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amazon nova api fix

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This commit is contained in:
Ishaan Jaffer 2025-12-06 16:08:28 -08:00
parent 8af1be31eb
commit b4970f6033
10 changed files with 27 additions and 24 deletions
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14
docs/my-website/docs/providers/amazon_nova.md
View file

@ -6,7 +6,7 @@ import TabItem from '@theme/TabItem';
| Property | Details |
|-------|-------|
| Description | Amazon Nova is a family of foundation models built by Amazon that deliver frontier intelligence and industry-leading price performance. |
| Provider Route on LiteLLM | `amazon-nova/` |
| Provider Route on LiteLLM | `amazon_nova/` |
| Provider Doc | [Amazon Nova ↗](https://docs.aws.amazon.com/nova/latest/userguide/what-is-nova.html) |
| Supported OpenAI Endpoints | `/chat/completions`, `v1/responses` |
| Other Supported Endpoints | `v1/messages`, `/generateContent` |
@ -32,7 +32,7 @@ from litellm import completion
os.environ["AMAZON_NOVA_API_KEY"] = "your-api-key"
response = completion(
model="amazon-nova/nova-micro-v1",
model="amazon_nova/nova-micro-v1",
messages=[
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "Hello, how are you?"}
@ -51,7 +51,7 @@ print(response)
model_list:
- model_name: amazon-nova-micro
litellm_params:
model: amazon-nova/nova-micro-v1
model: amazon_nova/nova-micro-v1
api_key: os.environ/AMAZON_NOVA_API_KEY
```
### 2. Start the proxy
@ -82,7 +82,7 @@ curl --location 'http://0.0.0.0:4000/chat/completions' \
| Model Name | Usage | Context Window |
|------------|-------|----------------|
| Nova Micro | `completion(model="amazon-nova/nova-micro-v1", messages=messages)` | 128K tokens |
| Nova Micro | `completion(model="amazon_nova/nova-micro-v1", messages=messages)` | 128K tokens |
| Nova Lite | `completion(model="amazon-nova/nova-lite-v1", messages=messages)` | 300K tokens |
| Nova Pro | `completion(model="amazon-nova/nova-pro-v1", messages=messages)` | 300K tokens |
| Nova Premier | `completion(model="amazon-nova/nova-premier-v1", messages=messages)` | 1M tokens |
@ -99,7 +99,7 @@ from litellm import completion
os.environ["AMAZON_NOVA_API_KEY"] = "your-api-key"
response = completion(
model="amazon-nova/nova-micro-v1",
model="amazon_nova/nova-micro-v1",
messages=[
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "Tell me about machine learning"}
@ -164,7 +164,7 @@ tools = [
]
response = completion(
model="amazon-nova/nova-micro-v1",
model="amazon_nova/nova-micro-v1",
messages=[
{"role": "user", "content": "What's the weather like in San Francisco?"}
],
@ -246,7 +246,7 @@ print(response)
model_list:
- model_name: amazon-nova-pro
litellm_params:
model: amazon-nova/nova-pro-v1
model: amazon_nova/nova-pro-v1
temperature: 0.8
max_tokens: 500
top_p: 0.9

4
litellm/__init__.py
View file

@ -816,7 +816,7 @@ def add_known_models():
lemonade_models.add(key)
elif value.get("litellm_provider") == "docker_model_runner":
docker_model_runner_models.add(key)
elif value.get("litellm_provider") == "amazon-nova":
elif value.get("litellm_provider") == "amazon_nova":
amazon_nova_models.add(key)
@ -1019,7 +1019,7 @@ models_by_provider: dict = {
"ovhcloud": ovhcloud_models | ovhcloud_embedding_models,
"lemonade": lemonade_models,
"clarifai": clarifai_models,
"amazon-nova": amazon_nova_models,
"amazon_nova": amazon_nova_models,
}
# mapping for those models which have larger equivalents

2
litellm/constants.py
View file

@ -414,7 +414,7 @@ LITELLM_CHAT_PROVIDERS = [
"ovhcloud",
"lemonade",
"docker_model_runner",
"amazon-nova",
"amazon_nova",
]
LITELLM_EMBEDDING_PROVIDERS_SUPPORTING_INPUT_ARRAY_OF_TOKENS = [

4
litellm/litellm_core_utils/get_llm_provider_logic.py
View file

@ -404,8 +404,8 @@ def get_llm_provider( # noqa: PLR0915
custom_llm_provider = "lemonade"
elif model.startswith("clarifai/"):
custom_llm_provider = "clarifai"
elif model.startswith("amazon-nova"):
custom_llm_provider = "amazon-nova"
elif model.startswith("amazon_nova"):
custom_llm_provider = "amazon_nova"
if not custom_llm_provider:
if litellm.suppress_debug_info is False:
print() # noqa

2
litellm/llms/amazon_nova/chat/transformation.py
View file

@ -41,7 +41,7 @@ class AmazonNovaChatConfig(OpenAILikeChatConfig):
@property
def custom_llm_provider(self) -> Optional[str]:
return "amazon-nova"
return "amazon_nova"
@classmethod
def get_config(cls):

2
litellm/llms/amazon_nova/cost_calculation.py
View file

@ -17,5 +17,5 @@ def cost_per_token(model: str, usage: "Usage") -> Tuple[float, float]:
Follows the same logic as Anthropic's cost per token calculation.
