diff --git a/deploy/charts/litellm-helm/templates/deployment.yaml b/deploy/charts/litellm-helm/templates/deployment.yaml index ab41e6cb5..06b933a6c 100644 --- a/deploy/charts/litellm-helm/templates/deployment.yaml +++ b/deploy/charts/litellm-helm/templates/deployment.yaml @@ -102,7 +102,7 @@ spec: imagePullPolicy: {{ .Values.image.pullPolicy }} env: - name: HOST - value: "0.0.0.0" + value: "::" - name: PORT value: {{ .Values.service.port | quote}} {{- if .Values.db.deployStandalone }} diff --git a/docs/my-website/docs/providers/vertex.md b/docs/my-website/docs/providers/vertex.md index 697aa0701..582636630 100644 --- a/docs/my-website/docs/providers/vertex.md +++ b/docs/my-website/docs/providers/vertex.md @@ -1768,7 +1768,7 @@ LiteLLM supports calling [Vertex AI Text to Speech API](https://console.cloud.go -Usage +### Usage - Basic @@ -1841,6 +1841,150 @@ print("response from proxy", response) +### Usage - `ssml` as input + +Pass your `ssml` as input to the `input` param, if it contains ``, it will be automatically detected and passed as `ssml` to the Vertex AI API + +If you need to force your `input` to be passed as `ssml`, set `use_ssml=True` + + + + +Vertex AI does not support passing a `model` param - so passing `model=vertex_ai/` is the only required param + + +```python +speech_file_path = Path(__file__).parent / "speech_vertex.mp3" + + +ssml = """ + +

Hello, world!

+

This is a test of the text-to-speech API.

+ +""" + +response = litellm.speech( + input=ssml, + model="vertex_ai/test", + voice={ + "languageCode": "en-UK", + "name": "en-UK-Studio-O", + }, + audioConfig={ + "audioEncoding": "LINEAR22", + "speakingRate": "10", + }, +) +response.stream_to_file(speech_file_path) +``` + + + + + +```python +import openai + +client = openai.OpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000") + +ssml = """ + +

Hello, world!

+

This is a test of the text-to-speech API.

+ +""" + +# see supported values for "voice" on vertex here: +# https://console.cloud.google.com/vertex-ai/generative/speech/text-to-speech +response = client.audio.speech.create( + model = "vertex-tts", + input=ssml, + voice={'languageCode': 'en-US', 'name': 'en-US-Studio-O'}, +) +print("response from proxy", response) +``` + + + + + +### Forcing SSML Usage + +You can force the use of SSML by setting the `use_ssml` parameter to `True`. This is useful when you want to ensure that your input is treated as SSML, even if it doesn't contain the `` tags. + +Here are examples of how to force SSML usage: + + + + + +Vertex AI does not support passing a `model` param - so passing `model=vertex_ai/` is the only required param + + +```python +speech_file_path = Path(__file__).parent / "speech_vertex.mp3" + + +ssml = """ + +

Hello, world!

+

This is a test of the text-to-speech API.

+ +""" + +response = litellm.speech( + input=ssml, + use_ssml=True, + model="vertex_ai/test", + voice={ + "languageCode": "en-UK", + "name": "en-UK-Studio-O", + }, + audioConfig={ + "audioEncoding": "LINEAR22", + "speakingRate": "10", + }, +) +response.stream_to_file(speech_file_path) +``` + + + + + +```python +import openai + +client = openai.OpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000") + +ssml = """ + +

Hello, world!

+

This is a test of the text-to-speech API.

