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set price for bu model
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1
.gitignore
vendored
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.gitignore
vendored
@@ -81,3 +81,4 @@ todo.md
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product_extraction.ipynb
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product_extraction.py
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*report.md
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plot.py
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@@ -10,30 +10,15 @@ from typing import Any
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# Format matches LiteLLM's model_prices_and_context_window.json structure
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CUSTOM_MODEL_PRICING: dict[str, dict[str, Any]] = {
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'bu-1-0': {
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'input_cost_per_token': 0.50 / 1_000_000, # $0.50 per 1M tokens
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'output_cost_per_token': 3.00 / 1_000_000, # $3.00 per 1M tokens
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'cache_read_input_token_cost': 0.10 / 1_000_000, # $0.10 per 1M tokens
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'input_cost_per_token': 0.2 / 1_000_000, # $0.50 per 1M tokens
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'output_cost_per_token': 2.00 / 1_000_000, # $3.00 per 1M tokens
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'cache_read_input_token_cost': 0.02 / 1_000_000, # $0.10 per 1M tokens
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'cache_creation_input_token_cost': None, # Not specified
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'max_tokens': None, # Not specified
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'max_input_tokens': None, # Not specified
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'max_output_tokens': None, # Not specified
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},
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'bu-latest': {
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'input_cost_per_token': 0.50 / 1_000_000, # $0.50 per 1M tokens
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'output_cost_per_token': 3.00 / 1_000_000, # $3.00 per 1M tokens
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'cache_read_input_token_cost': 0.10 / 1_000_000, # $0.10 per 1M tokens
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'cache_creation_input_token_cost': None, # Not specified
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'max_tokens': None, # Not specified
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'max_input_tokens': None, # Not specified
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'max_output_tokens': None, # Not specified
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},
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'smart': {
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'input_cost_per_token': 0.50 / 1_000_000, # $0.50 per 1M tokens
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'output_cost_per_token': 3.00 / 1_000_000, # $3.00 per 1M tokens
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'cache_read_input_token_cost': 0.10 / 1_000_000, # $0.10 per 1M tokens
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'cache_creation_input_token_cost': None, # Not specified
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'max_tokens': None, # Not specified
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'max_input_tokens': None, # Not specified
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'max_output_tokens': None, # Not specified
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},
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}
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}
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CUSTOM_MODEL_PRICING['bu-latest'] = CUSTOM_MODEL_PRICING['bu-1-0']
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CUSTOM_MODEL_PRICING['smart'] = CUSTOM_MODEL_PRICING['bu-1-0']
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