* fix(vertex_and_google_ai_studio_gemini.py): add web search request tracking
Enables cost calculation for google web search
* fix(vertex_and_gemini): use common processing logic across stream / non-stream calls
* fix(vertex_And_google_ai_studio_Gemini.py): fix initial choice
* fix: fix linting error
* fix: add initial support for google search cost tracking
* fix(tool_call_cost_tracking.py): working tool cost tracking for gemini
* fix(vertex_ai/gemini/cost_calculator.py): add google web search tool cost tracking for vertex ai
Closes LIT-210
* fix: fix check
* build(model_prices_and_context_window.json): fix amazon nova max output tokens
Closes https://github.com/BerriAI/litellm/issues/11441
* fix: fix ruff check
* fix: update model path for llama-v3p2-90b-vision-instruct in pricing configuration (missing fireworks_ai/ prefix)
* feat: add deepseek-r1-0528 model configuration to pricing JSON
* feat: add configurations for new Claude 4 model alias to pricing JSON
* undo prefix change
* fix: update supports_response_schema to false in pricing JSON for litellm_provider
* update supports_tool_choice and supports_response_schema
* Update model configuration to disable function calling and tool choice for multiple models in fireworks_ai. Adjusted supported parameters in FireworksAIConfig to conditionally include tools and tool_choice based on model compatibility.
* Refactor FireworksAIConfig to use supports_function_calling from utils
* Enhance FireworksAIConfig to conditionally support tool_choice based on model capabilities
- Updated model_prices_and_context_window.json to include embed-v4.0 with relevant pricing and metadata.
- Added embed-v4.0 to cohere_embedding_models in constants.py.
- Implemented comprehensive tests for Cohere Embed v4.0 in test_cohere.py, covering basic functionality, input types, error handling, and optional parameters.
* Update mistral-medium prices and context sizes
While testing the Mistral model, I noticed a discrepancy in the pricing shown on the logs screen. After reviewing the code, I confirmed that the pricing values were incorrect.
This PR corrects the input and output token pricing for the latest Mistral model and adds the newly released mistral-medium-2505 version.
* Adds tool calling flag to mistral-medium
* Adds mistral-medium price updates to the main model price file
* Update model_prices_and_context_window_backup.json
sets mistral medium alias to the old values as it probably points to the old version.
* Update model_prices_and_context_window.json
* Update model_prices_and_context_window_backup.json
* Update model_prices_and_context_window.json
* Add support for supports_computer_use in model info
* Corrected list of supports_computer_use models
* Further fix computer use compatible claude models, fix existing test that predated supports_computer_use in the model list
* Move computer use test case into existing test_utils file
* Moved tests in to test_utils.py
* fix(openai/gpt_transformation.py): handle missing filename for openai file data call
* fix(openai/gpt_transformation.py): clean handling for sync + async pdf url transformation flows
Fixes https://github.com/BerriAI/litellm/issues/10820
* build(model_prices_and_context_window.json): add 'supports_pdf_input' for all openai models which have 'vision' support
Follows openai guidelines
* feat(bedrock/chat): support cache pointing tool calls on Bedrock
Closes https://github.com/BerriAI/litellm/pull/10613
* fix: fix linting error
* Update Groq models on model_prices_and_context_window.json
Add support for 6 new models; add deprecations dates to 12 model; and update context-windows/max-tokens for 3 models
* Round model costs to 8 decimal places
* Add support for nscale provider
* Add image generation support and fix unit tests
* Add docs for nscale
* Fix unit test import issues
* Minor doc improvement
* Remove redundant null tokens from model cost map
* Address PR review comments for doc updates
* Revert changes to large text
* build(model_prices_and_context_window.json): add bedrock llama4 models to model cost map
* fix template conversion for Llama 4 models in Bedrock (#10557)
* test: add testing to repro https://github.com/BerriAI/litellm/pull/10557
* test: add unit testing
* test(test_main.py): refactor where test is kept
---------
Co-authored-by: aswny <87371411+aswny@users.noreply.github.com>
Fixes:
Error generating conversation title: litellm.BadRequestError: VertexAIException BadRequestError - {
"error": {
"code": 400,
"message": "Unable to submit request because it has a maxOutputTokens value of 65536 but the supported range is from 1 (inclusive) to 65536 (exclusive). Update the value and try again.",
"status": "INVALID_ARGUMENT"
}
}
* Support Llama-api as an LLM provider (#10451)
* init: support llama-api as a llm provider
* docs: fix endpoint url
* fix: rename meta dir to meta-llama
* docs: add meta-llama info
* fix: mv LlamaAPIConfig under chat directory
* feat: add LlamaAPIConfig in ProviderConfigManager
* fix: provider_config from ProviderConfigManager
* feat: add supports_tool_choice param
* fix: remove optional_params using model_info
* fix: rename meta-llama to meta_llama
* init: test for meta_llama
* fix: model names
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* fix file naming convention
* fix file naming convention for meta_llama
* docs meta llama api litellm
---------
Co-authored-by: Young Han <110819238+seyeong-han@users.noreply.github.com>
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
