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* Add date picker to usage tab + Add reasoning_content token tracking across all providers on streaming (#9722) * feat(new_usage.tsx): add date picker for new usage tab allow user to look back on their usage data * feat(anthropic/chat/transformation.py): report reasoning tokens in completion token details allows usage tracking on how many reasoning tokens are actually being used * feat(streaming_chunk_builder.py): return reasoning_tokens in anthropic/openai streaming response allows tracking reasoning_token usage across providers * Fix update team metadata + fix bulk adding models on Ui (#9721) * fix(handle_add_model_submit.tsx): fix bulk adding models * fix(team_info.tsx): fix team metadata update Fixes https://github.com/BerriAI/litellm/issues/9689 * (v0) Unified file id - allow calling multiple providers with same file id (#9718) * feat(files_endpoints.py): initial commit adding 'target_model_names' support allow developer to specify all the models they want to call with the file * feat(files_endpoints.py): return unified files endpoint * test(test_files_endpoints.py): add validation test - if invalid purpose submitted * feat: more updates * feat: initial working commit of unified file id translation * fix: additional fixes * fix(router.py): remove model replace logic in jsonl on acreate_file enables file upload to work for chat completion requests as well * fix(files_endpoints.py): remove whitespace around model name * fix(azure/handler.py): return acreate_file with correct response type * fix: fix linting errors * test: fix mock test to run on github actions * fix: fix ruff errors * fix: fix file too large error * fix(utils.py): remove redundant var * test: modify test to work on github actions * test: update tests * test: more debug logs to understand ci/cd issue * test: fix test for respx * test: skip mock respx test fails on ci/cd - not clear why * fix: fix ruff check * fix: fix test * fix(model_connection_test.tsx): fix linting error * test: update unit tests
14 lines
434 B
Python
14 lines
434 B
Python
import hashlib
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import json
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from litellm.types.router import CredentialLiteLLMParams
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def get_litellm_params_sensitive_credential_hash(litellm_params: dict) -> str:
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"""
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Hash of the credential params, used for mapping the file id to the right model
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"""
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sensitive_params = CredentialLiteLLMParams(**litellm_params)
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return hashlib.sha256(
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json.dumps(sensitive_params.model_dump()).encode()
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).hexdigest()
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