forked from phoenix/litellm-mirror
Merge branch 'main' into litellm_main_staging
This commit is contained in:
Krish Dholakia
GitHub
commit
a857f4a8ee
45 changed files with 541 additions and 79 deletions
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@ -102,7 +102,7 @@ spec:
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imagePullPolicy: {{ .Values.image.pullPolicy }}
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env:
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- name: HOST
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value: "0.0.0.0"
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value: "::"
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- name: PORT
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value: {{ .Values.service.port | quote}}
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{{- if .Values.db.deployStandalone }}
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@ -1768,7 +1768,7 @@ LiteLLM supports calling [Vertex AI Text to Speech API](https://console.cloud.go
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Usage
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### Usage - Basic
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<Tabs>
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<TabItem value="sdk" label="SDK">
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@ -1841,6 +1841,150 @@ print("response from proxy", response)
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</Tabs>
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### Usage - `ssml` as input
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Pass your `ssml` as input to the `input` param, if it contains `<speak>`, it will be automatically detected and passed as `ssml` to the Vertex AI API
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If you need to force your `input` to be passed as `ssml`, set `use_ssml=True`
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<Tabs>
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<TabItem value="sdk" label="SDK">
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Vertex AI does not support passing a `model` param - so passing `model=vertex_ai/` is the only required param
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```python
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speech_file_path = Path(__file__).parent / "speech_vertex.mp3"
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ssml = """
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<speak>
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<p>Hello, world!</p>
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<p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
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</speak>
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"""
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response = litellm.speech(
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input=ssml,
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model="vertex_ai/test",
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voice={
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"languageCode": "en-UK",
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"name": "en-UK-Studio-O",
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},
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audioConfig={
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"audioEncoding": "LINEAR22",
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"speakingRate": "10",
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},
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)
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response.stream_to_file(speech_file_path)
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```
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</TabItem>
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<TabItem value="proxy" label="LiteLLM PROXY (Unified Endpoint)">
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```python
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import openai
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client = openai.OpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000")
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ssml = """
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<speak>
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<p>Hello, world!</p>
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<p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
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</speak>
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"""
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# see supported values for "voice" on vertex here:
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# https://console.cloud.google.com/vertex-ai/generative/speech/text-to-speech
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response = client.audio.speech.create(
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model = "vertex-tts",
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input=ssml,
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voice={'languageCode': 'en-US', 'name': 'en-US-Studio-O'},
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)
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print("response from proxy", response)
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```
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</TabItem>
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</Tabs>
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### Forcing SSML Usage
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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 `<speak>` tags.
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Here are examples of how to force SSML usage:
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<Tabs>
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<TabItem value="sdk" label="SDK">
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Vertex AI does not support passing a `model` param - so passing `model=vertex_ai/` is the only required param
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```python
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speech_file_path = Path(__file__).parent / "speech_vertex.mp3"
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ssml = """
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<speak>
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<p>Hello, world!</p>
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<p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
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</speak>
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"""
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response = litellm.speech(
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input=ssml,
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use_ssml=True,
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model="vertex_ai/test",
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voice={
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"languageCode": "en-UK",
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"name": "en-UK-Studio-O",
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},
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audioConfig={
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"audioEncoding": "LINEAR22",
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"speakingRate": "10",
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},
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)
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response.stream_to_file(speech_file_path)
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```
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</TabItem>
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<TabItem value="proxy" label="LiteLLM PROXY (Unified Endpoint)">
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```python
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import openai
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client = openai.OpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000")
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ssml = """
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<speak>
