diff --git a/docs/my-website/docs/observability/agentops_integration.md b/docs/my-website/docs/observability/agentops_integration.md new file mode 100644 index 0000000000..e0599fab70 --- /dev/null +++ b/docs/my-website/docs/observability/agentops_integration.md @@ -0,0 +1,83 @@ +# 🖇️ AgentOps - LLM Observability Platform + +:::tip + +This is community maintained. Please make an issue if you run into a bug: +https://github.com/BerriAI/litellm + +::: + +[AgentOps](https://docs.agentops.ai) is an observability platform that enables tracing and monitoring of LLM calls, providing detailed insights into your AI operations. + +## Using AgentOps with LiteLLM + +LiteLLM provides `success_callbacks` and `failure_callbacks`, allowing you to easily integrate AgentOps for comprehensive tracing and monitoring of your LLM operations. + +### Integration + +Use just a few lines of code to instantly trace your responses **across all providers** with AgentOps: +Get your AgentOps API Keys from https://app.agentops.ai/ +```python +import litellm + +# Configure LiteLLM to use AgentOps +litellm.success_callback = ["agentops"] + +# Make your LLM calls as usual +response = litellm.completion( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "Hello, how are you?"}], +) +``` + +Complete Code: + +```python +import os +from litellm import completion + +# Set env variables +os.environ["OPENAI_API_KEY"] = "your-openai-key" +os.environ["AGENTOPS_API_KEY"] = "your-agentops-api-key" + +# Configure LiteLLM to use AgentOps +litellm.success_callback = ["agentops"] + +# OpenAI call +response = completion( + model="gpt-4", + messages=[{"role": "user", "content": "Hi 👋 - I'm OpenAI"}], +) + +print(response) +``` + +### Configuration Options + +The AgentOps integration can be configured through environment variables: + +- `AGENTOPS_API_KEY` (str, optional): Your AgentOps API key +- `AGENTOPS_ENVIRONMENT` (str, optional): Deployment environment (defaults to "production") +- `AGENTOPS_SERVICE_NAME` (str, optional): Service name for tracing (defaults to "agentops") + +### Advanced Usage + +You can configure additional settings through environment variables: + +```python +import os + +# Configure AgentOps settings +os.environ["AGENTOPS_API_KEY"] = "your-agentops-api-key" +os.environ["AGENTOPS_ENVIRONMENT"] = "staging" +os.environ["AGENTOPS_SERVICE_NAME"] = "my-service" + +# Enable AgentOps tracing +litellm.success_callback = ["agentops"] +``` + +### Support + +For issues or questions, please refer to: +- [AgentOps Documentation](https://docs.agentops.ai) +- [LiteLLM Documentation](https://docs.litellm.ai) \ No newline at end of file diff --git a/docs/my-website/docs/proxy/config_settings.md b/docs/my-website/docs/proxy/config_settings.md index bd8e2116c2..1e3c800b03 100644 --- a/docs/my-website/docs/proxy/config_settings.md +++ b/docs/my-website/docs/proxy/config_settings.md @@ -299,6 +299,9 @@ router_settings: |------|-------------| | ACTIONS_ID_TOKEN_REQUEST_TOKEN | Token for requesting ID in GitHub Actions | ACTIONS_ID_TOKEN_REQUEST_URL | URL for requesting ID token in GitHub Actions +| AGENTOPS_ENVIRONMENT | Environment for AgentOps logging integration +| AGENTOPS_API_KEY | API Key for AgentOps logging integration +| AGENTOPS_SERVICE_NAME | Service Name for AgentOps logging integration | AISPEND_ACCOUNT_ID | Account ID for AI Spend | AISPEND_API_KEY | API Key for AI Spend | ALLOWED_EMAIL_DOMAINS | List of email domains allowed for access diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js index c21c727b6a..60030a59bb 100644 --- a/docs/my-website/sidebars.js +++ b/docs/my-website/sidebars.js @@ -411,6 +411,7 @@ const sidebars = { type: "category", label: "Logging & Observability", items: [ + "observability/agentops_integration", "observability/langfuse_integration", "observability/lunary_integration", "observability/mlflow", diff --git a/litellm/__init__.py b/litellm/__init__.py index a7b747541a..59c8c78eb9 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -113,6 +113,7 @@ _custom_logger_compatible_callbacks_literal = Literal[ "pagerduty", "humanloop", "gcs_pubsub", + "agentops", "anthropic_cache_control_hook", ] logged_real_time_event_types: Optional[Union[List[str], Literal["*"]]] = None diff --git a/litellm/integrations/_types/open_inference.py b/litellm/integrations/_types/open_inference.py index bcfabe9b7b..65ecadcf37 100644 --- a/litellm/integrations/_types/open_inference.py +++ b/litellm/integrations/_types/open_inference.py @@ -45,6 +45,14 @@ class SpanAttributes: """ The name of the model being used. """ + LLM_PROVIDER = "llm.provider" + """ + The provider of the model, such as OpenAI, Azure, Google, etc. + """ + LLM_SYSTEM = "llm.system" + """ + The AI product as identified by the client or server + """ LLM_PROMPTS = "llm.prompts" """ Prompts provided to a completions API. @@ -65,15 +73,40 @@ class SpanAttributes: """ Number of tokens in the prompt. """ + LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_WRITE = "llm.token_count.prompt_details.cache_write" + """ + Number of tokens in the prompt that were written to cache. + """ + LLM_TOKEN_COUNT_PROMPT_DETAILS_CACHE_READ = "llm.token_count.prompt_details.cache_read" + """ + Number of tokens in the prompt that were read from cache. + """ + LLM_TOKEN_COUNT_PROMPT_DETAILS_AUDIO = "llm.token_count.prompt_details.audio" + """ + The number of audio input tokens presented in the prompt + """ LLM_TOKEN_COUNT_COMPLETION = "llm.token_count.completion" """ Number of tokens in the completion. """ + LLM_TOKEN_COUNT_COMPLETION_DETAILS_REASONING = "llm.token_count.completion_details.reasoning" + """ + Number of tokens used for reasoning steps in the completion. + """ + LLM_TOKEN_COUNT_COMPLETION_DETAILS_AUDIO = "llm.token_count.completion_details.audio" + """ + The number of audio input tokens generated by the model + """ LLM_TOKEN_COUNT_TOTAL = "llm.token_count.total" """ Total number of tokens, including both prompt and completion. """ + LLM_TOOLS = "llm.tools" + """ + List of tools that are advertised to the LLM to be able to call + """ + TOOL_NAME = "tool.name" """ Name of the tool being used. @@ -112,6 +145,19 @@ class SpanAttributes: The id of the user """ + PROMPT_VENDOR = "prompt.vendor" + """ + The vendor or origin of the prompt, e.g. a prompt library, a specialized service, etc. + """ + PROMPT_ID = "prompt.id" + """ + A vendor-specific id used to locate the prompt. + """ + PROMPT_URL = "prompt.url" + """ + A vendor-specific url used to locate the prompt. + """ + class MessageAttributes: """ @@ -151,6 +197,10 @@ class MessageAttributes: The JSON string representing the arguments passed to the function during a function call. """ + MESSAGE_TOOL_CALL_ID = "message.tool_call_id" + """ + The id of the tool call. + """ class MessageContentAttributes: @@ -186,6 +236,25 @@ class ImageAttributes: """ +class AudioAttributes: + """ + Attributes for audio + """ + + AUDIO_URL = "audio.url" + """ + The url to an audio file + """ + AUDIO_MIME_TYPE = "audio.mime_type" + """ + The mime type of the audio file + """ + AUDIO_TRANSCRIPT = "audio.transcript" + """ + The transcript of the audio file + """ + + class DocumentAttributes: """ Attributes for a document. @@ -257,6 +326,10 @@ class ToolCallAttributes: Attributes for a tool call """ + TOOL_CALL_ID = "tool_call.id" + """ + The id of the tool call. + """ TOOL_CALL_FUNCTION_NAME = "tool_call.function.name" """ The name of function that is being called during a tool call. @@ -268,6 +341,18 @@ class ToolCallAttributes: """ +class ToolAttributes: + """ + Attributes for a tools + """ + + TOOL_JSON_SCHEMA = "tool.json_schema" + """ + The json schema of a tool input, It is RECOMMENDED that this be in the + OpenAI tool calling format: https://platform.openai.com/docs/assistants/tools + """ + + class OpenInferenceSpanKindValues(Enum): TOOL = "TOOL" CHAIN = "CHAIN" @@ -284,3 +369,21 @@ class OpenInferenceSpanKindValues(Enum): class OpenInferenceMimeTypeValues(Enum): TEXT = "text/plain" JSON = "application/json" + + +class OpenInferenceLLMSystemValues(Enum): + OPENAI = "openai" + ANTHROPIC = "anthropic" + COHERE = "cohere" + MISTRALAI = "mistralai" + VERTEXAI = "vertexai" + + +class OpenInferenceLLMProviderValues(Enum): + OPENAI = "openai" + ANTHROPIC = "anthropic" + COHERE = "cohere" + MISTRALAI = "mistralai" + GOOGLE = "google" + AZURE = "azure" + AWS = "aws" diff --git a/litellm/integrations/agentops/__init__.py b/litellm/integrations/agentops/__init__.py new file mode 100644 index 0000000000..6ad02ce0ba --- /dev/null +++ b/litellm/integrations/agentops/__init__.py @@ -0,0 +1,3 @@ +from .agentops import AgentOps + +__all__ = ["AgentOps"] \ No newline at end of file diff --git a/litellm/integrations/agentops/agentops.py b/litellm/integrations/agentops/agentops.py new file mode 100644 index 0000000000..11e76841e9 --- /dev/null +++ b/litellm/integrations/agentops/agentops.py @@ -0,0 +1,118 @@ +""" +AgentOps integration for LiteLLM - Provides OpenTelemetry tracing for LLM calls +""" +import os +from dataclasses import dataclass +from typing import Optional, Dict, Any +from litellm.integrations.opentelemetry import OpenTelemetry, OpenTelemetryConfig +from litellm.llms.custom_httpx.http_handler import _get_httpx_client + +@dataclass +class AgentOpsConfig: + endpoint: str = "https://otlp.agentops.cloud/v1/traces" + api_key: Optional[str] = None + service_name: Optional[str] = None + deployment_environment: Optional[str] = None + auth_endpoint: str = "https://api.agentops.ai/v3/auth/token" + + @classmethod + def from_env(cls): + return cls( + endpoint="https://otlp.agentops.cloud/v1/traces", + api_key=os.getenv("AGENTOPS_API_KEY"), + service_name=os.getenv("AGENTOPS_SERVICE_NAME", "agentops"), + deployment_environment=os.getenv("AGENTOPS_ENVIRONMENT", "production"), + auth_endpoint="https://api.agentops.ai/v3/auth/token" + ) + +class AgentOps(OpenTelemetry): + """ + AgentOps integration - built on top of OpenTelemetry + + Example usage: + ```python + import litellm + + litellm.success_callback = ["agentops"] + + response = litellm.completion( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "Hello, how are you?"}], + ) + ``` + """ + def __init__( + self, + config: Optional[AgentOpsConfig] = None, + ): + if config is None: + config = AgentOpsConfig.from_env() + + # Prefetch JWT token for authentication + jwt_token = None + project_id = None + if config.api_key: + try: + response = self._fetch_auth_token(config.api_key, config.auth_endpoint) + jwt_token = response.get("token") + project_id = response.get("project_id") + except Exception: + pass + + headers = f"Authorization=Bearer {jwt_token}" if jwt_token else None + + otel_config = OpenTelemetryConfig( + exporter="otlp_http", + endpoint=config.endpoint, + headers=headers + ) + + # Initialize OpenTelemetry with our config + super().__init__( + config=otel_config, + callback_name="agentops" + ) + + # Set AgentOps-specific resource attributes + resource_attrs = { + "service.name": config.service_name or "litellm", + "deployment.environment": config.deployment_environment or "production", + "telemetry.sdk.name": "agentops", + } + + if project_id: + resource_attrs["project.id"] = project_id + + self.resource_attributes = resource_attrs + + def _fetch_auth_token(self, api_key: str, auth_endpoint: str) -> Dict[str, Any]: + """ + Fetch JWT authentication token from AgentOps API + + Args: + api_key: AgentOps API key + auth_endpoint: Authentication endpoint + + Returns: + Dict containing JWT token and project ID + """ + headers = { + "Content-Type": "application/json", + "Connection": "keep-alive", + } + + client = _get_httpx_client() + try: + response = client.post( + url=auth_endpoint, + headers=headers, + json={"api_key": api_key}, + timeout=10 + ) + + if response.status_code != 200: + raise Exception(f"Failed to fetch auth token: {response.text}") + + return response.json() + finally: + client.close() \ No newline at end of file diff --git a/litellm/integrations/arize/_utils.py b/litellm/integrations/arize/_utils.py index 5a090968b4..e93ef128b4 100644 --- a/litellm/integrations/arize/_utils.py +++ b/litellm/integrations/arize/_utils.py @@ -1,3 +1,4 @@ +import json from typing import TYPE_CHECKING, Any, Optional, Union from litellm._logging import verbose_logger @@ -12,36 +13,141 @@ else: Span = Any -def set_attributes(span: Span, kwargs, response_obj): +def cast_as_primitive_value_type(value) -> Union[str, bool, int, float]: + """ + Converts a value to an OTEL-supported primitive for Arize/Phoenix observability. + """ + if value is None: + return "" + if isinstance(value, (str, bool, int, float)): + return value + try: + return str(value) + except Exception: + return "" + + +def safe_set_attribute(span: Span, key: str, value: Any): + """ + Sets a span attribute safely with OTEL-compliant primitive typing for Arize/Phoenix. + """ + primitive_value = cast_as_primitive_value_type(value) + span.set_attribute(key, primitive_value) + + +def set_attributes(span: Span, kwargs, response_obj): # noqa: PLR0915 + """ + Populates span with OpenInference-compliant LLM attributes for Arize and Phoenix tracing. + """ from litellm.integrations._types.open_inference import ( MessageAttributes, OpenInferenceSpanKindValues, SpanAttributes, + ToolCallAttributes, ) try: + optional_params = kwargs.get("optional_params", {}) + litellm_params = kwargs.get("litellm_params", {}) standard_logging_payload: Optional[StandardLoggingPayload] = kwargs.get( "standard_logging_object" ) + if standard_logging_payload is None: + raise ValueError("standard_logging_object not found in kwargs") ############################################# ############ LLM CALL METADATA ############## ############################################# - if standard_logging_payload and ( - metadata := standard_logging_payload["metadata"] - ): - span.set_attribute(SpanAttributes.METADATA, safe_dumps(metadata)) + # Set custom metadata for observability and trace enrichment. + metadata = ( + standard_logging_payload.get("metadata") + if standard_logging_payload + else None + ) + if metadata is not None: + safe_set_attribute(span, SpanAttributes.METADATA, safe_dumps(metadata)) ############################################# ########## LLM Request Attributes ########### ############################################# - # The name of the LLM a request is being made to + # The name of the LLM a request is being made to. if kwargs.get("model"): - span.set_attribute(SpanAttributes.LLM_MODEL_NAME, kwargs.get("model")) + safe_set_attribute( + span, + SpanAttributes.LLM_MODEL_NAME, + kwargs.get("model"), + ) - span.set_attribute( + # The LLM request type. + safe_set_attribute( + span, + "llm.request.type", + standard_logging_payload["call_type"], + ) + + # The Generative AI Provider: Azure, OpenAI, etc. + safe_set_attribute( + span, + SpanAttributes.LLM_PROVIDER, + litellm_params.get("custom_llm_provider", "Unknown"), + ) + + # The maximum number of tokens the LLM generates for a request. + if optional_params.get("max_tokens"): + safe_set_attribute( + span, + "llm.request.max_tokens", + optional_params.get("max_tokens"), + ) + + # The temperature setting for the LLM request. + if optional_params.get("temperature"): + safe_set_attribute( + span, + "llm.request.temperature", + optional_params.get("temperature"), + ) + + # The top_p sampling setting for the LLM request. + if optional_params.get("top_p"): + safe_set_attribute( + span, + "llm.request.top_p", + optional_params.get("top_p"), + ) + + # Indicates whether response is streamed. + safe_set_attribute( + span, + "llm.is_streaming", + str(optional_params.get("stream", False)), + ) + + # Logs the user ID if present. + if optional_params.get("user"): + safe_set_attribute( + span, + "llm.user", + optional_params.get("user"), + ) + + # The unique identifier for the completion. + if response_obj and response_obj.get("id"): + safe_set_attribute(span, "llm.response.id", response_obj.get("id")) + + # The model used to generate the response. + if response_obj and response_obj.get("model"): + safe_set_attribute( + span, + "llm.response.model", + response_obj.get("model"), + ) + + # Required by OpenInference to mark span as LLM kind. + safe_set_attribute( + span, SpanAttributes.OPENINFERENCE_SPAN_KIND, OpenInferenceSpanKindValues.LLM.value, ) @@ -50,77 +156,132 @@ def set_attributes(span: Span, kwargs, response_obj): # for /chat/completions # https://docs.arize.com/arize/large-language-models/tracing/semantic-conventions if messages: - span.set_attribute( + last_message = messages[-1] + safe_set_attribute( + span, SpanAttributes.INPUT_VALUE, - messages[-1].get("content", ""), # get the last message for input + last_message.get("content", ""), ) - # LLM_INPUT_MESSAGES shows up under `input_messages` tab on the span page + # LLM_INPUT_MESSAGES shows up under `input_messages` tab on the span page. for idx, msg in enumerate(messages): - # Set the role per message - span.set_attribute( - f"{SpanAttributes.LLM_INPUT_MESSAGES}.