forked from phoenix/litellm-mirror
Litellm dev 10 26 2024 (#6472)
* docs(exception_mapping.md): add missing exception types Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183 * fix(main.py): register custom model pricing with specific key Ensure custom model pricing is registered to the specific model+provider key combination * test: make testing more robust for custom pricing * fix(redis_cache.py): instrument otel logging for sync redis calls ensures complete coverage for all redis cache calls
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9 changed files with 310 additions and 72 deletions
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@ -2,18 +2,33 @@
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LiteLLM maps exceptions across all providers to their OpenAI counterparts.
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| Status Code | Error Type |
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|-------------|--------------------------|
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| 400 | BadRequestError |
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| 401 | AuthenticationError |
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| 403 | PermissionDeniedError |
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| 404 | NotFoundError |
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| 422 | UnprocessableEntityError |
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| 429 | RateLimitError |
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| >=500 | InternalServerError |
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| N/A | ContextWindowExceededError|
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| 400 | ContentPolicyViolationError|
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| 500 | APIConnectionError |
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All exceptions can be imported from `litellm` - e.g. `from litellm import BadRequestError`
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## LiteLLM Exceptions
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| Status Code | Error Type | Inherits from | Description |
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|-------------|--------------------------|---------------|-------------|
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| 400 | BadRequestError | openai.BadRequestError |
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| 400 | UnsupportedParamsError | litellm.BadRequestError | Raised when unsupported params are passed |
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| 400 | ContextWindowExceededError| litellm.BadRequestError | Special error type for context window exceeded error messages - enables context window fallbacks |
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| 400 | ContentPolicyViolationError| litellm.BadRequestError | Special error type for content policy violation error messages - enables content policy fallbacks |
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| 400 | InvalidRequestError | openai.BadRequestError | Deprecated error, use BadRequestError instead |
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| 401 | AuthenticationError | openai.AuthenticationError |
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| 403 | PermissionDeniedError | openai.PermissionDeniedError |
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| 404 | NotFoundError | openai.NotFoundError | raise when invalid models passed, example gpt-8 |
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| 408 | Timeout | openai.APITimeoutError | Raised when a timeout occurs |
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| 422 | UnprocessableEntityError | openai.UnprocessableEntityError |
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| 429 | RateLimitError | openai.RateLimitError |
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| 500 | APIConnectionError | openai.APIConnectionError | If any unmapped error is returned, we return this error |
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| 500 | APIError | openai.APIError | Generic 500-status code error |
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| 503 | ServiceUnavailableError | openai.APIStatusError | If provider returns a service unavailable error, this error is raised |
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| >=500 | InternalServerError | openai.InternalServerError | If any unmapped 500-status code error is returned, this error is raised |
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| N/A | APIResponseValidationError | openai.APIResponseValidationError | If Rules are used, and request/response fails a rule, this error is raised |
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| N/A | BudgetExceededError | Exception | Raised for proxy, when budget is exceeded |
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| N/A | JSONSchemaValidationError | litellm.APIResponseValidationError | Raised when response does not match expected json schema - used if `response_schema` param passed in with `enforce_validation=True` |
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| N/A | MockException | Exception | Internal exception, raised by mock_completion class. Do not use directly |
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| N/A | OpenAIError | openai.OpenAIError | Deprecated internal exception, inherits from openai.OpenAIError. |
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Base case we return APIConnectionError
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@ -1,3 +1,4 @@
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import asyncio
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from datetime import datetime, timedelta
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from typing import TYPE_CHECKING, Any, Optional, Union
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@ -32,14 +33,63 @@ class ServiceLogging(CustomLogger):
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self.prometheusServicesLogger = PrometheusServicesLogger()
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def service_success_hook(
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self, service: ServiceTypes, duration: float, call_type: str
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self,
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service: ServiceTypes,
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duration: float,
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call_type: str,
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parent_otel_span: Optional[Span] = None,
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start_time: Optional[Union[datetime, float]] = None,
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end_time: Optional[Union[float, datetime]] = None,
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):
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"""
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[TODO] Not implemented for sync calls yet. V0 is focused on async monitoring (used by proxy).
