From 739e5ff6fe1f17749b258b34fd7c04f06ddb9f05 Mon Sep 17 00:00:00 2001 From: "Mr.Dong" <1042542469@qq.com> Date: Sun, 25 Oct 2026 02:32:35 +0800 Subject: [PATCH 01/32] vela: add the 0.8B native bundle export, manifest gate and wire contract MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - recipe/vela/export_native.py: gate-verified export into a native bundle — 320 backbone tensors re-keyed backbone. -> model. with per-tensor dtypes preserved (204 BF16 Linear/conv1d + 116 F32), the 37 F32 heads incl. the side-loaded broad span head in one file, backbone_config at the config root (the family Config::load shape), and a manifest pinning the source revision, the gate table, the tensor inventory and every bundle file's SHA-256. - src/models/vela/native (omni-vela-native): the bundle manifest gate and the wire admission mirroring protocol.py and the pinned runtime's preamble with byte-equal 422/400 bodies. - recipe/vela/export_token_plan.py and five frozen token plans under tests/vela/fixtures/: the predict mapping, the row decomposition and the rendered records (p_ids, blocks, readout positions, truncation, a windowed long-span case); example-request totals 1,041 tokens, matching the oracle's usage. Checks: cargo test (15 tests, no weights, no GPU), fmt/clippy clean, mkdocs --strict. --- Cargo.lock | 186 +++++++++--------- Cargo.toml | 2 +- README.md | 2 +- docs/supported-models.md | 2 +- mkdocs.yml | 1 + recipe/vela/export_native.py | 168 ++++++++++++++++ recipe/vela/export_token_plan.py | 153 ++++++++++++++ recipe/vela/native.md | 49 +++++ src/models/vela/README.md | 26 +++ src/models/vela/native/Cargo.toml | 26 +++ src/models/vela/native/src/bundle.rs | 112 +++++++++++ src/models/vela/native/src/contract.rs | 142 +++++++++++++ src/models/vela/native/src/lib.rs | 5 + .../native-plan-example-request-cjk.json | 1 + .../native-plan-example-request-score.json | 1 + ...ve-plan-example-request-set-threshold.json | 1 + .../fixtures/native-plan-example-request.json | 1 + .../native-plan-long-span-windowed.json | 1 + tests/vela/native_bundle.rs | 111 +++++++++++ tests/vela/native_contract.rs | 122 ++++++++++++ 20 files changed, 1021 insertions(+), 91 deletions(-) create mode 100644 recipe/vela/export_native.py create mode 100644 recipe/vela/export_token_plan.py create mode 100644 recipe/vela/native.md create mode 100644 src/models/vela/native/Cargo.toml create mode 100644 src/models/vela/native/src/bundle.rs create mode 100644 src/models/vela/native/src/contract.rs create mode 100644 src/models/vela/native/src/lib.rs create mode 100644 tests/vela/fixtures/native-plan-example-request-cjk.json create mode 100644 tests/vela/fixtures/native-plan-example-request-score.json create mode 100644 tests/vela/fixtures/native-plan-example-request-set-threshold.json create mode 100644 tests/vela/fixtures/native-plan-example-request.json create mode 100644 tests/vela/fixtures/native-plan-long-span-windowed.json create mode 100644 tests/vela/native_bundle.rs create mode 100644 tests/vela/native_contract.rs diff --git a/Cargo.lock b/Cargo.lock index 65562b9e..2a269f64 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -199,9 +199,9 @@ dependencies = [ [[package]] name = "cc" -version = "1.4.7" +version = "1.10.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "54413ede23c2daf518f35156dfde027feb2374004d63bd497f983c8db9c0e313" +checksum = "86e055fa6e3e40ad6187ba25b6855eeb635d5271f8e0f0e1e9a5826b8d75bea0" dependencies = [ "find-msvc-tools", "shlex", @@ -271,9 +271,9 @@ dependencies = [ [[package]] name = "crc32fast" -version = "1.5.2" +version = "1.5.3" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "01a7799fd6b852db0e61728dde9a204c423b44d689dbd432522543614b490e78" +checksum = "0ba106e844045ddc02c20768ac4b0b7cb45f2cc2ecbd833ac9f5dacb183c2055" dependencies = [ "cfg-if", ] @@ -438,20 +438,20 @@ checksum = "c6232dd377dcc64799954cbd3a9bb882e9cdc1308ccd87b1c098f1fb2eaf82a8" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", ] [[package]] name = "either" -version = "1.18.0" +version = "1.19.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "252afb9ae5eaa683babdc6a068b3f5726eb19e05070c731f9b2a23a7c3e8ed34" +checksum = "0e9c71c2167ca323c882b99918929403426e2373ea17242ff5653e0d5e1058be" [[package]] name = "equivalent" -version = "1.0.2" +version = "1.0.3" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "877a4ace8713b0bcf2a4e7eec82529c029f1d0619886d18145fea96c3ffe5c0f" +checksum = "00d174d5400e5e8fd687ad1049e2f578285fa914201b1af7e8b112a4546bd826" [[package]] name = "errno" @@ -497,9 +497,9 @@ dependencies = [ [[package]] name = "find-msvc-tools" -version = "0.1.13" +version = "0.1.15" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "ef25905e51abafe4dcea6c15fec58c57b601cdbd0ee53d22ea1d3016c587d39b" +checksum = "1c66915cc5391097de7a2b0b972e8505aa33c0df401fd3a6811dbdb32881ba48" [[package]] name = "flate2" @@ -563,7 +563,7 @@ checksum = "9fb9654ba8355388abeb8dcb4fc62f511300867002afc858860463bdd9fe0c44" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", ] [[package]] @@ -729,13 +729,12 @@ dependencies = [ [[package]] name = "hyper" -version = "1.11.1" +version = "1.12.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "27b501faa50e7a26c3d3560ca625132f4078a17771f4810baf70475ae48cbe43" +checksum = "2c3e324da4c95177d6291d4c8730197c0d1822f8a9766814a4a44fa5ab797c9c" dependencies = [ "atomic-waker", "bytes", - "futures-channel", "futures-core", "http", "http-body", @@ -790,9 +789,9 @@ dependencies = [ [[package]] name = "icu_collections" -version = "2.3.0" +version = "2.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "fa68d21081c4a05d5a901a1c62add574c77048b6a1c67be3b50ce0b60d4ca513" +checksum = "fe090a42a0d3140fed8c63263ed1fecc02422cb2f4bfe55cd8de2de1b8e105dd" dependencies = [ "displaydoc", "potential_utf", @@ -804,9 +803,9 @@ dependencies = [ [[package]] name = "icu_locale_core" -version = "2.3.0" +version = "2.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "d56e28588da92eee5c3201a6eff33fabdd49b62269c8938d4ff050ce4d900deb" +checksum = "25d29b57c17c6528d0dc4c2141cfa2d08200465acb537a3909c8b9b8a4a984c0" dependencies = [ "displaydoc", "litemap", @@ -817,9 +816,9 @@ dependencies = [ [[package]] name = "icu_normalizer" -version = "2.3.0" +version = "2.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "12f9cf5f235641ed274641dd81c3f28d870e276763d0797aeeab72317b1c646f" +checksum = "404a3b8c486f205c87fe7f23ab6894d84a4ad76d6e4671ae1981ba7def87c599" dependencies = [ "icu_collections", "icu_normalizer_data", @@ -831,15 +830,15 @@ dependencies = [ [[package]] name = "icu_normalizer_data" -version = "2.3.0" +version = "2.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "1563da1ed3e0b3bf3d74c9b85917ac9c56464d2f57242270c09c9e752f8021a0" +checksum = "20f0088bfb7441f7a37fa0c9e20cb1e9cba1cac6b9ce8cd2a6dc44294f8e8cbc" [[package]] name = "icu_properties" -version = "2.3.0" +version = "2.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "7e7ca276ad3145661a65914e6daf131ca5120cd3dcee8f8f3214b8875184a148" +checksum = "2ea83d991c56158f7cf898bf86436c1dfe7c07ee82fe88951f2695c9f37a379f" dependencies = [ "displaydoc", "icu_collections", @@ -852,15 +851,15 @@ dependencies = [ [[package]] name = "icu_properties_data" -version = "2.3.0" +version = "2.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "e590f038c1464a96894fd6d10127e90a8be4509f56ff7ecef851b15cee0b7caa" +checksum = "b98f29af82d02b163fe50161388350e743bb3107cc8e8c2f7314cb505faddfcf" [[package]] name = "icu_provider" -version = "2.3.1" +version = "2.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "d27bbb9d3abbefac45d55f647c9de1d44aafcd1186eb91879afef17c396c3e73" +checksum = "413099315636c588ee8f011190b329b971a09a8fae9d157e01dcae8379468514" dependencies = [ "displaydoc", "icu_locale_core", @@ -957,9 +956,9 @@ dependencies = [ [[package]] name = "libc" -version = "0.2.189" +version = "0.2.191" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "3eaf3ede3fee6db1a4c2ee091bf8a8b4dccdc6d17f656fb07896ee72867612f2" +checksum = "65cd87c9a6d60536580b316ad985726104730a5151c99845f2490428ef91240a" [[package]] name = "libloading" @@ -1031,9 +1030,9 @@ checksum = "cf8baf1c55e62ffcace7a9f06f4bd9cd3f0c4beb022d3b367256b91b87513d98" [[package]] name = "memmap2" -version = "0.9.11" +version = "0.9.12" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "d1219ed1b7f229ee7104d281dd01d6802fe28bb6e95d292942c4daacdeb798c0" +checksum = "6b0ca1155a9ecc25aa12e8313a119f32edf0255fea2f44839c4ac0a12b2ac157" dependencies = [ "libc", ] @@ -1072,9 +1071,9 @@ dependencies = [ [[package]] name = "mio" -version = "1.2.3" +version = "1.2.4" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "4b18443e9c262bfe8fa82f51666e2642c53393f7e5c27b3e1aeab922cff5b9d8" +checksum = "1788edb87fdc09c7e26304471e2f5be8cdefb1b6930d6e3985fc02ff53bf86ee" dependencies = [ "libc", "wasi", @@ -1216,7 +1215,7 @@ dependencies = [ "omni-runtime", "safetensors 0.8.0", "serde_json", - "sha2 0.11.0", + "sha2 0.11.1", "tempfile", "tokenizers 0.22.2", "tokio", @@ -1290,6 +1289,16 @@ dependencies = [ "tokio", ] +[[package]] +name = "omni-vela-native" +version = "0.1.0" +dependencies = [ + "anyhow", + "omni-qwen3-5-native", + "serde_json", + "sha2 0.11.1", +] + [[package]] name = "once_cell" version = "1.21.4" @@ -1416,9 +1425,9 @@ dependencies = [ [[package]] name = "quinn-proto" -version = "0.11.18" +version = "0.11.19" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "a9746dbde176634f4f2f1faf2404e30a31b2bc1e9cafb5329c95d8177a18c9fc" +checksum = "0e750cca55fe4f0439a15d0bb529da9651e79993e8e72c61a899a36d462befbe" dependencies = [ "bytes", "getrandom 0.4.3", @@ -1438,9 +1447,9 @@ dependencies = [ [[package]] name = "quinn-udp" -version = "0.5.15" +version = "0.5.16" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "35a133f956daabe89a61a685c2649f13d82d5aa4bd5d12d1277e1072a21c0694" +checksum = "af66907df18639dcf4db56ca65490cabc4b27a97dbadd96f2926cca73298f016" dependencies = [ "cfg_aliases", "libc", @@ -1663,9 +1672,9 @@ dependencies = [ [[package]] name = "rustls" -version = "0.23.45" +version = "0.23.46" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "0d41d731c7d2f962d1ccc364cec258de3c0e93b38c2fb3ba97ac74513048d634" +checksum = "48e13bd8c0e9365c43cfa5c9e8f9ad49d3c8444926c9aac819e0e4dc503c8fdf" dependencies = [ "once_cell", "ring", @@ -1687,9 +1696,9 @@ dependencies = [ [[package]] name = "rustls-webpki" -version = "0.103.15" +version = "0.103.16" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "f3c3cf1d8b1e7d4927e2d154c3fcb02979afb9939629c62cd9048d4f07b60ac2" +checksum = "4443b1b6d39d7c663139942cc4558262562d2c84123bb6282ef177009ca8b281" dependencies = [ "ring", "rustls-pki-types", @@ -1758,15 +1767,16 @@ checksum = "e7a5d71263a5a7d47b41f6b3f06ba276f10cc18b0931f1799f710578e2309348" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", ] [[package]] name = "serde_json" -version = "1.0.151" +version = "1.0.154" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "c841b55ecdae098c80dcae9cf767f6f8a0c2cdb3416bbef72181df4d0fe73f14" +checksum = "e7e9cc8b1b85264074fbcc02a88680c4096b1e47df8f739dceb03bf482f04bd6" dependencies = [ + "foldhash", "indexmap", "itoa", "memchr", @@ -1811,9 +1821,9 @@ dependencies = [ [[package]] name = "sha2" -version = "0.11.0" +version = "0.11.1" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "446ba717509524cb3f22f17ecc096f10f4822d76ab5c0b9822c5f9c284e825f4" +checksum = "47d7069beb7d6ac7b9acd1039986e73443f24234f41074da099d6f994ac9ad19" dependencies = [ "cfg-if", "cpufeatures 0.3.1", @@ -1850,9 +1860,9 @@ checksum = "0c790de23124f9ab44544d7ac05d60440adc586479ce501c1d6d7da3cd8c9cf5" [[package]] name = "smallvec" -version = "1.16.2" +version = "1.16.4" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "f9395f0f0eee849a9b707b2f06bb92a6a422090e2123bb2ef8e87a0e61892a8e" +checksum = "d0d5d4b1981b8bbbb7aed204cae5726d683d5d6ac7e74ec54122ea28f315e7c8" [[package]] name = "socket2" @@ -1913,9 +1923,9 @@ dependencies = [ [[package]] name = "syn" -version = "3.0.6" +version = "3.0.9" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "8593e8e72159ed2257d083c7a454a85cbf854f37a0966d8d483aff8c8a3ebcee" +checksum = "d78c8dee4c7bf0e14673097256fed6142ce9d3b85a408189d07482442145823b" dependencies = [ "proc-macro2", "quote", @@ -1939,7 +1949,7 @@ checksum = "901704edd0dfe137f1987838ee4f259e4e063c31371bdb423f7ae38ec6f77f02" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", ] [[package]] @@ -1972,14 +1982,14 @@ checksum = "fe5197923287db20a58125f0bc85c062f7f2c892de97b18c356f9efb14b28524" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", ] [[package]] name = "tinystr" -version = "0.8.4" +version = "0.8.5" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "b1e27c91459209c2986af3dcf603a5a74a4368754ce37414f59acc971167f643" +checksum = "abc840c238154d58f9e86b2792261edfde565a17696e1cda1a449de27979801a" dependencies = [ "displaydoc", "zerovec", @@ -2059,9 +2069,9 @@ dependencies = [ [[package]] name = "tokio" -version = "1.53.1" +version = "1.54.1" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "202caea871b69668250d242070849eb495be178ed697a3e98aebce5bc81a0bed" +checksum = "b52fd3255258d26fac7264ab5a76b53c13367136dc011d3d6ad4f8ed070396a3" dependencies = [ "bytes", "libc", @@ -2081,14 +2091,14 @@ checksum = "78773a2a397f451582ce068015985c33193cf6dea8b74d2a639fe457b2f07b0e" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", ] [[package]] name = "tokio-rustls" -version = "0.26.5" +version = "0.26.6" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "b0c85f2c3ef0b1cd58b36682f4b17aaa995f0e5db534d85692b4903abce21f67" +checksum = "c9cc2678c2cdd569ef8215e2afd7954ada2ae20b4fdd2c5fe6139a3b02d105db" dependencies = [ "rustls", "tokio", @@ -2096,9 +2106,9 @@ dependencies = [ [[package]] name = "tokio-util" -version = "0.7.19" +version = "0.7.20" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "494815d09bf52b5548659851081238f0ca39ff638363907596da739561c62c52" +checksum = "e464cf451ba96ebfc6f9b6542f17ee8b8956e33f1e40d9690624e59d7a7f8a4b" dependencies = [ "bytes", "futures-core", @@ -2187,9 +2197,9 @@ checksum = "b6f5e870be6c3b371b77fe0ee0bafb859fa4964b4404c27de1d380043c4dda20" [[package]] name = "unicode-ident" -version = "1.0.26" +version = "1.0.27" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "d245f478577f809a851594d02313b640fb437e0bb33866753cff937863096954" +checksum = "a2c754d6c33795a1c324727428e5a7dedb5b06195f9890bdbcba760d3e246563" [[package]] name = "unicode-normalization-alignments" @@ -2244,9 +2254,9 @@ checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a" [[package]] name = "want" -version = "0.3.1" +version = "0.3.2" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "bfa7760aed19e106de2c7c0b581b509f2f25d3dacaf737cb82ac61bc6d760b0e" +checksum = "ec4cdd0dd910afe868b7ef477227d8d538b46b3075031afee8a9f2acb0a2ed0b" dependencies = [ "try-lock", ] @@ -2309,7 +2319,7 @@ dependencies = [ "bumpalo", "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", "wasm-bindgen-shared", ] @@ -2357,9 +2367,9 @@ dependencies = [ [[package]] name = "webpki-roots" -version = "1.0.9" +version = "1.0.11" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "7dcd9d09a39985f5344844e66b0c530a33843579125f23e21e9f0f220850f22a" +checksum = "f5f280bbb2b287bc8e7de7e3852945a0ff50d1bbcb5ed42b6c7a568c546df171" dependencies = [ "rustls-pki-types", ] @@ -2466,9 +2476,9 @@ checksum = "3ad82d2a33cdc9674dc7465672f271e096168fcdbe0f799d9e6db8c5892679dc" [[package]] name = "yoke" -version = "0.8.3" +version = "0.8.4" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "709fe23a0424b6a435d82152b1bd3fdfb0833487d5fa90d05d42762a9891fef5" +checksum = "417ef3fcf6c300b7dbd25c85531a746931c02ad536f3cf4786ed1e88223340b3" dependencies = [ "stable_deref_trait", "yoke-derive", @@ -2477,30 +2487,30 @@ dependencies = [ [[package]] name = "yoke-derive" -version = "0.8.3" +version = "0.8.4" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "33811428bee40dbceb6d545e95754741d17a6aef9a4849f0fd62e2ba4f412a78" +checksum = "ec8ebde2db3681e8c9980cc27822030e68752690ddfa9473e739aeb4dbde6d71" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", "synstructure", ] [[package]] name = "zerocopy" -version = "0.8.59" +version = "0.8.63" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "6df92bf3d9227be3d53173901ddbffac2babc27ae50f397776ffd6dc33f800cb" +checksum = "e5fe1f8f1b06191a00962174c61aa5005e0bb391a6d80d07e24d115c01a92ed8" dependencies = [ "zerocopy-derive", ] [[package]] name = "zerocopy-derive" -version = "0.8.59" +version = "0.8.63" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "ac4f328cf2f05d084e496c3e9c3f33ed0a183656a16e1fcec4d464d8373aec82" +checksum = "863ad3ac83293fb4d740aedbfdc9240dd8d1a50c1099acd76ce80ce7c7230c7f" dependencies = [ "proc-macro2", "quote", @@ -2524,15 +2534,15 @@ checksum = "f75b4683f6c7f45248d4d64056a24298c6281e0993356d7d1b4a1a962ef10d4a" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", "synstructure", ] [[package]] name = "zeroize" -version = "1.9.0" +version = "1.9.1" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "e13c156562582aa81c60cb29407084cdb54c4164760106ab78e6c5b0858cf64e" +checksum = "e13084392c5e4bc371903e2935a5eaeed24905a7511356b883835e18a78f6879" [[package]] name = "zerotrie" @@ -2547,9 +2557,9 @@ dependencies = [ [[package]] name = "zerovec" -version = "0.11.8" +version = "0.11.9" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "bb0464e17806c1d976d5cba29399c7f08e516e279e2ba493f63123b5fca67dd8" +checksum = "f58a2799cfe9a1670c7ea8edbd52ef8edb93cb37a7f83bf31ba9e35d9dae6a40" dependencies = [ "yoke", "zerofrom", @@ -2558,13 +2568,13 @@ dependencies = [ [[package]] name = "zerovec-derive" -version = "0.11.6" +version = "0.11.7" source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "34df6fc39dbd26ddc9c10e6a2984476e13acce22e64e4487636ef494369225da" +checksum = "c3743ddbf47738d929cd1ae2e199d40d0162979dfe31aef8ae646d2bf00bf97a" dependencies = [ "proc-macro2", "quote", - "syn 3.0.6", + "syn 3.0.9", ] [[package]] diff --git a/Cargo.toml b/Cargo.toml index 580fbee2..221eabfd 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -1,3 +1,3 @@ [workspace] -members = ["src/frontend", "src/runtime", "src/models/clm", "src/models/cua_s1/native", "src/models/qwen3_5/native", "src/models/open_jev/native", "src/models/jev_vl/native", "src/models/omnijev/native", "src/models/laya", "src/backends/cuda", "src/models/decider/native"] +members = ["src/frontend", "src/runtime", "src/models/clm", "src/models/cua_s1/native", "src/models/qwen3_5/native", "src/models/open_jev/native", "src/models/jev_vl/native", "src/models/omnijev/native", "src/models/laya", "src/backends/cuda", "src/models/decider/native", "src/models/vela/native"] resolver = "3" diff --git a/README.md b/README.md index 88129980..cbfce500 100644 --- a/README.md +++ b/README.md @@ -183,7 +183,7 @@ extensions) on each checkpoint's own pinned runtime: | OmniJev-4B v1.1 | [Checkpoint export and CPU contract](recipe/omnijev/README.md) only; the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | | D3 (Decision 3.0) | [Python reference worker](recipe/d3/reference.md) on the checkpoint's pinned runtime; `choice`/`noul`/`score` text state, media inputs refused; author-run on A100 (evidence in the integration PR) | | Vela 2.0 0.3B | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; all five kinds (`choice`/`noul`/`score`/`span`/`set`) for text state; CPU FP32 validated (author-run, evidence in the integration PR) | -| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; CPU FP32 parity recorded in the integration PR | +| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; [native library](recipe/vela/native.md) (bundle export, wire contract); CPU FP32 parity recorded in the integration PR | [Supported models and hardware](docs/supported-models.md) lists the devices and where each worker has been run. diff --git a/docs/supported-models.md b/docs/supported-models.md index 52b31a0b..30a52c6b 100644 --- a/docs/supported-models.md +++ b/docs/supported-models.md @@ -25,7 +25,7 @@ Models that are being added are also tracked in issues labeled [new model](https | OmniJev-4B v1.1 | None yet: [checkpoint export and CPU contract](../recipe/omnijev/README.md); the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | Request contract, preparation, heads and finishing checked against the reference ([#120](https://github.com/ThinkFlowLab/system1-omni/pull/120)); no inference | Not yet | Not supported | Python 3.10 reference environment for the export and fixtures | | D3 (Decision 3.0) | [Python reference worker](../recipe/d3/reference.md) running the checkpoint's pinned runtime | Unverified | Author-run on NVIDIA A100 (sm_80): three-kind serving smoke with byte-identical frontend forwarding and reference parity (exact decisions, max delta 0.0, 348 == 348 tokens); evidence in the integration PR. Owner: @MrDongsls. | Unverified | Python 3.12, the [pinned runtime requirements](../recipe/d3/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/d3) (~52 GB) | | Vela 2.0 0.3B | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime | **CPU FP32 validated** (author-run, x86 WSL2, 24 cores): startup with all-kind warmup, the four example requests plus five synthetic rejections, and exact-match reference parity against the pinned upstream server on all nine (four 200s byte-equal incl. key order, agreed 422/413); byte-identical frontend forwarding; evidence in the integration PR. Owner: @MrDongsls. | Unverified (bf16-autocast is an untested deployment option) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.3B) (1.24 GB FP32 weights; ~4.4 GB with ONNX/assets) | -| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B) | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | +| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B); [native library](../recipe/vela/native.md) — bundle export, wire contract | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | - **Validated:** covered by the recipe on `main` or by the checks in the linked merged pull request. - **Author-run:** recorded by the recipe author on the stated hardware and not independently reproduced; the row names its owner. diff --git a/mkdocs.yml b/mkdocs.yml index 8f2d39fe..d6593f4a 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -77,4 +77,5 @@ nav: - LFM2.5-350M choice worker: recipe/lfm2/README.md - D3 reference worker: recipe/d3/reference.md - Vela 2.0 reference workers: recipe/vela/reference.md + - Vela 2.0 0.8B native library: recipe/vela/native.md - Contributing: CONTRIBUTING.md diff --git a/recipe/vela/export_native.py b/recipe/vela/export_native.py new file mode 100644 index 00000000..96e52ac6 --- /dev/null +++ b/recipe/vela/export_native.py @@ -0,0 +1,168 @@ +#!/usr/bin/env python3 +"""Export the pinned Vela 2.0 0.8B package into a native bundle. + +The bundle re-keys the hybrid +backbone for the shared qwen3_5 native loader — ``backbone.X`` tensors +become ``model.X`` (the loader's prefix probe accepts ``model.``), with +**per-tensor dtypes preserved verbatim** (Linear/conv1d in BF16, +embeddings/norms/A_log/dt_bias in FP32 — the reference's own mixed +layout, no re-save rounding) — and copies the Vela-owned F32 heads and +the side-loaded broad span head as separate files, plus calibration and +tokenizer. ``config.json`` is the package's ``backbone_config`` written +at the root, which is exactly the shape the family ``Config::load`` +reads. The manifest pins every source file by SHA-256 (re-using the +worker's own gate table) and records the exported tensor inventory. + + PYTHONPATH=src .venv/bin/python recipe/vela/export_native.py \ + --package weights/vela-2.0-0.8b --out weights/vela-2.0-0.8b-native +""" + +from __future__ import annotations + +import argparse +import hashlib +import json +import shutil +import sys +from pathlib import Path + +BACKBONE_PREFIX = "backbone." +HEAD_PREFIXES = ("head.", "span2.", "set_bias") +FORMAT = "vela2-native-bundle/1" + + +def parse_args(argv=None): + parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) + parser.add_argument("--package", required=True, help="pinned Vela 2.0 0.8B package directory") + parser.add_argument("--out", required=True, help="output bundle directory (created)") + parser.add_argument( + "--bf16-out", + default=None, + help="also write a uniform-BF16 backbone directory for the shared qwen3_5 " + "loader (model.safetensors + config.json)", + ) + return parser.parse_args(argv) + + +def sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as stream: + for chunk in iter(lambda: stream.read(8 * 1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def main(argv=None) -> int: + args = parse_args(argv) + sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "src")) + import torch + from safetensors.torch import load_file, save_file + + from models.vela.hybrid import ( + HYBRID_REPO, + HYBRID_REVISION, + PINNED_FILES_SHA256, + verify_package, + ) + + package = Path(args.package) + out = Path(args.out) + verify_package(package) # the worker's own gate: provenance before export + config = json.loads((package / "config.json").read_text(encoding="utf-8")) + backbone_config = config["backbone_config"] + + # The shard map names every backbone and head tensor; broad_head is a + # separate side-loaded file. + index = json.loads((package / "model.safetensors.index.json").read_text(encoding="utf-8")) + weight_map: dict[str, str] = index["weight_map"] + shard_files = sorted(set(weight_map.values())) + tensors = {} + for name in shard_files: + tensors.update(load_file(str(package / name))) + broad = load_file(str(package / "broad_head.safetensors")) + + backbone, heads = {}, {} + dtypes: dict[str, dict[str, str]] = {"backbone": {}, "heads": {}} + for name, tensor in sorted(weight_map.items()): + value = tensors[name] + dtype = str(value.dtype).removeprefix("torch.") + if name.startswith(BACKBONE_PREFIX): + rekeyed = "model." + name[len(BACKBONE_PREFIX):] + backbone[rekeyed] = value + dtypes["backbone"][rekeyed] = f"{dtype}:{list(value.shape)}" + elif name.startswith(HEAD_PREFIXES): + heads[name] = value + dtypes["heads"][name] = f"{dtype}:{list(value.shape)}" + else: + raise SystemExit(f"unexpected tensor key {name!r}; update the export for the new prefix") + for name, value in sorted(broad.items()): + heads[name] = value + dtypes["heads"][name] = f"{str(value.dtype).removeprefix('torch.')}:{list(value.shape)}" + + out.mkdir(parents=True, exist_ok=True) + save_file(backbone, str(out / "backbone.safetensors")) + save_file(heads, str(out / "heads.safetensors")) + # config.json for the family loader: backbone_config at the root. + (out / "config.json").write_text(json.dumps(backbone_config, indent=1) + "\n", encoding="utf-8") + for name in ("calibration.json", "tokenizer.json", "tokenizer_config.json"): + shutil.copyfile(package / name, out / name) + + bf16 = sum(1 for d in dtypes["backbone"].values() if d.startswith("bfloat16")) + fp32 = len(dtypes["backbone"]) - bf16 + manifest = { + "format": FORMAT, + "model_id": "vllm-sr/Vela-2.0-0.8B", + "model_name": config["model_name"], + "max_length": config["max_length"], + "description": config.get("description", ""), + "source": { + "repo": HYBRID_REPO, + "revision": HYBRID_REVISION, + # The worker gate's own table, re-verified above. + "pinned_files_sha256": dict(PINNED_FILES_SHA256), + "shard_files": shard_files, + }, + "backbone": { + "tensors": len(backbone), + "bf16": bf16, + "fp32": fp32, + "note": "per-tensor dtypes preserved from the package; backbone.X re-keyed to model.X", + "inventory": dtypes["backbone"], + }, + "heads": { + "tensors": len(heads), + "inventory": dtypes["heads"], + "note": "Vela-owned F32 heads (CandidateHead, set_bias, span2 router, span_broad) in one file", + }, + "files_sha256": {}, + } + for name in [ + "backbone.safetensors", "heads.safetensors", "config.json", + "calibration.json", "tokenizer.json", "tokenizer_config.json", + ]: + manifest["files_sha256"][name] = sha256(out / name) + (out / "vela_native_manifest.json").write_text( + json.dumps(manifest, indent=1, sort_keys=True) + "\n", encoding="utf-8" + ) + + if args.bf16_out: + # Uniform-BF16 re-save for the family crate's loader: every + # backbone tensor rounds to bfloat16 once, at export (the + # reference's own GPU setting runs the backbone under bf16 + # autocast too). + bf16_dir = Path(args.bf16_out) + bf16_dir.mkdir(parents=True, exist_ok=True) + uniform = {name: value.to(torch.bfloat16) for name, value in backbone.items()} + save_file(uniform, str(bf16_dir / "model.safetensors")) + (bf16_dir / "config.json").write_text(json.dumps(backbone_config, indent=1) + "\n", encoding="utf-8") + print(f"bf16 backbone: {len(uniform)} tensors -> {bf16_dir}") + + print(f"export ok: {out}") + print(f" backbone: {len(backbone)} tensors ({bf16} bf16, {fp32} fp32), re-keyed {BACKBONE_PREFIX} -> model.") + print(f" heads: {len(heads)} tensors (F32, incl. span_broad)") + print(f" config: backbone_config at root, model_type={backbone_config.get('model_type')}") + return 0 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/recipe/vela/export_token_plan.py b/recipe/vela/export_token_plan.py new file mode 100644 index 00000000..39bfb2ea --- /dev/null +++ b/recipe/vela/export_token_plan.py @@ -0,0 +1,153 @@ +#!