{idx}.{MessageAttributes.MESSAGE_ROLE}", - msg["role"], + prefix = f"{SpanAttributes.LLM_INPUT_MESSAGES}.{idx}" + # Set the role per message. + safe_set_attribute( + span, f"{prefix}.{MessageAttributes.MESSAGE_ROLE}", msg.get("role") ) - # Set the content per message - span.set_attribute( - f"{SpanAttributes.LLM_INPUT_MESSAGES}.{idx}.{MessageAttributes.MESSAGE_CONTENT}", + # Set the content per message. + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_CONTENT}", msg.get("content", ""), ) - if standard_logging_payload and ( - model_params := standard_logging_payload["model_parameters"] - ): + # Capture tools (function definitions) used in the LLM call. + tools = optional_params.get("tools") + if tools: + for idx, tool in enumerate(tools): + function = tool.get("function") + if not function: + continue + prefix = f"{SpanAttributes.LLM_TOOLS}.{idx}" + safe_set_attribute( + span, f"{prefix}.{SpanAttributes.TOOL_NAME}", function.get("name") + ) + safe_set_attribute( + span, + f"{prefix}.{SpanAttributes.TOOL_DESCRIPTION}", + function.get("description"), + ) + safe_set_attribute( + span, + f"{prefix}.{SpanAttributes.TOOL_PARAMETERS}", + json.dumps(function.get("parameters")), + ) + + # Capture tool calls made during function-calling LLM flows. + functions = optional_params.get("functions") + if functions: + for idx, function in enumerate(functions): + prefix = f"{MessageAttributes.MESSAGE_TOOL_CALLS}.{idx}" + safe_set_attribute( + span, + f"{prefix}.{ToolCallAttributes.TOOL_CALL_FUNCTION_NAME}", + function.get("name"), + ) + + # Capture invocation parameters and user ID if available. + model_params = ( + standard_logging_payload.get("model_parameters") + if standard_logging_payload + else None + ) + if model_params: # The Generative AI Provider: Azure, OpenAI, etc. - span.set_attribute( - SpanAttributes.LLM_INVOCATION_PARAMETERS, safe_dumps(model_params) + safe_set_attribute( + span, + SpanAttributes.LLM_INVOCATION_PARAMETERS, + safe_dumps(model_params), ) if model_params.get("user"): user_id = model_params.get("user") if user_id is not None: - span.set_attribute(SpanAttributes.USER_ID, user_id) + safe_set_attribute(span, SpanAttributes.USER_ID, user_id) ############################################# ########## LLM Response Attributes ########## - # https://docs.arize.com/arize/large-language-models/tracing/semantic-conventions ############################################# - if hasattr(response_obj, "get"): - for choice in response_obj.get("choices", []): - response_message = choice.get("message", {}) - span.set_attribute( - SpanAttributes.OUTPUT_VALUE, response_message.get("content", "") - ) - # This shows up under `output_messages` tab on the span page - # This code assumes a single response - span.set_attribute( - f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_ROLE}", - response_message.get("role"), - ) - span.set_attribute( - f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_CONTENT}", + # Captures response tokens, message, and content. + if hasattr(response_obj, "get"): + for idx, choice in enumerate(response_obj.get("choices", [])): + response_message = choice.get("message", {}) + safe_set_attribute( + span, + SpanAttributes.OUTPUT_VALUE, response_message.get("content", ""), ) - usage = response_obj.get("usage") + # This shows up under `output_messages` tab on the span page. + prefix = f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.{idx}" + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_ROLE}", + response_message.get("role"), + ) + safe_set_attribute( + span, + f"{prefix}.{MessageAttributes.MESSAGE_CONTENT}", + response_message.get("content", ""), + ) + + # Token usage info. + usage = response_obj and response_obj.get("usage") if usage: - span.set_attribute( + safe_set_attribute( + span, SpanAttributes.LLM_TOKEN_COUNT_TOTAL, usage.get("total_tokens"), ) # The number of tokens used in the LLM response (completion). - span.set_attribute( + safe_set_attribute( + span, SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, usage.get("completion_tokens"), ) # The number of tokens used in the LLM prompt. - span.set_attribute( + safe_set_attribute( + span, SpanAttributes.LLM_TOKEN_COUNT_PROMPT, usage.get("prompt_tokens"), ) - pass + except Exception as e: - verbose_logger.error(f"Error setting arize attributes: {e}") + verbose_logger.error( + f"[Arize/Phoenix] Failed to set OpenInference span attributes: {e}" + ) + if hasattr(span, "record_exception"): + span.record_exception(e) diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 4d0b93f390..77d4fd7d5d 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -28,6 +28,7 @@ from litellm._logging import _is_debugging_on, verbose_logger from litellm.batches.batch_utils import _handle_completed_batch from litellm.caching.caching import DualCache, InMemoryCache from litellm.caching.caching_handler import LLMCachingHandler + from litellm.constants import ( DEFAULT_MOCK_RESPONSE_COMPLETION_TOKEN_COUNT, DEFAULT_MOCK_RESPONSE_PROMPT_TOKEN_COUNT, @@ -36,6 +37,7 @@ from litellm.cost_calculator import ( RealtimeAPITokenUsageProcessor, _select_model_name_for_cost_calc, ) +from litellm.integrations.agentops import AgentOps from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook from litellm.integrations.arize.arize import ArizeLogger from litellm.integrations.custom_guardrail import CustomGuardrail @@ -2685,7 +2687,15 @@ def _init_custom_logger_compatible_class( # noqa: PLR0915 """ try: custom_logger_init_args = custom_logger_init_args or {} - if logging_integration == "lago": + if logging_integration == "agentops": # Add AgentOps initialization + for callback in _in_memory_loggers: + if isinstance(callback, AgentOps): + return callback # type: ignore + + agentops_logger = AgentOps() + _in_memory_loggers.append(agentops_logger) + return agentops_logger # type: ignore + elif logging_integration == "lago": for callback in _in_memory_loggers: if isinstance(callback, LagoLogger): return callback # type: ignore diff --git a/litellm/llms/azure/responses/transformation.py b/litellm/llms/azure/responses/transformation.py index a85ba73bec..499d21cb0e 100644 --- a/litellm/llms/azure/responses/transformation.py +++ b/litellm/llms/azure/responses/transformation.py @@ -1,11 +1,14 @@ -from typing import TYPE_CHECKING, Any, Optional, cast +from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, cast import httpx import litellm +from litellm._logging import verbose_logger from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import * +from litellm.types.responses.main import * +from litellm.types.router import GenericLiteLLMParams from litellm.utils import _add_path_to_api_base if TYPE_CHECKING: @@ -41,11 +44,7 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): def get_complete_url( self, api_base: Optional[str], - api_key: Optional[str], - model: str, - optional_params: dict, litellm_params: dict, - stream: Optional[bool] = None, ) -> str: """ Constructs a complete URL for the API request. @@ -92,3 +91,48 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): final_url = httpx.URL(new_url).copy_with(params=query_params) return str(final_url) + + ######################################################### + ########## DELETE RESPONSE API TRANSFORMATION ############## + ######################################################### + def transform_delete_response_api_request( + self, + response_id: str, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, + ) -> Tuple[str, Dict]: + """ + Transform the delete response API request into a URL and data + + Azure OpenAI API expects the following request: + - DELETE /openai/responses/{response_id}?api-version=xxx + + This function handles URLs with query parameters by inserting the response_id + at the correct location (before any query parameters). + """ + from urllib.parse import urlparse, urlunparse + + # Parse the URL to separate its components + parsed_url = urlparse(api_base) + + # Insert the response_id at the end of the path component + # Remove trailing slash if present to avoid double slashes + path = parsed_url.path.rstrip("/") + new_path = f"{path}/{response_id}" + + # Reconstruct the URL with all original components but with the modified path + delete_url = urlunparse( + ( + parsed_url.scheme, # http, https + parsed_url.netloc, # domain name, port + new_path, # path with response_id added + parsed_url.params, # parameters + parsed_url.query, # query string + parsed_url.fragment, # fragment + ) + ) + + data: Dict = {} + verbose_logger.debug(f"delete response url={delete_url}") + return delete_url, data diff --git a/litellm/llms/base_llm/responses/transformation.py b/litellm/llms/base_llm/responses/transformation.py index 649b91226f..15ce8cba3f 100644 --- a/litellm/llms/base_llm/responses/transformation.py +++ b/litellm/llms/base_llm/responses/transformation.py @@ -1,6 +1,6 @@ import types from abc import ABC, abstractmethod -from typing import TYPE_CHECKING, Any, Dict, Optional, Union +from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union import httpx @@ -10,6 +10,7 @@ from litellm.types.llms.openai import ( ResponsesAPIResponse, ResponsesAPIStreamingResponse, ) +from litellm.types.responses.main import * from litellm.types.router import GenericLiteLLMParams if TYPE_CHECKING: @@ -73,11 +74,7 @@ class BaseResponsesAPIConfig(ABC): def get_complete_url( self, api_base: Optional[str], - api_key: Optional[str], - model: str, - optional_params: dict, litellm_params: dict, - stream: Optional[bool] = None, ) -> str: """ OPTIONAL @@ -122,6 +119,31 @@ class BaseResponsesAPIConfig(ABC): """ pass + ######################################################### + ########## DELETE RESPONSE API TRANSFORMATION ############## + ######################################################### + @abstractmethod + def transform_delete_response_api_request( + self, + response_id: str, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, + ) -> Tuple[str, Dict]: + pass + + @abstractmethod + def transform_delete_response_api_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + ) -> DeleteResponseResult: + pass + + ######################################################### + ########## END DELETE RESPONSE API TRANSFORMATION ########## + ######################################################### + def get_error_class( self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers] ) -> BaseLLMException: diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py index 627dd8c9f9..f99e04ab9d 100644 --- a/litellm/llms/custom_httpx/http_handler.py +++ b/litellm/llms/custom_httpx/http_handler.py @@ -650,6 +650,49 @@ class HTTPHandler: except Exception as e: raise e + def delete( + self, + url: str, + data: Optional[Union[dict, str]] = None, # type: ignore + json: Optional[dict] = None, + params: Optional[dict] = None, + headers: Optional[dict] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + stream: bool = False, + ): + try: + if timeout is not None: + req = self.client.build_request( + "DELETE", url, data=data, json=json, params=params, headers=headers, timeout=timeout # type: ignore + ) + else: + req = self.client.build_request( + "DELETE", url, data=data, json=json, params=params, headers=headers # type: ignore + ) + response = self.client.send(req, stream=stream) + response.raise_for_status() + return response + except httpx.TimeoutException: + raise litellm.Timeout( + message=f"Connection timed out after {timeout} seconds.", + model="default-model-name", + llm_provider="litellm-httpx-handler", + ) + except httpx.HTTPStatusError as e: + if stream is True: + setattr(e, "message", mask_sensitive_info(e.response.read())) + setattr(e, "text", mask_sensitive_info(e.response.read())) + else: + error_text = mask_sensitive_info(e.response.text) + setattr(e, "message", error_text) + setattr(e, "text", error_text) + + setattr(e, "status_code", e.response.status_code) + + raise e + except Exception as e: + raise e + def __del__(self) -> None: try: self.close() diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index c7b18215d0..1958ef0b60 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -36,6 +36,7 @@ from litellm.types.llms.openai import ( ResponsesAPIResponse, ) from litellm.types.rerank import OptionalRerankParams, RerankResponse +from litellm.types.responses.main import DeleteResponseResult from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import EmbeddingResponse, FileTypes, TranscriptionResponse from litellm.utils import CustomStreamWrapper, ModelResponse, ProviderConfigManager @@ -1015,6 +1016,7 @@ class BaseLLMHTTPHandler: client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, _is_async: bool = False, fake_stream: bool = False, + litellm_metadata: Optional[Dict[str, Any]] = None, ) -> Union[ ResponsesAPIResponse, BaseResponsesAPIStreamingIterator, @@ -1041,6 +1043,7 @@ class BaseLLMHTTPHandler: timeout=timeout, client=client if isinstance(client, AsyncHTTPHandler) else None, fake_stream=fake_stream, + litellm_metadata=litellm_metadata, ) if client is None or not isinstance(client, HTTPHandler): @@ -1064,11 +1067,7 @@ class BaseLLMHTTPHandler: api_base = responses_api_provider_config.get_complete_url( api_base=litellm_params.api_base, - api_key=litellm_params.api_key, - model=model, - optional_params=response_api_optional_request_params, litellm_params=dict(litellm_params), - stream=stream, ) data = responses_api_provider_config.transform_responses_api_request( @@ -1113,6 +1112,8 @@ class BaseLLMHTTPHandler: model=model, logging_obj=logging_obj, responses_api_provider_config=responses_api_provider_config, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, ) return SyncResponsesAPIStreamingIterator( @@ -1120,6 +1121,8 @@ class BaseLLMHTTPHandler: model=model, logging_obj=logging_obj, responses_api_provider_config=responses_api_provider_config, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, ) else: # For non-streaming requests @@ -1156,6 +1159,7 @@ class BaseLLMHTTPHandler: timeout: Optional[Union[float, httpx.Timeout]] = None, client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, fake_stream: bool = False, + litellm_metadata: Optional[Dict[str, Any]] = None, ) -> Union[ResponsesAPIResponse, BaseResponsesAPIStreamingIterator]: """ Async version of the responses API handler. @@ -1183,11 +1187,7 @@ class BaseLLMHTTPHandler: api_base = responses_api_provider_config.get_complete_url( api_base=litellm_params.api_base, - api_key=litellm_params.api_key, - model=model, - optional_params=response_api_optional_request_params, litellm_params=dict(litellm_params), - stream=stream, ) data = responses_api_provider_config.transform_responses_api_request( @@ -1234,6 +1234,8 @@ class BaseLLMHTTPHandler: model=model, logging_obj=logging_obj, responses_api_provider_config=responses_api_provider_config, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, ) # Return the streaming iterator @@ -1242,6 +1244,8 @@ class BaseLLMHTTPHandler: model=model, logging_obj=logging_obj, responses_api_provider_config=responses_api_provider_config, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, ) else: # For non-streaming, proceed as before @@ -1265,6 +1269,163 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, ) + async def async_delete_response_api_handler( + self, + response_id: str, + responses_api_provider_config: BaseResponsesAPIConfig, + litellm_params: GenericLiteLLMParams, + logging_obj: LiteLLMLoggingObj, + custom_llm_provider: Optional[str], + extra_headers: Optional[Dict[str, Any]] = None, + extra_body: Optional[Dict[str, Any]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + _is_async: bool = False, + ) -> DeleteResponseResult: + """ + Async version of the delete response API handler. + Uses async HTTP client to make requests. + """ + if client is None or not isinstance(client, AsyncHTTPHandler): + async_httpx_client = get_async_httpx_client( + llm_provider=litellm.LlmProviders(custom_llm_provider), + params={"ssl_verify": litellm_params.get("ssl_verify", None)}, + ) + else: + async_httpx_client = client + + headers = responses_api_provider_config.validate_environment( + api_key=litellm_params.api_key, + headers=extra_headers or {}, + model="None", + ) + + if extra_headers: + headers.update(extra_headers) + + api_base = responses_api_provider_config.get_complete_url( + api_base=litellm_params.api_base, + litellm_params=dict(litellm_params), + ) + + url, data = responses_api_provider_config.transform_delete_response_api_request( + response_id=response_id, + api_base=api_base, + litellm_params=litellm_params, + headers=headers, + ) + + ## LOGGING + logging_obj.pre_call( + input=input, + api_key="", + additional_args={ + "complete_input_dict": data, + "api_base": api_base, + "headers": headers, + }, + ) + + try: + response = await async_httpx_client.delete( + url=url, headers=headers, data=json.dumps(data), timeout=timeout + ) + + except Exception as e: + raise self._handle_error( + e=e, + provider_config=responses_api_provider_config, + ) + + return responses_api_provider_config.transform_delete_response_api_response( + raw_response=response, + logging_obj=logging_obj, + ) + + def delete_response_api_handler( + self, + response_id: str, + responses_api_provider_config: BaseResponsesAPIConfig, + litellm_params: GenericLiteLLMParams, + logging_obj: LiteLLMLoggingObj, + custom_llm_provider: Optional[str], + extra_headers: Optional[Dict[str, Any]] = None, + extra_body: Optional[Dict[str, Any]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + _is_async: bool = False, + ) -> Union[DeleteResponseResult, Coroutine[Any, Any, DeleteResponseResult]]: + """ + Async version of the responses API handler. + Uses async HTTP client to make requests. + """ + if _is_async: + return self.async_delete_response_api_handler( + response_id=response_id, + responses_api_provider_config=responses_api_provider_config, + litellm_params=litellm_params, + logging_obj=logging_obj, + custom_llm_provider=custom_llm_provider, + extra_headers=extra_headers, + extra_body=extra_body, + timeout=timeout, + client=client, + ) + if client is None or not isinstance(client, HTTPHandler): + sync_httpx_client = _get_httpx_client( + params={"ssl_verify": litellm_params.get("ssl_verify", None)} + ) + else: + sync_httpx_client = client + + headers = responses_api_provider_config.validate_environment( + api_key=litellm_params.api_key, + headers=extra_headers or {}, + model="None", + ) + + if extra_headers: + headers.update(extra_headers) + + api_base = responses_api_provider_config.get_complete_url( + api_base=litellm_params.api_base, + litellm_params=dict(litellm_params), + ) + + url, data = responses_api_provider_config.transform_delete_response_api_request( + response_id=response_id, + api_base=api_base, + litellm_params=litellm_params, + headers=headers, + ) + + ## LOGGING + logging_obj.pre_call( + input=input, + api_key="", + additional_args={ + "complete_input_dict": data, + "api_base": api_base, + "headers": headers, + }, + ) + + try: + response = sync_httpx_client.delete( + url=url, headers=headers, data=json.dumps(data), timeout=timeout + ) + + except Exception as e: + raise self._handle_error( + e=e, + provider_config=responses_api_provider_config, + ) + + return responses_api_provider_config.transform_delete_response_api_response( + raw_response=response, + logging_obj=logging_obj, + ) + def create_file( self, create_file_data: CreateFileRequest, diff --git a/litellm/llms/openai/responses/transformation.py b/litellm/llms/openai/responses/transformation.py index 7ee64e1713..ab16a5647d 100644 --- a/litellm/llms/openai/responses/transformation.py +++ b/litellm/llms/openai/responses/transformation.py @@ -7,6 +7,7 @@ from litellm._logging import verbose_logger from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import * +from litellm.types.responses.main import * from litellm.types.router import GenericLiteLLMParams from ..common_utils import OpenAIError @@ -110,11 +111,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): def get_complete_url( self, api_base: Optional[str], - api_key: Optional[str], - model: str, - optional_params: dict, litellm_params: dict, - stream: Optional[bool] = None, ) -> str: """ Get the endpoint for OpenAI responses API @@ -217,3 +214,39 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): f"Error getting model info in OpenAIResponsesAPIConfig: {e}" ) return False + + ######################################################### + ########## DELETE RESPONSE API TRANSFORMATION ############## + ######################################################### + def transform_delete_response_api_request( + self, + response_id: str, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, + ) -> Tuple[str, Dict]: + """ + Transform the delete response API request into a URL and data + + OpenAI API expects the following request + - DELETE /v1/responses/{response_id} + """ + url = f"{api_base}/{response_id}" + data: Dict = {} + return url, data + + def transform_delete_response_api_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + ) -> DeleteResponseResult: + """ + Transform the delete response API response into a DeleteResponseResult + """ + try: + raw_response_json = raw_response.json() + except Exception: + raise OpenAIError( + message=raw_response.text, status_code=raw_response.status_code + ) + return DeleteResponseResult(**raw_response_json) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 74cb44a460..95543d09c2 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1490,7 +1490,6 @@ "supports_prompt_caching": false, "supports_system_messages": true, "supports_tool_choice": true, - "supports_native_streaming": false, "supports_reasoning": true }, "azure/gpt-4o-audio-preview-2024-12-17": { diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 150528fd8f..354f6bb54c 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -687,6 +687,8 @@ class GenerateKeyResponse(KeyRequestBase): token: Optional[str] = None created_by: Optional[str] = None updated_by: Optional[str] = None + created_at: Optional[datetime] = None + updated_at: Optional[datetime] = None @model_validator(mode="before") @classmethod diff --git a/litellm/proxy/management_endpoints/internal_user_endpoints.py b/litellm/proxy/management_endpoints/internal_user_endpoints.py index 42a5dd7e81..589b30d524 100644 --- a/litellm/proxy/management_endpoints/internal_user_endpoints.py +++ b/litellm/proxy/management_endpoints/internal_user_endpoints.py @@ -43,6 +43,9 @@ from litellm.types.proxy.management_endpoints.common_daily_activity import ( SpendAnalyticsPaginatedResponse, SpendMetrics, ) +from litellm.types.proxy.management_endpoints.internal_user_endpoints import ( + UserListResponse, +) router = APIRouter() @@ -899,15 +902,47 @@ async def get_user_key_counts( return result -@router.get( - "/user/get_users", - tags=["Internal User management"], - dependencies=[Depends(user_api_key_auth)], -) +def _validate_sort_params( + sort_by: Optional[str], sort_order: str +) -> Optional[Dict[str, str]]: + order_by: Dict[str, str] = {} + + if sort_by is None: + return None + # Validate sort_by is a valid column + valid_columns = [ + "user_id", + "user_email", + "created_at", + "spend", + "user_alias", + "user_role", + ] + if sort_by not in valid_columns: + raise HTTPException( + status_code=400, + detail={ + "error": f"Invalid sort column. Must be one of: {', '.join(valid_columns)}" + }, + ) + + # Validate sort_order + if sort_order.lower() not in ["asc", "desc"]: + raise HTTPException( + status_code=400, + detail={"error": "Invalid sort order. Must be 'asc' or 'desc'"}, + ) + + order_by[sort_by] = sort_order.lower() + + return order_by + + @router.get( "/user/list", tags=["Internal User management"], dependencies=[Depends(user_api_key_auth)], + response_model=UserListResponse, ) async def get_users( role: Optional[str] = fastapi.Query( @@ -916,15 +951,29 @@ async def get_users( user_ids: Optional[str] = fastapi.Query( default=None, description="Get list of users by user_ids" ), + sso_user_ids: Optional[str] = fastapi.Query( + default=None, description="Get list of users by sso_user_id" + ), + user_email: Optional[str] = fastapi.Query( + default=None, description="Filter users by partial email match" + ), + team: Optional[str] = fastapi.Query( + default=None, description="Filter users by team id" + ), page: int = fastapi.Query(default=1, ge=1, description="Page number"), page_size: int = fastapi.Query( default=25, ge=1, le=100, description="Number of items per page" ), + sort_by: Optional[str] = fastapi.Query( + default=None, + description="Column to sort by (e.g. 'user_id', 'user_email', 'created_at', 'spend')", + ), + sort_order: str = fastapi.Query( + default="asc", description="Sort order ('asc' or 'desc')" + ), ): """ - Get a paginated list of users, optionally filtered by role. - - Used by the UI to populate the user lists. + Get a paginated list of users with filtering and sorting options. Parameters: role: Optional[str] @@ -935,17 +984,20 @@ async def get_users( - internal_user_viewer user_ids: Optional[str] Get list of users by user_ids. Comma separated list of user_ids. + sso_ids: Optional[str] + Get list of users by sso_ids. Comma separated list of sso_ids. + user_email: Optional[str] + Filter users by partial email match + team: Optional[str] + Filter users by team id. Will match if user has this team in their teams array. page: int The page number to return page_size: int The number of items per page - - Currently - admin-only endpoint. - - Example curl: - ``` - http://0.0.0.0:4000/user/list?user_ids=default_user_id,693c1a4a-1cc0-4c7c-afe8-b5d2c8d52e17 - ``` + sort_by: Optional[str] + Column to sort by (e.g. 'user_id', 'user_email', 'created_at', 'spend') + sort_order: Optional[str] + Sort order ('asc' or 'desc') """ from litellm.proxy.proxy_server import prisma_client @@ -958,35 +1010,57 @@ async def get_users( # Calculate skip and take for pagination skip = (page - 1) * page_size - # Prepare the query conditions # Build where conditions based on provided parameters where_conditions: Dict[str, Any] = {} if role: - where_conditions["user_role"] = { - "contains": role, - "mode": "insensitive", # Case-insensitive search - } + where_conditions["user_role"] = role # Exact match instead of contains if user_ids and isinstance(user_ids, str): user_id_list = [uid.strip() for uid in user_ids.split(",") if uid.strip()] where_conditions["user_id"] = { - "in": user_id_list, # Now passing a list of strings as required by Prisma + "in": user_id_list, } - users: Optional[ - List[LiteLLM_UserTable] - ] = await prisma_client.db.litellm_usertable.find_many( + if user_email is not None and isinstance(user_email, str): + where_conditions["user_email"] = { + "contains": user_email, + "mode": "insensitive", # Case-insensitive search + } + + if team is not None and isinstance(team, str): + where_conditions["teams"] = { + "has": team # Array contains for string arrays in Prisma + } + + if sso_user_ids is not None and isinstance(sso_user_ids, str): + sso_id_list = [sid.strip() for sid in sso_user_ids.split(",") if sid.strip()] + where_conditions["sso_user_id"] = { + "in": sso_id_list, + } + + ## Filter any none fastapi.Query params - e.g. where_conditions: {'user_email': {'contains': Query(None), 'mode': 'insensitive'}, 'teams': {'has': Query(None)}} + where_conditions = {k: v for k, v in where_conditions.items() if v is not None} + + # Build order_by conditions + + order_by: Optional[Dict[str, str]] = ( + _validate_sort_params(sort_by, sort_order) + if sort_by is not None and isinstance(sort_by, str) + else None + ) + + users = await prisma_client.db.litellm_usertable.find_many( where=where_conditions, skip=skip, take=page_size, - order={"created_at": "desc"}, + order=order_by + if order_by + else {"created_at": "desc"}, # Default to created_at desc if no sort specified ) # Get total count of user rows - total_count = await prisma_client.db.litellm_usertable.count( - where=where_conditions # type: ignore - ) + total_count = await prisma_client.db.litellm_usertable.count(where=where_conditions) # Get key count for each user if users is not None: @@ -1009,7 +1083,7 @@ async def get_users( LiteLLM_UserTableWithKeyCount( **user.model_dump(), key_count=user_key_counts.get(user.user_id, 0) ) - ) # Return full key object + ) else: user_list = [] diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 8fd3b555d4..15edab8909 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -1347,10 +1347,13 @@ async def generate_key_helper_fn( # noqa: PLR0915 create_key_response = await prisma_client.insert_data( data=key_data, table_name="key" ) + key_data["token_id"] = getattr(create_key_response, "token", None) key_data["litellm_budget_table"] = getattr( create_key_response, "litellm_budget_table", None ) + key_data["created_at"] = getattr(create_key_response, "created_at", None) + key_data["updated_at"] = getattr(create_key_response, "updated_at", None) except Exception as e: verbose_proxy_logger.error( "litellm.proxy.proxy_server.generate_key_helper_fn(): Exception occured - {}".format( diff --git a/litellm/responses/main.py b/litellm/responses/main.py index 2d7426205e..004a19a0ae 100644 --- a/litellm/responses/main.py +++ b/litellm/responses/main.py @@ -1,7 +1,7 @@ import asyncio import contextvars from functools import partial -from typing import Any, Dict, Iterable, List, Literal, Optional, Union +from typing import Any, Coroutine, Dict, Iterable, List, Literal, Optional, Union import httpx @@ -24,6 +24,7 @@ from litellm.types.llms.openai import ( ToolChoice, ToolParam, ) +from litellm.types.responses.main import * from litellm.types.router import GenericLiteLLMParams from litellm.utils import ProviderConfigManager, client @@ -121,7 +122,8 @@ async def aresponses( if isinstance(response, ResponsesAPIResponse): response = ResponsesAPIRequestUtils._update_responses_api_response_id_with_model_id( responses_api_response=response, - kwargs=kwargs, + litellm_metadata=kwargs.get("litellm_metadata", {}), + custom_llm_provider=custom_llm_provider, ) return response except Exception as e: @@ -253,13 +255,15 @@ def responses( fake_stream=responses_api_provider_config.should_fake_stream( model=model, stream=stream, custom_llm_provider=custom_llm_provider ), + litellm_metadata=kwargs.get("litellm_metadata", {}), ) # Update the responses_api_response_id with the model_id if isinstance(response, ResponsesAPIResponse): response = ResponsesAPIRequestUtils._update_responses_api_response_id_with_model_id( responses_api_response=response, - kwargs=kwargs, + litellm_metadata=kwargs.get("litellm_metadata", {}), + custom_llm_provider=custom_llm_provider, ) return response @@ -271,3 +275,162 @@ def responses( completion_kwargs=local_vars, extra_kwargs=kwargs, ) + + +@client +async def adelete_responses( + response_id: str, + # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. + # The extra values given here take precedence over values defined on the client or passed to this method. + extra_headers: Optional[Dict[str, Any]] = None, + extra_query: Optional[Dict[str, Any]] = None, + extra_body: Optional[Dict[str, Any]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + # LiteLLM specific params, + custom_llm_provider: