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LiteLLM Minor Fixes & Improvements (09/21/2024) (#5819)
* fix(router.py): fix error message * Litellm disable keys (#5814) * build(schema.prisma): allow blocking/unblocking keys Fixes https://github.com/BerriAI/litellm/issues/5328 * fix(key_management_endpoints.py): fix pop * feat(auth_checks.py): allow admin to enable/disable virtual keys Closes https://github.com/BerriAI/litellm/issues/5328 * docs(vertex.md): add auth section for vertex ai Addresses - https://github.com/BerriAI/litellm/issues/5768#issuecomment-2365284223 * build(model_prices_and_context_window.json): show which models support prompt_caching Closes https://github.com/BerriAI/litellm/issues/5776 * fix(router.py): allow setting default priority for requests * fix(router.py): add 'retry-after' header for concurrent request limit errors Fixes https://github.com/BerriAI/litellm/issues/5783 * fix(router.py): correctly raise and use retry-after header from azure+openai Fixes https://github.com/BerriAI/litellm/issues/5783 * fix(user_api_key_auth.py): fix valid token being none * fix(auth_checks.py): fix model dump for cache management object * fix(user_api_key_auth.py): pass prisma_client to obj * test(test_otel.py): update test for new key check * test: fix test
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25 changed files with 1006 additions and 182 deletions
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@ -292,8 +292,12 @@ class RateLimitError(openai.RateLimitError): # type: ignore
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self.litellm_debug_info = litellm_debug_info
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self.max_retries = max_retries
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self.num_retries = num_retries
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_response_headers = (
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getattr(response, "headers", None) if response is not None else None
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)
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self.response = httpx.Response(
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status_code=429,
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headers=_response_headers,
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request=httpx.Request(
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method="POST",
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url=" https://cloud.google.com/vertex-ai/",
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@ -750,8 +754,14 @@ class InvalidRequestError(openai.BadRequestError): # type: ignore
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self.message = message
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self.model = model
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self.llm_provider = llm_provider
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self.response = httpx.Response(
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status_code=400,
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request=httpx.Request(
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method="GET", url="https://litellm.ai"
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), # mock request object
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)
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super().__init__(
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self.message, f"{self.model}"
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message=self.message, response=self.response, body=None
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) # Call the base class constructor with the parameters it needs
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