/usr/bin/env python3 +"""Freeze the token-level row plan of the pinned Vela 2.0 0.8B runtime. + +This tool records, for a set of request +bodies, exactly what the pinned runtime feeds the backbone — the +SystemOne → predict mapping, the per-row decomposition (parts pass + +question blocks; one span question per row), and the rendered records +(``p_ids``, block token ids with option/label end positions, query +positions, span word positions, truncation and segment lengths). The +native Rust processor must reproduce these byte-for-byte; the frozen +files under ``tests/vela/fixtures/native-plan-*.json`` are that parity +target. Model outputs are not recorded here — the oracle fixtures from +``compare_reference.py`` own the output side. + + PYTHONPATH=src .venv/bin/python recipe/vela/export_token_plan.py \ + --model weights/vela-2.0-0.8b --out tests/vela/fixtures/ +""" + +from __future__ import annotations + +import argparse +import json +import sys +from pathlib import Path + +import numpy as np + +HERE = Path(__file__).resolve().parent +MODEL_NAME = "vllm-sr/Vela-2.0-0.8B" + + +def parse_args(argv=None): + parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) + parser.add_argument("--model", required=True, help="pinned Vela 2.0 0.8B package directory") + parser.add_argument("--out", default=None, help="fixture output directory") + return parser.parse_args(argv) + + +def long_span_body(): + """A span target beyond HYBRID_RMAX (2,048 tokens) to exercise the + windowed layout: the full-render span block is skipped and one row + per 1,800-token window (stride 1,536, cut at word starts) carries + the span question.""" + + filler = " ".join(f"Sentence {i} reports a routine delivery event." for i in range(220)) + return { + "model": MODEL_NAME, + "state": {"request": filler}, + "questions": { + "claims": { + "type": "span", + "instructions": "Which spans mention a delivery?", + "criteria": {"delivery": "a delivery event"}, + "over": "request", + } + }, + } + + +def cases(): + named = [ + ("example-request", HERE / "example-request.json"), + ("example-request-set-threshold", HERE / "example-request-set-threshold.json"), + ("example-request-cjk", HERE / "example-request-cjk.json"), + ("example-request-score", HERE / "example-request-score.json"), + ] + loaded = [ + ( + name, + {**json.loads(path.read_text(encoding="utf-8")), "model": MODEL_NAME}, + ) + for name, path in named + ] + loaded.append(("long-span-windowed", long_span_body())) + return loaded + + +def plain(value): + """numpy-free JSON for the rendered records.""" + + if isinstance(value, dict): + return {key: plain(item) for key, item in value.items()} + if isinstance(value, (list, tuple)): + return [plain(item) for item in value] + if isinstance(value, np.ndarray): + return plain(value.tolist()) + if isinstance(value, (np.integer,)): + return int(value) + if isinstance(value, (np.floating,)): + return float(value) + if isinstance(value, (np.bool_,)): + return bool(value) + return value + + +def rows_of(engine, body): + """Mirror ``Vela2._predict``'s row decomposition and render each row.""" + + from vela2_inference import system_one_to_predict + + req, plan = system_one_to_predict(body["state"], body["questions"]) + parts, qs, _thr = engine._to_generic(req) + spans = [q for q in qs if q["type"] == "span"] + rest = [q for q in qs if q["type"] != "span"] + rows = [dict(parts=parts, questions=rest + spans[:1])] + [ + dict(parts=parts, questions=[s]) for s in spans[1:] + ] + rendered, windows = [], [] + for row in rows: + if not row["questions"]: + continue + prepped = engine._prep(row) + rec = plain(engine._render(prepped)) + rec["head"] = prepped["head"] + rec["head_reason"] = prepped["head_reason"] + rendered.append(rec) + for wrow in engine._window_rows(prepped) or []: + wrec = plain(engine._render(wrow)) + wrec["head"] = prepped["head"] + windows.append(wrec) + return plain(req), plain(plan), rendered, windows + + +def main(argv=None) -> int: + args = parse_args(argv) + sys.path.insert(0, str(Path(args.model).resolve())) + from vela2_inference import Vela2 + + engine = Vela2.from_pretrained(args.model, backend="torch", device="cpu") + out = Path(args.out) if args.out else HERE.parents[1] / "tests" / "vela" / "fixtures" + out.mkdir(parents=True, exist_ok=True) + for name, body in cases(): + req, plan, rows, windows = rows_of(engine, body) + fixture = { + "case": name, + "request": body, + "predict_request": req, + "plan": plan, + "rows": rows, + "window_rows": windows, + } + target = out / f"native-plan-{name}.json" + target.write_text(json.dumps(fixture, ensure_ascii=False) + "\n", encoding="utf-8") + tokens = sum(r["n_tokens"] for r in rows) + sum(r["n_tokens"] for r in windows) + print( + f"{name}: {len(rows)} row(s) + {len(windows)} window row(s), " + f"{tokens} tokens -> {target.name}" + ) + return 0 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/recipe/vela/native.md b/recipe/vela/native.md new file mode 100644 index 00000000..a9328003 --- /dev/null +++ b/recipe/vela/native.md @@ -0,0 +1,49 @@ +# Vela 2.0 0.8B native library + +The native implementation for +[vllm-sr/Vela-2.0-0.8B](https://huggingface.co/vllm-sr/Vela-2.0-0.8B): +the exported-bundle gate and the wire contract, mirrored from the +pinned runtime. This is a library; serving runs through the +[reference recipe](reference.md)'s Python worker. + +Run the commands from the repository root with the same `.venv` and +pinned package as the reference recipe. The export needs about 6 GB of +free disk next to the package; the checks need no GPU. + +## Export the native bundle + +~~~sh +PYTHONPATH=src .venv/bin/python recipe/vela/export_native.py \ + --package weights/vela-2.0-0.8b --out weights/vela-2.0-0.8b-native +~~~ + +The export re-runs the reference worker's package gate first +(provenance), then writes `weights/vela-2.0-0.8b-native/`: the backbone +re-keyed `backbone.` → `model.` with **per-tensor dtypes preserved** +(204 BF16 Linear/conv1d, 116 F32 embed/norms/A_log/dt_bias — the +reference's own mixed layout), the 37 F32 heads in `heads.safetensors` +(including the side-loaded broad span head), `backbone_config` at the +config root (the shared qwen3_5 `Config::load` shape), calibration and +tokenizer, and `vela_native_manifest.json` pinning the source +revision, the gate's file table, the tensor inventory and every file's +SHA-256. + +## Checks + +~~~sh +cargo test -p omni-vela-native +cargo fmt --all --check +cargo clippy -p omni-vela-native --all-targets -- -D warnings +~~~ + +15 tests, no weights, no GPU: the wire contract against the pinned +runtime's 422/400 bodies and the bundle manifest gate against a +synthetic bundle. + +## Scope and limits + +- Implemented: the bundle export + manifest gate and the wire + admission. +- Not implemented: token-level processing, the F32 heads, scoring, + backbone execution, and an HTTP worker. No performance claims are + made. diff --git a/src/models/vela/README.md b/src/models/vela/README.md index 9407d4fa..888658fc 100644 --- a/src/models/vela/README.md +++ b/src/models/vela/README.md @@ -225,3 +225,29 @@ the shared worker-contract issue, and nothing is posted upstream. a deployment option outside these slices' evidence. - The serving procedure, hardware requirements and the recorded evidence pointer are [recipe/vela/reference.md](../../recipe/vela/reference.md). + +## Native path (0.8B) + +The native implementation lives in [`native/`](native/) as the +`omni-vela-native` crate, a library around the exported bundle: + +- [`recipe/vela/export_native.py`](../../recipe/vela/export_native.py) + exports the pinned package into a native bundle: the 320 backbone + tensors re-keyed `backbone.` → `model.` with **per-tensor dtypes + preserved** (204 BF16 Linear/conv1d + 116 F32 embed/norms/A_log/ + dt_bias — the reference's own layout), the 37 F32 head tensors + (CandidateHead, `set_bias`, span2 router, span_broad) in one file, + `backbone_config` at the config root, calibration and tokenizer + copied, and a manifest pinning the source revision, the worker + gate's own file table, the tensor inventory and every bundle file's + SHA-256. +- `native/src/bundle.rs` re-verifies that manifest (revision, + inventory counts, per-file hashes) before anything loads it. +- `native/src/contract.rs` is the wire admission, mirroring + `protocol.py` and the pinned runtime's preamble with byte-equal + 422/400 bodies. + +Token-level processing, the F32 heads, backbone execution and an HTTP +worker are not implemented. Checks: `cargo test -p omni-vela-native` +(15 tests, no weights, no GPU; see +[recipe/vela/native.md](../../recipe/vela/native.md)). diff --git a/src/models/vela/native/Cargo.toml b/src/models/vela/native/Cargo.toml new file mode 100644 index 00000000..814d32b0 --- /dev/null +++ b/src/models/vela/native/Cargo.toml @@ -0,0 +1,26 @@ +[package] +name = "omni-vela-native" +version = "0.1.0" +edition = "2024" +publish = false +description = "Native library for vllm-sr/Vela-2.0-0.8B: bundle gate and wire contract" + +[dependencies] +anyhow = "1.0.100" +omni-qwen3-5-native = { path = "../../qwen3_5/native" } +serde_json = { version = "1.0.149", features = ["preserve_order"] } +sha2 = "0.11" + +[dev-dependencies] +sha2 = "0.11" + +[lib] +path = "src/lib.rs" + +[[test]] +name = "vela_native_contract" +path = "../../../../tests/vela/native_contract.rs" + +[[test]] +name = "vela_native_bundle" +path = "../../../../tests/vela/native_bundle.rs" diff --git a/src/models/vela/native/src/bundle.rs b/src/models/vela/native/src/bundle.rs new file mode 100644 index 00000000..ce31f839 --- /dev/null +++ b/src/models/vela/native/src/bundle.rs @@ -0,0 +1,112 @@ +//! The exported native bundle's manifest gate. +//! +//! [`recipe/vela/export_native.py`](../../../recipe/vela/export_native.py) +//! produces the bundle from the pinned package; this module loads its +//! manifest, pins the source revision and the member's tensor +//! inventory, and re-hashes every bundle file before the (future) +//! executor touches it — the same provenance-before-import discipline +//! as the reference worker's package gate. + +use std::path::{Path, PathBuf}; + +use anyhow::{Context, Result, ensure}; +use serde_json::Value; + +pub const FORMAT: &str = "vela2-native-bundle/1"; +pub const MODEL_ID: &str = "vllm-sr/Vela-2.0-0.8B"; +pub const SOURCE_REVISION: &str = "326b01d81f61fff7fd4ae570e54b87a49119e490"; +/// This member's exported inventory, pinned from the pinned package: +/// 320 backbone tensors (204 BF16 Linear/conv1d + 116 F32) and 37 F32 +/// head tensors (CandidateHead, set_bias, span2 router, span_broad). +pub const BACKBONE_TENSORS: (usize, usize, usize) = (320, 204, 116); +pub const HEAD_TENSORS: usize = 37; + +#[derive(Debug)] +pub struct Bundle { + pub dir: PathBuf, + pub manifest: Value, +} + +impl Bundle { + /// Load and fully verify one exported bundle directory. + pub fn load(dir: &Path) -> Result { + let manifest: Value = serde_json::from_slice( + &std::fs::read(dir.join("vela_native_manifest.json")) + .context("export the pinned package first; see recipe/vela/export_native.py")?, + ) + .context("vela_native_manifest.json must be JSON")?; + ensure!( + manifest["format"] == FORMAT + && manifest["model_id"] == MODEL_ID + && manifest["source"]["revision"] == SOURCE_REVISION, + "expected a bundle exported from the pinned {MODEL_ID} package" + ); + let backbone = &manifest["backbone"]; + ensure!( + backbone["tensors"].as_u64() == Some(BACKBONE_TENSORS.0 as u64) + && backbone["bf16"].as_u64() == Some(BACKBONE_TENSORS.1 as u64) + && backbone["fp32"].as_u64() == Some(BACKBONE_TENSORS.2 as u64), + "unexpected backbone inventory; re-export from the pinned package" + ); + ensure!( + manifest["heads"]["tensors"].as_u64() == Some(HEAD_TENSORS as u64), + "unexpected head inventory; re-export from the pinned package" + ); + for (name, digest) in manifest["files_sha256"] + .as_object() + .context("files_sha256 must be an object")? + { + let actual = hash_file(&dir.join(name))?; + ensure!( + actual == digest.as_str().unwrap_or(""), + "{name} does not match the manifest SHA-256" + ); + } + ensure!( + manifest["max_length"].as_u64() == Some(16_384) + && manifest["model_name"].as_str() == Some(MODEL_ID), + "unexpected member identity in the manifest" + ); + Ok(Self { + dir: dir.to_owned(), + manifest, + }) + } + + /// The served model name (upstream: config.json `model_name`). + pub fn model_name(&self) -> &str { + self.manifest["model_name"].as_str().unwrap_or(MODEL_ID) + } + + /// The member's input window. + pub fn max_length(&self) -> usize { + self.manifest["max_length"].as_u64().unwrap_or(16_384) as usize + } +} + +fn hash_file(path: &Path) -> Result { + use anyhow::bail; + use sha2::{Digest, Sha256}; + use std::io::Read; + + let mut hasher = Sha256::new(); + let file = match std::fs::File::open(path) { + Ok(file) => file, + Err(error) => bail!("cannot read {}: {error}", path.display()), + }; + let mut reader = std::io::BufReader::new(file); + let mut chunk = vec![0u8; 8 * 1024 * 1024]; + loop { + let read = reader.read(&mut chunk)?; + if read == 0 { + break; + } + hasher.update(&chunk[..read]); + } + Ok(hex(&hasher.finalize())) +} + +/// Lower-hex of a digest; sha2 0.11's output has no `LowerHex` impl. +fn hex(bytes: &[u8]) -> String { + bytes.iter().map(|byte| format!