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Documentation Index

Fetch the complete documentation index at: https://docs.galtea.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Returns

Returns the updated Model object.

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Example

model = galtea.models.update(
    model_id=model_id,
    input_cost_per_token=0.000015,
    output_cost_per_token=0.000035,
)

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Parameters

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model_id
string
required
ID of the model to update.
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name
string
New name for the model.
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input_cost_per_token
float
New cost in dollars per input token.
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output_cost_per_token
float
New cost in dollars per output token.
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cache_read_input_token_cost
float
New cost in dollars per cached input token.
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cache_creation_input_token_cost
float
New cost in dollars per input token when creating a cache entry.
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input_cost_per_token_above_128k_tokens
float
New cost in dollars per input token for contexts larger than 128k tokens.
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output_cost_per_token_above_128k_tokens
float
New cost in dollars per output token for contexts larger than 128k tokens.
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tokenizer_provider
string
New tokenizer provider (e.g., "OpenAI", "Anthropic").
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source
string
New pricing source. This can be a URL to the model’s pricing page or documentation.
All fields except model_id default to PydanticUndefined (from pydantic_core). Omit a field (or pass PydanticUndefined) to leave it unchanged. Pass None to explicitly clear an optional field. Pass a value to update it.