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Handles both sync and async monitoring by checking for existing event loop.
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"""
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# if service == ServiceTypes.REDIS:
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# print(f"SYNC service: {service}, call_type: {call_type}")
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if self.mock_testing:
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self.mock_testing_sync_success_hook += 1
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try:
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# Try to get the current event loop
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loop = asyncio.get_event_loop()
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# Check if the loop is running
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if loop.is_running():
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# If we're in a running loop, create a task
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loop.create_task(
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self.async_service_success_hook(
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service=service,
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duration=duration,
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call_type=call_type,
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parent_otel_span=parent_otel_span,
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start_time=start_time,
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end_time=end_time,
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)
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)
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else:
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# Loop exists but not running, we can use run_until_complete
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loop.run_until_complete(
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self.async_service_success_hook(
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service=service,
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duration=duration,
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call_type=call_type,
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parent_otel_span=parent_otel_span,
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start_time=start_time,
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end_time=end_time,
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)
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)
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except RuntimeError:
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# No event loop exists, create a new one and run
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asyncio.run(
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self.async_service_success_hook(
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service=service,
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duration=duration,
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call_type=call_type,
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parent_otel_span=parent_otel_span,
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start_time=start_time,
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end_time=end_time,
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)
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)
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def service_failure_hook(
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self, service: ServiceTypes, duration: float, error: Exception, call_type: str
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):
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@ -62,6 +112,8 @@ class ServiceLogging(CustomLogger):
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"""
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- For counting if the redis, postgres call is successful
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"""
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# if service == ServiceTypes.REDIS:
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# print(f"service: {service}, call_type: {call_type}")
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if self.mock_testing:
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self.mock_testing_async_success_hook += 1
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@ -143,7 +143,17 @@ class RedisCache(BaseCache):
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)
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key = self.check_and_fix_namespace(key=key)
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try:
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start_time = time.time()
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self.redis_client.set(name=key, value=str(value), ex=ttl)
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end_time = time.time()
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_duration = end_time - start_time
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self.service_logger_obj.service_success_hook(
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service=ServiceTypes.REDIS,
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duration=_duration,
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call_type="set_cache",
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start_time=start_time,
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end_time=end_time,
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)
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except Exception as e:
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# NON blocking - notify users Redis is throwing an exception
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print_verbose(
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start_time = time.time()
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set_ttl = self.get_ttl(ttl=ttl)
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try:
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start_time = time.time()
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result: int = _redis_client.incr(name=key, amount=value) # type: ignore
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end_time = time.time()
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_duration = end_time - start_time
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self.service_logger_obj.service_success_hook(
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service=ServiceTypes.REDIS,
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duration=_duration,
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call_type="increment_cache",
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start_time=start_time,
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end_time=end_time,
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)
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if set_ttl is not None:
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# check if key already has ttl, if not -> set ttl
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start_time = time.time()
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current_ttl = _redis_client.ttl(key)
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end_time = time.time()
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_duration = end_time - start_time
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self.service_logger_obj.service_success_hook(
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service=ServiceTypes.REDIS,
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duration=_duration,
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call_type="increment_cache_ttl",
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start_time=start_time,
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end_time=end_time,
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)
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if current_ttl == -1:
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# Key has no expiration
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start_time = time.time()
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_redis_client.expire(key, set_ttl) # type: ignore
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end_time = time.time()
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_duration = end_time - start_time
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self.service_logger_obj.service_success_hook(
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service=ServiceTypes.REDIS,
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duration=_duration,
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call_type="increment_cache_expire",
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start_time=start_time,
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end_time=end_time,
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)
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return result
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except Exception as e:
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## LOGGING ##
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@ -565,7 +605,17 @@ class RedisCache(BaseCache):
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try:
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key = self.check_and_fix_namespace(key=key)
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print_verbose(f"Get Redis Cache: key: {key}")
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start_time = time.time()
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cached_response = self.redis_client.get(key)
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end_time = time.time()
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_duration = end_time - start_time
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self.service_logger_obj.service_success_hook(
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service=ServiceTypes.REDIS,
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duration=_duration,
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call_type="get_cache",
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start_time=start_time,
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end_time=end_time,
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)
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print_verbose(
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f"Got Redis Cache: key: {key}, cached_response {cached_response}"
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)
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@ -586,7 +636,17 @@ class RedisCache(BaseCache):
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for cache_key in key_list:
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cache_key = self.check_and_fix_namespace(key=cache_key)
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_keys.append(cache_key)
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start_time = time.time()
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results: List = self.redis_client.mget(keys=_keys) # type: ignore
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end_time = time.time()
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_duration = end_time - start_time
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self.service_logger_obj.service_success_hook(
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service=ServiceTypes.REDIS,
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duration=_duration,
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call_type="batch_get_cache",
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start_time=start_time,
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end_time=end_time,
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)
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# Associate the results back with their keys.