("{byte:02x}")).collect() +} diff --git a/src/models/vela/native/src/contract.rs b/src/models/vela/native/src/contract.rs new file mode 100644 index 00000000..06a3de95 --- /dev/null +++ b/src/models/vela/native/src/contract.rs @@ -0,0 +1,142 @@ +//! Vela 2.0 wire admission for the native worker, mirroring +//! `models.vela.protocol` and the pinned runtime's request preamble so +//! clients cannot tell this layer from the reference worker: the +//! three-field envelope with upstream's exact `{"detail": [{"loc", +//! "msg", "type"}]}` triples, and the whole-request error model. +//! +//! Deeper validation — state rendering, question semantics, the 413 — +//! lives in the processing modules and mirrors the pinned runtime +//! against the `native-plan-*` fixtures. One known residual +//! difference: a non-finite JSON number answers the generic 400 +//! message here, where the Python worker names the value; duplicate +//! keys are mirrored verbatim. + +use serde_json::{Map, Value, json}; + +/// Slice-scoped transport cap, as on the reference worker. +pub const MAX_BODY: usize = 8 * 1024 * 1024; +/// The envelope fields, in upstream's missing-field check order. +pub const REQUEST_FIELDS: [&str; 3] = ["state", "model", "questions"]; + +/// A request rejection: an HTTP status and the JSON body a client sees. +#[derive(Debug, PartialEq)] +pub struct RequestError { + pub status: u16, + pub body: Value, +} + +impl RequestError { + fn detail(status: u16, message: &str) -> Self { + Self { + status, + body: json!({"detail": message}), + } + } + + /// One upstream `SystemOneError` as a whole-request 422 triple. + pub fn envelope(loc: &[&str], msg: &str, type_: &str) -> Self { + let mut path = vec![Value::from("body")]; + path.extend(loc.iter().map(|part| Value::from(*part))); + Self { + status: 422, + body: json!({"detail": [{"loc": path, "msg": msg, "type": type_}]}), + } + } +} + +/// Decode a bounded JSON body and reject ambiguous JSON values. +pub fn parse_body(raw: &[u8]) -> Result, RequestError> { + if raw.len() > MAX_BODY { + return Err(RequestError::detail(413, "request body exceeds 8 MiB")); + } + let message = + omni_qwen3_5_native::json::parse(raw).map_err(|error| normalize_parse_error(&error))?; + Ok(message) +} + +/// Mirror the reference worker's 400 messages: duplicate keys verbatim, +/// everything else the shared generic message. +fn normalize_parse_error(error: &str) -> RequestError { + if let Some(rest) = error.split("duplicate key ").nth(1) { + // serde appends its position suffix after the quoted key. + if let Some(key) = rest + .strip_prefix('"') + .and_then(|tail| tail.split('"').next()) + { + return RequestError::detail(400, &format!("duplicate JSON key '{key}'")); + } + } + RequestError::detail(400, "request body must contain valid JSON and UTF-8 text") +} + +/// Admit the envelope exactly as upstream's request preamble does, for +/// one served model name: the three required fields present, no extra +/// field, `model` non-blank and equal to the served name. +pub fn admit_request(body: &Map, served: &str) -> Result<(), RequestError> { + for field in REQUEST_FIELDS { + if !body.contains_key(field) { + return Err(RequestError::envelope( + &[field], + "Field required", + "missing", + )); + } + } + let mut extra: Vec<&String> = body + .keys() + .filter(|key| !REQUEST_FIELDS.contains(&key.as_str())) + .collect(); + extra.sort(); + if let Some(first) = extra.first() { + return Err(RequestError::envelope( + &[first], + "Extra inputs are not permitted", + "extra_forbidden", + )); + } + let model = body["model"].as_str().unwrap_or(""); + if model.trim().is_empty() { + return Err(RequestError::envelope( + &["model"], + "model must not be empty or whitespace", + "value_error", + )); + } + if model != served { + return Err(RequestError::envelope( + &["model"], + "Model is not served by this runtime", + "value_error.model", + )); + } + Ok(()) +} + +/// Admit one complete raw request body: parse, then envelope-check. +pub fn compile(raw: &[u8], served: &str) -> Result, RequestError> { + let body = parse_body(raw)?; + admit_request(&body, served)?; + Ok(body) +} + +/// A pinned-runtime `ValueError` rejection as the reference worker maps +/// it (`map_runtime_error`): a whole-request 422 naming the runtime. +pub fn runtime_rejection(message: &str) -> RequestError { + RequestError::detail( + 422, + &format!("request rejected by the pinned runtime: {message}"), + ) +} + +#[cfg(test)] +mod tests { + use super::*; + + #[test] + fn duplicate_keys_mirror_the_reference_message() { + let error = + normalize_parse_error("request body is not valid JSON: duplicate key \"state\""); + assert_eq!(error.status, 400); + assert_eq!(error.body, json!({"detail": "duplicate JSON key 'state'"})); + } +} diff --git a/src/models/vela/native/src/lib.rs b/src/models/vela/native/src/lib.rs new file mode 100644 index 00000000..32f64c4f --- /dev/null +++ b/src/models/vela/native/src/lib.rs @@ -0,0 +1,5 @@ +//! Native library for vllm-sr/Vela-2.0-0.8B: the exported-bundle gate +//! and the wire contract, mirrored from the pinned runtime. + +pub mod bundle; +pub mod contract; diff --git a/tests/vela/fixtures/native-plan-example-request-cjk.json b/tests/vela/fixtures/native-plan-example-request-cjk.json new file mode 100644 index 00000000..01973a26 --- /dev/null +++ b/tests/vela/fixtures/native-plan-example-request-cjk.json @@ -0,0 +1 @@ +{"case": "example-request-cjk", "request": {"model": "vllm-sr/Vela-2.0-0.8B", "state": {"request": "客户张伟（zhang.wei@example.cn）于2026年10月1日在上海市浦东新区世纪大道100号办理了业务，联系电话13800138000。", "source": "客户的业务申请需要在三个工作日内审核完成。", "answer": "客户的业务已经即时完成了。"}, "questions": {"pii": {"type": "span", "instructions": "Which spans are personal information?", "criteria": {"PERSON": "a person's name", "EMAIL_ADDRESS": "an e-mail address", "PHONE_NUMBER": "a telephone number", "STREET_ADDRESS": "a street address or postal address"}, "over": "request"}, "unsupported": {"type": "span", "instructions": "Which spans of the answer are not supported by the context?", "criteria": {"unsupported": "a claim not supported by the context"}}, "billing": {"type": "noul", "instructions": "这个请求是否与账单有关？"}}}, "predict_request": {"parts": [{"type": "user", "text": "客户张伟（zhang.wei@example.cn）于2026年10月1日在上海市浦东新区世纪大道100号办理了业务，联系电话13800138000。"}, {"type": "context", "text": "客户的业务申请需要在三个工作日内审核完成。"}, {"type": "answer", "text": "客户的业务已经即时完成了。"}], "questions": [{"id": "pii", "type": "span", "text": "Which spans are personal information?", "target_part": "user", "labels": [{"name": "PERSON", "description": "a person's name"}, {"name": "EMAIL_ADDRESS", "description": "an e-mail address"}, {"name": "PHONE_NUMBER", "description": "a telephone number"}, {"name": "STREET_ADDRESS", "description": "a street address or postal address"}]}, {"id": "unsupported", "type": "span", "text": "Which spans of the answer are not supported by the context?", "target_part": "answer", "labels": [{"name": "unsupported", "description": "a claim not supported by the context"}]}, {"id": "billing", "type": "choice", "text": "这个请求是否与账单有关？", "target_part": ["user", "context", "answer"], "options": [{"name": "no", "description": "No. The statement or question is not satisfied."}, {"name": "yes", "description": "Yes. 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a/tests/vela/fixtures/native-plan-example-request-score.json b/tests/vela/fixtures/native-plan-example-request-score.json new file mode 100644 index 00000000..fc67c0f8 --- /dev/null +++ b/tests/vela/fixtures/native-plan-example-request-score.json @@ -0,0 +1 @@ +{"case": "example-request-score", "request": {"model": "vllm-sr/Vela-2.0-0.8B", "state": "Hello, I would like to check the status of my order. It has been five days and I have heard nothing back.", "questions": {"tone": {"type": "score", "instructions": "How formal is the message?", "criteria": ["casual", "neutral", "formal"]}, "urgency": {"type": "score", "instructions": "How urgently does the sender need a reply?", "criteria": ["no rush", "soon", "today", "immediately"]}}}, "predict_request": {"parts": [{"type": "user", "text": "Hello, I would like to check the status of my order. 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refunds or invoices", "shipping": "delivery of an order or a parcel", "login": "signing in, passwords or account access"}, "threshold": 0.15}}}, "predict_request": {"parts": [{"type": "user", "text": "My card was charged twice and the parcel never arrived."}], "questions": [{"id": "issues", "type": "set", "text": "Which issues does the customer report?", "target_part": "user", "options": [{"name": "billing", "description": "payments, charges, refunds or invoices"}, {"name": "shipping", "description": "delivery of an order or a parcel"}, {"name": "login", "description": "signing in, passwords or account access"}], "threshold": 0.15}]}, "plan": [{"qid": "issues", "type": "set", "criteria": {"billing": "payments, charges, refunds or invoices", "shipping": "delivery of an order or a parcel", "login": "signing in, passwords or account access"}, "range": null, "part": "user"}], "rows": [{"p_ids": [1905, 25, 198, 27, 22446, 3364, 420, 846, 731, 198, 4888, 3575, 557, 11102, 10598, 321, 279, 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a/tests/vela/fixtures/native-plan-example-request.json b/tests/vela/fixtures/native-plan-example-request.json new file mode 100644 index 00000000..09bab119 --- /dev/null +++ b/tests/vela/fixtures/native-plan-example-request.json @@ -0,0 +1 @@ +{"case": "example-request", "request": {"model": "vllm-sr/Vela-2.0-0.8B", "state": {"request": "Hi, I'm Tom Baker (tom.baker@example.com). What is the maximum daily dose of paracetamol for an adult?", "source": "For adults, the maximum dose of paracetamol is 4 grams in 24 hours, taken as 500 mg to 1 g every 4 to 6 hours.", "answer": "Adults can take up to 6 grams of paracetamol in 24 hours, in doses of 500 mg to 1 g every 4 to 6 hours."}, "questions": {"pii": {"type": "span", "instructions": "Which spans are personal information?", "criteria": {"AGE": "a person's age", "CREDIT_CARD": "a payment card number", "DATE_TIME": "a date, time or date of birth", "DOMAIN_NAME": "an internet domain name or website address", "EMAIL_ADDRESS": "an e-mail address", "GPE": "a country, city, state or other geopolitical place", "IBAN_CODE": "an international bank account number (IBAN)", "IP_ADDRESS": "an IPv4 or IPv6 address", "NRP": "a nationality, religious or political group", "ORGANIZATION": "the name of a company, institution or other organisation", "PERSON": "a person's name", "PHONE_NUMBER": "a telephone number", "STREET_ADDRESS": "a street address or postal address", "TITLE": "a personal or professional title such as Dr. or Mrs.", "US_DRIVER_LICENSE": "a US driver's licence number", "US_SSN": "a US social security number", "ZIP_CODE": "a postal or ZIP code"}, "over": "request"}, "halu": {"type": "span", "instructions": "Which spans of the answer are not supported by the context?", "criteria": {"unsupported": "a claim not supported by the context"}}, "domain": {"type": "choice", "instructions": "Which subject area is this request about?", "over": "request", "criteria": {"health": "medicine, clinical practice, nutrition, ageing or sexual health", "math": "arithmetic, algebra, geometry, statistics or other mathematics", "other": "a subject that fits none of the listed areas"}}}}, "predict_request": {"parts": [{"type": "user", "text": "Hi, I'm Tom Baker (tom.baker@example.com). 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@@ -0,0 +1 @@ +{"case": "long-span-windowed", "request": {"model": "vllm-sr/Vela-2.0-0.8B", "state": {"request": "Sentence 0 reports a routine delivery event. 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Sentence 64 reports a routine delivery event. Sentence 65 reports a routine delivery event. Sentence 66 reports a routine delivery event. Sentence 67 reports a routine delivery event. Sentence 68 reports a routine delivery event. Sentence 69 reports a routine delivery event. Sentence 70 reports a routine delivery event. Sentence 71 reports a routine delivery event. Sentence 72 reports a routine delivery event. Sentence 73 reports a routine delivery event. Sentence 74 reports a routine delivery event. Sentence 75 reports a routine delivery event. Sentence 76 reports a routine delivery event. Sentence 77 reports a routine delivery event. Sentence 78 reports a routine delivery event. Sentence 79 reports a routine delivery event. Sentence 80 reports a routine delivery event. Sentence 81 reports a routine delivery event. Sentence 82 reports a routine delivery event. Sentence 83 reports a routine delivery event. Sentence 84 reports a routine delivery event. 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a/tests/vela/native_bundle.rs b/tests/vela/native_bundle.rs new file mode 100644 index 00000000..81ae9038 --- /dev/null +++ b/tests/vela/native_bundle.rs @@ -0,0 +1,111 @@ +//! Bundle-gate tests: a synthetic bundle built in a unique temp +//! directory (no weights, no network) drives the manifest gate — pins, +//! inventory counts and per-file hashes. + +use omni_vela_native::bundle::{self, Bundle}; +use serde_json::json; + +fn temp_dir(name: &str) -> std::path::PathBuf { + let dir = + std::env::temp_dir().join(format!("vela-native-bundle-{name}-{}", std::process::id())); + let _ = std::fs::remove_dir_all(&dir); + std::fs::create_dir_all(&dir).expect("tempdir"); + dir +} + +fn sha256(bytes: &[u8]) -> String { + use sha2::{Digest, Sha256}; + let digest = Sha256::new_with_prefix(bytes).finalize(); + digest.iter().map(|byte| format!("{byte:02x}")).collect() +} + +/// The minimal manifest of a correctly exported member; `files` are the +/// bundle files the gate hashes. +fn write_bundle(dir: &std::path::Path) { + let files: [(&str, &[u8]); 6] = [ + ("backbone.safetensors", b"backbone tensors"), + ("heads.safetensors", b"head tensors"), + ("config.json", b"{}"), + ("calibration.json", b"{}"), + ("tokenizer.json", b"{}"), + ("tokenizer_config.json", b"{}"), + ]; + let mut hashes = serde_json::Map::new(); + for (name, content) in files { + std::fs::write(dir.join(name), content).expect("write"); + hashes.insert(name.to_string(), json!(sha256(content))); + } + let manifest = json!