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LiteLLM Minor Fixes and Improvements (08/06/2024) (#5567)
* fix(utils.py): return citations for perplexity streaming Fixes https://github.com/BerriAI/litellm/issues/5535 * fix(anthropic/chat.py): support fallbacks for anthropic streaming (#5542) * fix(anthropic/chat.py): support fallbacks for anthropic streaming Fixes https://github.com/BerriAI/litellm/issues/5512 * fix(anthropic/chat.py): use module level http client if none given (prevents early client closure) * fix: fix linting errors * fix(http_handler.py): fix raise_for_status error handling * test: retry flaky test * fix otel type * fix(bedrock/embed): fix error raising * test(test_openai_batches_and_files.py): skip azure batches test (for now) quota exceeded * fix(test_router.py): skip azure batch route test (for now) - hit batch quota limits --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> * All `model_group_alias` should show up in `/models`, `/model/info` , `/model_group/info` (#5539) * fix(router.py): support returning model_alias model names in `/v1/models` * fix(proxy_server.py): support returning model alias'es on `/model/info` * feat(router.py): support returning model group alias for `/model_group/info` * fix(proxy_server.py): fix linting errors * fix(proxy_server.py): fix linting errors * build(model_prices_and_context_window.json): add amazon titan text premier pricing information Closes https://github.com/BerriAI/litellm/issues/5560 * feat(litellm_logging.py): log standard logging response object for pass through endpoints. Allows bedrock /invoke agent calls to be correctly logged to langfuse + s3 * fix(success_handler.py): fix linting error * fix(success_handler.py): fix linting errors * fix(team_endpoints.py): Allows admin to update team member budgets --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
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25 changed files with 509 additions and 99 deletions
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@ -1,4 +1,6 @@
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import json
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import re
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import threading
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from datetime import datetime
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from typing import Union
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@ -10,6 +12,7 @@ from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_stu
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VertexLLM,
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)
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from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
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from litellm.types.utils import StandardPassThroughResponseObject
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class PassThroughEndpointLogging:
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@ -43,8 +46,24 @@ class PassThroughEndpointLogging:
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**kwargs,
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)
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else:
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standard_logging_response_object = StandardPassThroughResponseObject(
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response=httpx_response.text
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)
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threading.Thread(
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target=logging_obj.success_handler,
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args=(
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standard_logging_response_object,
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start_time,
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end_time,
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cache_hit,
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),
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).start()
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await logging_obj.async_success_handler(
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result="",
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result=(
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json.dumps(result)
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if isinstance(result, dict)
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else standard_logging_response_object
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),
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start_time=start_time,
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end_time=end_time,
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cache_hit=False,
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