"""
return generic_cost_per_token(
model=model, usage=usage, custom_llm_provider="amazon-nova"
model=model, usage=usage, custom_llm_provider="amazon_nova"
)

5
litellm/main.py
View file

@ -52,10 +52,13 @@ from pydantic import BaseModel
from typing_extensions import overload
import litellm
# client must be imported from litellm as it's a decorator used at function definition time
from litellm import client
# Other utils are imported directly to avoid circular imports
from litellm.utils import exception_type, get_litellm_params, get_optional_params
# Logging is imported lazily when needed to avoid loading litellm_logging at import time
if TYPE_CHECKING:
from litellm.litellm_core_utils.litellm_logging import Logging
@ -2662,7 +2665,7 @@ def completion( # type: ignore # noqa: PLR0915
)
response = model_response
elif custom_llm_provider == "amazon-nova":
elif custom_llm_provider == "amazon_nova":
api_key = (
api_key
or litellm.amazon_nova_api_key

8
litellm/model_prices_and_context_window_backup.json
View file

@ -16957,7 +16957,7 @@
},
"amazon-nova/nova-micro-v1": {
"input_cost_per_token": 3.5e-08,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 128000,
"max_output_tokens": 10000,
"max_tokens": 10000,
@ -16969,7 +16969,7 @@
},
"amazon-nova/nova-lite-v1": {
"input_cost_per_token": 6e-08,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 300000,
"max_output_tokens": 10000,
"max_tokens": 10000,
@ -16983,7 +16983,7 @@
},
"amazon-nova/nova-premier-v1": {
"input_cost_per_token": 2.5e-06,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 1000000,
"max_output_tokens": 10000,
"max_tokens": 10000,
@ -16997,7 +16997,7 @@
},
"amazon-nova/nova-pro-v1": {
"input_cost_per_token": 8e-07,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 300000,
"max_output_tokens": 10000,
"max_tokens": 10000,

2
litellm/types/utils.py
View file

@ -3002,7 +3002,7 @@ class LlmProviders(str, Enum):
WANDB = "wandb"
OVHCLOUD = "ovhcloud"
LEMONADE = "lemonade"
AMAZON_NOVA = "amazon-nova"
AMAZON_NOVA = "amazon_nova"
A2A_AGENT = "a2a_agent"

8
model_prices_and_context_window.json
View file

@ -16957,7 +16957,7 @@
},
"amazon-nova/nova-micro-v1": {
"input_cost_per_token": 3.5e-08,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 128000,
"max_output_tokens": 10000,
"max_tokens": 10000,
@ -16969,7 +16969,7 @@
},
"amazon-nova/nova-lite-v1": {
"input_cost_per_token": 6e-08,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 300000,
"max_output_tokens": 10000,
"max_tokens": 10000,
@ -16983,7 +16983,7 @@
},
"amazon-nova/nova-premier-v1": {
"input_cost_per_token": 2.5e-06,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 1000000,
"max_output_tokens": 10000,
"max_tokens": 10000,
@ -16997,7 +16997,7 @@
},
"amazon-nova/nova-pro-v1": {
"input_cost_per_token": 8e-07,
"litellm_provider": "amazon-nova",
"litellm_provider": "amazon_nova",
"max_input_tokens": 300000,
"max_output_tokens": 10000,
"max_tokens": 10000,