CLI

Command-line interface for Tinfoil’s secure AI inference API
GitHub: tinfoil-cli

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Overview

The Tinfoil CLI provides a command-line interface for making verified HTTP requests to Tinfoil enclaves and validating attestation documents. It supports all major AI inference operations including chat completions, audio transcription, and text embeddings through a unified inference proxy.

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Installation

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Pre-built Binaries

Download the latest release for your OS from the Releases page.

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Install Script

You can install tinfoil CLI using our install script. This script automatically detects your operating system and architecture, downloads the correct binary, and installs it to /usr/local/bin. 
curl -fsSL https://github.com/tinfoilsh/tinfoil-cli/raw/main/install.sh | sh
If you receive permission errors (for example, if you’re not running as root), you may need to run the command with sudo.

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Build from Source

  1. Ensure you have Go installed.
  2. Clone the repository:
git clone https://github.com/tinfoilsh/tinfoil-cli.git
cd tinfoil-cli
  1. Build the binary:
go build -o tinfoil

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Command Reference

Usage:
  tinfoil [command]

Available Commands:
  attestation Attestation commands (verify or audit)
  audio       Transcribe audio files using Whisper
  certificate Audit enclave certificate
  chat        Chat with a language model
  completion  Generate the autocompletion script for the specified shell
  embed       Generate embeddings for the provided text input(s)
  help        Help about any command
  http        Make verified HTTP requests
  proxy       Run a local HTTP proxy
  tts         Convert text to speech using TTS models

Flags:
  -h, --help          Help for tinfoil
  -e, --host string   Enclave hostname
  -r, --repo string   Source repo
  -t, --trace         Trace output
  -v, --verbose       Verbose output

Use "tinfoil [command] --help" for more information about a command.

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Model Examples

Below are specific examples for each supported model. Click on any model to see its configuration and usage example.

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Chat Models

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Audio Models

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Embedding Models

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Chat

The chat command lets you interact with a model by simply specifying a model name and your prompt. You need to specify the model with the -m flag.

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Using the Chat Command

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Basic Usage (running DeepSeek R1)

tinfoil chat -m deepseek -k "YOUR_API_KEY" "Why is tinfoil now called aluminum foil?"
You can use either the friendly name (deepseek) or the full name (deepseek-r1-0528).

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Response Modes

  • Non-streaming (default): The complete response is returned all at once after generation is finished
  • Streaming (-s flag): Tokens are displayed in real-time as they’re generated, providing a more interactive experience
# Non-streaming (default)
tinfoil chat -m deepseek -k "YOUR_API_KEY" "Explain quantum computing"

# Streaming response
tinfoil chat -m deepseek -k "YOUR_API_KEY" -s "Explain quantum computing"

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Specifying a Custom Model

You can use any model name directly. For models requiring custom enclave settings, supply the -e and -r overrides: 
tinfoil chat -m custom-model -k "YOUR_API_KEY" "Explain string theory" \
  -e custom.enclave.example.com \
  -r cool-user/custom-model-repo
If you omit -e or -r for a model that isn’t in the configuration, a warning will be displayed prompting you to specify these flags.

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Command Options

  • -m, --model: The model name to use for chat. Must be specified.
  • -k, --api-key: The API key for authentication.
  • -s, --stream: Stream response output (real-time token generation). Optional, defaults to false.
  • -l, --list: List available chat models.
  • -e, --host: The hostname of the enclave. Optional if defined in the config file.
  • -r, --repo: The GitHub repository containing code measurements. Optional if defined in the config file.

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Audio

The audio command allows you to transcribe audio files using Whisper models.

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Basic Usage

# Using default Whisper model
tinfoil audio -k "YOUR_API_KEY" -f path/to/audio/file.mp3

# Using friendly alias
tinfoil audio -m whisper -k "YOUR_API_KEY" -f path/to/audio/file.mp3

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Specifying a Custom Model

tinfoil audio -m custom-whisper-model -k "YOUR_API_KEY" -f path/to/audio/file.mp3 \
  -e custom.enclave.example.com \
  -r cool-user/custom-model-repo

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Command Options

  • -m, --model: The model name to use for transcription. Defaults to whisper-large-v3-turbo.
  • -k, --api-key: The API key for authentication.
  • -f, --file: The audio file to transcribe.
  • -e, --host: The hostname of the enclave. Optional if defined in the config file.
  • -r, --repo: The GitHub repository containing code measurements. Optional if defined in the config file.

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TTS (Text-to-Speech)

The tts command allows you to convert text to speech using TTS models. By default, it uses the kokoro model.

