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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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@ -208,6 +208,14 @@ class LangFuseLogger:
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):
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input = prompt
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output = response_obj["text"]
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elif (
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kwargs.get("call_type") is not None
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and kwargs.get("call_type") == "pass_through_endpoint"
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and response_obj is not None
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and isinstance(response_obj, dict)
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):
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input = prompt
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output = response_obj.get("response", "")
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print_verbose(f"OUTPUT IN LANGFUSE: {output}; original: {response_obj}")
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trace_id = None
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generation_id = None
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