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<p>Hello, world!</p>
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<p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
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</speak>
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"""
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# see supported values for "voice" on vertex here:
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# https://console.cloud.google.com/vertex-ai/generative/speech/text-to-speech
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response = client.audio.speech.create(
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model = "vertex-tts",
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input=ssml, # pass as None since OpenAI SDK requires this param
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voice={'languageCode': 'en-US', 'name': 'en-US-Studio-O'},
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extra_body={"use_ssml": True},
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)
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print("response from proxy", response)
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```
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</TabItem>
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</Tabs>
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## Extra
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### Using `GOOGLE_APPLICATION_CREDENTIALS`
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@ -349,19 +349,23 @@ class PrometheusLogger(CustomLogger):
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# latency metrics
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total_time: timedelta = kwargs.get("end_time") - kwargs.get("start_time")
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total_time_seconds = total_time.total_seconds()
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api_call_total_time: timedelta = kwargs.get("end_time") - kwargs.get(
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"api_call_start_time"
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)
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api_call_start_time = kwargs.get("api_call_start_time", None)
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if api_call_start_time is not None and isinstance(
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api_call_start_time, datetime
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):
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api_call_total_time: timedelta = (
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kwargs.get("end_time") - api_call_start_time
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)
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api_call_total_time_seconds = api_call_total_time.total_seconds()
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self.litellm_llm_api_latency_metric.labels(model).observe(
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api_call_total_time_seconds
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)
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# log metrics
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self.litellm_request_total_latency_metric.labels(model).observe(
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total_time_seconds
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)
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self.litellm_llm_api_latency_metric.labels(model).observe(
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api_call_total_time_seconds
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)
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# set x-ratelimit headers
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if premium_user is True:
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@ -19,7 +19,8 @@ from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_stu
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class VertexInput(TypedDict, total=False):
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text: str
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text: Optional[str]
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ssml: Optional[str]
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class VertexVoice(TypedDict, total=False):
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@ -86,10 +87,13 @@ class VertexTextToSpeechAPI(VertexLLM):
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####### Build the request ################
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# API Ref: https://cloud.google.com/text-to-speech/docs/reference/rest/v1/text/synthesize
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vertex_input = VertexInput(text=input)
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# required param
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optional_params = optional_params or {}
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kwargs = kwargs or {}
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optional_params = optional_params or {}
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vertex_input = VertexInput(text=input)
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validate_vertex_input(vertex_input, kwargs, optional_params)
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# required param
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if voice is not None:
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vertex_voice = VertexVoice(**voice)
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elif "voice" in kwargs:
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@ -203,3 +207,34 @@ class VertexTextToSpeechAPI(VertexLLM):
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# Initialize the HttpxBinaryResponseContent instance
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http_binary_response = HttpxBinaryResponseContent(response)
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return http_binary_response
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def validate_vertex_input(
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input_data: VertexInput, kwargs: dict, optional_params: dict
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) -> None:
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# Remove None values
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if input_data.get("text") is None:
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input_data.pop("text", None)
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if input_data.get("ssml") is None:
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input_data.pop("ssml", None)
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# Check if use_ssml is set
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use_ssml = kwargs.get("use_ssml", optional_params.get("use_ssml", False))
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if use_ssml:
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if "text" in input_data:
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input_data["ssml"] = input_data.pop("text")
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elif "ssml" not in input_data:
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raise ValueError("SSML input is required when use_ssml is True.")
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else:
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# LiteLLM will auto-detect if text is in ssml format
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# check if "text" is an ssml - in this case we should pass it as ssml instead of text
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if input_data:
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_text = input_data.get("text", None) or ""
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if "<speak>" in _text:
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input_data["ssml"] = input_data.pop("text")
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if not input_data:
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raise ValueError("Either 'text' or 'ssml' must be provided.")
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if "text" in input_data and "ssml" in input_data:
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raise ValueError("Only one of 'text' or 'ssml' should be provided, not both.")
