a13n
Build AI agents and run them on cloud.
Private execution. Public proof.
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Developer toolsPython · TypeScriptGitHub @catmcgeeOnlineOwner unconfirmed
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The maker's introduction consists of the line above. Read the repository README for more details. Repository README ↗
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Read the full README ↗Measures when open-source inference inside a Trusted Execution Environment (TEE) is worth its latency and cost. The system compares the same local models with and without a TEE, measures a Claude proxy separately, anchors evidence on Solana devnet, and exposes the results through an API, CLI, report, and browser.
https://verified-inference.vercel.apphttps://vinfer.mcgee.cat@solana/addresses for read-only PDA derivation; no user wallet signs.llama.cpp or bitnet.cpp runtime execute inside
a read-only dm-verity guest. The public guest has no SSH service or QEMU
monitor; deployment work happens in a separate, non-public builder VM.The loaded browser code remains part of the trust boundary. Receipt hashes do not expose text directly, but low-entropy text can still be tested by guessing and hashing candidate values.
The public guest boots a directly measured kernel and initrd, then mounts its
root filesystem and both model volumes read-only through dm-verity. Browser
verification permits one exact (measurement, build, execution mode) tuple;
old mutable builds are not trusted. This proves the approved image booted with
the declared model bytes. It does not prove model correctness, eliminate CPU
side channels, or prevent the operator or hosting provider from taking the
service offline.
The published dataset reports only the configurations that were actually measured. It does not extrapolate unmeasured model, context, thread, or encryption combinations.
BitNet remains available because it is the 1.58-bit measurement anchor, but its
published i2_s runtime produces unreliable chat answers in live checks. The
browser therefore defaults to the more capable 8B Q4 model.
models.yaml is the single model registry. The canonical inference surface is
OpenAI-compatible POST /v1/chat/completions; the browser uses
POST /v1/chat_e2e for bidirectional sealing. Free endpoints expose models,
attestation, and receipts.
The OpenAI-compatible endpoint accepts normal plaintext OpenAI messages under TLS; it does not inherit the browser endpoint's end-to-end sealing. The current x402 gateway targets that compatibility endpoint, so an edge payment gateway can read those messages. Clients that require the TEE privacy boundary must use the sealed endpoint or its CLI wrapper.
Browser testing uses an authenticated session without payment. The generated pay/x402 gateway sits in front of the same OpenAI-compatible API; its sandbox flow passes, but no mainnet gateway or provider listing is published.
export VINFER_URL=https://vinfer.mcgee.cat
export VINFER_AUTH_TOKEN="strong-gateway-bearer-token"
export VINFER_ACCESS_CODE="operator-issued-browser-code"
uv run vinfer attest
uv run vinfer infer --model bitnet-2b --prompt 'hello' --e2e
uv run vinfer verify runs/snp-receipt.json
make test
make check
make verify-registry
make report
make pay-sandbox-test
Add a model by placing and hashing its weights, adding one models.yaml entry,
then running make bench MODEL=<id>, make pricing, restarting and
re-attesting the origin, and running make payskill.
models.yaml; pricing and pay artifacts are
generated from it.Detailed host evidence is in recon/findings.md. The measured-boot procedure and test-maintained Solana compute data remain beside their implementations.