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# 'results' is a list of values corresponding to the order of keys in 'key_list'.
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service=ServiceTypes.REDIS,
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duration=_duration,
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call_type="sync_ping",
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start_time=start_time,
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end_time=end_time,
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)
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return response
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except Exception as e:
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@ -661,13 +661,7 @@ class APIResponseValidationError(openai.APIResponseValidationError): # type: ig
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return _message
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class OpenAIError(openai.OpenAIError): # type: ignore
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def __init__(self, original_exception=None):
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super().__init__()
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self.llm_provider = "openai"
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class JSONSchemaValidationError(APIError):
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class JSONSchemaValidationError(APIResponseValidationError):
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def __init__(
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self, model: str, llm_provider: str, raw_response: str, schema: str
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) -> None:
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model, raw_response, schema
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)
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self.message = message
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super().__init__(
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model=model, message=message, llm_provider=llm_provider, status_code=500
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)
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super().__init__(model=model, message=message, llm_provider=llm_provider)
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class OpenAIError(openai.OpenAIError): # type: ignore
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def __init__(self, original_exception=None):
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super().__init__()
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self.llm_provider = "openai"
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class UnsupportedParamsError(BadRequestError):
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@ -933,12 +933,7 @@ def completion( # type: ignore # noqa: PLR0915
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"input_cost_per_token": input_cost_per_token,
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"output_cost_per_token": output_cost_per_token,
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"litellm_provider": custom_llm_provider,
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},
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model: {
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"input_cost_per_token": input_cost_per_token,
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"output_cost_per_token": output_cost_per_token,
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"litellm_provider": custom_llm_provider,
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},
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}
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}
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)
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elif (
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@ -951,12 +946,7 @@ def completion( # type: ignore # noqa: PLR0915
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"input_cost_per_second": input_cost_per_second,
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"output_cost_per_second": output_cost_per_second,
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"litellm_provider": custom_llm_provider,
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},
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model: {
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"input_cost_per_second": input_cost_per_second,
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"output_cost_per_second": output_cost_per_second,
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"litellm_provider": custom_llm_provider,
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},
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}
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}
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)
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### BUILD CUSTOM PROMPT TEMPLATE -- IF GIVEN ###
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@ -3331,7 +3321,7 @@ def embedding( # noqa: PLR0915
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if input_cost_per_token is not None and output_cost_per_token is not None:
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litellm.register_model(
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{
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model: {
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f"{custom_llm_provider}/{model}": {
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"input_cost_per_token": input_cost_per_token,
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"output_cost_per_token": output_cost_per_token,
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"litellm_provider": custom_llm_provider,