Optional[str] = None, + **kwargs, +) -> DeleteResponseResult: + """ + Async version of the DELETE Responses API + + DELETE /v1/responses/{response_id} endpoint in the responses API + + """ + local_vars = locals() + try: + loop = asyncio.get_event_loop() + kwargs["adelete_responses"] = True + + # get custom llm provider from response_id + decoded_response_id: DecodedResponseId = ( + ResponsesAPIRequestUtils._decode_responses_api_response_id( + response_id=response_id, + ) + ) + response_id = decoded_response_id.get("response_id") or response_id + custom_llm_provider = ( + decoded_response_id.get("custom_llm_provider") or custom_llm_provider + ) + + func = partial( + delete_responses, + response_id=response_id, + custom_llm_provider=custom_llm_provider, + extra_headers=extra_headers, + extra_query=extra_query, + extra_body=extra_body, + timeout=timeout, + **kwargs, + ) + + ctx = contextvars.copy_context() + func_with_context = partial(ctx.run, func) + init_response = await loop.run_in_executor(None, func_with_context) + + if asyncio.iscoroutine(init_response): + response = await init_response + else: + response = init_response + return response + except Exception as e: + raise litellm.exception_type( + model=None, + custom_llm_provider=custom_llm_provider, + original_exception=e, + completion_kwargs=local_vars, + extra_kwargs=kwargs, + ) + + +@client +def delete_responses( + response_id: str, + # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. + # The extra values given here take precedence over values defined on the client or passed to this method. + extra_headers: Optional[Dict[str, Any]] = None, + extra_query: Optional[Dict[str, Any]] = None, + extra_body: Optional[Dict[str, Any]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + # LiteLLM specific params, + custom_llm_provider: Optional[str] = None, + **kwargs, +) -> Union[DeleteResponseResult, Coroutine[Any, Any, DeleteResponseResult]]: + """ + Synchronous version of the DELETE Responses API + + DELETE /v1/responses/{response_id} endpoint in the responses API + + """ + local_vars = locals() + try: + litellm_logging_obj: LiteLLMLoggingObj = kwargs.get("litellm_logging_obj") # type: ignore + litellm_call_id: Optional[str] = kwargs.get("litellm_call_id", None) + _is_async = kwargs.pop("adelete_responses", False) is True + + # get llm provider logic + litellm_params = GenericLiteLLMParams(**kwargs) + + # get custom llm provider from response_id + decoded_response_id: DecodedResponseId = ( + ResponsesAPIRequestUtils._decode_responses_api_response_id( + response_id=response_id, + ) + ) + response_id = decoded_response_id.get("response_id") or response_id + custom_llm_provider = ( + decoded_response_id.get("custom_llm_provider") or custom_llm_provider + ) + + if custom_llm_provider is None: + raise ValueError("custom_llm_provider is required but passed as None") + + # get provider config + responses_api_provider_config: Optional[BaseResponsesAPIConfig] = ( + ProviderConfigManager.get_provider_responses_api_config( + model=None, + provider=litellm.LlmProviders(custom_llm_provider), + ) + ) + + if responses_api_provider_config is None: + raise ValueError( + f"DELETE responses is not supported for {custom_llm_provider}" + ) + + local_vars.update(kwargs) + + # Pre Call logging + litellm_logging_obj.update_environment_variables( + model=None, + optional_params={ + "response_id": response_id, + }, + litellm_params={ + "litellm_call_id": litellm_call_id, + }, + custom_llm_provider=custom_llm_provider, + ) + + # Call the handler with _is_async flag instead of directly calling the async handler + response = base_llm_http_handler.delete_response_api_handler( + response_id=response_id, + custom_llm_provider=custom_llm_provider, + responses_api_provider_config=responses_api_provider_config, + litellm_params=litellm_params, + logging_obj=litellm_logging_obj, + extra_headers=extra_headers, + extra_body=extra_body, + timeout=timeout or request_timeout, + _is_async=_is_async, + client=kwargs.get("client"), + ) + + return response + except Exception as e: + raise litellm.exception_type( + model=None, + custom_llm_provider=custom_llm_provider, + original_exception=e, + completion_kwargs=local_vars, + extra_kwargs=kwargs, + ) diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py index 14525ee70e..a111fbec09 100644 --- a/litellm/responses/streaming_iterator.py +++ b/litellm/responses/streaming_iterator.py @@ -1,7 +1,7 @@ import asyncio import json from datetime import datetime -from typing import Optional +from typing import Any, Dict, Optional import httpx @@ -10,6 +10,7 @@ from litellm.litellm_core_utils.asyncify import run_async_function from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.thread_pool_executor import executor from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig +from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.openai import ( OutputTextDeltaEvent, ResponseCompletedEvent, @@ -33,6 +34,8 @@ class BaseResponsesAPIStreamingIterator: model: str, responses_api_provider_config: BaseResponsesAPIConfig, logging_obj: LiteLLMLoggingObj, + litellm_metadata: Optional[Dict[str, Any]] = None, + custom_llm_provider: Optional[str] = None, ): self.response = response self.model = model @@ -41,6 +44,10 @@ class BaseResponsesAPIStreamingIterator: self.responses_api_provider_config = responses_api_provider_config self.completed_response: Optional[ResponsesAPIStreamingResponse] = None self.start_time = datetime.now() + + # set request kwargs + self.litellm_metadata = litellm_metadata + self.custom_llm_provider = custom_llm_provider def _process_chunk(self, chunk) -> Optional[ResponsesAPIStreamingResponse]: """Process a single chunk of data from the stream""" @@ -70,6 +77,17 @@ class BaseResponsesAPIStreamingIterator: logging_obj=self.logging_obj, ) ) + + # if "response" in parsed_chunk, then encode litellm specific information like custom_llm_provider + response_object = getattr(openai_responses_api_chunk, "response", None) + if response_object: + response = ResponsesAPIRequestUtils._update_responses_api_response_id_with_model_id( + responses_api_response=response_object, + litellm_metadata=self.litellm_metadata, + custom_llm_provider=self.custom_llm_provider, + ) + setattr(openai_responses_api_chunk, "response", response) + # Store the completed response if ( openai_responses_api_chunk @@ -102,8 +120,17 @@ class ResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): model: str, responses_api_provider_config: BaseResponsesAPIConfig, logging_obj: LiteLLMLoggingObj, + litellm_metadata: Optional[Dict[str, Any]] = None, + custom_llm_provider: Optional[str] = None, ): - super().__init__(response, model, responses_api_provider_config, logging_obj) + super().__init__( + response, + model, + responses_api_provider_config, + logging_obj, + litellm_metadata, + custom_llm_provider, + ) self.stream_iterator = response.aiter_lines() def __aiter__(self): @@ -163,8 +190,17 @@ class SyncResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): model: str, responses_api_provider_config: BaseResponsesAPIConfig, logging_obj: LiteLLMLoggingObj, + litellm_metadata: Optional[Dict[str, Any]] = None, + custom_llm_provider: Optional[str] = None, ): - super().__init__(response, model, responses_api_provider_config, logging_obj) + super().__init__( + response, + model, + responses_api_provider_config, + logging_obj, + litellm_metadata, + custom_llm_provider, + ) self.stream_iterator = response.iter_lines() def __iter__(self): @@ -228,12 +264,16 @@ class MockResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator): model: str, responses_api_provider_config: BaseResponsesAPIConfig, logging_obj: LiteLLMLoggingObj, + litellm_metadata: Optional[Dict[str, Any]] = None, + custom_llm_provider: Optional[str] = None, ): super().__init__( response=response, model=model, responses_api_provider_config=responses_api_provider_config, logging_obj=logging_obj, + litellm_metadata=litellm_metadata, + custom_llm_provider=custom_llm_provider, ) # one-time transform diff --git a/litellm/responses/utils.py b/litellm/responses/utils.py index 5e95cbd93a..9fa455de71 100644 --- a/litellm/responses/utils.py +++ b/litellm/responses/utils.py @@ -1,5 +1,5 @@ import base64 -from typing import Any, Dict, Optional, Tuple, Union, cast, get_type_hints +from typing import Any, Dict, Optional, Union, cast, get_type_hints import litellm from litellm._logging import verbose_logger @@ -9,6 +9,7 @@ from litellm.types.llms.openai import ( ResponsesAPIOptionalRequestParams, ResponsesAPIResponse, ) +from litellm.types.responses.main import DecodedResponseId from litellm.types.utils import SpecialEnums, Usage @@ -83,30 +84,36 @@ class ResponsesAPIRequestUtils: @staticmethod def _update_responses_api_response_id_with_model_id( responses_api_response: ResponsesAPIResponse, - kwargs: Dict[str, Any], + custom_llm_provider: Optional[str], + litellm_metadata: Optional[Dict[str, Any]] = None, ) -> ResponsesAPIResponse: - """Update the responses_api_response_id with the model_id""" - litellm_metadata: Dict[str, Any] = kwargs.get("litellm_metadata", {}) or {} + """ + Update the responses_api_response_id with model_id and custom_llm_provider + + This builds a composite ID containing the custom LLM provider, model ID, and original response ID + """ + litellm_metadata = litellm_metadata or {} model_info: Dict[str, Any] = litellm_metadata.get("model_info", {}) or {} model_id = model_info.get("id") updated_id = ResponsesAPIRequestUtils._build_responses_api_response_id( model_id=model_id, + custom_llm_provider=custom_llm_provider, response_id=responses_api_response.id, ) + responses_api_response.id = updated_id return responses_api_response @staticmethod def _build_responses_api_response_id( + custom_llm_provider: Optional[str], model_id: Optional[str], response_id: str, ) -> str: """Build the responses_api_response_id""" - if model_id is None: - return response_id assembled_id: str = str( SpecialEnums.LITELLM_MANAGED_RESPONSE_COMPLETE_STR.value - ).format(model_id, response_id) + ).format(custom_llm_provider, model_id, response_id) base64_encoded_id: str = base64.b64encode(assembled_id.encode("utf-8")).decode( "utf-8" ) @@ -115,12 +122,12 @@ class ResponsesAPIRequestUtils: @staticmethod def _decode_responses_api_response_id( response_id: str, - ) -> Tuple[Optional[str], str]: + ) -> DecodedResponseId: """ Decode the responses_api_response_id Returns: - Tuple of model_id, response_id (from upstream provider) + DecodedResponseId: Structured tuple with custom_llm_provider, model_id, and response_id """ try: # Remove prefix and decode @@ -129,16 +136,45 @@ class ResponsesAPIRequestUtils: # Parse components using known prefixes if ";" not in decoded_id: - return None, response_id + return DecodedResponseId( + custom_llm_provider=None, + model_id=None, + response_id=response_id, + ) - model_part, response_part = decoded_id.split(";", 1) - model_id = model_part.replace("litellm:model_id:", "") - decoded_response_id = response_part.replace("response_id:", "") + parts = decoded_id.split(";") - return model_id, decoded_response_id + # Format: litellm:custom_llm_provider:{};model_id:{};response_id:{} + custom_llm_provider = None + model_id = None + + if ( + len(parts) >= 3 + ): # Full format with custom_llm_provider, model_id, and response_id + custom_llm_provider_part = parts[0] + model_id_part = parts[1] + response_part = parts[2] + + custom_llm_provider = custom_llm_provider_part.replace( + "litellm:custom_llm_provider:", "" + ) + model_id = model_id_part.replace("model_id:", "") + decoded_response_id = response_part.replace("response_id:", "") + else: + decoded_response_id = response_id + + return DecodedResponseId( + custom_llm_provider=custom_llm_provider, + model_id=model_id, + response_id=decoded_response_id, + ) except Exception as e: verbose_logger.debug(f"Error decoding response_id '{response_id}': {e}") - return None, response_id + return DecodedResponseId( + custom_llm_provider=None, + model_id=None, + response_id=response_id, + ) class ResponseAPILoggingUtils: diff --git a/litellm/router_utils/pre_call_checks/responses_api_deployment_check.py b/litellm/router_utils/pre_call_checks/responses_api_deployment_check.py index 445460c237..b030fc28c8 100644 --- a/litellm/router_utils/pre_call_checks/responses_api_deployment_check.py +++ b/litellm/router_utils/pre_call_checks/responses_api_deployment_check.py @@ -31,11 +31,10 @@ class ResponsesApiDeploymentCheck(CustomLogger): if previous_response_id is None: return healthy_deployments - model_id, response_id = ( - ResponsesAPIRequestUtils._decode_responses_api_response_id( - response_id=previous_response_id, - ) + decoded_response = ResponsesAPIRequestUtils._decode_responses_api_response_id( + response_id=previous_response_id, ) + model_id = decoded_response.get("model_id") if model_id is None: return healthy_deployments diff --git a/litellm/types/proxy/management_endpoints/internal_user_endpoints.py b/litellm/types/proxy/management_endpoints/internal_user_endpoints.py new file mode 100644 index 0000000000..5c2c5bf371 --- /dev/null +++ b/litellm/types/proxy/management_endpoints/internal_user_endpoints.py @@ -0,0 +1,18 @@ +from typing import Any, Dict, List, Literal, Optional, Union + +from fastapi import HTTPException +from pydantic import BaseModel, EmailStr + +from litellm.proxy._types import LiteLLM_UserTableWithKeyCount + + +class UserListResponse(BaseModel): + """ + Response model for the user list endpoint + """ + + users: List[LiteLLM_UserTableWithKeyCount] + total: int + page: int + page_size: int + total_pages: int diff --git a/litellm/types/responses/main.py b/litellm/types/responses/main.py index 63a548bbfd..b85df206bc 100644 --- a/litellm/types/responses/main.py +++ b/litellm/types/responses/main.py @@ -1,5 +1,6 @@ from typing import Literal +from pydantic import PrivateAttr from typing_extensions import Any, List, Optional, TypedDict from litellm.types.llms.base import BaseLiteLLMOpenAIResponseObject @@ -46,3 +47,30 @@ class GenericResponseOutputItem(BaseLiteLLMOpenAIResponseObject): status: str # "completed", "in_progress", etc. role: str # "assistant", "user", etc. content: List[OutputText] + + +class DeleteResponseResult(BaseLiteLLMOpenAIResponseObject): + """ + Result of a delete response request + + { + "id": "resp_6786a1bec27481909a17d673315b29f6", + "object": "response", + "deleted": true + } + """ + + id: Optional[str] + object: Optional[str] + deleted: Optional[bool] + + # Define private attributes using PrivateAttr + _hidden_params: dict = PrivateAttr(default_factory=dict) + + +class DecodedResponseId(TypedDict, total=False): + """Structure representing a decoded response ID""" + + custom_llm_provider: Optional[str] + model_id: Optional[str] + response_id: str diff --git a/litellm/types/utils.py b/litellm/types/utils.py index e9859513b9..532162e60f 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -2254,7 +2254,9 @@ class SpecialEnums(Enum): LITELM_MANAGED_FILE_ID_PREFIX = "litellm_proxy" LITELLM_MANAGED_FILE_COMPLETE_STR = "litellm_proxy:{};unified_id,{}" - LITELLM_MANAGED_RESPONSE_COMPLETE_STR = "litellm:model_id:{};response_id:{}" + LITELLM_MANAGED_RESPONSE_COMPLETE_STR = ( + "litellm:custom_llm_provider:{};model_id:{};response_id:{}" + ) LLMResponseTypes = Union[ diff --git a/litellm/utils.py b/litellm/utils.py index 38e604943a..98a9c34b47 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -180,10 +180,18 @@ from litellm.types.utils import ( all_litellm_params, ) -with resources.open_text( - "litellm.litellm_core_utils.tokenizers", "anthropic_tokenizer.json" -) as f: - json_data = json.load(f) +try: + # Python 3.9+ + with resources.files("litellm.litellm_core_utils.tokenizers").joinpath( + "anthropic_tokenizer.json" + ).open("r") as f: + json_data = json.load(f) +except (ImportError, AttributeError, TypeError): + with resources.open_text( + "litellm.litellm_core_utils.tokenizers", "anthropic_tokenizer.json" + ) as f: + json_data = json.load(f) + # Convert to str (if necessary) claude_json_str = json.dumps(json_data) import importlib.metadata @@ -516,9 +524,9 @@ def function_setup( # noqa: PLR0915 function_id: Optional[str] = kwargs["id"] if "id" in kwargs else None ## DYNAMIC CALLBACKS ## - dynamic_callbacks: Optional[ - List[Union[str, Callable, CustomLogger]] - ] = kwargs.pop("callbacks", None) + dynamic_callbacks: Optional[List[Union[str, Callable, CustomLogger]]] = ( + kwargs.pop("callbacks", None) + ) all_callbacks = get_dynamic_callbacks(dynamic_callbacks=dynamic_callbacks) if len(all_callbacks) > 0: @@ -1202,9 +1210,9 @@ def client(original_function): # noqa: PLR0915 exception=e, retry_policy=kwargs.get("retry_policy"), ) - kwargs[ - "retry_policy" - ] = reset_retry_policy() # prevent infinite loops + kwargs["retry_policy"] = ( + reset_retry_policy() + ) # prevent infinite loops litellm.num_retries = ( None # set retries to None to prevent infinite loops ) @@ -3028,16 +3036,16 @@ def get_optional_params( # noqa: PLR0915 True # so that main.py adds the function call to the prompt ) if "tools" in non_default_params: - optional_params[ - "functions_unsupported_model" - ] = non_default_params.pop("tools") + optional_params["functions_unsupported_model"] = ( + non_default_params.pop("tools") + ) non_default_params.pop( "tool_choice", None ) # causes ollama requests to hang elif "functions" in non_default_params: - optional_params[ - "functions_unsupported_model" - ] = non_default_params.pop("functions") + optional_params["functions_unsupported_model"] = ( + non_default_params.pop("functions") + ) elif ( litellm.add_function_to_prompt ): # if user opts to add it to prompt instead @@ -3060,10 +3068,10 @@ def get_optional_params( # noqa: PLR0915 if "response_format" in non_default_params: if provider_config is not None: - non_default_params[ - "response_format" - ] = provider_config.get_json_schema_from_pydantic_object( - response_format=non_default_params["response_format"] + non_default_params["response_format"] = ( + provider_config.get_json_schema_from_pydantic_object( + response_format=non_default_params["response_format"] + ) ) else: non_default_params["response_format"] = type_to_response_format_param( @@ -4079,9 +4087,9 @@ def _count_characters(text: str) -> int: def get_response_string(response_obj: Union[ModelResponse, ModelResponseStream]) -> str: - _choices: Union[ - List[Union[Choices, StreamingChoices]], List[StreamingChoices] - ] = response_obj.choices + _choices: Union[List[Union[Choices, StreamingChoices]], List[StreamingChoices]] = ( + response_obj.choices + ) response_str = "" for choice in _choices: @@ -6625,8 +6633,8 @@ class ProviderConfigManager: @staticmethod def get_provider_responses_api_config( - model: str, provider: LlmProviders, + model: Optional[str] = None, ) -> Optional[BaseResponsesAPIConfig]: if litellm.LlmProviders.OPENAI == provider: return litellm.OpenAIResponsesAPIConfig() diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 74cb44a460..95543d09c2 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1490,7 +1490,6 @@ "supports_prompt_caching": false, "supports_system_messages": true, "supports_tool_choice": true, - "supports_native_streaming": false, "supports_reasoning": true }, "azure/gpt-4o-audio-preview-2024-12-17": { diff --git a/poetry.lock b/poetry.lock index 02ec90cc31..1ad74a07a6 100644 --- a/poetry.lock +++ b/poetry.lock @@ -548,7 +548,7 @@ version = "3.4.1" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." optional = false python-versions = ">=3.7" -groups = ["main"] +groups = ["main", "dev", "proxy-dev"] files = [ {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"}, {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"}, @@ -742,6 +742,24 @@ ssh = ["bcrypt (>=3.1.5)"] test = ["certifi", "cryptography-vectors (==43.0.3)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"] test-randomorder = ["pytest-randomly"] +[[package]] +name = "deprecated" +version = "1.2.18" +description = "Python @deprecated decorator to deprecate old python classes, functions or methods." +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7" +groups = ["dev", "proxy-dev"] +files = [ + {file = "Deprecated-1.2.18-py2.py3-none-any.whl", hash = "sha256:bd5011788200372a32418f888e326a09ff80d0214bd961147cfed01b5c018eec"}, + {file = "deprecated-1.2.18.tar.gz", hash = "sha256:422b6f6d859da6f2ef57857761bfb392480502a64c3028ca9bbe86085d72115d"}, +] + +[package.dependencies] +wrapt = ">=1.10,<2" + +[package.extras] +dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "setuptools ; python_version >= \"3.12\"", "tox"] + [[package]] name = "distro" version = "1.9.0" @@ -1116,14 +1134,14 @@ protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4 name = "googleapis-common-protos" version = "1.70.0" description = "Common protobufs used in Google APIs" -optional = true +optional = false python-versions = ">=3.7" -groups = ["main"] -markers = "extra == \"extra-proxy\"" +groups = ["main", "dev", "proxy-dev"] files = [ {file = "googleapis_common_protos-1.70.0-py3-none-any.whl", hash = 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[tool.poetry.group.proxy-dev.dependencies] prisma = "0.11.0" hypercorn = "^0.15.0" prometheus-client = "0.20.0" +opentelemetry-api = "1.25.0" +opentelemetry-sdk = "1.25.0" +opentelemetry-exporter-otlp = "1.25.0" [build-system] requires = ["poetry-core", "wheel"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "1.67.1" +version = "1.67.2" version_files = [ "pyproject.toml:^version" ] diff --git a/test-results/.last-run.json b/test-results/.last-run.json new file mode 100644 index 0000000000..5fca3f84bc --- /dev/null +++ b/test-results/.last-run.json @@ -0,0 +1,4 @@ +{ + "status": "failed", + "failedTests": [] +} \ No newline at end of file diff --git a/tests/litellm/integrations/arize/test_arize_utils.py b/tests/litellm/integrations/arize/test_arize_utils.py new file mode 100644 index 0000000000..bea42faaa8 --- /dev/null +++ b/tests/litellm/integrations/arize/test_arize_utils.py @@ -0,0 +1,231 @@ +import json +import os +import sys +from typing import Optional + +# Adds the grandparent directory to sys.path to allow importing project modules +sys.path.insert(0, os.path.abspath("../..")) + +import asyncio +import litellm +import pytest +from litellm.integrations.arize.arize import ArizeLogger +from litellm.integrations.custom_logger import CustomLogger +from litellm.integrations._types.open_inference import ( + SpanAttributes, + MessageAttributes, + ToolCallAttributes, +) +from litellm.types.utils import Choices, StandardCallbackDynamicParams + + +def test_arize_set_attributes(): + """ + Test setting attributes for Arize, including all custom LLM attributes. + Ensures that the correct span attributes are being added during a request. + """ + from unittest.mock import MagicMock + from litellm.types.utils import ModelResponse + + span = MagicMock() # Mocked tracing span to test attribute setting + + # Construct kwargs to simulate a real LLM request scenario + kwargs = { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "Basic Request Content"}], + "standard_logging_object": { + "model_parameters": {"user": "test_user"}, + "metadata": {"key_1": "value_1", "key_2": None}, + "call_type": "completion", + }, + "optional_params": { + "max_tokens": "100", + "temperature": "1", + "top_p": "5", + "stream": False, + "user": "test_user", + "tools": [ + { + "function": { + "name": "get_weather", + "description": "Fetches weather details.", + "parameters": { + "type": "object", + "properties": { + "location": { + "type": "string", + "description": "City name", + } + }, + "required": ["location"], + }, + } + } + ], + "functions": [{"name": "get_weather"}, {"name": "get_stock_price"}], + }, + "litellm_params": {"custom_llm_provider": "openai"}, + } + + # Simulated LLM response object + response_obj = ModelResponse( + usage={"total_tokens": 100, "completion_tokens": 60, "prompt_tokens": 40}, + choices=[ + Choices(message={"role": "assistant", "content": "Basic Response Content"}) + ], + model="gpt-4o", + id="chatcmpl-ID", + ) + + # Apply attribute setting via ArizeLogger + ArizeLogger.set_arize_attributes(span, kwargs, response_obj) + + # Validate that the expected number of attributes were set + assert span.set_attribute.call_count == 28 + + # Metadata attached to the span + span.set_attribute.assert_any_call( + SpanAttributes.METADATA, json.dumps({"key_1": "value_1", "key_2": None}) + ) + + # Basic LLM information + span.set_attribute.assert_any_call(SpanAttributes.LLM_MODEL_NAME, "gpt-4o") + span.set_attribute.assert_any_call("llm.request.type", "completion") + span.set_attribute.assert_any_call(SpanAttributes.LLM_PROVIDER, "openai") + + # LLM generation parameters + span.set_attribute.assert_any_call("llm.request.max_tokens", "100") + span.set_attribute.assert_any_call("llm.request.temperature", "1") + span.set_attribute.assert_any_call("llm.request.top_p", "5") + + # Streaming and user info + span.set_attribute.assert_any_call("llm.is_streaming", "False") + span.set_attribute.assert_any_call("llm.user", "test_user") + + # Response metadata + span.set_attribute.assert_any_call("llm.response.id", "chatcmpl-ID") + span.set_attribute.assert_any_call("llm.response.model", "gpt-4o") + span.set_attribute.assert_any_call(SpanAttributes.OPENINFERENCE_SPAN_KIND, "LLM") + + # Request message content and metadata + span.set_attribute.assert_any_call( + SpanAttributes.INPUT_VALUE, "Basic Request Content" + ) + span.set_attribute.assert_any_call( + f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_ROLE}", + "user", + ) + span.set_attribute.assert_any_call( + f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_CONTENT}", + "Basic Request Content", + ) + + # Tool call definitions and function names + span.set_attribute.assert_any_call( + f"{SpanAttributes.LLM_TOOLS}.0.{SpanAttributes.TOOL_NAME}", "get_weather" + ) + span.set_attribute.assert_any_call( + f"{SpanAttributes.LLM_TOOLS}.0.{SpanAttributes.TOOL_DESCRIPTION}", + "Fetches weather details.", + ) + span.set_attribute.assert_any_call( + f"{SpanAttributes.LLM_TOOLS}.0.{SpanAttributes.TOOL_PARAMETERS}", + json.dumps( + { + "type": "object", + "properties": { + "location": {"type": "string", "description": "City name"} + }, + "required": ["location"], + } + ), + ) + + # Tool calls captured from optional_params + span.set_attribute.assert_any_call( + f"{MessageAttributes.MESSAGE_TOOL_CALLS}.0.{ToolCallAttributes.TOOL_CALL_FUNCTION_NAME}", + "get_weather", + ) + span.set_attribute.assert_any_call( + f"{MessageAttributes.MESSAGE_TOOL_CALLS}.1.{ToolCallAttributes.TOOL_CALL_FUNCTION_NAME}", + "get_stock_price", + ) + + # Invocation parameters + span.set_attribute.assert_any_call( + SpanAttributes.LLM_INVOCATION_PARAMETERS, '{"user": "test_user"}' + ) + + # User ID + span.set_attribute.assert_any_call(SpanAttributes.USER_ID, "test_user") + + # Output message content + span.set_attribute.assert_any_call( + SpanAttributes.OUTPUT_VALUE, "Basic Response Content" + ) + span.set_attribute.assert_any_call( + f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_ROLE}", + "assistant", + ) + span.set_attribute.assert_any_call( + f"{SpanAttributes.LLM_OUTPUT_MESSAGES}.0.{MessageAttributes.MESSAGE_CONTENT}", + "Basic Response Content", + ) + + # Token counts + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, 100) + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, 60) + span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_PROMPT, 40) + + +class TestArizeLogger(CustomLogger): + """ + Custom logger implementation to capture standard_callback_dynamic_params. + Used to verify that dynamic config keys are being passed to callbacks. + """ + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.standard_callback_dynamic_params: Optional[ + StandardCallbackDynamicParams + ] = None + + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + # Capture dynamic params and print them for verification + print("logged kwargs", json.dumps(kwargs, indent=4, default=str)) + self.standard_callback_dynamic_params = kwargs.get( + "standard_callback_dynamic_params" + ) + + +@pytest.mark.asyncio +async def test_arize_dynamic_params(): + """ + Test to ensure that dynamic Arize keys (API key and space key) + are received inside the callback logger at runtime. + """ + test_arize_logger = TestArizeLogger() + litellm.callbacks = [test_arize_logger] + + # Perform a mocked async completion call to trigger logging + await litellm.acompletion( + model="gpt-4o", + messages=[{"role": "user", "content": "Basic Request Content"}], + mock_response="test", + arize_api_key="test_api_key_dynamic", + arize_space_key="test_space_key_dynamic", + ) + + # Allow for async propagation + await asyncio.sleep(2) + + # Assert dynamic parameters were received in the callback + assert test_arize_logger.standard_callback_dynamic_params is not None + assert ( + test_arize_logger.standard_callback_dynamic_params.get("arize_api_key") + == "test_api_key_dynamic" + ) + assert ( + test_arize_logger.standard_callback_dynamic_params.get("arize_space_key") + == "test_space_key_dynamic" + ) diff --git a/tests/litellm/integrations/test_agentops.py b/tests/litellm/integrations/test_agentops.py new file mode 100644 index 0000000000..3302736177 --- /dev/null +++ b/tests/litellm/integrations/test_agentops.py @@ -0,0 +1,98 @@ +import os +import sys +import pytest +from unittest.mock import patch, MagicMock + +sys.path.insert(0, os.path.abspath("../..")) # Adds the parent directory to the system-path + +from litellm.integrations.agentops.agentops import AgentOps, AgentOpsConfig + +@pytest.fixture +def mock_auth_response(): + return { + "token": "test_jwt_token", + "project_id": "test_project_id" + } + +@pytest.fixture +def agentops_config(): + return AgentOpsConfig( + endpoint="https://otlp.agentops.cloud/v1/traces", + api_key="test_api_key", + service_name="test_service", + deployment_environment="test_env", + auth_endpoint="https://api.agentops.ai/v3/auth/token" + ) + +def test_agentops_config_from_env(): + """Test that AgentOpsConfig correctly reads from environment variables""" + with patch.dict(os.environ, { + "AGENTOPS_API_KEY": "test_key", + "AGENTOPS_SERVICE_NAME": "test_service", + "AGENTOPS_ENVIRONMENT": "test_env" + }): + config = AgentOpsConfig.from_env() + assert config.api_key == "test_key" + assert config.service_name == "test_service" + assert config.deployment_environment == "test_env" + assert config.endpoint == "https://otlp.agentops.cloud/v1/traces" + assert config.auth_endpoint == "https://api.agentops.ai/v3/auth/token" + +def test_agentops_config_defaults(): + """Test that AgentOpsConfig uses correct default values""" + config = AgentOpsConfig() + assert config.service_name is None + assert config.deployment_environment is None + assert config.api_key is None + assert config.endpoint == "https://otlp.agentops.cloud/v1/traces" + assert config.auth_endpoint == "https://api.agentops.ai/v3/auth/token" + +@patch('litellm.integrations.agentops.agentops.AgentOps._fetch_auth_token') +def test_fetch_auth_token_success(mock_fetch_auth_token, mock_auth_response): + """Test successful JWT token fetch""" + mock_fetch_auth_token.return_value = mock_auth_response + + config = AgentOpsConfig(api_key="test_key") + agentops = AgentOps(config=config) + + mock_fetch_auth_token.assert_called_once_with("test_key", "https://api.agentops.ai/v3/auth/token") + assert agentops.resource_attributes.get("project.id") == mock_auth_response.get("project_id") + +@patch('litellm.integrations.agentops.agentops.AgentOps._fetch_auth_token') +def test_fetch_auth_token_failure(mock_fetch_auth_token): + """Test failed JWT token fetch""" + mock_fetch_auth_token.side_effect = Exception("Failed to fetch auth token: Unauthorized") + + config = AgentOpsConfig(api_key="test_key") + agentops = AgentOps(config=config) + + mock_fetch_auth_token.assert_called_once() + assert "project.id" not in agentops.resource_attributes + +@patch('litellm.integrations.agentops.agentops.AgentOps._fetch_auth_token') +def test_agentops_initialization(mock_fetch_auth_token, agentops_config, mock_auth_response): + """Test