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@ -1988,17 +1988,33 @@
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"supports_vision": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-experimental": {
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"gemini-pro-experimental": {
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"max_tokens": 8192,
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"max_input_tokens": 1000000,
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"max_output_tokens": 8192,
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"input_cost_per_token": 0,
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"output_cost_per_token": 0,
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"input_cost_per_character": 0,
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"output_cost_per_character": 0,
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": false,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/gemini-experimental"
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},
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"gemini-pro-flash": {
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"max_tokens": 8192,
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"max_input_tokens": 1000000,
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"max_output_tokens": 8192,
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"input_cost_per_token": 0,
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"output_cost_per_token": 0,
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"input_cost_per_character": 0,
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"output_cost_per_character": 0,
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": false,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/gemini-experimental"
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},
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"gemini-pro-vision": {
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"max_tokens": 2048,
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1
litellm/proxy/_experimental/out/404.html
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1
litellm/proxy/_experimental/out/404.html
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@ -1 +1 @@
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<!DOCTYPE html><html id="__next_error__"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="script" fetchPriority="low" href="/ui/_next/static/chunks/webpack-193a7eac80c8baba.js" crossorigin=""/><script src="/ui/_next/static/chunks/fd9d1056-f593049e31b05aeb.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/69-8316d07d1f41e39f.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/main-app-9b4fb13a7db53edf.js" async="" crossorigin=""></script><title>LiteLLM Dashboard</title><meta name="description" content="LiteLLM Proxy Admin UI"/><link rel="icon" href="/ui/favicon.ico" type="image/x-icon" sizes="16x16"/><meta name="next-size-adjust"/><script src="/ui/_next/static/chunks/polyfills-c67a75d1b6f99dc8.js" crossorigin="" noModule=""></script></head><body><script src="/ui/_next/static/chunks/webpack-193a7eac80c8baba.js" crossorigin="" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0]);self.__next_f.push([2,null])</script><script>self.__next_f.push([1,"1:HL[\"/ui/_next/static/media/a34f9d1faa5f3315-s.p.woff2\",\"font\",{\"crossOrigin\":\"\",\"type\":\"font/woff2\"}]\n2:HL[\"/ui/_next/static/css/cd10067a0a3408b4.css\",\"style\",{\"crossOrigin\":\"\"}]\n0:\"$L3\"\n"])</script><script>self.