+ +""" + +# see supported values for "voice" on vertex here: +# https://console.cloud.google.com/vertex-ai/generative/speech/text-to-speech +response = client.audio.speech.create( + model = "vertex-tts", + input=ssml, # pass as None since OpenAI SDK requires this param + voice={'languageCode': 'en-US', 'name': 'en-US-Studio-O'}, + extra_body={"use_ssml": True}, +) +print("response from proxy", response) +``` + + + + + + + + + + ## Extra ### Using `GOOGLE_APPLICATION_CREDENTIALS` diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index b6f94bb46..642a776b6 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -349,19 +349,23 @@ class PrometheusLogger(CustomLogger): # latency metrics total_time: timedelta = kwargs.get("end_time") - kwargs.get("start_time") total_time_seconds = total_time.total_seconds() - api_call_total_time: timedelta = kwargs.get("end_time") - kwargs.get( - "api_call_start_time" - ) + api_call_start_time = kwargs.get("api_call_start_time", None) - api_call_total_time_seconds = api_call_total_time.total_seconds() + if api_call_start_time is not None and isinstance( + api_call_start_time, datetime + ): + api_call_total_time: timedelta = ( + kwargs.get("end_time") - api_call_start_time + ) + api_call_total_time_seconds = api_call_total_time.total_seconds() + self.litellm_llm_api_latency_metric.labels(model).observe( + api_call_total_time_seconds + ) # log metrics self.litellm_request_total_latency_metric.labels(model).observe( total_time_seconds ) - self.litellm_llm_api_latency_metric.labels(model).observe( - api_call_total_time_seconds - ) # set x-ratelimit headers if premium_user is True: diff --git a/litellm/llms/text_to_speech/vertex_ai.py b/litellm/llms/text_to_speech/vertex_ai.py index 0aac32eb5..99ebfae1e 100644 --- a/litellm/llms/text_to_speech/vertex_ai.py +++ b/litellm/llms/text_to_speech/vertex_ai.py @@ -19,7 +19,8 @@ from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_stu class VertexInput(TypedDict, total=False): - text: str + text: Optional[str] + ssml: Optional[str] class VertexVoice(TypedDict, total=False): @@ -86,10 +87,13 @@ class VertexTextToSpeechAPI(VertexLLM): ####### Build the request ################ # API Ref: https://cloud.google.com/text-to-speech/docs/reference/rest/v1/text/synthesize - vertex_input = VertexInput(text=input) - # required param - optional_params = optional_params or {} kwargs = kwargs or {} + optional_params = optional_params or {} + + vertex_input = VertexInput(text=input) + validate_vertex_input(vertex_input, kwargs, optional_params) + + # required param if voice is not None: vertex_voice = VertexVoice(**voice) elif "voice" in kwargs: @@ -203,3 +207,34 @@ class VertexTextToSpeechAPI(VertexLLM): # Initialize the HttpxBinaryResponseContent instance http_binary_response = HttpxBinaryResponseContent(response) return http_binary_response + + +def validate_vertex_input( + input_data: VertexInput, kwargs: dict, optional_params: dict +) -> None: + # Remove None values + if input_data.get("text") is None: + input_data.pop("text", None) + if input_data.get("ssml") is None: + input_data.pop("ssml", None) + + # Check if use_ssml is set + use_ssml = kwargs.get("use_ssml", optional_params.get("use_ssml", False)) + + if use_ssml: + if "text" in input_data: + input_data["ssml"] = input_data.pop("text") + elif "ssml" not in input_data: + raise ValueError("SSML input is required when use_ssml is True.") + else: + # LiteLLM will auto-detect if text is in ssml format + # check if "text" is an ssml - in this case we should pass it as ssml instead of text + if input_data: + _text = input_data.get("text", None) or "" + if "" in _text: + input_data["ssml"] = input_data.pop("text") + + if not input_data: + raise ValueError("Either 'text' or 'ssml' must be provided.") + if "text" in input_data and "ssml" in input_data: + raise ValueError("Only one of 'text' or 'ssml' should be provided, not both.") diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index df996dac0..ef032db96 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1988,17 +1988,33 @@ "supports_vision": true, "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" }, - "gemini-experimental": { + "gemini-pro-experimental": { "max_tokens": 8192, "max_input_tokens": 1000000, "max_output_tokens": 8192, "input_cost_per_token": 0, "output_cost_per_token": 0, + "input_cost_per_character": 0, + "output_cost_per_character": 0, "litellm_provider": "vertex_ai-language-models", "mode": "chat", "supports_function_calling": false, "supports_tool_choice": true, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/gemini-experimental" + }, + "gemini-pro-flash": { + "max_tokens": 8192, + "max_input_tokens": 1000000, + "max_output_tokens": 8192, + "input_cost_per_token": 0, + "output_cost_per_token": 0, + "input_cost_per_character": 0, + "output_cost_per_character": 0, + "litellm_provider": "vertex_ai-language-models", + "mode": "chat", + "supports_function_calling": false, + "supports_tool_choice": true, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/gemini-experimental" }, "gemini-pro-vision": { "max_tokens": 2048, diff --git a/litellm/proxy/_experimental/out/404.html b/litellm/proxy/_experimental/out/404.html new file mode 100644 index 000000000..0f6c985e6 --- /dev/null +++ b/litellm/proxy/_experimental/out/404.html @@ -0,0 +1 @@ +404: This page could not be found.LiteLLM Dashboard