AgentOps initialization with config""" + mock_fetch_auth_token.return_value = mock_auth_response + + agentops = AgentOps(config=agentops_config) + + assert agentops.resource_attributes["service.name"] == "test_service" + assert agentops.resource_attributes["deployment.environment"] == "test_env" + assert agentops.resource_attributes["telemetry.sdk.name"] == "agentops" + assert agentops.resource_attributes["project.id"] == "test_project_id" + +def test_agentops_initialization_no_auth(): + """Test AgentOps initialization without authentication""" + test_config = AgentOpsConfig( + endpoint="https://otlp.agentops.cloud/v1/traces", + api_key=None, # No API key + service_name="test_service", + deployment_environment="test_env" + ) + + agentops = AgentOps(config=test_config) + + assert agentops.resource_attributes["service.name"] == "test_service" + assert agentops.resource_attributes["deployment.environment"] == "test_env" + assert agentops.resource_attributes["telemetry.sdk.name"] == "agentops" + assert "project.id" not in agentops.resource_attributes \ No newline at end of file diff --git a/tests/litellm/llms/openai/responses/test_openai_responses_transformation.py b/tests/litellm/llms/openai/responses/test_openai_responses_transformation.py index 444a3acbbb..04b9de5616 100644 --- a/tests/litellm/llms/openai/responses/test_openai_responses_transformation.py +++ b/tests/litellm/llms/openai/responses/test_openai_responses_transformation.py @@ -203,9 +203,6 @@ class TestOpenAIResponsesAPIConfig: result = self.config.get_complete_url( api_base=api_base, - model=self.model, - api_key="test_api_key", - optional_params={}, litellm_params={}, ) @@ -215,9 +212,6 @@ class TestOpenAIResponsesAPIConfig: with patch("litellm.api_base", "https://litellm-api-base.example.com/v1"): result = self.config.get_complete_url( api_base=None, - model=self.model, - api_key="test_api_key", - optional_params={}, litellm_params={}, ) @@ -231,9 +225,6 @@ class TestOpenAIResponsesAPIConfig: ): result = self.config.get_complete_url( api_base=None, - model=self.model, - api_key="test_api_key", - optional_params={}, litellm_params={}, ) @@ -247,9 +238,6 @@ class TestOpenAIResponsesAPIConfig: ): result = self.config.get_complete_url( api_base=None, - model=self.model, - api_key="test_api_key", - optional_params={}, litellm_params={}, ) @@ -260,9 +248,6 @@ class TestOpenAIResponsesAPIConfig: result = self.config.get_complete_url( api_base=api_base, - model=self.model, - api_key="test_api_key", - optional_params={}, litellm_params={}, ) diff --git a/tests/litellm/proxy/management_endpoints/test_internal_user_endpoints.py b/tests/litellm/proxy/management_endpoints/test_internal_user_endpoints.py index deef94c15a..360f21f171 100644 --- a/tests/litellm/proxy/management_endpoints/test_internal_user_endpoints.py +++ b/tests/litellm/proxy/management_endpoints/test_internal_user_endpoints.py @@ -153,3 +153,19 @@ async def test_get_users_includes_timestamps(mocker): assert user_response.created_at == mock_user_data["created_at"] assert user_response.updated_at == mock_user_data["updated_at"] assert user_response.key_count == 0 + + +def test_validate_sort_params(): + """ + Test that validate_sort_params returns None if sort_by is None + """ + from litellm.proxy.management_endpoints.internal_user_endpoints import ( + _validate_sort_params, + ) + + assert _validate_sort_params(None, "asc") is None + assert _validate_sort_params(None, "desc") is None + assert _validate_sort_params("user_id", "asc") == {"user_id": "asc"} + assert _validate_sort_params("user_id", "desc") == {"user_id": "desc"} + with pytest.raises(Exception): + _validate_sort_params("user_id", "invalid") diff --git a/tests/llm_responses_api_testing/base_responses_api.py b/tests/llm_responses_api_testing/base_responses_api.py index fd39c13604..905b9b3219 100644 --- a/tests/llm_responses_api_testing/base_responses_api.py +++ b/tests/llm_responses_api_testing/base_responses_api.py @@ -189,6 +189,90 @@ class BaseResponsesAPITest(ABC): + @pytest.mark.parametrize("sync_mode", [False, True]) + @pytest.mark.asyncio + async def test_basic_openai_responses_delete_endpoint(self, sync_mode): + litellm._turn_on_debug() + litellm.set_verbose = True + base_completion_call_args = self.get_base_completion_call_args() + if sync_mode: + response = litellm.responses( + input="Basic ping", max_output_tokens=20, + **base_completion_call_args + ) + + # delete the response + if isinstance(response, ResponsesAPIResponse): + litellm.delete_responses( + response_id=response.id, + **base_completion_call_args + ) + else: + raise ValueError("response is not a ResponsesAPIResponse") + else: + response = await litellm.aresponses( + input="Basic ping", max_output_tokens=20, + **base_completion_call_args + ) + + # async delete the response + if isinstance(response, ResponsesAPIResponse): + await litellm.adelete_responses( + response_id=response.id, + **base_completion_call_args + ) + else: + raise ValueError("response is not a ResponsesAPIResponse") + + + @pytest.mark.parametrize("sync_mode", [True, False]) + @pytest.mark.asyncio + async def test_basic_openai_responses_streaming_delete_endpoint(self, sync_mode): + #litellm._turn_on_debug() + #litellm.set_verbose = True + base_completion_call_args = self.get_base_completion_call_args() + response_id = None + if sync_mode: + response_id = None + response = litellm.responses( + input="Basic ping", max_output_tokens=20, + stream=True, + **base_completion_call_args + ) + for event in response: + print("litellm response=", json.dumps(event, indent=4, default=str)) + if "response" in event: + response_obj = event.get("response") + if response_obj is not None: + response_id = response_obj.get("id") + print("got response_id=", response_id) + + # delete the response + assert response_id is not None + litellm.delete_responses( + response_id=response_id, + **base_completion_call_args + ) + else: + response = await litellm.aresponses( + input="Basic ping", max_output_tokens=20, + stream=True, + **base_completion_call_args + ) + async for event in response: + print("litellm response=", json.dumps(event, indent=4, default=str)) + if "response" in event: + response_obj = event.get("response") + if response_obj is not None: + response_id = response_obj.get("id") + print("got response_id=", response_id) + + # delete the response + assert response_id is not None + await litellm.adelete_responses( + response_id=response_id, + **base_completion_call_args + ) diff --git a/tests/llm_responses_api_testing/test_anthropic_responses_api.py b/tests/llm_responses_api_testing/test_anthropic_responses_api.py index 0fcb771f73..b02c9b8d11 100644 --- a/tests/llm_responses_api_testing/test_anthropic_responses_api.py +++ b/tests/llm_responses_api_testing/test_anthropic_responses_api.py @@ -29,6 +29,12 @@ class TestAnthropicResponsesAPITest(BaseResponsesAPITest): return { "model": "anthropic/claude-3-5-sonnet-latest", } + + async def test_basic_openai_responses_delete_endpoint(self, sync_mode=False): + pass + + async def test_basic_openai_responses_streaming_delete_endpoint(self, sync_mode=False): + pass def test_multiturn_tool_calls(): diff --git a/tests/llm_responses_api_testing/test_openai_responses_api.py b/tests/llm_responses_api_testing/test_openai_responses_api.py index b3cd88190b..333f99f9d4 100644 --- a/tests/llm_responses_api_testing/test_openai_responses_api.py +++ b/tests/llm_responses_api_testing/test_openai_responses_api.py @@ -804,7 +804,7 @@ async def test_openai_o1_pro_response_api(sync_mode): print("Response:", json.dumps(response, indent=4, default=str)) # Check that the response has the expected structure - assert response["id"] == mock_response["id"] + assert response["id"] is not None assert response["status"] == "incomplete" assert response["incomplete_details"].reason == "max_output_tokens" assert response["max_output_tokens"] == 20 diff --git a/tests/logging_callback_tests/test_arize_logging.py b/tests/logging_callback_tests/test_arize_logging.py deleted file mode 100644 index aca3ae9a02..0000000000 --- a/tests/logging_callback_tests/test_arize_logging.py +++ /dev/null @@ -1,111 +0,0 @@ -import os -import sys -import time -from unittest.mock import Mock, patch -import json -import opentelemetry.exporter.otlp.proto.grpc.trace_exporter -from typing import Optional - -sys.path.insert( - 0, os.path.abspath("../..") -) # Adds the parent directory to the system-path -from litellm.integrations._types.open_inference import SpanAttributes -from litellm.integrations.arize.arize import ArizeConfig, ArizeLogger -from litellm.integrations.custom_logger import CustomLogger -from litellm.main import completion -import litellm -from litellm.types.utils import Choices, StandardCallbackDynamicParams -import pytest -import asyncio - - -def test_arize_set_attributes(): - """ - Test setting attributes for Arize - """ - from unittest.mock import MagicMock - from litellm.types.utils import ModelResponse - - span = MagicMock() - kwargs = { - "role": "user", - "content": "simple arize test", - "model": "gpt-4o", - "messages": [{"role": "user", "content": "basic arize test"}], - "standard_logging_object": { - "model_parameters": {"user": "test_user"}, - "metadata": {"key": "value", "key2": None}, - }, - } - response_obj = ModelResponse( - usage={"total_tokens": 100, "completion_tokens": 60, "prompt_tokens": 40}, - choices=[Choices(message={"role": "assistant", "content": "response content"})], - ) - - ArizeLogger.set_arize_attributes(span, kwargs, response_obj) - - assert span.set_attribute.call_count == 14 - span.set_attribute.assert_any_call( - SpanAttributes.METADATA, json.dumps({"key": "value", "key2": None}) - ) - span.set_attribute.assert_any_call(SpanAttributes.LLM_MODEL_NAME, "gpt-4o") - span.set_attribute.assert_any_call(SpanAttributes.OPENINFERENCE_SPAN_KIND, "LLM") - span.set_attribute.assert_any_call(SpanAttributes.INPUT_VALUE, "basic arize test") - span.set_attribute.assert_any_call("llm.input_messages.0.message.role", "user") - span.set_attribute.assert_any_call( - "llm.input_messages.0.message.content", "basic arize test" - ) - span.set_attribute.assert_any_call( - SpanAttributes.LLM_INVOCATION_PARAMETERS, '{"user": "test_user"}' - ) - span.set_attribute.assert_any_call(SpanAttributes.USER_ID, "test_user") - span.set_attribute.assert_any_call(SpanAttributes.OUTPUT_VALUE, "response content") - span.set_attribute.assert_any_call( - "llm.output_messages.0.message.role", "assistant" - ) - span.set_attribute.assert_any_call( - "llm.output_messages.0.message.content", "response content" - ) - span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, 100) - span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, 60) - span.set_attribute.assert_any_call(SpanAttributes.LLM_TOKEN_COUNT_PROMPT, 40) - - -class TestArizeLogger(CustomLogger): - def __init__(self, *args, **kwargs): - super().__init__(*args, **kwargs) - self.standard_callback_dynamic_params: Optional[ - StandardCallbackDynamicParams - ] = None - - async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): - print("logged kwargs", json.dumps(kwargs, indent=4, default=str)) - self.standard_callback_dynamic_params = kwargs.get( - "standard_callback_dynamic_params" - ) - - -@pytest.mark.asyncio -async def test_arize_dynamic_params(): - """verify arize ai dynamic params are recieved by a callback""" - test_arize_logger = TestArizeLogger() - litellm.callbacks = [test_arize_logger] - await litellm.acompletion( - model="gpt-4o", - messages=[{"role": "user", "content": "basic arize test"}], - mock_response="test", - arize_api_key="test_api_key_dynamic", - arize_space_key="test_space_key_dynamic", - ) - - await asyncio.sleep(2) - - assert test_arize_logger.standard_callback_dynamic_params is not None - assert ( - test_arize_logger.standard_callback_dynamic_params.get("arize_api_key") - == "test_api_key_dynamic" - ) - assert ( - test_arize_logger.standard_callback_dynamic_params.get("arize_space_key") - == "test_space_key_dynamic" - ) diff --git a/tests/logging_callback_tests/test_unit_tests_init_callbacks.py b/tests/logging_callback_tests/test_unit_tests_init_callbacks.py index 3ffa97be9f..445c773d99 100644 --- a/tests/logging_callback_tests/test_unit_tests_init_callbacks.py +++ b/tests/logging_callback_tests/test_unit_tests_init_callbacks.py @@ -38,6 +38,7 @@ from litellm.integrations.langfuse.langfuse_prompt_management import ( LangfusePromptManagement, ) from litellm.integrations.azure_storage.azure_storage import AzureBlobStorageLogger +from litellm.integrations.agentops import AgentOps from litellm.integrations.humanloop import HumanloopLogger from litellm.proxy.hooks.dynamic_rate_limiter import _PROXY_DynamicRateLimitHandler from unittest.mock import patch @@ -75,6 +76,7 @@ callback_class_str_to_classType = { "pagerduty": PagerDutyAlerting, "gcs_pubsub": GcsPubSubLogger, "anthropic_cache_control_hook": AnthropicCacheControlHook, + "agentops": AgentOps, } expected_env_vars = { diff --git a/tests/proxy_admin_ui_tests/e2e_ui_tests/search_users.spec.ts b/tests/proxy_admin_ui_tests/e2e_ui_tests/search_users.spec.ts new file mode 100644 index 0000000000..7b9da6a27d --- /dev/null +++ b/tests/proxy_admin_ui_tests/e2e_ui_tests/search_users.spec.ts @@ -0,0 +1,214 @@ +/* +Search Users in Admin UI +E2E Test for user search functionality + +Tests: +1. Navigate to Internal Users tab +2. Verify search input exists +3. Test search functionality +4. Verify results update +5. Test filtering by email, user ID, and SSO user ID +*/ + +import { test, expect } from "@playwright/test"; + +test("user search test", async ({ page }) => { + // Set a longer timeout for the entire test + test.setTimeout(60000); + + // Enable console logging + page.on("console", (msg) => console.log("PAGE LOG:", msg.text())); + + // Login first + await page.goto("http://localhost:4000/ui"); + console.log("Navigated to login page"); + + // Wait for login form to be visible + await page.waitForSelector('input[name="username"]', { timeout: 10000 }); + console.log("Login form is visible"); + + await page.fill('input[name="username"]', "admin"); + await page.fill('input[name="password"]', "gm"); + console.log("Filled login credentials"); + + const loginButton = page.locator('input[type="submit"]'); + await expect(loginButton).toBeEnabled(); + await loginButton.click(); + console.log("Clicked login button"); + + // Wait for navigation to complete and dashboard to load + await page.waitForLoadState("networkidle"); + console.log("Page loaded after login"); + + // Take a screenshot for debugging + await page.screenshot({ path: "after-login.png" }); + console.log("Took screenshot after login"); + + // Try to find the Internal User tab with more debugging + console.log("Looking for Internal User tab..."); + const internalUserTab = page.locator("span.ant-menu-title-content", { + hasText: "Internal User", + }); + + // Wait for the tab to be visible + await internalUserTab.waitFor({ state: "visible", timeout: 10000 }); + console.log("Internal User tab is visible"); + + // Take another screenshot before clicking + await page.screenshot({ path: "before-tab-click.png" }); + console.log("Took screenshot before tab click"); + + await internalUserTab.click(); + console.log("Clicked Internal User tab"); + + // Wait for the page to load and table to be visible + await page.waitForSelector("tbody tr", { timeout: 30000 }); + await page.waitForTimeout(2000); // Additional wait for table to stabilize + console.log("Table is visible"); + + // Take a final screenshot + await page.screenshot({ path: "after-tab-click.png" }); + console.log("Took screenshot after tab click"); + + // Verify search input exists + const searchInput = page.locator('input[placeholder="Search by email..."]'); + await expect(searchInput).toBeVisible(); + console.log("Search input is visible"); + + // Test search functionality + const initialUserCount = await page.locator("tbody tr").count(); + console.log(`Initial user count: ${initialUserCount}`); + + // Perform a search + const testEmail = "test@"; + await searchInput.fill(testEmail); + console.log("Filled search input"); + + // Wait for the debounced search to complete + await page.waitForTimeout(500); + console.log("Waited for debounce"); + + // Wait for the results count to update + await page.waitForFunction((initialCount) => { + const currentCount = document.querySelectorAll("tbody tr").length; + return currentCount !