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Tinfoil Python Client

PyPI - Version SDK Test Documentation

A Python client for verifiably private AI inference with Tinfoil. It wraps the OpenAI Python client with the same API, and before sending any request it verifies the enclave's attestation and encrypts the request body to the attested key using EHBP, so only the verified enclave can read it.

For complete documentation, see the Python SDK documentation.

Installation

uv add tinfoil
# or
pip install tinfoil

Quick Start

import os
from tinfoil import TinfoilAI

client = TinfoilAI(api_key=os.environ["TINFOIL_API_KEY"])

# Enclave verification and encryption happen automatically.
chat_completion = client.chat.completions.create(
    model="llama3-3-70b",  # see https://docs.tinfoil.sh/models/catalog
    messages=[{"role": "user", "content": "Hi"}],
)
print(chat_completion.choices[0].message.content)

Async and streaming

Use AsyncTinfoilAI and await each call; the API is otherwise identical.

import asyncio
import os
from tinfoil import AsyncTinfoilAI

client = AsyncTinfoilAI(api_key=os.environ["TINFOIL_API_KEY"])

async def main() -> None:
    stream = await client.chat.completions.create(
        model="llama3-3-70b",
        messages=[{"role": "user", "content": "Say this is a test"}],
        stream=True,
    )
    async for chunk in stream:
        if chunk.choices and chunk.choices[0].delta.content is not None:
            print(chunk.choices[0].delta.content, end="", flush=True)
    print()

asyncio.run(main())

Audio transcription

with open("audio.mp3", "rb") as audio_file:
    transcription = client.audio.transcriptions.create(
        file=audio_file,
        model="whisper-large-v3-turbo",
    )
print(transcription.text)

Verification document

document = client.get_verification_document()

print(document.release_tag)  # None when verifying against a pinned measurement
print(document.release_digest)
print(document.code_fingerprint)
print(document.enclave_fingerprint)
print(document.verifier)
print(document.verified_at)

verified_at is recorded from the local clock after successful verification. It is not an attested timestamp or a freshness guarantee.

Prompt Cache Scoping

The router partitions prompt caches by API identity and a user_cache_secret that the SDK adds to eligible requests. By default it generates one and persists it at ~/.tinfoil/user_cache_secret, which is suitable for single-user applications. Multi-user services should scope each request to its end user:

# Pin a stable, opaque secret for this client (or set TINFOIL_USER_CACHE_SECRET).
client = TinfoilAI(api_key=api_key, user_cache_secret=secret)

# A per-request value wins over the client-level secret.
chat_completion = client.chat.completions.create(
    model="llama3-3-70b",
    messages=[{"role": "user", "content": "Hi"}],
    extra_body={"user_cache_secret": per_user_secret},
)

AsyncTinfoilAI and NewSecureClient accept the same parameter. See Prompt caching for resolution order and guidance on choosing a scope.

Advanced Functionality

NewSecureClient makes verified GET and POST requests to any path on the enclave. Requests to other origins are rejected.

import os
from tinfoil import NewSecureClient

api_key = os.environ["TINFOIL_API_KEY"]
tfclient = NewSecureClient()

resp = tfclient.get(
    f"https://{tfclient.enclave}/health",
    headers={"Authorization": f"Bearer {api_key}"},
    timeout=30,
)
print(resp.status_code, resp.text)

API Documentation

This library is a drop-in replacement for the official OpenAI Python client. All methods and types are identical; see the OpenAI Python client documentation for API usage.

Development

Install uv, then:

uv sync
uv run pytest -m "not integration"

# Integration tests require TINFOIL_API_KEY
export TINFOIL_API_KEY="..."
uv run pytest -m integration

Reporting Vulnerabilities

Please report security vulnerabilities by either:

We aim to respond to (legitimate) security reports within 24 hours.

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