404

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e4609ce75..d68398350 100644 --- a/litellm/proxy/_new_secret_config.yaml +++ b/litellm/proxy/_new_secret_config.yaml @@ -1,19 +1,9 @@ model_list: - model_name: fake-openai-endpoint litellm_params: - model: gpt-3.5-turbo - # model: sagemaker/jumpstart-dft-hf-textgeneration1-mp-20240815-185614 - # sagemaker_base_url: https://exampleopenaiendpoint-production.up.railway.app/invocations/ - # api_base: https://exampleopenaiendpoint-production.up.railway.app - input_cost_per_token: 10 - output_cost_per_token: 10 - -litellm_settings: - max_internal_user_budget: 0.00001 - internal_user_budget_duration: "3s" # reset every 3seconds - -general_settings: - proxy_budget_rescheduler_min_time: 1 - proxy_budget_rescheduler_max_time: 2 + model: openai/my-fake-model + api_key: my-fake-key + api_base: https://exampleopenaiendpoint-production.up.railway.app/ + diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 0f1452651..6b4be7261 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -40,6 +40,22 @@ else: all_routes = LiteLLMRoutes.openai_routes.value + LiteLLMRoutes.management_routes.value +def is_request_body_safe(request_body: dict) -> bool: + """ + Check if the request body is safe. + + A malicious user can set the api_base to their own domain and invoke POST /chat/completions to intercept and steal the OpenAI API key. + Relevant issue: https://huntr.com/bounties/4001e1a2-7b7a-4776-a3ae-e6692ec3d997 + """ + banned_params = ["api_base", "base_url"] + + for param in banned_params: + if param in request_body: + raise ValueError(f"BadRequest: {param} is not allowed in request body") + + return True + + def common_checks( request_body: dict, team_object: Optional[LiteLLM_TeamTable], @@ -60,6 +76,7 @@ def common_checks( 6. [OPTIONAL] If 'enforce_end_user' enabled - did developer pass in 'user' param for openai endpoints 7. [OPTIONAL] If 'litellm.max_budget' is set (>0), is proxy under budget 8. [OPTIONAL] If guardrails modified - is request allowed to change this + 9. Check if request body is safe """ _model = request_body.get("model", None) if team_object is not None and team_object.blocked is True: diff --git a/litellm/proxy/auth/oauth2_proxy_hook.py b/litellm/proxy/auth/oauth2_proxy_hook.py new file mode 100644 index 000000000..a1db5d842 --- /dev/null +++ b/litellm/proxy/auth/oauth2_proxy_hook.py @@ -0,0 +1,45 @@ +from typing import Any, Dict + +from fastapi import Request + +from litellm._logging import verbose_proxy_logger +from litellm.proxy._types import UserAPIKeyAuth + + +async def handle_oauth2_proxy_request(request: Request) -> UserAPIKeyAuth: + """ + Handle request from oauth2 proxy. + """ + from litellm.proxy.proxy_server import general_settings + + verbose_proxy_logger.debug("Handling oauth2 proxy request") + # Define the OAuth2 config mappings + oauth2_config_mappings: Dict[str, str] = general_settings.get( + "oauth2_config_mappings", None + ) + verbose_proxy_logger.debug(f"Oauth2 config mappings: {oauth2_config_mappings}") + + if not oauth2_config_mappings: + raise ValueError("Oauth2 config mappings not found in general_settings") + # Initialize a dictionary to store the mapped values + auth_data: Dict[str, Any] = {} + + # Extract values from headers based on the mappings + for key, header in oauth2_config_mappings.items(): + value = request.headers.get(header) + if value: + # Convert max_budget to float if present + if key == "max_budget": + auth_data[key] = float(value) + # Convert models to list if present + elif key == "models": + auth_data[key] = [model.strip() for model in value.split(",")] + else: + auth_data[key] = value + verbose_proxy_logger.debug( + f"Auth data before creating UserAPIKeyAuth object: {auth_data}" + ) + user_api_key_auth = UserAPIKeyAuth(**auth_data) + verbose_proxy_logger.debug(f"UserAPIKeyAuth object created: {user_api_key_auth}") + # Create and return UserAPIKeyAuth object + return user_api_key_auth diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 9623267ee..433480bc4 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -54,6 +54,7 @@ from litellm.proxy.auth.auth_checks import ( get_org_object, get_team_object, get_user_object, + is_request_body_safe, log_to_opentelemetry, ) from litellm.proxy.auth.auth_utils import ( @@ -63,6 +64,7 @@ from litellm.proxy.auth.auth_utils import ( route_in_additonal_public_routes, ) from litellm.proxy.auth.oauth2_check import check_oauth2_token +from litellm.proxy.auth.oauth2_proxy_hook import handle_oauth2_proxy_request from litellm.proxy.common_utils.http_parsing_utils import _read_request_body from litellm.proxy.utils import _to_ns @@ -122,6 +124,9 @@ async def user_api_key_auth( try: route: str = get_request_route(request=request) + # get the request body + request_data = await _read_request_body(request=request) + is_request_body_safe(request_body=request_data) ### LiteLLM Enterprise Security Checks # Check 1. Check if request size is under max_request_size_mb @@ -213,6 +218,9 @@ async def user_api_key_auth( return await check_oauth2_token(token=api_key) + if general_settings.get("enable_oauth2_proxy_auth", False) is True: + return await handle_oauth2_proxy_request(request=request) + if general_settings.get("enable_jwt_auth", False) is True: is_jwt = jwt_handler.is_jwt(token=api_key) verbose_proxy_logger.debug("is_jwt: %s", is_jwt) @@ -353,9 +361,6 @@ async def user_api_key_auth( user_info=user_info, ) ) - # get the request body - request_data = await _read_request_body(request=request) - # run through common checks _ = common_checks( request_body=request_data, @@ -448,7 +453,6 @@ async def user_api_key_auth( ) ## Check END-USER OBJECT - request_data = await _read_request_body(request=request) _end_user_object = None end_user_params = {} if "user" in request_data: diff --git a/litellm/proxy/proxy_config.yaml b/litellm/proxy/proxy_config.yaml index 536f6e2e5..ac17a1d84 100644 --- a/litellm/proxy/proxy_config.yaml +++ b/litellm/proxy/proxy_config.yaml @@ -13,6 +13,15 @@ model_list: model: cohere/rerank-english-v3.0 api_key: os.environ/COHERE_API_KEY +general_settings: + enable_oauth2_proxy_auth: True + oauth2_config_mappings: + token: X-Auth-Token + user_id: X-Auth-Client-ID + team_id: X-Auth-Team-ID + max_budget: X-Auth-Max-Budget + models: X-Auth-Allowed-Models + # default off mode litellm_settings: set_verbose: True \ No newline at end of file diff --git a/litellm/router.py b/litellm/router.py index bc23972b6..37ca435d7 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -92,6 +92,7 @@ from litellm.types.router import ( RouterErrors, RouterGeneralSettings, RouterRateLimitError, + RouterRateLimitErrorBasic, updateDeployment, updateLiteLLMParams, ) @@ -4459,16 +4460,8 @@ class Router: """ if _rate_limit_error is True: # allow generic fallback logic to take place - model_ids = self.get_model_ids(model_name=model) - cooldown_time = self.cooldown_cache.get_min_cooldown( - model_ids=model_ids - ) - cooldown_list = self._get_cooldown_deployments() - raise RouterRateLimitError( + raise RouterRateLimitErrorBasic( model=model, - cooldown_time=cooldown_time, - enable_pre_call_checks=True, - cooldown_list=cooldown_list, ) elif _context_window_error is True: @@ -4579,14 +4572,10 @@ class Router: litellm.print_verbose(f"initial list of deployments: {healthy_deployments}") if len(healthy_deployments) == 0: - model_ids = self.get_model_ids(model_name=model) - _cooldown_time = self.cooldown_cache.get_min_cooldown(model_ids=model_ids) - _cooldown_list = self._get_cooldown_deployments() - raise RouterRateLimitError( - model=model, - cooldown_time=_cooldown_time, - enable_pre_call_checks=self.enable_pre_call_checks, - cooldown_list=_cooldown_list, + raise ValueError( + "{}. You passed in model={}. There is no 'model_name' with this string ".format( + RouterErrors.no_deployments_available.value, model + ) ) if litellm.model_alias_map and model in litellm.model_alias_map: diff --git a/litellm/tests/test_amazing_vertex_completion.py b/litellm/tests/test_amazing_vertex_completion.py index de1f1007d..4c5c3dc8e 100644 --- a/litellm/tests/test_amazing_vertex_completion.py +++ b/litellm/tests/test_amazing_vertex_completion.py @@ -50,8 +50,9 @@ VERTEX_MODELS_TO_NOT_TEST = [ "text-bison@001", "gemini-1.5-pro", "gemini-1.5-pro-preview-0215", - "gemini-pro-flash", "gemini-pro-experimental", + "gemini-flash-experimental", + "gemini-pro-flash", ] diff --git a/litellm/tests/test_assistants.py b/litellm/tests/test_assistants.py index 787c38335..c376eecc2 100644 --- a/litellm/tests/test_assistants.py +++ b/litellm/tests/test_assistants.py @@ -214,6 +214,7 @@ async def test_add_message_litellm(sync_mode, provider): [True, False], ) # @pytest.mark.asyncio +@pytest.mark.flaky(retries=3, delay=1) async def test_aarun_thread_litellm(sync_mode, provider, is_streaming): """ - Get Assistants diff --git a/litellm/tests/test_audio_speech.py b/litellm/tests/test_audio_speech.py index 5de996fa1..2c710d37e 100644 --- a/litellm/tests/test_audio_speech.py +++ b/litellm/tests/test_audio_speech.py @@ -243,3 +243,61 @@ async def test_speech_litellm_vertex_async_with_voice(): "voice": {"languageCode": "en-UK", "name": "en-UK-Studio-O"}, "audioConfig": {"audioEncoding": "LINEAR22", "speakingRate": "10"}, } + + +@pytest.mark.asyncio +async def test_speech_litellm_vertex_async_with_voice_ssml(): + # Mock the response + mock_response = AsyncMock() + + def return_val(): + return { + "audioContent": "dGVzdCByZXNwb25zZQ==", + } + + mock_response.json = return_val + mock_response.status_code = 200 + + ssml = """ + +