__next_f.push([1,"4:I[47690,[],\"\"]\n6:I[77831,[],\"\"]\n7:I[18018,[\"665\",\"static/chunks/3014691f-b24e8254c7593934.js\",\"936\",\"static/chunks/2f6dbc85-cac2949a76539886.js\",\"505\",\"static/chunks/505-5ff3c318fddfa35c.js\",\"131\",\"static/chunks/131-73d0a4f8e09896fe.js\",\"684\",\"static/chunks/684-16b194c83a169f6d.js\",\"605\",\"static/chunks/605-35a95945041f7699.js\",\"777\",\"static/chunks/777-5360b5460eba0779.js\",\"931\",\"static/chunks/app/page-01641b817a14ea88.js\"],\"\"]\n8:I[5613,[],\"\"]\n9:I[31778,[],\"\"]\nb:I[48955,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"3:[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/cd10067a0a3408b4.css\",\"precedence\":\"next\",\"crossOrigin\":\"\"}]],[\"$\",\"$L4\",null,{\"buildId\":\"LO0Sm6uVF0pa4RdHSL0dN\",\"assetPrefix\":\"/ui\",\"initialCanonicalUrl\":\"/\",\"initialTree\":[\"\",{\"children\":[\"__PAGE__\",{}]},\"$undefined\",\"$undefined\",true],\"initialSeedData\":[\"\",{\"children\":[\"__PAGE__\",{},[\"$L5\",[\"$\",\"$L6\",null,{\"propsForComponent\":{\"params\":{}},\"Component\":\"$7\",\"isStaticGeneration\":true}],null]]},[null,[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[\"$\",\"body\",null,{\"className\":\"__className_86ef86\",\"children\":[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\"],\"loading\":\"$undefined\",\"loadingStyles\":\"$undefined\",\"loadingScripts\":\"$undefined\",\"hasLoading\":false,\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 0\",\"fontSize\":24,\"fontWeight\":500,\"verticalAlign\":\"top\",\"lineHeight\":\"49px\"},\"children\":\"404\"}],[\"$\",\"div\",null,{\"style\":{\"display\":\"inline-block\"},\"children\":[\"$\",\"h2\",null,{\"style\":{\"fontSize\":14,\"fontWeight\":400,\"lineHeight\":\"49px\",\"margin\":0},\"children\":\"This page could not be found.\"}]}]]}]}]],\"notFoundStyles\":[],\"styles\":null}]}]}],null]],\"initialHead\":[false,\"$La\"],\"globalErrorComponent\":\"$b\",\"missingSlots\":\"$Wc\"}]]\n"])</script><script>self.__next_f.push([1,"a:[[\"$\",\"meta\",\"0\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}],[\"$\",\"meta\",\"1\",{\"charSet\":\"utf-8\"}],[\"$\",\"title\",\"2\",{\"children\":\"LiteLLM Dashboard\"}],[\"$\",\"meta\",\"3\",{\"name\":\"description\",\"content\":\"LiteLLM Proxy Admin UI\"}],[\"$\",\"link\",\"4\",{\"rel\":\"icon\",\"href\":\"/ui/favicon.ico\",\"type\":\"image/x-icon\",\"sizes\":\"16x16\"}],[\"$\",\"meta\",\"5\",{\"name\":\"next-size-adjust\"}]]\n5:null\n"])</script><script>self.__next_f.push([1,""])</script></body></html>
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- 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/
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -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:
|
||||
|
|
|
|||
45
litellm/proxy/auth/oauth2_proxy_hook.py
Normal file
45
litellm/proxy/auth/oauth2_proxy_hook.py
Normal file
|
|
@ -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
|
||||
|
|
@ -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:
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
@ -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:
|
||||
|
|
|
|||
|
|
@ -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",
|
||||
]
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -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 = """
|
||||
<speak>
|
||||
<p>Hello, world!</p>
|
||||
<p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
|
||||
</speak>
|
||||
"""
|
||||
|
||||
# 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"},
|
||||
}
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
|
|||
|
|
@ -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"]
|
|||
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3:I[667,["665","static/chunks/3014691f-b24e8254c7593934.js","505","static/chunks/505-5ff3c318fddfa35c.js","684","static/chunks/684-16b194c83a169f6d.js","777","static/chunks/777-5360b5460eba0779.js","461","static/chunks/app/onboarding/page-0034957a9fa387e0.js"],""]
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||||
3:I[667,["665","static/chunks/3014691f-b24e8254c7593934.js","505","static/chunks/505-5a85dd1c70cda98a.js","684","static/chunks/684-16b194c83a169f6d.js","777","static/chunks/777-5360b5460eba0779.js","461","static/chunks/app/onboarding/page-0034957a9fa387e0.js"],""]
|
||||
4:I[5613,[],""]
|
||||
5:I[31778,[],""]
|
||||