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@ -3342,7 +3332,7 @@ def embedding( # noqa: PLR0915
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output_cost_per_second = output_cost_per_second or 0.0
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litellm.register_model(
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{
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model: {
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f"{custom_llm_provider}/{model}": {
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"input_cost_per_second": input_cost_per_second,
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"output_cost_per_second": output_cost_per_second,
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"litellm_provider": custom_llm_provider,
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@ -1,15 +1,19 @@
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model_list:
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- model_name: gpt-4o
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- model_name: claude-3-5-sonnet-20240620
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litellm_params:
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model: openai/fake
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api_key: fake-key
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api_base: https://exampleopenaiendpoint-production.up.railway.app/
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model: claude-3-5-sonnet-20240620
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api_key: os.environ/ANTHROPIC_API_KEY
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- model_name: claude-3-5-sonnet-aihubmix
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litellm_params:
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model: openai/claude-3-5-sonnet-20240620
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input_cost_per_token: 0.000003 # 3$/M
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output_cost_per_token: 0.000015 # 15$/M
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api_base: "https://exampleopenaiendpoint-production.up.railway.app"
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api_key: my-fake-key
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litellm_settings:
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callbacks: ["prometheus", "otel"]
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general_settings:
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user_api_key_cache_ttl: 3600
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fallbacks: [{ "claude-3-5-sonnet-20240620": ["claude-3-5-sonnet-aihubmix"] }]
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callbacks: ["otel"]
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router_settings:
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routing_strategy: latency-based-routing
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@ -19,32 +23,6 @@ router_settings:
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# consider last five minutes of calls for latency calculation
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ttl: 300
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# model_group_alias:
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# gpt-4o: gpt-4o-128k-2024-05-13
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# gpt-4o-mini: gpt-4o-mini-128k-2024-07-18
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enable_tag_filtering: True
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# retry call 3 times on each model_name (we don't use fallbacks, so this would be 3 times total)
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num_retries: 3
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# -- cooldown settings --
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# see https://github.com/BerriAI/litellm/blob/main/litellm/router_utils/cooldown_handlers.py#L265
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# cooldown model if it fails > n calls in a minute.
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allowed_fails: 2
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# (in seconds) how long to cooldown model if fails/min > allowed_fails
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cooldown_time: 60
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allowed_fails_policy:
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InternalServerErrorAllowedFails: 1
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RateLimitErrorAllowedFails: 2
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TimeoutErrorAllowedFails: 3
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# -- end cooldown settings --
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# see https://docs.litellm.ai/docs/proxy/prod#3-use-redis-porthost-password-not-redis_url
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redis_host: os.environ/REDIS_HOST
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redis_port: os.environ/REDIS_PORT
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redis_password: os.environ/REDIS_PASSWORD
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|
|
|
@ -2003,6 +2003,7 @@ def register_model(model_cost: Union[str, dict]): # noqa: PLR0915
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},
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}
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"""
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loaded_model_cost = {}
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if isinstance(model_cost, dict):
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loaded_model_cost = model_cost
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|
|
81
tests/documentation_tests/test_exception_types.py
Normal file
81
tests/documentation_tests/test_exception_types.py
Normal file