({ + "format": bundle::FORMAT, + "model_id": bundle::MODEL_ID, + "model_name": "vllm-sr/Vela-2.0-0.8B", + "max_length": 16384, + "source": {"repo": "vllm-sr/Vela-2.0-0.8B", "revision": bundle::SOURCE_REVISION}, + "backbone": {"tensors": 320, "bf16": 204, "fp32": 116}, + "heads": {"tensors": 37}, + "files_sha256": hashes, + }); + std::fs::write( + dir.join("vela_native_manifest.json"), + serde_json::to_vec(&manifest).expect("manifest"), + ) + .expect("write"); +} + +#[test] +fn a_matching_bundle_loads_and_exposes_the_member() { + let dir = temp_dir("ok"); + write_bundle(&dir); + let loaded = Bundle::load(&dir).expect("loads"); + assert_eq!(loaded.model_name(), "vllm-sr/Vela-2.0-0.8B"); + assert_eq!(loaded.max_length(), 16384); + let _ = std::fs::remove_dir_all(&dir); +} + +#[test] +fn a_tampered_file_fails_its_hash() { + let dir = temp_dir("tampered"); + write_bundle(&dir); + std::fs::write(dir.join("calibration.json"), b"{\"tampered\": true}").expect("write"); + let error = Bundle::load(&dir).unwrap_err(); + assert!(error.to_string().contains("calibration.json"), "{error}"); + let _ = std::fs::remove_dir_all(&dir); +} + +#[test] +fn a_foreign_revision_is_refused() { + let dir = temp_dir("foreign"); + write_bundle(&dir); + let manifest_path = dir.join("vela_native_manifest.json"); + let mut manifest: serde_json::Value = + serde_json::from_slice(&std::fs::read(&manifest_path).expect("read")).expect("json"); + manifest["source"]["revision"] = json!("d692394127f6f87fc581d8634c9558fe4776efce"); + std::fs::write(&manifest_path, serde_json::to_vec(&manifest).expect("json")).expect("write"); + let error = Bundle::load(&dir).unwrap_err(); + assert!(error.to_string().contains("pinned"), "{error}"); + let _ = std::fs::remove_dir_all(&dir); +} + +#[test] +fn an_unexpected_inventory_is_refused() { + let dir = temp_dir("inventory"); + write_bundle(&dir); + let manifest_path = dir.join("vela_native_manifest.json"); + let mut manifest: serde_json::Value = + serde_json::from_slice(&std::fs::read(&manifest_path).expect("read")).expect("json"); + manifest["backbone"]["bf16"] = json!(320); + manifest["backbone"]["fp32"] = json!(0); + std::fs::write(&manifest_path, serde_json::to_vec(&manifest).expect("json")).expect("write"); + let error = Bundle::load(&dir).unwrap_err(); + assert!(error.to_string().contains("inventory"), "{error}"); + let _ = std::fs::remove_dir_all(&dir); +} + +#[test] +fn a_missing_manifest_names_the_export_step() { + let dir = temp_dir("empty"); + std::fs::create_dir_all(&dir).expect("tempdir"); + let error = Bundle::load(&dir).unwrap_err(); + assert!(error.to_string().contains("export_native.py"), "{error}"); + let _ = std::fs::remove_dir_all(&dir); +} diff --git a/tests/vela/native_contract.rs b/tests/vela/native_contract.rs new file mode 100644 index 00000000..fbbcf853 --- /dev/null +++ b/tests/vela/native_contract.rs @@ -0,0 +1,122 @@ +//! Wire-contract tests for the native Vela 2.0 worker, mirroring the +//! reference worker's protocol tests: the envelope triples must be +//! byte-equal to the pinned runtime's rejections. + +use omni_vela_native::contract::{self, RequestError}; +use serde_json::json; + +fn body(raw: &str) -> serde_json::Map { + contract::parse_body(raw.as_bytes()).expect("valid body") +} + +fn detail(loc: &[&str], msg: &str, type_: &str) -> serde_json::Value { + let mut path = vec![json!("body")]; + path.extend(loc.iter().map(|part| json!(part))); + json!({"detail": [{"loc": path, "msg": msg, "type": type_}]}) +} + +const SERVED: &str = "vllm-sr/Vela-2.0-0.8B"; + +fn raw_body() -> String { + format!( + r#"{{"model": "{SERVED}", "state": "My card was charged twice.", "questions": {{"billing": {{"type": "noul", "instructions": "any?"}}}}}}"# + ) +} + +#[test] +fn the_envelope_passes_through_unchanged() { + let parsed = body(&raw_body()); + contract::admit_request(&parsed, SERVED).expect("admitted"); + assert_eq!(parsed.len(), 3); +} + +#[test] +fn a_missing_field_reports_upstreams_missing_triple() { + for drop in ["state", "model", "questions"] { + let mut parsed = body(&raw_body()); + parsed.shift_remove(drop); + let error = contract::admit_request(&parsed, SERVED).unwrap_err(); + assert_eq!( + error, + RequestError::envelope(&[drop], "Field required", "missing") + ); + assert_eq!(error.body, detail(&[drop], "Field required", "missing")); + } +} + +#[test] +fn an_extra_field_reports_upstreams_extra_forbidden() { + let mut parsed = body(&raw_body()); + parsed.insert("images".into(), json!([])); + let error = contract::admit_request(&parsed, SERVED).unwrap_err(); + assert_eq!(error.status, 422); + assert_eq!( + error.body, + detail( + &["images"], + "Extra inputs are not permitted", + "extra_forbidden" + ) + ); +} + +#[test] +fn a_blank_model_is_rejected_before_the_name_check() { + let mut parsed = body(&raw_body()); + parsed.insert("model".into(), json!(" ")); + let error = contract::admit_request(&parsed, SERVED).unwrap_err(); + assert_eq!( + error.body, + detail( + &["model"], + "model must not be empty or whitespace", + "value_error" + ) + ); +} + +#[test] +fn another_members_name_is_rejected_with_the_model_triple() { + let mut parsed = body(&raw_body()); + parsed.insert("model".into(), json!("vllm-sr/Vela-2.0-0.3B")); + let error = contract::admit_request(&parsed, SERVED).unwrap_err(); + assert_eq!( + error.body, + detail( + &["model"], + "Model is not served by this runtime", + "value_error.model" + ) + ); +} + +#[test] +fn duplicate_keys_are_rejected_with_the_reference_message() { + let error = + contract::parse_body(br#"{"model": "x", "model": "y", "state": "s", "questions": {}}"#) + .unwrap_err(); + assert_eq!(error.status, 400); + assert_eq!(error.body, json!({"detail": "duplicate JSON key 'model'"})); +} + +#[test] +fn invalid_json_is_a_generic_400() { + let error = contract::parse_body(b"{not json").unwrap_err(); + assert_eq!(error.status, 400); + assert_eq!( + error.body, + json!({"detail": "request body must contain valid JSON and UTF-8 text"}) + ); +} + +#[test] +fn a_non_object_body_is_rejected() { + let error = contract::parse_body(b"[1, 2]").unwrap_err(); + assert_eq!(error.status, 400); +} + +#[test] +fn compile_admits_and_returns_the_body() { + let parsed = contract::compile(raw_body().as_bytes(), SERVED).expect("admitted"); + assert!(parsed.contains_key("questions")); +} From 9812853b28795467871fe78318460a3f75d05994 Mon Sep 17 00:00:00 2001 From: "Mr.Dong" <1042542469@qq.com> Date: Sun, 25 Oct 2026 02:34:48 +0800 Subject: [PATCH 02/32] vela: add the 0.8B native token-level processing MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The Rust processing of the native path, mirrored from the pinned runtime and checked field-for-field against the five frozen token plans (opt-in render parity with the exported bundle's tokenizer): - state.rs: the state -> typed-parts mapping (role grouping, field ranges, canonical DEV2.0 JSON) with the pinned rejection triples; - questions.rs: the SystemOne -> predict mapping — the validation walk and order, Noul folded into a two-option choice (choice renders [ABS], the reference's abstain default), over resolution, threshold/head carried, the set-label collision check; - words.rs: the GLiNER2/CJK _WORD splitter and the first-token word mapping; - render.rs: the encoder (char-offset tokens, memoized), the six-rule span-head dispatch with the hallucination-alias label replacement, the truncation budget, the DEV2.0 rendering (parts pass, question blocks with option ends and query positions, span layout a/c with word positions) and the window rows (head only, as the reference); - processing.rs: the Processor over the exported bundle. Also: the envelope error locs are flat arrays, matching the reference triples exactly. Checks: cargo test (26 tests) + fmt/clippy clean + opt-in render parity (5/5 fixtures). --- Cargo.lock | 3 + README.md | 2 +- docs/supported-models.md | 2 +- recipe/vela/native.md | 44 +- src/models/vela/README.md | 17 +- src/models/vela/native/Cargo.toml | 13 +- src/models/vela/native/examples/parity.rs | 87 +++ src/models/vela/native/src/contract.rs | 15 +- src/models/vela/native/src/lib.rs | 12 +- src/models/vela/native/src/processing.rs | 274 ++++++++ src/models/vela/native/src/questions.rs | 441 ++++++++++++ src/models/vela/native/src/render.rs | 789 ++++++++++++++++++++++ src/models/vela/native/src/state.rs | 235 +++++++ src/models/vela/native/src/words.rs | 119 ++++ tests/vela/native_contract_unit.rs | 14 + tests/vela/native_processing.rs | 137 ++++ tests/vela/native_units.rs | 97 +++ 17 files changed, 2271 insertions(+), 30 deletions(-) create mode 100644 src/models/vela/native/examples/parity.rs create mode 100644 src/models/vela/native/src/processing.rs create mode 100644 src/models/vela/native/src/questions.rs create mode 100644 src/models/vela/native/src/render.rs create mode 100644 src/models/vela/native/src/state.rs create mode 100644 src/models/vela/native/src/words.rs create mode 100644 tests/vela/native_contract_unit.rs create mode 100644 tests/vela/native_processing.rs create mode 100644 tests/vela/native_units.rs diff --git a/Cargo.lock b/Cargo.lock index 2a269f64..bd63bd1c 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -1295,8 +1295,11 @@ version = "0.1.0" dependencies = [ "anyhow", "omni-qwen3-5-native", + "onig", + "serde", "serde_json", "sha2 0.11.1", + "tokenizers 0.22.2", ] [[package]] diff --git a/README.md b/README.md index cbfce500..a68b0fd2 100644 --- a/README.md +++ b/README.md @@ -183,7 +183,7 @@ extensions) on each checkpoint's own pinned runtime: | OmniJev-4B v1.1 | [Checkpoint export and CPU contract](recipe/omnijev/README.md) only; the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | | D3 (Decision 3.0) | [Python reference worker](recipe/d3/reference.md) on the checkpoint's pinned runtime; `choice`/`noul`/`score` text state, media inputs refused; author-run on A100 (evidence in the integration PR) | | Vela 2.0 0.3B | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; all five kinds (`choice`/`noul`/`score`/`span`/`set`) for text state; CPU FP32 validated (author-run, evidence in the integration PR) | -| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; [native library](recipe/vela/native.md) (bundle export, wire contract); CPU FP32 parity recorded in the integration PR | +| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; [native library](recipe/vela/native.md) (bundle export, wire contract, token-level processing); CPU FP32 parity recorded in the integration PR | [Supported models and hardware](docs/supported-models.md) lists the devices and where each worker has been run. diff --git a/docs/supported-models.md b/docs/supported-models.md index 30a52c6b..399ea09a 100644 --- a/docs/supported-models.md +++ b/docs/supported-models.md @@ -25,7 +25,7 @@ Models that are being added are also tracked in issues labeled [new model](https | OmniJev-4B v1.1 | None yet: [checkpoint export and CPU contract](../recipe/omnijev/README.md); the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | Request contract, preparation, heads and finishing checked against the reference ([#120](https://github.com/ThinkFlowLab/system1-omni/pull/120)); no inference | Not yet | Not supported | Python 3.10 reference environment for the export and fixtures | | D3 (Decision 3.0) | [Python reference worker](../recipe/d3/reference.md) running the checkpoint's pinned runtime | Unverified | Author-run on NVIDIA A100 (sm_80): three-kind serving smoke with byte-identical frontend forwarding and reference parity (exact decisions, max delta 0.0, 348 == 348 tokens); evidence in the integration PR. Owner: @MrDongsls. | Unverified | Python 3.12, the [pinned runtime requirements](../recipe/d3/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/d3) (~52 GB) | | Vela 2.0 0.3B | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime | **CPU FP32 validated** (author-run, x86 WSL2, 24 cores): startup with all-kind warmup, the four example requests plus five synthetic rejections, and exact-match reference parity against the pinned upstream server on all nine (four 200s byte-equal incl. key order, agreed 422/413); byte-identical frontend forwarding; evidence in the integration PR. Owner: @MrDongsls. | Unverified (bf16-autocast is an untested deployment option) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.3B) (1.24 GB FP32 weights; ~4.4 GB with ONNX/assets) | -| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B); [native library](../recipe/vela/native.md) — bundle export, wire contract | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | +| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B); [native library](../recipe/vela/native.md) — bundle export, wire contract, token-level processing | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | - **Validated:** covered by the recipe on `main` or by the checks in the linked merged pull request. - **Author-run:** recorded by the recipe author on the stated hardware and not independently reproduced; the row names its owner. diff --git a/recipe/vela/native.md b/recipe/vela/native.md index a9328003..4c3cefa3 100644 --- a/recipe/vela/native.md +++ b/recipe/vela/native.md @@ -2,8 +2,9 @@ The native implementation for [vllm-sr/Vela-2.0-0.8B](https://huggingface.co/vllm-sr/Vela-2.0-0.8B): -the exported-bundle gate and the wire contract, mirrored from the -pinned runtime. This is a library; serving runs through the +the exported-bundle gate, the wire contract, and the token-level +processing — all mirrored from the pinned runtime and checked against +frozen fixtures. This is a library; serving runs through the [reference recipe](reference.md)'s Python worker. Run the commands from the repository root with the same `.venv` and @@ -28,22 +29,45 @@ tokenizer, and `vela_native_manifest.json` pinning the source revision, the gate's file table, the tensor inventory and every file's SHA-256. +## Freeze the token-plan fixtures (opt-in, needs the package) + +~~~sh +PYTHONPATH=src .venv/bin/python recipe/vela/export_token_plan.py \ + --model weights/vela-2.0-0.8b --out tests/vela/fixtures/ +~~~ + +The token plans record what the pinned runtime feeds the backbone (the +predict mapping, the per-row decomposition, the rendered `p_ids`, +blocks and readout positions, truncation, a windowed long-span case). +The example-request token plan totals 1,041 tokens, matching the +oracle fixture's `usage.input_tokens`. + ## Checks ~~~sh