0:["LO0Sm6uVF0pa4RdHSL0dN",[[["",{"children":["onboarding",{"children":["__PAGE__",{}]}]},"$undefined","$undefined",true],["",{"children":["onboarding",{"children":["__PAGE__",{},["$L1",["$","$L2",null,{"propsForComponent":{"params":{}},"Component":"$3","isStaticGeneration":true}],null]]},["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children","onboarding","children"],"loading":"$undefined","loadingStyles":"$undefined","loadingScripts":"$undefined","hasLoading":false,"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","notFoundStyles":"$undefined","styles":null}]]},[null,["$","html",null,{"lang":"en","children":["$","body",null,{"className":"__className_86ef86","children":["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children"],"loading":"$undefined","loadingStyles":"$undefined","loadingScripts":"$undefined","hasLoading":false,"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[["$","title",null,{"children":"404: This page could not be found."}],["$","div",null,{"style":{"fontFamily":"system-ui,\"Segoe UI\",Roboto,Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\"","height":"100vh","textAlign":"center","display":"flex","flexDirection":"column","alignItems":"center","justifyContent":"center"},"children":["$","div",null,{"children":[["$","style",null,{"dangerouslySetInnerHTML":{"__html":"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}"}}],["$","h1",null,{"className":"next-error-h1","style":{"display":"inline-block","margin":"0 20px 0 0","padding":"0 23px 0 0","fontSize":24,"fontWeight":500,"verticalAlign":"top","lineHeight":"49px"},"children":"404"}],["$","div",null,{"style":{"display":"inline-block"},"children":["$","h2",null,{"style":{"fontSize":14,"fontWeight":400,"lineHeight":"49px","margin":0},"children":"This page could not be found."}]}]]}]}]],"notFoundStyles":[],"styles":null}]}]}],null]],[[["$","link","0",{"rel":"stylesheet","href":"/ui/_next/static/css/cd10067a0a3408b4.css","precedence":"next","crossOrigin":""}]],"$L6"]]]]
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0:["auooEytIka5iEx4r3srzM",[[["",{"children":["onboarding",{"children":["__PAGE__",{}]}]},"$undefined","$undefined",true],["",{"children":["onboarding",{"children":["__PAGE__",{},["$L1",["$","$L2",null,{"propsForComponent":{"params":{}},"Component":"$3","isStaticGeneration":true}],null]]},["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children","onboarding","children"],"loading":"$undefined","loadingStyles":"$undefined","loadingScripts":"$undefined","hasLoading":false,"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","notFoundStyles":"$undefined","styles":null}]]},[null,["$","html",null,{"lang":"en","children":["$","body",null,{"className":"__className_86ef86","children":["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children"],"loading":"$undefined","loadingStyles":"$undefined","loadingScripts":"$undefined","hasLoading":false,"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[["$","title",null,{"children":"404: This page could not be found."}],["$","div",null,{"style":{"fontFamily":"system-ui,\"Segoe UI\",Roboto,Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\"","height":"100vh","textAlign":"center","display":"flex","flexDirection":"column","alignItems":"center","justifyContent":"center"},"children":["$","div",null,{"children":[["$","style",null,{"dangerouslySetInnerHTML":{"__html":"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}"}}],["$","h1",null,{"className":"next-error-h1","style":{"display":"inline-block","margin":"0 20px 0 0","padding":"0 23px 0 0","fontSize":24,"fontWeight":500,"verticalAlign":"top","lineHeight":"49px"},"children":"404"}],["$","div",null,{"style":{"display":"inline-block"},"children":["$","h2",null,{"style":{"fontSize":14,"fontWeight":400,"lineHeight":"49px","margin":0},"children":"This page could not be found."}]}]]}]}]],"notFoundStyles":[],"styles":null}]}]}],null]],[[["$","link","0",{"rel":"stylesheet","href":"/ui/_next/static/css/cd10067a0a3408b4.css","precedence":"next","crossOrigin":""}]],"$L6"]]]]
|
||||
