
from litellm.cost_calculator import cost_per_token
prompt_cost, completion_cost = cost_per_token(
model=model,
prompt_tokens=1_000_000,
completion_tokens=1_000_000,
custom_llm_provider="prism",
)
model_info = litellm.get_model_info(model)
assert prompt_cost == pytest.approx(model_info["input_cost_per_token"] * 1_000_000)
assert completion_cost == pytest.approx(model_info["output_cost_per_token"] * 1_000_000)
assert 0 < model_info["cache_read_input_token_cost"] < model_info["input_cost_per_token"]
assert model_info["output_cost_per_token"] > 0
assert model_info["max_tokens"] == model_info["max_output_tokens"] <= model_info["max_input_tokens"]
assert model_info["litellm_provider"] == "prism"
assert model_info["mode"] == "chat"
assert model_info["supports_function_calling"] is True
assert model_info["supports_native_streaming"] is True
assert model_info["supports_reasoning"] is True
assert model_info["supports_response_schema"] is True
assert litellm.supports_vision(model) is model_info["supports_vision"]
def test_prism_backup_registry_mirrors_cost_map():
package_root = Path(litellm.__file__).parent
cost_map = json.loads((package_root.parent / "model_prices_and_context_window.json").read_text())
backup = json.loads((package_root / "model_prices_and_context_window_backup.json").read_text())
prism_entries = {name: entry for name, entry in cost_map.items() if name.startswith("prism/")}
assert tuple(sorted(prism_entries)) == PRISM_MODELS
assert prism_entries
assert all("supports_vision" in entry for entry in prism_entries.values())
assert prism_entries == {name: backup[name] for name in prism_entries}
def test_prism_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())
prism = next(provider for provider in providers if provider["litellm_provider"] == "prism")
assert prism["provider"] == "PRISM"
assert prism["provider_display_name"] == "Prism"
assert prism["default_model_placeholder"] == "prism/deepseek-v4.1-flash"
assert {field["key"]: field["required"] for field in prism["credential_fields"]} == {
"api_base": False,
"api_key": True,
}
def test_prism_supported_endpoints():
matrix_path = Path(litellm.__file__).parent / "provider_endpoints_support_backup.json"
providers = json.loads(matrix_path.read_text())["providers"]
assert providers["prism"]["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,
}
def test_prism_responses_request():
with respx.mock() as upstream:
route: Final = upstream.post("https://api.prisminference.com/v1/responses").respond(
200,
json={
"id": "resp_prism",
"object": "response",
"created_at": 1_789_550_000,
"model": "deepseek-v4-flash",
"status": "completed",
"output": [
{
"id": "msg_prism",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [{"type": "output_text", "text": "Hello from Prism", "annotations": []}],
}
],
"usage": {"input_tokens": 4, "output_tokens": 3, "total_tokens": 7},
},
)
response: Final = litellm.responses(
model="prism/deepseek-v4-flash",
input="Say hello",
api_key="prism-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.prisminference.com/v1/responses"
assert request.headers["authorization"] == "Bearer prism-test-key"
assert body["model"] == "deepseek-v4-flash"
assert body["input"] == "Say hello"
assert response.output[0].content[0].text == "Hello from Prism"
@pytest.mark.asyncio
async def test_prism_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.prisminference.com/v1/messages").respond(
200,
json={
"id": "msg_prism",
"type": "message",
"role": "assistant",
"model": "deepseek-v4-flash",
"content": [{"type": "text", "text": "Hello from Prism"}],
"stop_reason": "end_turn",
"stop_sequence": None,
"usage": {"input_tokens": 4, "output_tokens": 3},
},
)
response: Final = await litellm.anthropic.messages.acreate(
model="prism/deepseek-v4-flash",
messages=[{"role": "user", "content": "Say hello"}],
max_tokens=32,
api_key="prism-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.prisminference.com/v1/messages"
assert request.headers["authorization"] == "Bearer prism-test-key"
assert request.headers["anthropic-version"] == "2023-06-01"
assert body["model"] == "deepseek-v4-flash"
assert body["messages"] == [{"role": "user", "content": "Say hello"}]
assert response["content"][0]["text"] == "Hello from Prism"