litellm-mirror/tests/test_model_prices_and_context_window_schema.py
Utkash Dubey fa88bc9632 changes
2025-03-03 04:16:12 -08:00

111 lines
5.6 KiB
Python

import litellm
from jsonschema import validate
def test_model_prices_and_context_window_json_is_valid():
'''
Validates the `model_prices_and_context_window.json` file.
If this test fails after you update the json, you need to update the schema or correct the change you made.
'''
INTENDED_SCHEMA = {
"type": "object",
"additionalProperties": {
"type": "object",
"properties": {
"cache_creation_input_audio_token_cost": {"type": "number"},
"cache_creation_input_token_cost": {"type": "number"},
"cache_read_input_token_cost": {"type": "number"},
"deprecation_date": {"type": "string"},
"input_cost_per_audio_per_second": {"type": "number"},
"input_cost_per_audio_per_second_above_128k_tokens": {"type": "number"},
"input_cost_per_audio_token": {"type": "number"},
"input_cost_per_character": {"type": "number"},
"input_cost_per_character_above_128k_tokens": {"type": "number"},
"input_cost_per_image": {"type": "number"},
"input_cost_per_image_above_128k_tokens": {"type": "number"},
"input_cost_per_pixel": {"type": "number"},
"input_cost_per_query": {"type": "number"},
"input_cost_per_request": {"type": "number"},
"input_cost_per_second": {"type": "number"},
"input_cost_per_token": {"type": "number"},
"input_cost_per_token_above_128k_tokens": {"type": "number"},
"input_cost_per_token_batch_requests": {"type": "number"},
"input_cost_per_token_batches": {"type": "number"},
"input_cost_per_token_cache_hit": {"type": "number"},
"input_cost_per_video_per_second": {"type": "number"},
"input_cost_per_video_per_second_above_128k_tokens": {"type": "number"},
"input_dbu_cost_per_token": {"type": "number"},
"litellm_provider": {"type": "string"},
"max_audio_length_hours": {"type": "number"},
"max_audio_per_prompt": {"type": "number"},
"max_document_chunks_per_query": {"type": "number"},
"max_images_per_prompt": {"type": "number"},
"max_input_tokens": {"type": "number"},
"max_output_tokens": {"type": "number"},
"max_pdf_size_mb": {"type": "number"},
"max_query_tokens": {"type": "number"},
"max_tokens": {"type": "number"},
"max_tokens_per_document_chunk": {"type": "number"},
"max_video_length": {"type": "number"},
"max_videos_per_prompt": {"type": "number"},
"metadata": {"type": "object"},
"mode": {
"type": "string",
"enum": [
"audio_speech",
"audio_transcription",
"chat",
"completion",
"embedding",
"image_generation",
"moderation",
"moderations",
"rerank"
],
},
"output_cost_per_audio_token": {"type": "number"},
"output_cost_per_character": {"type": "number"},
"output_cost_per_character_above_128k_tokens": {"type": "number"},
"output_cost_per_image": {"type": "number"},
"output_cost_per_pixel": {"type": "number"},
"output_cost_per_second": {"type": "number"},
"output_cost_per_token": {"type": "number"},
"output_cost_per_token_above_128k_tokens": {"type": "number"},
"output_cost_per_token_batches": {"type": "number"},
"output_db_cost_per_token": {"type": "number"},
"output_dbu_cost_per_token": {"type": "number"},
"output_vector_size": {"type": "number"},
"rpd": {"type": "number"},
"rpm": {"type": "number"},
"source": {"type": "string"},
"supports_assistant_prefill": {"type": "boolean"},
"supports_audio_input": {"type": "boolean"},
"supports_audio_output": {"type": "boolean"},
"supports_embedding_image_input": {"type": "boolean"},
"supports_function_calling": {"type": "boolean"},
"supports_image_input": {"type": "boolean"},
"supports_parallel_function_calling": {"type": "boolean"},
"supports_pdf_input": {"type": "boolean"},
"supports_prompt_caching": {"type": "boolean"},
"supports_response_schema": {"type": "boolean"},
"supports_system_messages": {"type": "boolean"},
"supports_tool_choice": {"type": "boolean"},
"supports_video_input": {"type": "boolean"},
"supports_vision": {"type": "boolean"},
"tool_use_system_prompt_tokens": {"type": "number"},
"tpm": {"type": "number"},
},
"additionalProperties": False,
},
}
actual_json = litellm.get_locally_cached_model_cost_map()
assert isinstance(actual_json, dict)
temporarily_removed = actual_json.pop('sample_spec', None) # remove the sample, whose schema is inconsistent with the real data
validate(actual_json, INTENDED_SCHEMA)
if temporarily_removed is not None:
# put back the sample spec that we removed
actual_json.update({'sample_spec': temporarily_removed})