Hello, world!

+

This is a test of the text-to-speech API.

+ + """ + + # Set up the mock for asynchronous calls + with patch( + "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post", + new_callable=AsyncMock, + ) as mock_async_post: + mock_async_post.return_value = mock_response + model = "vertex_ai/test" + + response = await litellm.aspeech( + input=ssml, + model=model, + voice={ + "languageCode": "en-UK", + "name": "en-UK-Studio-O", + }, + audioConfig={ + "audioEncoding": "LINEAR22", + "speakingRate": "10", + }, + ) + + # Assert asynchronous call + mock_async_post.assert_called_once() + _, kwargs = mock_async_post.call_args + print("call args", kwargs) + + assert kwargs["url"] == "https://texttospeech.googleapis.com/v1/text:synthesize" + + assert "x-goog-user-project" in kwargs["headers"] + assert kwargs["headers"]["Authorization"] is not None + + assert kwargs["json"] == { + "input": {"ssml": ssml}, + "voice": {"languageCode": "en-UK", "name": "en-UK-Studio-O"}, + "audioConfig": {"audioEncoding": "LINEAR22", "speakingRate": "10"}, + } diff --git a/litellm/tests/test_dynamic_rate_limit_handler.py b/litellm/tests/test_dynamic_rate_limit_handler.py index bc50fc16f..f49a760af 100644 --- a/litellm/tests/test_dynamic_rate_limit_handler.py +++ b/litellm/tests/test_dynamic_rate_limit_handler.py @@ -120,6 +120,7 @@ async def test_available_tpm(num_projects, dynamic_rate_limit_handler): @pytest.mark.parametrize("num_projects", [1, 2, 100]) @pytest.mark.asyncio +@pytest.mark.flaky(retries=3, delay=1) async def test_available_rpm(num_projects, dynamic_rate_limit_handler): model = "my-fake-model" ## SET CACHE W/ ACTIVE PROJECTS diff --git a/litellm/tests/test_openai_batches_and_files.py b/litellm/tests/test_openai_batches_and_files.py index d55d868b3..7f79da8e2 100644 --- a/litellm/tests/test_openai_batches_and_files.py +++ b/litellm/tests/test_openai_batches_and_files.py @@ -114,7 +114,7 @@ async def test_async_create_batch(provider): ) print("Response from creating file=", file_obj) - await asyncio.sleep(5) + await asyncio.sleep(10) batch_input_file_id = file_obj.id assert ( batch_input_file_id is not None diff --git a/litellm/tests/test_user_api_key_auth.py b/litellm/tests/test_user_api_key_auth.py index e0595ac13..5a292bb4a 100644 --- a/litellm/tests/test_user_api_key_auth.py +++ b/litellm/tests/test_user_api_key_auth.py @@ -11,8 +11,10 @@ from typing import Dict, List, Optional from unittest.mock import MagicMock import pytest +from starlette.datastructures import URL import litellm +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth class Request: @@ -209,3 +211,38 @@ async def test_user_personal_budgets(key_ownership): except Exception: if key_ownership == "team_key": pytest.fail("Expected this call to work. Key is below team budget.") + + +@pytest.mark.asyncio +@pytest.mark.parametrize("prohibited_param", ["api_base", "base_url"]) +async def test_user_api_key_auth_fails_with_prohibited_params(prohibited_param): + """ + Relevant issue: https://huntr.com/bounties/4001e1a2-7b7a-4776-a3ae-e6692ec3d997 + """ + import json + + from fastapi import Request + + # Setup + user_key = "sk-1234" + + setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") + + # Create request with prohibited parameter in body + request = Request(scope={"type": "http"}) + request._url = URL(url="/chat/completions") + + async def return_body(): + body = {prohibited_param: "https://custom-api.com"} + return bytes(json.dumps(body), "utf-8") + + request.body = return_body + try: + response = await user_api_key_auth( + request=request, api_key="Bearer " + user_key + ) + except Exception as e: + print("error str=", str(e)) + error_message = str(e.message) + print("error message=", error_message) + assert "is not allowed in request body" in error_message diff --git a/litellm/types/router.py b/litellm/types/router.py index e38fec075..b05e9be4a 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -551,6 +551,20 @@ class RouterGeneralSettings(BaseModel): ) # if passed a model not llm_router model list, pass through the request to litellm.acompletion/embedding +class RouterRateLimitErrorBasic(ValueError): + """ + Raise a basic error inside helper functions. + """ + + def __init__( + self, + model: str, + ): + self.model = model + _message = f"{RouterErrors.no_deployments_available.value}." + super().__init__(_message) + + class RouterRateLimitError(ValueError): def __init__( self, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index df996dac0..ef032db96 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1988,17 +1988,33 @@ "supports_vision": true, "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" }, - "gemini-experimental": { + "gemini-pro-experimental": { "max_tokens": 8192, "max_input_tokens": 1000000, "max_output_tokens": 8192, "input_cost_per_token": 0, "output_cost_per_token": 0, + "input_cost_per_character": 0, + "output_cost_per_character": 0, "litellm_provider": "vertex_ai-language-models", "mode": "chat", "supports_function_calling": false, "supports_tool_choice": true, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/gemini-experimental" + }, + "gemini-pro-flash": { + "max_tokens": 8192, + "max_input_tokens": 1000000, + "max_output_tokens": 8192, + "input_cost_per_token": 0, + "output_cost_per_token": 0, + "input_cost_per_character": 0, + "output_cost_per_character": 0, + "litellm_provider": "vertex_ai-language-models", + "mode": "chat", + "supports_function_calling": false, + "supports_tool_choice": true, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/gemini-experimental" }, "gemini-pro-vision": { "max_tokens": 2048, diff --git a/pyproject.toml b/pyproject.toml index 2b4f21f1a..3708bc79b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm" -version = "1.44.8" +version = "1.44.9" description = "Library to easily interface with LLM API providers" authors = ["BerriAI"] license = "MIT" @@ -91,7 +91,7 @@ requires = ["poetry-core", "wheel"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "1.44.8" +version = "1.44.9" version_files = [ "pyproject.toml:^version" ] diff --git a/ui/litellm-dashboard/out/404.html b/ui/litellm-dashboard/out/404.html index 1939ceec4..0f6c985e6 100644 --- a/ui/litellm-dashboard/out/404.html +++ b/ui/litellm-dashboard/out/404.html @@ -1 +1 @@ -404: This page could not be found.LiteLLM Dashboard