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Using the TTS Command

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Basic Usage

tinfoil tts -k "YOUR_API_KEY" "Hello, this is a test of text-to-speech synthesis"
This command uses the default model kokoro and saves the generated audio to output.mp3. You can also use the friendly name tts: 
tinfoil tts -m tts -k "YOUR_API_KEY" "Hello world"

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Specifying Voice and Output File

tinfoil tts -m kokoro -k "YOUR_API_KEY" --voice "af_sky+af_bella" -o "my_speech.mp3" "Custom text to speak"

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Command Options

  • -m, --model: The model name to use for TTS. Defaults to kokoro.
  • -k, --api-key: The API key for authentication.
  • --voice: Voice to use for synthesis. Defaults to af_sky+af_bella.
  • -o, --output: Output file path. Defaults to output.mp3.
  • -e, --host: The hostname of the enclave. Optional if defined in the config file.
  • -r, --repo: The GitHub repository containing code measurements. Optional if defined in the config file.

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Embed

The embed command allows you to generate embeddings for text inputs.

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Basic Usage

# Using default embedding model
tinfoil embed -k "YOUR_API_KEY" "This is a text I want to get embeddings for."

# Using friendly alias
tinfoil embed -m embed -k "YOUR_API_KEY" "Text to embed"

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With Multiple Text Inputs

You can provide multiple text inputs to get embeddings for all of them: 
tinfoil embed -k "YOUR_API_KEY" "First text" "Second text" "Third text"

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Specifying a Custom Model

tinfoil embed -m custom-embed-model -k "YOUR_API_KEY" "Text to embed" \
  -e custom.enclave.example.com \
  -r cool-user/custom-model-repo

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Command Options

  • -m, --model: The model name to use for embeddings. Defaults to nomic-embed-text.
  • -k, --api-key: The API key for authentication.
  • -e, --host: The hostname of the enclave. Optional if defined in the config file.
  • -r, --repo: The GitHub repository containing code measurements. Optional if defined in the config file.

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Attestation Verification

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Verify Attestation

Use the attestation verify command to manually verify that an enclave is running the expected code. The output will be a series of INFO logs describing each verification step. Sample successful output: 
$ tinfoil attestation verify \
  -e inference.tinfoil.sh \
  -r tinfoilsh/confidential-inference-proxy
INFO[0000] Fetching latest release for tinfoilsh/confidential-inference-proxy 
INFO[0000] Fetching sigstore bundle from tinfoilsh/confidential-inference-proxy for digest f2f48557c8b0c1b268f8d8673f380242ad8c4983fe9004c02a8688a89f94f333 
INFO[0001] Fetching trust root                          
INFO[0001] Verifying code measurements                  
INFO[0001] Fetching attestation doc from inference.tinfoil.sh 
INFO[0001] Verifying enclave measurements               
INFO[0001] Public key fingerprint: 5f6c24f54ed862c404a558aa3fa85b686b77263ceeda86131e7acd90e8af5db2 
INFO[0001] Remote public key fingerprint: 5f6c24f54ed862c404a558aa3fa85b686b77263ceeda86131e7acd90e8af5db2 
INFO[0001] Measurements match

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JSON Output

You can also record the verification to a machine-readable audit log: 
tinfoil attestation verify \
  -e inference.tinfoil.sh \
  -r tinfoilsh/confidential-inference-proxy \
  -j > verification.json
The audit log record includes the timestamp, enclave host, code and enclave measurement fingerprints, and the verification status.

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Audit Attestation

You can also verify attestations at random and record a machine-readable audit log. Use the attestation audit command for this purpose. By default the audit record is printed to stdout as JSON. To write it to a file, use the -l/--log-file flag: 
tinfoil attestation audit \
  -e inference.tinfoil.sh \
  -r tinfoilsh/confidential-inference-proxy \
  -l /var/log/tinfoil_audit.log
The audit log record includes the timestamp, enclave host, code and enclave measurement fingerprints, and the verification status.

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Proxy

Use tinfoil proxy to start a local HTTP proxy that verifies connections and forwards them to the specified enclave: 
tinfoil proxy \
  -r tinfoilsh/confidential-inference-proxy \
  -e inference.tinfoil.sh \
  -p 8080

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Docker

A docker image is available at ghcr.io/tinfoilsh/tinfoil-cli.

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Troubleshooting

Common error resolutions:
  • PCR register mismatch: Running enclave code differs from source repo

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Guides

Tool Calling

Learn how to use function calling capabilities with AI models.

Structured Outputs

Use JSON schema validation for reliable data extraction.

Image Processing

Process images with multimodal AI models.

Document Processing

Upload and process documents securely.