== initialCount; + }, initialUserCount); + console.log("Results updated"); + + const filteredUserCount = await page.locator("tbody tr").count(); + console.log(`Filtered user count: ${filteredUserCount}`); + + expect(filteredUserCount).toBeDefined(); + + // Clear the search + await searchInput.clear(); + console.log("Cleared search"); + + await page.waitForTimeout(500); + console.log("Waited for debounce after clear"); + + await page.waitForFunction((initialCount) => { + const currentCount = document.querySelectorAll("tbody tr").length; + return currentCount === initialCount; + }, initialUserCount); + console.log("Results reset"); + + const resetUserCount = await page.locator("tbody tr").count(); + console.log(`Reset user count: ${resetUserCount}`); + + expect(resetUserCount).toBe(initialUserCount); +}); + +test("user filter test", async ({ page }) => { + // Set a longer timeout for the entire test + test.setTimeout(60000); + + // Enable console logging + page.on("console", (msg) => console.log("PAGE LOG:", msg.text())); + + // Login first + await page.goto("http://localhost:4000/ui"); + console.log("Navigated to login page"); + + // Wait for login form to be visible + await page.waitForSelector('input[name="username"]', { timeout: 10000 }); + console.log("Login form is visible"); + + await page.fill('input[name="username"]', "admin"); + await page.fill('input[name="password"]', "gm"); + console.log("Filled login credentials"); + + const loginButton = page.locator('input[type="submit"]'); + await expect(loginButton).toBeEnabled(); + await loginButton.click(); + console.log("Clicked login button"); + + // Wait for navigation to complete and dashboard to load + await page.waitForLoadState("networkidle"); + console.log("Page loaded after login"); + + // Navigate to Internal Users tab + const internalUserTab = page.locator("span.ant-menu-title-content", { + hasText: "Internal User", + }); + await internalUserTab.waitFor({ state: "visible", timeout: 10000 }); + await internalUserTab.click(); + console.log("Clicked Internal User tab"); + + // Wait for the page to load and table to be visible + await page.waitForSelector("tbody tr", { timeout: 30000 }); + await page.waitForTimeout(2000); // Additional wait for table to stabilize + console.log("Table is visible"); + + // Get initial user count + const initialUserCount = await page.locator("tbody tr").count(); + console.log(`Initial user count: ${initialUserCount}`); + + // Click the filter button to show additional filters + const filterButton = page.getByRole("button", { + name: "Filters", + exact: true, + }); + await filterButton.click(); + console.log("Clicked filter button"); + await page.waitForTimeout(500); // Wait for filters to appear + + // Test user ID filter + const userIdInput = page.locator('input[placeholder="Filter by User ID"]'); + await expect(userIdInput).toBeVisible(); + console.log("User ID filter is visible"); + + await userIdInput.fill("user"); + console.log("Filled user ID filter"); + await page.waitForTimeout(1000); + const userIdFilteredCount = await page.locator("tbody tr").count(); + console.log(`User ID filtered count: ${userIdFilteredCount}`); + expect(userIdFilteredCount).toBeLessThan(initialUserCount); + + // Clear user ID filter + await userIdInput.clear(); + await page.waitForTimeout(1000); + console.log("Cleared user ID filter"); + + // Test SSO user ID filter + const ssoUserIdInput = page.locator('input[placeholder="Filter by SSO ID"]'); + await expect(ssoUserIdInput).toBeVisible(); + console.log("SSO user ID filter is visible"); + + await ssoUserIdInput.fill("sso"); + console.log("Filled SSO user ID filter"); + await page.waitForTimeout(1000); + const ssoUserIdFilteredCount = await page.locator("tbody tr").count(); + console.log(`SSO user ID filtered count: ${ssoUserIdFilteredCount}`); + expect(ssoUserIdFilteredCount).toBeLessThan(initialUserCount); + + // Clear SSO user ID filter + await ssoUserIdInput.clear(); + await page.waitForTimeout(5000); + console.log("Cleared SSO user ID filter"); + + // Verify count returns to initial after clearing all filters + const finalUserCount = await page.locator("tbody tr").count(); + console.log(`Final user count: ${finalUserCount}`); + expect(finalUserCount).toBe(initialUserCount); +}); diff --git a/tests/proxy_admin_ui_tests/e2e_ui_tests/view_internal_user.spec.ts b/tests/proxy_admin_ui_tests/e2e_ui_tests/view_internal_user.spec.ts index 4d27a4a7ce..bb6df91c39 100644 --- a/tests/proxy_admin_ui_tests/e2e_ui_tests/view_internal_user.spec.ts +++ b/tests/proxy_admin_ui_tests/e2e_ui_tests/view_internal_user.spec.ts @@ -2,45 +2,74 @@ Test view internal user page */ -import { test, expect } from '@playwright/test'; +import { test, expect } from "@playwright/test"; -test('view internal user page', async ({ page }) => { +test("view internal user page", async ({ page }) => { // Go to the specified URL - await page.goto('http://localhost:4000/ui'); + await page.goto("http://localhost:4000/ui"); // Enter "admin" in the username input field - await page.fill('input[name="username"]', 'admin'); + await page.fill('input[name="username"]', "admin"); // Enter "gm" in the password input field - await page.fill('input[name="password"]', 'gm'); + await page.fill('input[name="password"]', "gm"); - // Optionally, you can add an assertion to verify the login button is enabled + // Click the login button const loginButton = page.locator('input[type="submit"]'); await expect(loginButton).toBeEnabled(); - - // Optionally, you can click the login button to submit the form await loginButton.click(); - const tabElement = page.locator('span.ant-menu-title-content', { hasText: 'Internal User' }); + // Wait for the Internal User tab and click it + const tabElement = page.locator("span.ant-menu-title-content", { + hasText: "Internal User", + }); await tabElement.click(); - // try to click on button - // - // wait 1-2 seconds - await page.waitForTimeout(10000); + // Wait for the table to load + await page.waitForSelector("tbody tr", { timeout: 10000 }); + await page.waitForTimeout(2000); // Additional wait for table to stabilize - // Test all expected fields are present - // number of keys owned by user - const keysBadges = page.locator('p.tremor-Badge-text.text-sm.whitespace-nowrap', { hasText: 'Keys' }); - const keysCountArray = await keysBadges.evaluateAll(elements => elements.map(el => parseInt(el.textContent.split(' ')[0], 10))); + // Test all expected fields are present + // number of keys owned by user + const keysBadges = page.locator( + "p.tremor-Badge-text.text-sm.whitespace-nowrap", + { hasText: "Keys" } + ); + const keysCountArray = await keysBadges.evaluateAll((elements) => + elements.map((el) => { + const text = el.textContent; + return text ? parseInt(text.split(" ")[0], 10) : 0; + }) + ); - const hasNonZeroKeys = keysCountArray.some(count => count > 0); + const hasNonZeroKeys = keysCountArray.some((count) => count > 0); expect(hasNonZeroKeys).toBe(true); // test pagination - const prevButton = page.locator('button.px-3.py-1.text-sm.border.rounded-md.hover\\:bg-gray-50.disabled\\:opacity-50.disabled\\:cursor-not-allowed', { hasText: 'Previous' }); - await expect(prevButton).toBeDisabled(); + // Wait for pagination controls to be visible + await page.waitForSelector(".flex.justify-between.items-center", { + timeout: 5000, + }); - const nextButton = page.locator('button.px-3.py-1.text-sm.border.rounded-md.hover\\:bg-gray-50.disabled\\:opacity-50.disabled\\:cursor-not-allowed', { hasText: 'Next' }); - await expect(nextButton).toBeEnabled(); + // Check if we're on the first page by looking at the results count + const resultsText = + (await page.locator(".text-sm.text-gray-700").textContent()) || ""; + const isFirstPage = resultsText.includes("1 -"); + + if (isFirstPage) { + // On first page, previous button should be disabled + const prevButton = page.locator("button", { hasText: "Previous" }); + await expect(prevButton).toBeDisabled(); + } + + // Next button should be enabled if there are more pages + const nextButton = page.locator("button", { hasText: "Next" }); + const totalResults = + (await page.locator(".text-sm.text-gray-700").textContent()) || ""; + const hasMorePages = + totalResults.includes("of") && !totalResults.includes("1 - 25 of 25"); + + if (hasMorePages) { + await expect(nextButton).toBeEnabled(); + } }); diff --git a/tests/proxy_admin_ui_tests/e2e_ui_tests/view_user_info.spec.ts b/tests/proxy_admin_ui_tests/e2e_ui_tests/view_user_info.spec.ts new file mode 100644 index 0000000000..cc138f0946 --- /dev/null +++ b/tests/proxy_admin_ui_tests/e2e_ui_tests/view_user_info.spec.ts @@ -0,0 +1,82 @@ +import { test, expect } from "@playwright/test"; +import { loginToUI } from "../utils/login"; + +test.describe("User Info View", () => { + test.beforeEach(async ({ page }) => { + await loginToUI(page); + // Navigate to users page + await page.goto("http://localhost:4000/ui?page=users"); + }); + + test("should display user info when clicking on user ID", async ({ + page, + }) => { + // Wait for users table to load + await page.waitForSelector("table"); + + // Get the first user ID cell + const firstUserIdCell = page.locator( + "table tbody tr:first-child td:first-child" + ); + const userId = await firstUserIdCell.textContent(); + console.log("Found user ID:", userId); + + // Click on the user ID + await firstUserIdCell.click(); + + // Wait for user info view to load + await page.waitForSelector('h1:has-text("User")'); + console.log("User info view loaded"); + + // Check for tabs + await expect(page.locator('button:has-text("Overview")')).toBeVisible(); + await expect(page.locator('button:has-text("Details")')).toBeVisible(); + + // Switch to details tab + await page.locator('button:has-text("Details")').click(); + + // Check details section + await expect(page.locator("text=User ID")).toBeVisible(); + await expect(page.locator("text=Email")).toBeVisible(); + + // Go back to users list + await page.locator('button:has-text("Back to Users")').click(); + + // Verify we're back on the users page + await expect(page.locator('h1:has-text("Users")')).toBeVisible(); + }); + + // test("should handle user deletion", async ({ page }) => { + // // Wait for users table to load + // await page.waitForSelector("table"); + + // // Get the first user ID cell + // const firstUserIdCell = page.locator( + // "table tbody tr:first-child td:first-child" + // ); + // const userId = await firstUserIdCell.textContent(); + + // // Click on the user ID + // await firstUserIdCell.click(); + + // // Wait for user info view to load + // await page.waitForSelector('h1:has-text("User")'); + + // // Click delete button + // await page.locator('button:has-text("Delete User")').click(); + + // // Confirm deletion in modal + // await page.locator('button:has-text("Delete")').click(); + + // // Verify success message + // await expect(page.locator("text=User deleted successfully")).toBeVisible(); + + // // Verify we're back on the users page + // await expect(page.locator('h1:has-text("Users")')).toBeVisible(); + + // // Verify user is no longer in the table + // if (userId) { + // await expect(page.locator(`text=${userId}`)).not.toBeVisible(); + // } + // }); +}); diff --git a/tests/proxy_admin_ui_tests/test-results/.last-run.json b/tests/proxy_admin_ui_tests/test-results/.last-run.json new file mode 100644 index 0000000000..0c96e15dce --- /dev/null +++ b/tests/proxy_admin_ui_tests/test-results/.last-run.json @@ -0,0 +1,8 @@ +{ + "status": "failed", + "failedTests": [ + "8306bf902634636ae770-183086b993a71bc98dd6", + "1bfc70f64c2dd4741dbb-58cd256736ebe53a2d97", + "ea1c46def20befad7a54-cb6c473c41474485b610" + ] +} \ No newline at end of file diff --git a/tests/proxy_admin_ui_tests/utils/login.ts b/tests/proxy_admin_ui_tests/utils/login.ts new file mode 100644 index 0000000000..e875508997 --- /dev/null +++ b/tests/proxy_admin_ui_tests/utils/login.ts @@ -0,0 +1,23 @@ +import { Page, expect } from "@playwright/test"; + +export async function loginToUI(page: Page) { + // Login first + await page.goto("http://localhost:4000/ui"); + console.log("Navigated to login page"); + + // Wait for login form to be visible + await page.waitForSelector('input[name="username"]', { timeout: 10000 }); + console.log("Login form is visible"); + + await page.fill('input[name="username"]', "admin"); + await page.fill('input[name="password"]', "gm"); + console.log("Filled login credentials"); + + const loginButton = page.locator('input[type="submit"]'); + await expect(loginButton).toBeEnabled(); + await loginButton.click(); + console.log("Clicked login button"); + + // Wait for navigation to complete + await page.waitForURL("**/*"); +} diff --git a/tests/test_keys.py b/tests/test_keys.py index eaf9369d89..89b54ba92c 100644 --- a/tests/test_keys.py +++ b/tests/test_keys.py @@ -109,6 +109,18 @@ async def test_key_gen(): await asyncio.gather(*tasks) +@pytest.mark.asyncio +async def test_simple_key_gen(): + async with aiohttp.ClientSession() as session: + key_data = await generate_key(session, i=0) + key = key_data["key"] + assert key_data["token"] is not None + assert key_data["token"] != key + assert key_data["token_id"] is not None + assert key_data["created_at"] is not None + assert key_data["updated_at"] is not None + + @pytest.mark.asyncio async def test_key_gen_bad_key(): """ diff --git a/ui/litellm-dashboard/src/components/networking.tsx b/ui/litellm-dashboard/src/components/networking.tsx index f16aaf30fa..e518314e64 100644 --- a/ui/litellm-dashboard/src/components/networking.tsx +++ b/ui/litellm-dashboard/src/components/networking.tsx @@ -676,6 +676,12 @@ export const userListCall = async ( userIDs: string[] | null = null, page: number | null = null, page_size: number | null = null, + userEmail: string | null = null, + userRole: string | null = null, + team: string | null = null, + sso_user_id: string | null = null, + sortBy: string | null = null, + sortOrder: 'asc' | 'desc' | null = null, ) => { /** * Get all available teams on proxy @@ -698,6 +704,30 @@ export const userListCall = async ( if (page_size) { queryParams.append('page_size', page_size.toString()); } + + if (userEmail) { + queryParams.append('user_email', userEmail); + } + + if (userRole) { + queryParams.append('role', userRole); + } + + if (team) { + queryParams.append('team', team); + } + + if (sso_user_id) { + queryParams.append('sso_user_ids', sso_user_id); + } + + if (sortBy) { + queryParams.append('sort_by', sortBy); + } + + if (sortOrder) { + queryParams.append('sort_order', sortOrder); + } const queryString = queryParams.toString(); if (queryString) { @@ -736,8 +766,10 @@ export const userInfoCall = async ( userRole: String, viewAll: Boolean = false, page: number | null, - page_size: number | null + page_size: number | null, + lookup_user_id: boolean = false ) => { + console.log(`userInfoCall: ${userID}, ${userRole}, ${viewAll}, ${page}, ${page_size}, ${lookup_user_id}`) try { let url: string; @@ -751,7 +783,7 @@ export const userInfoCall = async ( } else { // Use /user/info endpoint for individual user info url = proxyBaseUrl ? `${proxyBaseUrl}/user/info` : `/user/info`; - if (userRole === "Admin" || userRole === "Admin Viewer") { + if ((userRole === "Admin" || userRole === "Admin Viewer") && !lookup_user_id) { // do nothing } else if (userID) { url += `?user_id=${userID}`; diff --git a/ui/litellm-dashboard/src/components/view_users.tsx b/ui/litellm-dashboard/src/components/view_users.tsx index 6052269586..1fdcbc5a09 100644 --- a/ui/litellm-dashboard/src/components/view_users.tsx +++ b/ui/litellm-dashboard/src/components/view_users.tsx @@ -1,4 +1,4 @@ -import React, { useState, useEffect } from "react"; +import React, { useState, useEffect, useCallback, useRef } from "react"; import { Card, Title, @@ -23,6 +23,7 @@ import { DialogPanel, Icon, TextInput, + NumberInput, } from "@tremor/react"; import { message } from "antd"; @@ -32,6 +33,7 @@ import { userInfoCall, userUpdateUserCall, getPossibleUserRoles, + userListCall, } from "./networking"; import { Badge, BadgeDelta, Button } from "@tremor/react"; import RequestAccess from "./request_model_access"; @@ -50,6 +52,7 @@ import { UserDataTable } from "./view_users/table"; import { UserInfo } from "./view_users/types"; import BulkCreateUsers from "./bulk_create_users_button"; import SSOSettings from "./SSOSettings"; +import debounce from "lodash/debounce"; interface ViewUserDashboardProps { accessToken: string | null; @@ -77,6 +80,19 @@ interface CreateuserProps { onUserCreated: () => Promise; } +interface FilterState { + email: string; + user_id: string; + user_role: string; + sso_user_id: string; + team: string; + model: string; + min_spend: number | null; + max_spend: number | null; + sort_by: string; + sort_order: 'asc' | 'desc'; +} + const isLocal = process.env.NODE_ENV === "development"; const proxyBaseUrl = isLocal ? "http://localhost:4000" : null; if (isLocal != true) { @@ -93,7 +109,6 @@ const ViewUserDashboard: React.FC = ({ setKeys, }) => { const [userListResponse, setUserListResponse] = useState(null); - const [userData, setUserData] = useState(null); const [endUsers, setEndUsers] = useState(null); const [currentPage, setCurrentPage] = useState(1); const [openDialogId, setOpenDialogId] = React.useState(null); @@ -108,6 +123,23 @@ const ViewUserDashboard: React.FC = ({ const defaultPageSize = 25; const [searchTerm, setSearchTerm] = useState(""); const [activeTab, setActiveTab] = useState("users"); + const [filters, setFilters] = useState({ + email: "", + user_id: "", + user_role: "", + sso_user_id: "", + team: "", + model: "", + min_spend: null, + max_spend: null, + sort_by: "created_at", + sort_order: "desc" + }); + const [showFilters, setShowFilters] = useState(false); + const [showColumnDropdown, setShowColumnDropdown] = useState(false); + const [selectedFilter, setSelectedFilter] = useState("Email"); + const filtersRef = useRef(null); + const lastSearchTimestamp = useRef(0); // check if window is not undefined if (typeof window !