404

This page could not be found.

\ No newline at end of file +404: This page could not be found.LiteLLM Dashboard

404

This page could not be found.

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b/ui/litellm-dashboard/src/components/view_key_table.tsx index 019a11179..d54fb1386 100644 --- a/ui/litellm-dashboard/src/components/view_key_table.tsx +++ b/ui/litellm-dashboard/src/components/view_key_table.tsx @@ -33,6 +33,7 @@ import { InputNumber, message, Select, + Tooltip } from "antd"; import { CopyToClipboard } from "react-copy-to-clipboard"; @@ -87,6 +88,8 @@ interface ItemData { metadata: any; user_id: string | null; expires: any; + budget_duration: string | null; + budget_reset_at: string | null; // Add any other properties that exist in the item data } @@ -223,7 +226,7 @@ const ViewKeyTable: React.FC = ({
= ({ > + + + + + = ({ @@ -536,7 +556,30 @@ const ViewKeyTable: React.FC = ({ } } - setSelectedToken(token); + // Convert the budget_duration to the corresponding select option + let budgetDuration = null; + if (token.budget_duration) { + switch (token.budget_duration) { + case "24h": + budgetDuration = "daily"; + break; + case "7d": + budgetDuration = "weekly"; + break; + case "30d": + budgetDuration = "monthly"; + break; + default: + budgetDuration = "None"; + } + } + + setSelectedToken({ + ...token, + budget_duration: budgetDuration + }); + + //setSelectedToken(token); setEditModalVisible(true); }; @@ -558,6 +601,21 @@ const ViewKeyTable: React.FC = ({ const currentKey = formValues.token; formValues.key = currentKey; + // Convert the budget_duration back to the API expected format + if (formValues.budget_duration) { + switch (formValues.budget_duration) { + case "daily": + formValues.budget_duration = "24h"; + break; + case "weekly": + formValues.budget_duration = "7d"; + break; + case "monthly": + formValues.budget_duration = "30d"; + break; + } + } + console.log("handleEditSubmit:", formValues); let newKeyValues = await keyUpdateCall(accessToken, formValues); @@ -666,6 +724,7 @@ const ViewKeyTable: React.FC = ({ Secret Key Spend (USD) Budget (USD) + Budget Reset Models Rate Limits Rate Limits per model @@ -722,6 +781,17 @@ const ViewKeyTable: React.FC = ({ Unlimited )} + + {item.budget_reset_at != null ? ( +
+

{new Date(item.budget_reset_at).toLocaleString()}

+ +
+ + ) : ( +

Never

+ )} + {/* = ({ - + = ({

{selectedToken.max_budget != null ? ( - <>{selectedToken.max_budget} + <> + {selectedToken.max_budget} + {selectedToken.budget_duration && ( + <> +
+ Budget will be reset at {selectedToken.budget_reset_at ? new Date(selectedToken.budget_reset_at).toLocaleString() : 'Never'} + + )} + ) : ( <>Unlimited )}