cargo test -p omni-vela-native cargo fmt --all --check cargo clippy -p omni-vela-native --all-targets -- -D warnings +VELA_NATIVE_BUNDLE="$PWD/weights/vela-2.0-0.8b-native" \ + cargo test -p omni-vela-native --test vela_native_processing -- --nocapture ~~~ -15 tests, no weights, no GPU: the wire contract against the pinned -runtime's 422/400 bodies and the bundle manifest gate against a -synthetic bundle. +26 tests run everywhere with no weights and no GPU: the wire contract +against the pinned runtime's 422/400 bodies, the bundle manifest gate, +and the predict-mapping/plan parity on every frozen fixture. The +opt-in render check replays the five token plans through the Rust +processing field-for-field. For a field-level diff of one case: + +~~~sh +VELA_NATIVE_BUNDLE="$PWD/weights/vela-2.0-0.8b-native" \ + cargo run -p omni-vela-native --example parity -- example-request +~~~ ## Scope and limits -- Implemented: the bundle export + manifest gate and the wire - admission. -- Not implemented: token-level processing, the F32 heads, scoring, - backbone execution, and an HTTP worker. No performance claims are - made. +- Implemented: the bundle export + manifest gate, the wire admission, + and the token-level processing (state mapping, predict mapping with + the validation triples, word units, span-head dispatch, the DEV2.0 + rendering, the truncation budget, window rows). +- Not implemented: the F32 heads, scoring and span decoding, backbone + execution, and an HTTP worker. No performance claims are made. diff --git a/src/models/vela/README.md b/src/models/vela/README.md index 888658fc..92fc4f82 100644 --- a/src/models/vela/README.md +++ b/src/models/vela/README.md @@ -246,8 +246,19 @@ The native implementation lives in [`native/`](native/) as the - `native/src/contract.rs` is the wire admission, mirroring `protocol.py` and the pinned runtime's preamble with byte-equal 422/400 bodies. +- `native/src/{state,questions,words,render,processing}.rs` are the + token-level processing: the state → parts mapping, the SystemOne → + predict mapping with the pinned runtime's validation triples (Noul + folded into a two-option choice; choice renders `[ABS]`, the + reference's abstain default), the GLiNER2/CJK word splitter, the + six-rule span-head dispatch with the hallucination-alias label + replacement, the DEV2.0 prompt rendering (parts pass, question + blocks with option end and query positions, span layout a/c with + word positions, the truncation budget, the 16,384-window 413) and + the long-target window rows. All five frozen token plans + (`tests/vela/fixtures/native-plan-*.json`) match field-for-field. -Token-level processing, the F32 heads, backbone execution and an HTTP -worker are not implemented. Checks: `cargo test -p omni-vela-native` -(15 tests, no weights, no GPU; see +The F32 heads, scoring, backbone execution and an HTTP worker are not +implemented. Checks: `cargo test -p omni-vela-native` (26 tests, no +weights, no GPU; render parity opt-in with `VELA_NATIVE_BUNDLE`; see [recipe/vela/native.md](../../recipe/vela/native.md)). diff --git a/src/models/vela/native/Cargo.toml b/src/models/vela/native/Cargo.toml index 814d32b0..40308a34 100644 --- a/src/models/vela/native/Cargo.toml +++ b/src/models/vela/native/Cargo.toml @@ -3,11 +3,14 @@ name = "omni-vela-native" version = "0.1.0" edition = "2024" publish = false -description = "Native library for vllm-sr/Vela-2.0-0.8B: bundle gate and wire contract" +description = "Native library for vllm-sr/Vela-2.0-0.8B: bundle gate, wire contract and token-level processing" [dependencies] anyhow = "1.0.100" +onig = { package = "onig", version = "6", default-features = false } omni-qwen3-5-native = { path = "../../qwen3_5/native" } +serde = { version = "1", features = ["derive"] } +tokenizers = { version = "=0.22.2", default-features = false, features = ["onig"] } serde_json = { version = "1.0.149", features = ["preserve_order"] } sha2 = "0.11" @@ -24,3 +27,11 @@ path = "../../../../tests/vela/native_contract.rs" [[test]] name = "vela_native_bundle" path = "../../../../tests/vela/native_bundle.rs" + +[[test]] +name = "vela_native_processing" +path = "../../../../tests/vela/native_processing.rs" + +[[test]] +name = "vela_native_units" +path = "../../../../tests/vela/native_units.rs" diff --git a/src/models/vela/native/examples/parity.rs b/src/models/vela/native/examples/parity.rs new file mode 100644 index 00000000..071d0f52 --- /dev/null +++ b/src/models/vela/native/examples/parity.rs @@ -0,0 +1,87 @@ +//! Debug helper: compare the rendered rows against one fixture and +//! print the first differing field. Run with: +//! +//! VELA_NATIVE_BUNDLE=/abs/path cargo run -p omni-vela-native --example parity -- example-request + +use std::path::PathBuf; + +use serde_json::Value; + +fn main() { + let case = std::env::args().nth(1).unwrap_or("example-request".into()); + let bundle = PathBuf::from( + std::env::var("VELA_NATIVE_BUNDLE").expect("VELA_NATIVE_BUNDLE points at the export"), + ); + let fixture: Value = serde_json::from_str( + &std::fs::read_to_string( + PathBuf::from(env!("CARGO_MANIFEST_DIR")) + .join("../../../../tests/vela/fixtures") + .join(format!("native-plan-{case}.json")), + ) + .expect("fixture"), + ) + .expect("fixture json"); + + let processor = omni_vela_native::processing::Processor::load(&bundle).expect("load"); + let request = fixture["request"].as_object().expect("request"); + match processor.plan(request) { + Ok(planned) => { + let got = serde_json::json!({ + "rows": serde_json::to_value(&planned.rows).unwrap(), + "window_rows": serde_json::to_value(&planned.window_rows).unwrap(), + }); + compare( + "rows", + got["rows"].as_array().unwrap(), + fixture["rows"].as_array().unwrap(), + ); + if !fixture["window_rows"].is_null() { + compare( + "window_rows", + got["window_rows"].as_array().unwrap(), + fixture["window_rows"].as_array().unwrap(), + ); + } + println!("parity: no field differences found"); + } + Err(error) => println!( + "plan error: {}", + serde_json::to_string(&error.body).unwrap() + ), + } +} + +fn compare(name: &str, got: &[Value], want: &[Value]) { + println!("{name}: {} vs {} row(s)", got.len(), want.len()); + for (index, (a, b)) in got.iter().zip(want).enumerate() { + let (Some(a), Some(b)) = (a.as_object(), b.as_object()) else { + continue; + }; + for key in b.keys() { + if a.get(key) != b.get(key) { + println!("row {index} field {key}: differs"); + println!( + " want: {}", + serde_json::to_string(&b[key]) + .unwrap() + .chars() + .take(300) + .collect::() + ); + println!( + " got: {}", + serde_json::to_string(&a[key]) + .unwrap() + .chars() + .take(300) + .collect::() + ); + } + } + for key in a.keys() { + if !b.contains_key(key) { + println!("row {index} field {key}: extra in ours"); + } + } + } +} diff --git a/src/models/vela/native/src/contract.rs b/src/models/vela/native/src/contract.rs index 06a3de95..734dcb25 100644 --- a/src/models/vela/native/src/contract.rs +++ b/src/models/vela/native/src/contract.rs @@ -56,7 +56,7 @@ pub fn parse_body(raw: &[u8]) -> Result, RequestError> { /// Mirror the reference worker's 400 messages: duplicate keys verbatim, /// everything else the shared generic message. -fn normalize_parse_error(error: &str) -> RequestError { +pub(crate) fn normalize_parse_error(error: &str) -> RequestError { if let Some(rest) = error.split("duplicate key ").nth(1) { // serde appends its position suffix after the quoted key. if let Some(key) = rest @@ -129,14 +129,5 @@ pub fn runtime_rejection(message: &str) -> RequestError { } #[cfg(test)] -mod tests { - use super::*; - - #[test] - fn duplicate_keys_mirror_the_reference_message() { - let error = - normalize_parse_error("request body is not valid JSON: duplicate key \"state\""); - assert_eq!(error.status, 400); - assert_eq!(error.body, json!({"detail": "duplicate JSON key 'state'"})); - } -} +#[path = "../../../../../tests/vela/native_contract_unit.rs"] +mod tests; diff --git a/src/models/vela/native/src/lib.rs b/src/models/vela/native/src/lib.rs index 32f64c4f..1d849284 100644 --- a/src/models/vela/native/src/lib.rs +++ b/src/models/vela/native/src/lib.rs @@ -1,5 +1,13 @@ -//! Native library for vllm-sr/Vela-2.0-0.8B: the exported-bundle gate -//! and the wire contract, mirrored from the pinned runtime. +//! Native library for vllm-sr/Vela-2.0-0.8B: the exported-bundle gate, +//! the wire contract, and the token-level processing (state → parts, +//! the SystemOne → predict mapping with the pinned runtime's validation +//! triples, word units, the DEV2.0 prompt rendering — mirrored against +//! the frozen `native-plan-*` fixtures). pub mod bundle; pub mod contract; +pub mod processing; +pub mod questions; +pub mod render; +pub mod state; +pub mod words; diff --git a/src/models/vela/native/src/processing.rs b/src/models/vela/native/src/processing.rs new file mode 100644 index 00000000..12370856 --- /dev/null +++ b/src/models/vela/native/src/processing.rs @@ -0,0 +1,274 @@ +//! The processor: one admitted request body → predict mapping, plan, +//! and rendered rows, mirroring the reference path +//! (`system_one_to_predict` → `_to_generic` → `_predict`'s row split → +//! `_prep`/`_render`, plus the long-target window rows). Everything the +//! frozen `native-plan-*` fixtures record. + +use std::collections::HashSet; +use std::path::Path; + +use anyhow::{Context, Result}; +use serde_json::{Map, Value}; + +use crate::contract::RequestError; +use crate::questions::{PredictQuestion, system_one_to_predict}; +use crate::render::{ + Encoder, GenericQuestion, HALU_LABEL, PreparedPart, RMAX, RenderContext, RenderedRow, + window_part, +}; +use crate::state::system_one_state; + +pub struct Processor { + encoder: Encoder, + max_length: usize, + router_label_sets: Vec>, + has_broad: bool, + halu_desc: String, +} + +pub struct Planned { + pub predict_request: Value, + pub plan: Value, + pub rows: Vec, + pub window_rows: Vec, +} + +impl Processor { + /// Load from an exported native bundle (tokenizer + calibration; + /// the manifest gate runs first). + pub fn load(bundle: &Path) -> Result { + let manifest = crate::bundle::Bundle::load(bundle)?; + let calibration: Value = serde_json::from_slice( + &std::fs::read(bundle.join("calibration.json")).context("calibration.json")?, + ) + .context("calibration.json must be JSON")?; + let broad = calibration.get("broad_head").filter(|b| !b.is_null()); + let router_label_sets: Vec> = broad + .and_then(|b| b.get("router_label_sets")) + .and_then(Value::as_array) + .filter(|sets| !sets.is_empty()) + .map(|sets| { + sets.iter() + .filter_map(Value::as_array) + .map(|labels| { + labels + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect() + }) + .collect() + }) + .unwrap_or_else(|| { + vec![ + calibration["pii_types"].as_array().map(|types| { + types + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect() + }), + calibration["halu_schema"]["labels"] + .as_object() + .map(|labels| labels.keys().cloned().collect()), + ] + .into_iter() + .flatten() + .collect() + }); + let has_broad = broad.is_some(); // the bundle gate pinned the broad tensors + let halu_desc = calibration["halu_schema"]["labels"][HALU_LABEL] + .as_str() + .unwrap_or("a claim not supported by the context") + .to_owned(); + Ok(Self { + encoder: Encoder::load(&bundle.join("tokenizer.json"))?, + max_length: manifest.max_length(), + router_label_sets, + has_broad, + halu_desc, + }) + } + + /// The full planning path for one admitted request body. + pub fn plan(&self, body: &Map) -> Result { + let state = system_one_state(&body["state"])?; + let questions = body["questions"] + .as_object() + .ok_or_else(crate::questions::empty_questions_error)?; + let mapped = system_one_to_predict(state, questions)?; + let predict_request = serde_json::to_value(&mapped.request).expect("serializable"); + let plan = serde_json::to_value(&mapped.plan).expect("serializable"); + let state_parts = mapped.request.parts.clone(); + + // `_to_generic`: predict questions → generic render questions + // (Noul is already folded; choice always carries [ABS]). + let generic: Vec = + mapped.request.questions.iter().map(to_generic).collect(); + // `_predict`'s row split: non-span questions plus the first span + // in one row, every further span its own row. + let spans: Vec<&GenericQuestion> = generic.iter().filter(|q| q.kind == "span").collect(); + let rest: Vec = generic + .iter() + .filter(|q| q.kind != "span") + .cloned() + .collect(); + let mut rows: Vec> = Vec::new(); + if !rest.is_empty() || !spans.is_empty() { + let mut first = rest.clone(); + if let Some(span) = spans.first() { + first.push((*span).clone()); + } + rows.push(first); + for span in spans.iter().skip(1) { + rows.push(vec![(*span).clone()]); + } + } + let context = RenderContext { + encoder: &self.encoder, + max_length: self.max_length, + router_label_sets: &self.router_label_sets, + has_broad: self.has_broad, + halu_desc: self.halu_desc.clone(), + }; + let span_roles: HashSet = + spans.iter().flat_map(|q| q.over.iter().cloned()).collect(); + let mut rendered = Vec::new(); + let mut window_rows = Vec::new(); + let mut parts_by_role = std::collections::HashMap::new(); + for part in self.prepared_parts(&state_parts, &span_roles) { + parts_by_role.insert(part.role.clone(), part); + } + for row in rows { + if row.is_empty() { + continue; + } + let (adjusted, dispatch) = context.prepare_questions(&row)?; + let parts: Vec = state_parts + .iter() + .map(|part| { + parts_by_role + .get(&part.r#type) + .cloned() + .expect("prepared part") + }) + .collect(); + let record = context.render(&parts, &adjusted, &dispatch)?; + // `_window_rows`: a span target beyond RMAX becomes one row + // per window (the full-render span block stays on the row). + let span = row.iter().find(|q| q.kind == "span"); + if let Some(span) = span { + let index = parts.iter().position(|p| p.role == span.over[0]); + if let Some(index) = index { + let part = &parts[index]; + let has_words = part.words.is_some(); + if part.ids.len() > RMAX && has_words { + let (_, first_tokens) = part.words.as_ref().expect("words"); + for (a, b) in crate::render::span_windows(first_tokens, part.ids.len()) { + let mut windowed_parts = parts.clone(); + windowed_parts[index] = window_part(part, a, b); + let (w_adjusted, w_dispatch) = context.prepare_questions(&row)?; + let mut record = + context.render(&windowed_parts, &w_adjusted, &w_dispatch)?; + // The runtime's window rows carry the head only. + record.window = true; + window_rows.push(record); + } + } + } + } + rendered.push(record); + } + Ok(Planned { + predict_request, + plan, + rows: rendered, + window_rows, + }) + } + + /// The prepared parts for one request: tokens everywhere, offsets + /// and word units on span-target parts. + fn prepared_parts( + &self, + state_parts: &[crate::state::Part], + span_roles: &HashSet, + ) -> Vec { + state_parts + .iter() + .map(|part| { + let (ids, offsets) = self.encoder.ids_offsets(&part.text); + if span_roles.contains(&part.r#type) { + let words = crate::words::word_first_tokens(&part.text, &offsets); + PreparedPart { + role: part.r#type.clone(), + ids, + offsets: Some(offsets), + words: Some(words), + } + } else { + PreparedPart { + role: part.r#type.clone(), + ids, + offsets: None, + words: None, + } + } + }) + .collect() + } +} + +/// `_to_generic` for the SystemOne path: options/labels carry over in +/// order (score levels have empty descriptions), the target part is the +/// resolved `over`, choice always carries `[ABS]` (the reference's +/// `abstain` default is true and the mapper never sets it), and span +/// keeps its threshold and head override. +fn to_generic(question: &PredictQuestion) -> GenericQuestion { + let over: Vec = match &question.target_part { + Value::String(role) => vec![role.clone()], + Value::Array(roles) => roles + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect(), + _ => Vec::new(), + }; + let (names, descriptions) = match (&question.labels, &question.options) { + (Some(labels), _) => ( + labels.iter().map(|n| n.name.clone()).collect(), + labels.iter().map(|n| n.description.clone()).collect(), + ), + (None, Some(Value::Array(items))) => { + // Objects carry name/description; score levels are strings. + let mut names = Vec::new(); + let mut descriptions = Vec::new(); + for item in items { + match item { + Value::String(name) => { + names.push(name.clone()); + descriptions.push(String::new()); + } + Value::Object(named) => { + names.push(named["name"].as_str().unwrap_or_default().to_owned()); + descriptions + .push(named["description"].as_str().unwrap_or_default().to_owned()); + } + _ => {} + } + } + (names, descriptions) + } + _ => (Vec::new(), Vec::new()), + }; + GenericQuestion { + id: question.id.clone(), + kind: question.kind.clone(), + over, + text: question.text.clone(), + names, + descriptions, + threshold: question.threshold, + head_override: question.head.clone(), + } +} diff --git a/src/models/vela/native/src/questions.rs b/src/models/vela/native/src/questions.rs new file mode 100644 index 00000000..4c095032 --- /dev/null +++ b/src/models/vela/native/src/questions.rs @@ -0,0 +1,441 @@ +//! The SystemOne (state, questions) → predict-request mapping, mirroring +//! the pinned runtime's `system_one_to_predict` exactly: the validation +//! walk and its whole-request error triples, the Noul folding into a +//! two-option choice, and the per-question plan used to build responses. + +use serde_json::{Map, Value}; + +use crate::contract::RequestError; +use crate::state::{Part, StateParts, content_text}; + +/// The `questions` container rejection shared by the mapping and the +/// processor's body walk. +pub fn empty_questions_error() -> RequestError { + qerror( + &["questions"], + "questions must be a non-empty object of named questions", + ) +} + +pub const SYSTEM_ONE_TYPES: [&str; 5] = ["noul", "choice", "score", "span", "set"]; +pub const NOUL_DEFAULT_NO: &str = "No. The statement or question is not satisfied."; +pub const NOUL_DEFAULT_YES: &str = "Yes. The statement or question is satisfied."; + +/// One option / label of a predict question (name, description). +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +pub struct Named { + pub name: String, + pub description: String, +} + +/// The predict-level question, exactly as it serializes into the frozen +/// fixtures: Noul questions arrive here already folded into a choice. +#[derive(Debug, Clone, serde::Serialize)] +pub struct PredictQuestion { + pub id: String, + #[serde(rename = "type")] + pub kind: String, + pub text: String, + pub target_part: Value, + #[serde(skip_serializing_if = "Option::is_none")] + pub labels: Option>, + #[serde(skip_serializing_if = "Option::is_none")] + pub options: Option, + #[serde(skip_serializing_if = "Option::is_none")] + pub threshold: Option, + #[serde(skip_serializing_if = "Option::is_none")] + pub head: Option, +} + +#[derive(Debug, Clone, serde::Serialize)] +pub struct PredictRequest { + pub parts: Vec, + pub questions: Vec, +} + +/// The response-side plan entry for one original question. +#[derive(Debug, Clone, serde::Serialize)] +pub struct PlanEntry { + pub qid: String, + #[serde(rename = "type")] + pub kind: String, + pub criteria: Value, + pub range: Option<(usize, usize)>, + pub part: Value, +} + +#[derive(Debug)] +pub struct Mapped { + pub request: PredictRequest, + pub plan: Vec, +} + +fn qerror(loc: &[&str], msg: &str) -> RequestError { + RequestError::envelope(loc, msg, "value_error") +} + +fn nonblank(value: &Value) -> bool { + match value { + Value::String(text) => !text.trim().is_empty(), + _ => true, + } +} + +/// `over` (state key | part name | list) → (target part(s), field range). +fn resolve_over( + over: &Value, + parts: &StateParts, + qloc: &[&str], +) -> Result<(Value, Option<(usize, usize)>), RequestError> { + let roles: Vec<&str> = parts.parts.iter().map(|p| p.r#type.as_str()).collect(); + let items: Vec<&Value> = match over { + Value::Array(list) => list.iter().collect(), + single => vec![single], + }; + let mut out: Vec<&str> = Vec::new(); + let mut range = None; + for item in items { + let Some(name) = item.as_str() else { + return Err(qerror( + &[qloc[0], qloc[1], "over"], + "over must be a state key, a part name or a list of them", + )); + }; + if let Some(field) = parts.fields.get(name) { + if !over.is_array() { + range = Some((field.start, field.end)); + } + if !out.contains(&field.role) { + out.push(field.role); + } + } else if roles.contains(&name) { + if !out.contains(&name) { + out.push(name); + } + } else { + let role = crate::state::key_role(name); + if roles.contains(&role) && !out.contains(&role) { + out.push(role); + } else { + return Err(qerror( + &[qloc[0], qloc[1], "over"], + &format!( + "'{name}' is not a field of the state (fields: [{fields}], parts: [{roles}])", + fields = parts + .fields + .keys() + .map(|k| format!("'{k}'")) + .collect::>() + .join(", "), + roles = roles.join(", "), + ), + )); + } + } + } + if out.is_empty() { + return Err(qerror( + &[qloc[0], qloc[1], "over"], + "over must not be empty", + )); + } + // Sequence order, so the pooled range covers exactly these parts. + let ordered: Vec<&str> = roles + .iter() + .filter(|role| out.contains(role)) + .copied() + .collect(); + let target = match ordered.len() { + 1 => Value::String(ordered[0].into()), + _ => Value::Array( + ordered + .into_iter() + .map(|r| Value::String(r.into())) + .collect(), + ), + }; + Ok((target, range)) +} + +/// The full mapping. `state` and `questions` are the admitted request's +/// fields; validation runs in the pinned runtime's order so error +/// precedence matches. +pub fn system_one_to_predict( + state_parts: StateParts, + questions: &Map, +) -> Result { + if questions.is_empty() { + return Err(qerror( + &["questions"], + "questions must be a non-empty object of named questions", + )); + } + let roles: Vec<&str> = state_parts + .parts + .iter() + .map(|p| p.r#type.as_str()) + .collect(); + let mut predict = Vec::new(); + let mut plan = Vec::new(); + for (qid, question) in questions { + if qid.trim().is_empty() { + return Err(qerror( + &["questions"], + "question IDs must not be empty or whitespace", + )); + } + let Some(question) = question.as_object() else { + return Err(qerror( + &["questions", qid], + "a question must be an object with a type", + )); + }; + let loc = ["questions", qid]; + let kind = question.get("type").and_then(Value::as_str).unwrap_or(""); + if !SYSTEM_ONE_TYPES.contains(&kind) { + return Err(RequestError::envelope( + &[loc[0], loc[1], "type"], + "type must be one of ['noul', 'choice', 'score', 'span', 'set']", + "literal_error", + )); + } + let mut allowed: Vec<&str> = vec!["type", "instructions", "criteria", "over"]; + if kind == "span" || kind == "set" { + allowed.push("threshold"); + } + if kind == "span" { + allowed.push("head"); + } + let extra: Vec<&String> = question + .keys() + .filter(|key| !allowed.contains(&key.as_str())) + .collect(); + if let Some(first) = extra.first() { + return Err(RequestError::envelope( + &[loc[0], loc[1], first], + "Extra inputs are not permitted", + "extra_forbidden", + )); + } + let instructions = question.get("instructions").unwrap_or(&Value::Null); + if !nonblank(instructions) { + return Err(qerror( + &[loc[0], loc[1], "instructions"], + "instructions must not be empty or whitespace", + )); + } + let text = match instructions { + Value::Null => String::new(), + other => content_text(other), + }; + let criteria = question.get("criteria").unwrap_or(&Value::Null); + // Target part: the resolved `over`, the span default, or all parts. + let (target_part, range) = match question.get("over") { + Some(Value::Null) | None => { + if kind == "span" { + let role = if roles.contains(&"answer") { + "answer" + } else if roles.contains(&"user") { + "user" + } else { + roles[0] + }; + (Value::String(role.into()), None) + } else if roles.len() == 1 { + (Value::String(roles[0].into()), None) + } else { + ( + Value::Array(roles.iter().map(|r| Value::String((*r).into())).collect()), + None, + ) + } + } + Some(over) => resolve_over(over, &state_parts, &loc)?, + }; + let mut predict_question = PredictQuestion { + id: qid.clone(), + kind: kind.to_string(), + text: text.clone(), + target_part: target_part.clone(), + labels: None, + options: None, + threshold: None, + head: None, + }; + let mut plan_criteria = criteria.clone(); + match kind { + "noul" => { + if !criteria.is_null() + && (!criteria.is_object() + || criteria + .as_object() + .is_some_and(|map| map.keys().any(|k| k != "true" && k != "false"))) + { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "noul criteria is an object with optional true / false", + )); + } + let map = criteria.as_object().cloned().unwrap_or_default(); + for key in ["true", "false"] { + if let Some(value) = map.get(key) + && !nonblank(value) + { + return Err(qerror( + &[loc[0], loc[1], "criteria", key], + "Noul criterion must not be empty or whitespace", + )); + } + } + let no = match map.get("false") { + Some(Value::Null) | None => NOUL_DEFAULT_NO.to_string(), + Some(value) => content_text(value), + }; + let yes = match map.get("true") { + Some(Value::Null) | None => NOUL_DEFAULT_YES.to_string(), + Some(value) => content_text(value), + }; + predict_question.kind = "choice".into(); + predict_question.options = Some(serde_json::json!([ + {"name": "no", "description": no}, + {"name": "yes", "description": yes}, + ])); + } + "choice" | "set" | "span" => { + let (lo, hi) = if kind == "choice" { (2, 255) } else { (1, 255) }; + let Some(map) = criteria.as_object() else { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + &format!("{kind} criteria must be an object with {lo} to {hi} entries"), + )); + }; + if !(lo..=hi).contains(&map.len()) { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + &format!("{kind} criteria must be an object with {lo} to {hi} entries"), + )); + } + let mut named = Vec::new(); + for (name, value) in map { + if name.trim().is_empty() || !nonblank(value) { + return Err(qerror( + &[loc[0], loc[1], "criteria", name], + "option names and descriptions must not be empty or whitespace", + )); + } + let description = match value { + Value::Null => String::new(), + other => content_text(other), + }; + named.push(Named { + name: name.clone(), + description, + }); + } + if kind == "span" { + predict_question.labels = Some(named); + } else { + predict_question.options = Some(serde_json::to_value(&named).unwrap()); + } + } + _ => { + // score + let Some(levels) = criteria.as_array() else { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "score criteria must be a list of 2 to 10 levels", + )); + }; + if !(2..=10).contains(&levels.len()) { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "score criteria must be a list of 2 to 10 levels", + )); + } + let mut names = Vec::new(); + for (index, value) in levels.iter().enumerate() { + if value.is_null() || !nonblank(value) { + return Err(qerror( + &[loc[0], loc[1], "criteria", &index.to_string()], + "Score criterion must not be empty or whitespace", + )); + } + names.push(content_text(value)); + } + if names.iter().collect::>().len() != names.len() { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "score levels must be distinct", + )); + } + predict_question.options = Some(serde_json::to_value(&names).unwrap()); + } + } + if let Some(threshold) = question.get("threshold") + && !threshold.is_null() + { + match threshold.as_f64().filter(|_| threshold.is_number()) { + Some(value) if (0.0..=1.0).contains(&value) => { + predict_question.threshold = Some(value); + } + _ => { + return Err(qerror( + &[loc[0], loc[1], "threshold"], + "threshold must be a number in [0, 1]", + )); + } + } + } + if kind == "span" + && let Some(head) = question.get("head") + && !head.is_null() + { + match head.as_str() { + Some(value @ ("router" | "broad")) => { + predict_question.head = Some(value.to_string()); + } + _ => { + return Err(RequestError::envelope( + &[loc[0], loc[1], "head"], + "head must be one of ['router', 'broad']", + "literal_error", + )); + } + } + } + // Python's plan keeps `crit`; noul normalized null -> {} earlier. + if kind == "noul" && plan_criteria.is_null() { + plan_criteria = serde_json::json!({}); + } + predict.push(predict_question); + plan.push(PlanEntry { + qid: qid.clone(), + kind: kind.to_string(), + criteria: plan_criteria, + range, + part: target_part, + }); + } + // The Noul views of set labels must not overwrite a question. + for entry in &plan { + if entry.kind == "set" + && let Value::Object(map) = &entry.criteria + { + for label in map.keys() { + if questions.contains_key(&format!