6:[["$","meta","0",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","1",{"charSet":"utf-8"}],["$","title","2",{"children":"LiteLLM Dashboard"}],["$","meta","3",{"name":"description","content":"LiteLLM Proxy Admin UI"}],["$","link","4",{"rel":"icon","href":"/ui/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","meta","5",{"name":"next-size-adjust"}]]
|
||||
1:null
|
||||
|
|
|
|||
|
|
@ -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<ViewKeyTableProps> = ({
|
|||
<Form
|
||||
form={form}
|
||||
onFinish={handleEditSubmit}
|
||||
initialValues={token} // Pass initial values here
|
||||
initialValues={{...token, budget_duration: token.budget_duration}} // Pass initial values here
|
||||
labelCol={{ span: 8 }}
|
||||
wrapperCol={{ span: 16 }}
|
||||
labelAlign="left"
|
||||
|
|
@ -297,6 +300,22 @@ const ViewKeyTable: React.FC<ViewKeyTableProps> = ({
|
|||
>
|
||||
<InputNumber step={0.01} precision={2} width={200} />
|
||||
</Form.Item>
|
||||
|
||||
<Form.Item
|
||||
className="mt-8"
|
||||
label="Reset Budget"
|
||||
name="budget_duration"
|
||||
help={`Current Reset Budget: ${
|
||||
token.budget_duration
|
||||
}, budget will be reset: ${token.budget_reset_at ? new Date(token.budget_reset_at).toLocaleString() : 'Never'}`}
|
||||
>
|
||||
<Select placeholder="n/a">
|
||||
<Select.Option value="daily">daily</Select.Option>
|
||||
<Select.Option value="weekly">weekly</Select.Option>
|
||||
<Select.Option value="monthly">monthly</Select.Option>
|
||||
</Select>
|
||||
</Form.Item>
|
||||
|
||||
<Form.Item
|
||||
label="token"
|
||||
name="token"
|
||||
|
|
@ -305,6 +324,7 @@ const ViewKeyTable: React.FC<ViewKeyTableProps> = ({
|
|||
<Form.Item
|
||||
label="Team"
|
||||
name="team_id"
|
||||
className="mt-8"
|
||||
help="the team this key belongs to"
|
||||
>
|
||||
<Select3 value={token.team_alias}>
|
||||
|
|
@ -536,7 +556,30 @@ const ViewKeyTable: React.FC<ViewKeyTableProps> = ({
|
|||
}
|
||||
}
|
||||
|
||||
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<ViewKeyTableProps> = ({
|
|||
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<ViewKeyTableProps> = ({
|
|||
<TableHeaderCell>Secret Key</TableHeaderCell>
|
||||
<TableHeaderCell>Spend (USD)</TableHeaderCell>
|
||||
<TableHeaderCell>Budget (USD)</TableHeaderCell>
|
||||
<TableHeaderCell>Budget Reset</TableHeaderCell>
|
||||
<TableHeaderCell>Models</TableHeaderCell>
|
||||
<TableHeaderCell>Rate Limits</TableHeaderCell>
|
||||
<TableHeaderCell>Rate Limits per model</TableHeaderCell>
|
||||
|
|
@ -722,6 +781,17 @@ const ViewKeyTable: React.FC<ViewKeyTableProps> = ({
|
|||
<Text>Unlimited</Text>
|
||||
)}
|
||||
</TableCell>
|
||||
<TableCell>
|
||||
{item.budget_reset_at != null ? (
|
||||
<div>
|
||||
<p style={{ fontSize: '0.70rem' }}>{new Date(item.budget_reset_at).toLocaleString()}</p>
|
||||
|
||||
</div>
|
||||
|
||||
) : (
|
||||
<p style={{ fontSize: '0.70rem' }}>Never</p>
|
||||
)}
|
||||
</TableCell>
|
||||
{/* <TableCell style={{ maxWidth: '2px' }}>
|
||||
<ViewKeySpendReport
|
||||
token={item.token}
|
||||
|
|
@ -796,7 +866,7 @@ const ViewKeyTable: React.FC<ViewKeyTableProps> = ({
|
|||
</Text>
|
||||
</TableCell>
|
||||
<TableCell>
|
||||
<Button onClick={() => handleModelLimitClick(item)}>Edit Limits</Button>
|
||||
<Button size="xs" onClick={() => handleModelLimitClick(item)}>Edit Limits</Button>
|
||||
</TableCell>
|
||||
<TableCell>
|
||||
<Icon
|
||||
|
|
@ -847,7 +917,15 @@ const ViewKeyTable: React.FC<ViewKeyTableProps> = ({
|
|||
<div className="mt-2 flex items-baseline space-x-2.5">
|
||||
<p className="text-tremor font-semibold text-tremor-content-strong dark:text-dark-tremor-content-strong">
|
||||
{selectedToken.max_budget != null ? (
|
||||
<>{selectedToken.max_budget}</>
|
||||
<>
|
||||
{selectedToken.max_budget}
|
||||
{selectedToken.budget_duration && (
|
||||
<>
|
||||
<br />
|
||||
Budget will be reset at {selectedToken.budget_reset_at ? new Date(selectedToken.budget_reset_at).toLocaleString() : 'Never'}
|
||||
</>
|
||||
)}
|
||||
</>
|
||||
) : (
|
||||
<>Unlimited</>
|
||||
)}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue