TensorZero aims to provide a great developer experience while giving you full access to the underlying capabilities of each model provider. We provide advanced features that let you customize requests and access provider-specific functionality that isn’t directly supported in TensorZero. You shouldn’t need these features most of the time, but they’re around if necessary.
Is there something you weren’t able to do with TensorZero? Please let us know and we’ll try to tackle it — not just for the specific case but a general solution for that class of workflow.

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Features

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extra_body

You can use the extra_body field to override the request body that TensorZero sends to model providers. You can set extra_body on a variant configuration block, a model provider configuration block, or at inference time. See Configuration Reference and Inference API Reference for more details.

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extra_headers

You can use the extra_headers field to override the request headers that TensorZero sends to model providers. You can set extra_headers on a variant configuration block, a model provider configuration block, or at inference time. See Configuration Reference and Inference API Reference for more details.

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include_original_response

If you enable this feature while running inference, the gateway will return the original response from the model provider along with the TensorZero response. See Inference API Reference for more details.

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TensorZero Data

TensorZero stores all its data on your own ClickHouse database. You can query this data directly by running SQL queries against your ClickHouse instance. If you’re feeling particularly adventurous, you can also write to ClickHouse directly (though you should be careful when upgrading your TensorZero deployment to account for any database migrations). See Data model for more details.

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Example: Anthropic Computer Use

At the time of writing, TensorZero hadn’t integrated with Anthropic’s Computer Use features directly — but they worked out of the box! Concretely, Anthropic Computer Use requires setting additional fields to the request body as well as a request header. Let’s define a TensorZero function that includes these additional parameters: 
[functions.bash_assistant]
type = "chat"

[functions.bash_assistant.variants.anthropic_claude_3_7_sonnet_20250219]
type = "chat_completion"
model = "anthropic::claude-3-7-sonnet-20250219"
max_tokens = 2048
extra_body = [
    { pointer = "/tools", value = [{ type = "bash_20250124", name = "bash" }] },
    { pointer = "/thinking", value = { type = "enabled", budget_tokens = 1024 } },
]
extra_headers = [
    { name = "anthropic-beta", value = "computer-use-2025-01-24" },
]
This example illustrates how you should be able to use the vast majority of features supported by the model provider even if TensorZero doesn’t have explicit support for them yet.