== "undefined") { @@ -122,15 +154,88 @@ const ViewUserDashboard: React.FC = ({ setIsDeleteModalOpen(true); }; + const handleFilterChange = (key: keyof FilterState, value: string | number | null) => { + const newFilters = { ...filters, [key]: value }; + setFilters(newFilters); + console.log("called from handleFilterChange - newFilters:", JSON.stringify(newFilters)); + debouncedSearch(newFilters); + }; + + const handleSortChange = (sortBy: string, sortOrder: 'asc' | 'desc') => { + const newFilters = { + ...filters, + sort_by: sortBy, + sort_order: sortOrder + }; + setFilters(newFilters); + debouncedSearch(newFilters); + }; + + // Create a debounced version of the search function + const debouncedSearch = useCallback( + debounce(async (filters: FilterState) => { + if (!accessToken || !token || !userRole || !userID) { + return; + } + + const currentTimestamp = Date.now(); + lastSearchTimestamp.current = currentTimestamp; + + try { + // Make the API call using userListCall with all filter parameters + const data = await userListCall( + accessToken, + filters.user_id ? [filters.user_id] : null, + 1, // Reset to first page when searching + defaultPageSize, + filters.email || null, + filters.user_role || null, + filters.team || null, + filters.sso_user_id || null, + filters.sort_by, + filters.sort_order + ); + + // Only update state if this is the most recent search + if (currentTimestamp === lastSearchTimestamp.current) { + if (data) { + setUserListResponse(data); + console.log("called from debouncedSearch filters:", JSON.stringify(filters)); + console.log("called from debouncedSearch data:", JSON.stringify(data)); + } + } + } catch (error) { + console.error("Error searching users:", error); + } + }, 300), + [accessToken, token, userRole, userID] + ); + + // Cleanup the debounced function on component unmount + useEffect(() => { + return () => { + debouncedSearch.cancel(); + }; + }, [debouncedSearch]); + + const handleSearch = (value: string) => { + setSearchTerm(value); + if (value === "") { + refreshUserData(); // Reset to original data when search is cleared + } else { + debouncedSearch(filters); + } + }; + const confirmDelete = async () => { if (userToDelete && accessToken) { try { await userDeleteCall(accessToken, [userToDelete]); message.success("User deleted successfully"); // Update the user list after deletion - if (userData) { - const updatedUserData = userData.filter(user => user.user_id !== userToDelete); - setUserData(updatedUserData); + if (userListResponse) { + const updatedUserData = userListResponse.users?.filter(user => user.user_id !== userToDelete); + setUserListResponse({ ...userListResponse, users: updatedUserData || [] }); } } catch (error) { console.error("Error deleting user:", error); @@ -164,11 +269,11 @@ const ViewUserDashboard: React.FC = ({ } catch (error) { console.error("There was an error updating the user", error); } - if (userData) { - const updatedUserData = userData.map((user) => + if (userListResponse) { + const updatedUserData = userListResponse.users?.map((user) => user.user_id === editedUser.user_id ? editedUser : user ); - setUserData(updatedUserData); + setUserListResponse({ ...userListResponse, users: updatedUserData || [] }); } setSelectedUser(null); setEditModalVisible(false); @@ -176,6 +281,7 @@ const ViewUserDashboard: React.FC = ({ }; const refreshUserData = async () => { + console.log("called from refreshUserData"); if (!accessToken || !token || !userRole || !userID) { return; } @@ -195,14 +301,45 @@ const ViewUserDashboard: React.FC = ({ `userList_${currentPage}`, JSON.stringify(userDataResponse) ); - + console.log("called from refreshUserData"); setUserListResponse(userDataResponse); - setUserData(userDataResponse.users || []); } catch (error) { console.error("Error refreshing user data:", error); } }; + const handlePageChange = async (newPage: number) => { + if (!accessToken || !token || !userRole || !userID) { + return; + } + + try { + const userDataResponse = await userListCall( + accessToken, + filters.user_id ? [filters.user_id] : null, + newPage, + defaultPageSize, + filters.email || null, + filters.user_role || null, + filters.team || null, + filters.sso_user_id || null, + filters.sort_by, + filters.sort_order + ); + + // Update session storage with new data + sessionStorage.setItem( + `userList_${newPage}`, + JSON.stringify(userDataResponse) + ); + + setUserListResponse(userDataResponse); + setCurrentPage(newPage); + } catch (error) { + console.error("Error changing page:", error); + } + }; + useEffect(() => { if (!accessToken || !token || !userRole || !userID) { return; @@ -214,16 +351,20 @@ const ViewUserDashboard: React.FC = ({ if (cachedUserData) { const parsedData = JSON.parse(cachedUserData); setUserListResponse(parsedData); - setUserData(parsedData.users || []); + console.log("called from useEffect"); } else { - // Fetch from API if not in cache - const userDataResponse = await userInfoCall( + // Fetch from API using userListCall with current filters + const userDataResponse = await userListCall( accessToken, - null, - userRole, - true, + filters.user_id ? [filters.user_id] : null, currentPage, - defaultPageSize + defaultPageSize, + filters.email || null, + filters.user_role || null, + filters.team || null, + filters.sso_user_id || null, + filters.sort_by, + filters.sort_order ); // Store in session storage @@ -233,7 +374,7 @@ const ViewUserDashboard: React.FC = ({ ); setUserListResponse(userDataResponse); - setUserData(userDataResponse.users || []); + console.log("called from useEffect 2"); } // Fetch roles if not cached @@ -254,9 +395,9 @@ const ViewUserDashboard: React.FC = ({ fetchData(); } - }, [accessToken, token, userRole, userID, currentPage]); + }, [accessToken, token, userRole, userID]); - if (!userData) { + if (!userListResponse) { return
Loading...
; } @@ -297,8 +438,164 @@ const ViewUserDashboard: React.FC = ({
-
-
+
+ {/* Search and Filter Controls */} +
+ {/* Email Search */} +
+ handleFilterChange('email', e.target.value)} + /> + + + +
+ + {/* Filter Button */} + + + {/* Reset Filters Button */} + +
+ + {/* Additional Filters */} + {showFilters && ( +
+ {/* User ID Search */} +
+ handleFilterChange('user_id', e.target.value)} + /> + + + +
+ + {/* Role Dropdown */} +
+ +
+ + {/* Team Dropdown */} +
+ +
+ + {/* SSO ID Search */} +
+ handleFilterChange('sso_user_id', e.target.value)} + /> +
+
+ )} + + {/* Results Count and Pagination */} +
Showing{" "} {userListResponse && userListResponse.users && userListResponse.users.length > 0 @@ -313,25 +610,28 @@ const ViewUserDashboard: React.FC = ({ : 0}{" "} of {userListResponse ? userListResponse.total : 0} results -
+ + {/* Pagination Buttons */} +
- - Page {userListResponse ? userListResponse.page : "-"} of{" "} - {userListResponse ? userListResponse.total_pages : "-"} - @@ -339,10 +639,18 @@ const ViewUserDashboard: React.FC = ({
+
diff --git a/ui/litellm-dashboard/src/components/view_users/table.tsx b/ui/litellm-dashboard/src/components/view_users/table.tsx index c426b42127..7674a6491f 100644 --- a/ui/litellm-dashboard/src/components/view_users/table.tsx +++ b/ui/litellm-dashboard/src/components/view_users/table.tsx @@ -18,21 +18,37 @@ import { } from "@tremor/react"; import { SwitchVerticalIcon, ChevronUpIcon, ChevronDownIcon } from "@heroicons/react/outline"; import { UserInfo } from "./types"; +import UserInfoView from "./user_info_view"; interface UserDataTableProps { data: UserInfo[]; columns: ColumnDef[]; isLoading?: boolean; + onSortChange?: (sortBy: string, sortOrder: 'asc' | 'desc') => void; + currentSort?: { + sortBy: string; + sortOrder: 'asc' | 'desc'; + }; + accessToken: string | null; + userRole: string | null; } export function UserDataTable({ data = [], columns, isLoading = false, + onSortChange, + currentSort, + accessToken, + userRole, }: UserDataTableProps) { const [sorting, setSorting] = React.useState([ - { id: "created_at", desc: true } + { + id: currentSort?.sortBy || "created_at", + desc: currentSort?.sortOrder === "desc" + } ]); + const [selectedUserId, setSelectedUserId] = React.useState(null); const table = useReactTable({ data, @@ -40,12 +56,49 @@ export function UserDataTable({ state: { sorting, }, - onSortingChange: setSorting, + onSortingChange: (newSorting: any) => { + setSorting(newSorting); + if (newSorting.length > 0) { + const sortState = newSorting[0]; + const sortBy = sortState.id; + const sortOrder = sortState.desc ? 'desc' : 'asc'; + onSortChange?.(sortBy, sortOrder); + } + }, getCoreRowModel: getCoreRowModel(), getSortedRowModel: getSortedRowModel(), enableSorting: true, }); + const handleUserClick = (userId: string) => { + setSelectedUserId(userId); + }; + + const handleCloseUserInfo = () => { + setSelectedUserId(null); + }; + + // Update local sorting state when currentSort prop changes + React.useEffect(() => { + if (currentSort) { + setSorting([{ + id: currentSort.sortBy, + desc: currentSort.sortOrder === 'desc' + }]); + } + }, [currentSort]); + + if (selectedUserId) { + return ( + + ); + } + return (
@@ -110,6 +163,15 @@ export function UserDataTable({ ? 'sticky right-0 bg-white shadow-[-4px_0_8px_-6px_rgba(0,0,0,0.1)]' : '' }`} + onClick={() => { + if (cell.column.id === 'user_id') { + handleUserClick(cell.getValue() as string); + } + }} + style={{ + cursor: cell.column.id === 'user_id' ? 'pointer' : 'default', + color: cell.column.id === 'user_id' ? '#3b82f6' : 'inherit', + }} > {flexRender(cell.column.columnDef.cell, cell.getContext())} diff --git a/ui/litellm-dashboard/src/components/view_users/user_info_view.tsx b/ui/litellm-dashboard/src/components/view_users/user_info_view.tsx new file mode 100644 index 0000000000..4e82f20821 --- /dev/null +++ b/ui/litellm-dashboard/src/components/view_users/user_info_view.tsx @@ -0,0 +1,297 @@ +import React, { useState } from "react"; +import { + Card, + Text, + Button, + Grid, + Col, + Tab, + TabList, + TabGroup, + TabPanel, + TabPanels, + Title, + Badge, +} from "@tremor/react"; +import { ArrowLeftIcon, TrashIcon } from "@heroicons/react/outline"; +import { userInfoCall, userDeleteCall } from "../networking"; +import { message } from "antd"; +import { rolesWithWriteAccess } from '../../utils/roles'; + +interface UserInfoViewProps { + userId: string; + onClose: () => void; + accessToken: string | null; + userRole: string | null; + onDelete?: () => void; +} + +interface UserInfo { + user_id: string; + user_info: { + user_email: string | null; + user_role: string | null; + teams: any[] | null; + models: string[] | null; + max_budget: number | null; + spend: number | null; + metadata: Record | null; + created_at: string | null; + updated_at: string | null; + }; + keys: any[] | null; + teams: any[] | null; +} + +export default function UserInfoView({ userId, onClose, accessToken, userRole, onDelete }: UserInfoViewProps) { + const [userData, setUserData] = useState(null); + const [isDeleteModalOpen, setIsDeleteModalOpen] = useState(false); + const [isLoading, setIsLoading] = useState(true); + + React.useEffect(() => { + console.log(`userId: ${userId}, userRole: ${userRole}, accessToken: ${accessToken}`) + const fetchUserData = async () => { + try { + if (!accessToken) return; + const data = await userInfoCall(accessToken, userId, userRole || "", false, null, null, true); + setUserData(data); + } catch (error) { + console.error("Error fetching user data:", error); + message.error("Failed to fetch user data"); + } finally { + setIsLoading(false); + } + }; + + fetchUserData(); + }, [accessToken, userId, userRole]); + + const handleDelete = async () => { + try { + if (!accessToken) return; + await userDeleteCall(accessToken, [userId]); + message.success("User deleted successfully"); + if (onDelete) { + onDelete(); + } + onClose(); + } catch (error) { + console.error("Error deleting user:", error); + message.error("Failed to delete user"); + } + }; + + if (isLoading) { + return ( +
+ + Loading user data... +
+ ); + } + + if (!userData) { + return ( +
+ + User not found +
+ ); + } + + return ( +
+
+
+ + {userData.user_info?.user_email || "User"} + {userData.user_id} +
+ {userRole && rolesWithWriteAccess.includes(userRole) && ( + + )} +
+ + {/* Delete Confirmation Modal */} + {isDeleteModalOpen && ( +
+
+ + + + +
+
+
+
+

+ Delete User +

+
+

+ Are you sure you want to delete this user? +

+
+
+
+
+
+ + +
+
+
+
+ )} + + + + Overview + Details + + + + {/* Overview Panel */} + + + + Spend +
+ ${Number(userData.user_info?.spend || 0).toFixed(4)} + of {userData.user_info?.max_budget !== null ? `$${userData.user_info.max_budget}` : "Unlimited"} +
+ + + + Teams +
+ {userData.teams?.length || 0} teams +
+ + + + API Keys +
+ {userData.keys?.length || 0} keys +
+ + + + + {/* Details Panel */} + + +
+
+ User ID + {userData.user_id} +
+ +
+ Email + {userData.user_info?.user_email || "Not Set"} +
+ +
+ Role + {userData.user_info?.user_role || "Not Set"} +
+ +
+ Created + {userData.user_info?.created_at ? new Date(userData.user_info.created_at).toLocaleString() : "Unknown"} +
+ +
+ Last Updated + {userData.user_info?.updated_at ? new Date(userData.user_info.updated_at).toLocaleString() : "Unknown"} +
+ +
+ Teams +
+ {userData.teams?.length && userData.teams?.length > 0 ? ( + userData.teams?.map((team, index) => ( + + {team.team_alias || team.team_id} + + )) + ) : ( + No teams + )} +
+
+ +
+ API Keys +
+ {userData.keys?.length && userData.keys?.length > 0 ? ( + userData.keys.map((key, index) => ( + + {key.key_alias || key.token} + + )) + ) : ( + No API keys + )} +
+
+ +
+ Metadata + 
+                    {JSON.stringify(userData.user_info?.metadata || {}, null, 2)}
+
+
+
+ + + + +
+ ); +} \ No newline at end of file