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@ -0,0 +1,81 @@
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import os
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import sys
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import io
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import re
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# Backup the original sys.path
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original_sys_path = sys.path.copy()
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import litellm
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public_exceptions = litellm.LITELLM_EXCEPTION_TYPES
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# Regular expression to extract the error name
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error_name_pattern = re.compile(r"\.exceptions\.([A-Za-z]+Error)")
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# Extract error names from each item
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error_names = {
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error_name_pattern.search(str(item)).group(1)
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for item in public_exceptions
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if error_name_pattern.search(str(item))
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}
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# sys.path = original_sys_path
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# Parse the documentation to extract documented keys
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# repo_base = "./"
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repo_base = "../../"
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print(os.listdir(repo_base))
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docs_path = f"{repo_base}/docs/my-website/docs/exception_mapping.md" # Path to the documentation
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documented_keys = set()
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try:
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with open(docs_path, "r", encoding="utf-8") as docs_file:
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content = docs_file.read()
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exceptions_section = re.search(
|
||||
r"## LiteLLM Exceptions(.*?)\n##", content, re.DOTALL
|
||||
)
|
||||
if exceptions_section:
|
||||
# Step 2: Extract the table content
|
||||
table_content = exceptions_section.group(1)
|
||||
|
||||
# Step 3: Create a pattern to capture the Error Types from each row
|
||||
error_type_pattern = re.compile(r"\|\s*[^|]+\s*\|\s*([^\|]+?)\s*\|")
|
||||
|
||||
# Extract the error types
|
||||
exceptions = error_type_pattern.findall(table_content)
|
||||
print(f"exceptions: {exceptions}")
|
||||
|
||||
# Remove extra spaces if any
|
||||
exceptions = [exception.strip() for exception in exceptions]
|
||||
|
||||
print(exceptions)
|
||||
documented_keys.update(exceptions)
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(
|
||||
f"Error reading documentation: {e}, \n repo base - {os.listdir(repo_base)}"
|
||||
)
|
||||
|
||||
print(documented_keys)
|
||||
print(public_exceptions)
|
||||
print(error_names)
|
||||
|
||||
# Compare and find undocumented keys
|
||||
undocumented_keys = error_names - documented_keys
|
||||
|
||||
if undocumented_keys:
|
||||
raise Exception(
|
||||
f"\nKeys not documented in 'LiteLLM Exceptions': {undocumented_keys}"
|
||||
)
|
||||
else:
|
||||
print("\nAll keys are documented in 'LiteLLM Exceptions'. - {}".format(error_names))
|
|
@ -1337,3 +1337,64 @@ async def test_anthropic_streaming_fallbacks(sync_mode):
|
|||
mock_client.assert_called_once()
|
||||
print(chunks)
|
||||
assert len(chunks) > 0
|
||||
|
||||
|
||||
def test_router_fallbacks_with_custom_model_costs():
|
||||
"""
|
||||
Tests prod use-case where a custom model is registered with a different provider + custom costs.
|
||||
|
||||
Goal: make sure custom model doesn't override default model costs.
|
||||
"""
|
||||
model_list = [
|
||||
{
|
||||
"model_name": "claude-3-5-sonnet-20240620",
|
||||
"litellm_params": {
|
||||
"model": "claude-3-5-sonnet-20240620",
|
||||
"api_key": os.environ["ANTHROPIC_API_KEY"],
|
||||
"input_cost_per_token": 30,
|
||||
"output_cost_per_token": 60,
|
||||
},
|
||||
},
|
||||
{
|
||||
"model_name": "claude-3-5-sonnet-aihubmix",
|
||||
"litellm_params": {
|
||||
"model": "openai/claude-3-5-sonnet-20240620",
|
||||
"input_cost_per_token": 0.000003, # 3$/M
|
||||
"output_cost_per_token": 0.000015, # 15$/M
|
||||
"api_base": "https://exampleopenaiendpoint-production.up.railway.app",
|
||||
"api_key": "my-fake-key",
|
||||
},
|
||||
},
|
||||
]
|
||||
|
||||
router = Router(
|
||||
model_list=model_list,
|
||||
fallbacks=[{"claude-3-5-sonnet-20240620": ["claude-3-5-sonnet-aihubmix"]}],
|
||||
)
|
||||
|
||||
router.completion(
|
||||
model="claude-3-5-sonnet-aihubmix",
|
||||
messages=[{"role": "user", "content": "Hey, how's it going?"}],
|
||||
)
|
||||
|
||||
model_info = litellm.get_model_info(model="claude-3-5-sonnet-20240620")
|
||||
|
||||
print(f"key: {model_info['key']}")
|
||||
|
||||
assert model_info["litellm_provider"] == "anthropic"
|
||||
|
||||
response = router.completion(
|
||||
model="claude-3-5-sonnet-20240620",
|
||||
messages=[{"role": "user", "content": "Hey, how's it going?"}],
|
||||
)
|
||||
|
||||
print(f"response_cost: {response._hidden_params['response_cost']}")
|
||||
|
||||
assert response._hidden_params["response_cost"] > 10
|
||||
|
||||
model_info = litellm.get_model_info(model="claude-3-5-sonnet-20240620")
|
||||
|
||||
print(f"key: {model_info['key']}")
|
||||
|
||||
assert model_info["input_cost_per_token"] == 30
|
||||
assert model_info["output_cost_per_token"] == 60
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue