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* build(model_prices_and_context_window.json): add gemini-1.5-flash context caching * fix(context_caching/transformation.py): just use last identified cache point Fixes https://github.com/BerriAI/litellm/issues/6738 * fix(context_caching/transformation.py): pick first contiguous block - handles system message error from google Fixes https://github.com/BerriAI/litellm/issues/6738 * fix(vertex_ai/gemini/): track context caching tokens * refactor(gemini/): place transformation.py inside `chat/` folder make it easy for user to know we support the equivalent endpoint * fix: fix import * refactor(vertex_ai/): move vertex_ai cost calc inside vertex_ai/ folder make it easier to see cost calculation logic * fix: fix linting errors * fix: fix circular import * feat(gemini/cost_calculator.py): support gemini context caching cost calculation generifies anthropic's cost calculation function and uses it across anthropic + gemini * build(model_prices_and_context_window.json): add cost tracking for gemini-1.5-flash-002 w/ context caching Closes https://github.com/BerriAI/litellm/issues/6891 * docs(gemini.md): add gemini context caching architecture diagram make it easier for user to understand how context caching works * docs(gemini.md): link to relevant gemini context caching code * docs(gemini/context_caching): add readme in github, make it easy for dev to know context caching is supported + where to go for code * fix(llm_cost_calc/utils.py): handle gemini 128k token diff cost calc scenario * fix(deepseek/cost_calculator.py): support deepseek context caching cost calculation * test: fix test |
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|---|---|---|
| .. | ||
| audio_utils | ||
| llm_cost_calc | ||
| llm_response_utils | ||
| prompt_templates | ||
| tokenizers | ||
| asyncify.py | ||
| core_helpers.py | ||
| default_encoding.py | ||
| duration_parser.py | ||
| exception_mapping_utils.py | ||
| get_llm_provider_logic.py | ||
| get_supported_openai_params.py | ||
| json_validation_rule.py | ||
| litellm_logging.py | ||
| llm_request_utils.py | ||
| logging_utils.py | ||
| mock_functions.py | ||
| README.md | ||
| realtime_streaming.py | ||
| redact_messages.py | ||
| response_header_helpers.py | ||
| rules.py | ||
| streaming_chunk_builder_utils.py | ||
| streaming_handler.py | ||
| token_counter.py | ||
Folder Contents
This folder contains general-purpose utilities that are used in multiple places in the codebase.
Core files:
streaming_handler.py: The core streaming logic + streaming related helper utilscore_helpers.py: code used intypes/- e.g.map_finish_reason.exception_mapping_utils.py: utils for mapping exceptions to openai-compatible error types.default_encoding.py: code for loading the default encoding (tiktoken)get_llm_provider_logic.py: code for inferring the LLM provider from a given model name.duration_parser.py: code for parsing durations - e.g. "1d", "1mo", "10s"