("{}.{}", entry.qid, label)) { + return Err(qerror( + &["questions", &format!("{}.{}", entry.qid, label)], + "collides with the Noul view of a set label", + )); + } + } + } + } + Ok(Mapped { + request: PredictRequest { + parts: state_parts.parts, + questions: predict, + }, + plan, + }) +} diff --git a/src/models/vela/native/src/render.rs b/src/models/vela/native/src/render.rs new file mode 100644 index 00000000..c4fc2367 --- /dev/null +++ b/src/models/vela/native/src/render.rs @@ -0,0 +1,789 @@ +//! Prompt rendering, mirroring the pinned runtime's `_prep` + `_render` +//! (the DEV2.0 decoder layout): the parts pass, per-question blocks +//! with option end and query positions, the span block in layout a/c +//! with word positions, the truncation budget, and the long-target +//! windows. Output structs serialize exactly like the frozen +//! `native-plan-*` fixtures. + +use std::cell::RefCell; +use std::collections::{HashMap, HashSet}; +use std::path::Path; + +use std::collections::BTreeMap; +use tokenizers::Tokenizer; + +use crate::contract::RequestError; +use crate::state::canonical; + +pub const SUFFIX_CHOICE_SCORE: &str = + "\n\nSelect the single option best supported by the context and instructions.\nDecision:"; +pub const SUFFIX_SET: &str = + "\n\nSelect every option supported by the context and instructions.\nDecision:"; +pub const SUFFIX_SPAN: &str = + "\n\nMark every span of the target text that carries one of the labels.\nSpans:"; +pub const ABS_KEY: &str = "[ABS]"; +pub const ABS_DESC: &str = "None of the shown options applies."; +pub const PARTS_HEAD: &str = "Context:\n"; +pub const SEG_CLOSE: &str = "\n\n"; +pub const TEXT_HEAD: &str = "\n\nText:\n"; +pub const HYBRID_RMAX: usize = 2048; +pub const WIN: usize = 1800; +pub const STRIDE: usize = 1536; +pub const RMAX: usize = 2048; + +pub const ROUTER_SPAN_IDS: [&str; 3] = ["pii", "halu", "toxic"]; +pub const HALU_LABEL: &str = "unsupported"; +pub const HALU_ALIASES: [&str; 9] = [ + "unsupported", + "unsupportedclaim", + "hallucinated", + "hallucination", + "hallucinatedspan", + "notsupported", + "unsupportedspan", + "fabricated", + "fabrication", +]; +pub const PII_TYPES: [&str; 17] = [ + "AGE", + "CREDIT_CARD", + "DATE_TIME", + "DOMAIN_NAME", + "EMAIL_ADDRESS", + "GPE", + "IBAN_CODE", + "IP_ADDRESS", + "NRP", + "ORGANIZATION", + "PERSON", + "PHONE_NUMBER", + "STREET_ADDRESS", + "TITLE", + "US_DRIVER_LICENSE", + "US_SSN", + "ZIP_CODE", +]; + +fn seg_open(role: &str) -> String { + format!("\n") +} + +fn option_block(key: &str, desc: &str, tag: &str) -> String { + format!( + "\n<{tag}>\n{}\n", + canonical(&serde_json::json!({"key": key, "description": desc})) + ) +} + +fn q_head(kind: &str, over: &[String], text: &str, span: bool) -> String { + let target = over.join(", "); + format!( + "\n\nTask type: {kind}\nTarget: {target}\nQuestion:\n{text}\n{}", + if span { "Labels:" } else { "Options:" } + ) +} + +// ------------------------------------------------------------------ tokenizer + +/// The pinned tokenizer, with the reference's memoized plain-`ids` view +/// and char-offset encodings (the tokenizers crate reports byte +/// offsets; the reference works in Unicode code points). +/// Ids plus char offsets, the encoder cache entry. +type Encoded = (Vec, Vec<(usize, usize)>); + +pub struct Encoder { + tokenizer: Tokenizer, + cache: RefCell>, +} + +impl Encoder { + pub fn load(path: &Path) -> anyhow::Result { + let tokenizer = Tokenizer::from_file(path).map_err(anyhow::Error::msg)?; + Ok(Self { + tokenizer, + cache: RefCell::new(HashMap::new()), + }) + } + + fn encode(&self, text: &str) -> (Vec, Vec<(usize, usize)>) { + if let Some(hit) = self.cache.borrow().get(text) { + return hit.clone(); + } + let encoding = self + .tokenizer + .encode(text, false) + .expect("tokenizer failure"); + let byte_offsets = encoding.get_offsets(); + // Byte → code-point offsets. + let char_starts: Vec = text + .char_indices() + .map(|(byte, _)| byte) + .chain(std::iter::once(text.len())) + .collect(); + let to_char = |byte: usize| char_starts.partition_point(|&start| start < byte); + let offsets: Vec<(usize, usize)> = byte_offsets + .iter() + .map(|(start, end)| (to_char(*start), to_char(*end))) + .collect(); + let entry = (encoding.get_ids().to_vec(), offsets); + self.cache + .borrow_mut() + .insert(text.to_owned(), entry.clone()); + entry + } + + /// Memoized token ids of a whole string (the reference's `_ids`). + pub fn ids(&self, text: &str) -> Vec { + self.encode(text).0 + } + + /// Ids and char offsets (the reference's `_ids_offs`). + pub fn ids_offsets(&self, text: &str) -> (Vec, Vec<(usize, usize)>) { + self.encode(text) + } +} + +// ------------------------------------------------------------- span dispatch + +/// `[\s_\-]+` removed, lower-cased — the reference's `_norm_label`. +pub fn norm_label(name: &str) -> String { + let mut out = String::with_capacity(name.len()); + for ch in name.chars() { + if !ch.is_whitespace() && ch != '_' && ch != '-' { + out.extend(ch.to_lowercase()); + } + } + out +} + +/// The user's label when the span question has exactly one label that +/// is a hallucination alias, else none. +pub fn halu_alias(names: &[String]) -> Option { + if names.len() == 1 && HALU_ALIASES.contains(&norm_label(&names[0]).as_str()) { + Some(names[0].clone()) + } else { + None + } +} + +pub struct SpanDispatch { + pub head: &'static str, + pub reason: &'static str, +} + +/// The reference's six-rule dispatch, in order: `"head"` override, +/// trained ids, an exact router label set, a non-empty subset of the 17 +/// PII types, one hallucination alias, else broad (router when the +/// broad head is not loaded). +pub fn span_head_for( + id: &str, + labels: &HashSet, + head_override: Option<&str>, + router_label_sets: &[HashSet], + broad_available: bool, +) -> Result { + if let Some(head) = head_override { + if !matches!(head, "router" | "broad") { + return Err(format!( + "head must be one of ['router', 'broad'], got '{head:?}'" + )); + } + if head == "broad" && !broad_available { + return Err("the broad span head is not loaded (needs broad_head.safetensors)".into()); + } + return Ok(SpanDispatch { + head: if head == "broad" { "broad" } else { "router" }, + reason: "override", + }); + } + if ROUTER_SPAN_IDS.contains(&id) { + return Ok(SpanDispatch { + head: "router", + reason: "id", + }); + } + if router_label_sets.iter().any(|set| set == labels) { + return Ok(SpanDispatch { + head: "router", + reason: "label_set", + }); + } + let pii: HashSet<&str> = PII_TYPES.into_iter().collect(); + if !labels.is_empty() && labels.iter().all(|label| pii.contains(label.as_str())) { + return Ok(SpanDispatch { + head: "router", + reason: "pii_subset", + }); + } + if halu_alias(&labels.iter().cloned().collect::>()).is_some() { + return Ok(SpanDispatch { + head: "router", + reason: "halu_alias", + }); + } + if !broad_available { + return Ok(SpanDispatch { + head: "router", + reason: "broad_unavailable", + }); + } + Ok(SpanDispatch { + head: "broad", + reason: "default", + }) +} + +// ------------------------------------------------------------------ rendering + +/// One generic-contract question at render time (Noul is already folded +/// into a two-option choice; choice always carries `[ABS]` on the +/// SystemOne path — the reference's `_to_generic` defaults abstain to +/// true and the mapper never sets it). +#[derive(Clone)] +pub struct GenericQuestion { + pub id: String, + pub kind: String, + pub over: Vec, + pub text: String, + pub names: Vec, + pub descriptions: Vec, + pub threshold: Option, + pub head_override: Option, +} + +/// One prepared part: tokens, and for span-target parts also char +/// offsets and word units. +/// Word char offsets and each word's first token index. +pub type WordUnits = (Vec<(usize, usize)>, Vec); + +#[derive(Clone)] +pub struct PreparedPart { + pub role: String, + pub ids: Vec, + pub offsets: Option>, + pub words: Option, +} + +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +pub struct TruncRecord { + pub shrink_cut: usize, + pub protected_cut: usize, +} + +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +#[serde(tag = "kind")] +pub enum Block { + #[serde(rename = "q")] + Question { + ids: Vec, + ends: Vec, + query: usize, + qid: String, + qtype: String, + names: Vec, + has_abs: bool, + }, + #[serde(rename = "span")] + Span { + ends: Vec, + label_ranges: Vec<(usize, usize)>, + words_in_block: bool, + ids: Vec, + query: usize, + w_pos: Vec, + }, +} + +#[derive(Debug, Clone, PartialEq)] +pub struct RenderedRow { + pub p_ids: Vec, + pub blocks: Vec, + pub trunc: TruncRecord, + pub seg_lens: BTreeMap, + pub layout: Option, + pub names: Option>, + pub w_offs: Option>, + pub w_pos: Option>, + pub span_over: Option, + pub n_tokens: usize, + pub head: String, + pub head_reason: Option, + /// The runtime's window rows carry the head only — no head_reason + /// key at all (predict_raw assigns head alone). + pub window: bool, +} + +/// Serialize exactly like the frozen fixtures: main rows always carry +/// `head_reason` (null when the row has no span); window rows omit it. +impl serde::Serialize for RenderedRow { + fn serialize(&self, serializer: S) -> Result + where + S: serde::Serializer, + { + serialize_row(self, serializer) + } +} + +fn serialize_row(row: &RenderedRow, serializer: S) -> Result +where + S: serde::Serializer, +{ + use serde::ser::SerializeMap; + let mut map = serializer.serialize_map(None)?; + macro_rules! put { + ($key:literal, $value:expr) => { + map.serialize_entry($key, &$value)? + }; + } + put!("p_ids", row.p_ids); + put!("blocks", row.blocks); + put!("trunc", row.trunc); + put!("seg_lens", row.seg_lens); + put!("layout", row.layout); + if let Some(names) = &row.names { + put!("names", names); + } + if let Some(w_offs) = &row.w_offs { + put!("w_offs", w_offs); + } + if let Some(w_pos) = &row.w_pos { + put!("w_pos", w_pos); + } + if let Some(span_over) = &row.span_over { + put!("span_over", span_over); + } + put!("n_tokens", row.n_tokens); + put!("head", row.head); + if !row.window { + put!("head_reason", row.head_reason); + } + map.end() +} + +/// Everything the renderer needs beyond tokens. +pub struct RenderContext<'a> { + pub encoder: &'a Encoder, + pub max_length: usize, + pub router_label_sets: &'a [HashSet], + pub has_broad: bool, + pub halu_desc: String, +} + +/// The whole-request 413: questions plus schema alone do not fit. +pub fn too_long(max_length: usize) -> RequestError { + RequestError { + status: 413, + body: serde_json::json!({"detail": [{"loc": ["body", "questions"], + "msg": format!("the questions alone do not fit the {max_length}-token window"), + "type": "too_long"}]}), + } +} + +/// `schema_lib_r4.assemble`, eval path: the truncation order on the +/// decoder's token costs. Returns kept segment lengths and the record. +fn assemble_budget( + q_lens: &[usize], + el_lens: &[usize], + segs: &mut [(String, usize)], + max_len: usize, + protected: &HashSet, + shrink: Option<&str>, +) -> Result<(BTreeMap, TruncRecord), ()> { + let fixed = 2 + 1 + segs.len(); + fn over( + q_lens: &[usize], + el_lens: &[usize], + segs: &[(String, usize)], + fixed: usize, + max_len: usize, + ) -> i64 { + fixed as i64 + + q_lens.iter().sum::() as i64 + + el_lens.iter().sum::() as i64 + + segs.iter().map(|(_, n)| *n).sum::() as i64 + - max_len as i64 + } + let mut trunc = TruncRecord { + shrink_cut: 0, + protected_cut: 0, + }; + let shrink_index = shrink.and_then(|role| segs.iter().position(|(r, _)| r == role)); + for floor in [64, 1] { + if over(q_lens, el_lens, segs, fixed, max_len) > 0 + && let Some(index) = shrink_index + { + let full = segs[index].1; + let excess = over(q_lens, el_lens, segs, fixed, max_len).max(0) as usize; + let keep = full.min(floor.max(full.saturating_sub(excess))); + trunc.shrink_cut += full - keep; + segs[index].1 = keep; + } + } + if over(q_lens, el_lens, segs, fixed, max_len) > 0 { + for index in 0..segs.len() { + if over(q_lens, el_lens, segs, fixed, max_len) > 0 && protected.contains(&segs[index].0) + { + let full = segs[index].1; + let excess = over(q_lens, el_lens, segs, fixed, max_len).max(0) as usize; + let keep = 1.max(full.saturating_sub(excess)); + trunc.protected_cut += full - keep; + segs[index].1 = keep; + } + } + } + if over(q_lens, el_lens, segs, fixed, max_len) > 0 { + return Err(()); + } + let seg_lens: BTreeMap = + segs.iter().map(|(role, n)| (role.clone(), *n)).collect(); + Ok((seg_lens, trunc)) +} + +/// Token windows [a, b) over a part of n tokens, starting and cut at +/// word starts (`schema_lib_d3_20261001.windows`). +pub fn span_windows(first_tokens: &[usize], n: usize) -> Vec<(usize, usize)> { + let mut starts: Vec = first_tokens.to_vec(); + starts.sort_unstable(); + starts.dedup(); + if starts.is_empty() { + return vec![(0, n)]; + } + let mut out = Vec::new(); + let mut a = starts[0]; + loop { + let limit = a + WIN; + let next: Vec = starts + .iter() + .copied() + .filter(|&s| s > a && s < limit) + .collect(); + let b = if limit >= n { + n + } else if !next.is_empty() { + *starts + .iter() + .filter(|&&s| s < limit && s > a) + .max() + .unwrap() + } else { + n.min(limit) + }; + out.push((a, b)); + if b >= n { + break; + } + let candidate: Vec = starts + .iter() + .copied() + .filter(|&s| s >= a + STRIDE && s < b) + .collect(); + a = candidate.first().copied().unwrap_or(b); + } + out +} + +/// A windowed copy of a prepared part: tokens [a, b) and the words that +/// start inside them. +pub fn window_part(part: &PreparedPart, a: usize, b: usize) -> PreparedPart { + let (word_offsets, first_tokens) = part.words.as_ref().expect("windowed parts carry words"); + let selected: Vec = first_tokens + .iter() + .enumerate() + .filter(|&(_, &t)| t >= a && t < b) + .map(|(index, _)| index) + .collect(); + let kept_offsets: Vec<(usize, usize)> = selected.iter().map(|&i| word_offsets[i]).collect(); + PreparedPart { + role: part.role.clone(), + ids: part.ids[a..b].to_vec(), + offsets: part.offsets.as_ref().map(|offs| offs[a..b].to_vec()), + words: Some(( + kept_offsets, + selected.iter().map(|&i| first_tokens[i] - a).collect(), + )), + } +} + +impl RenderContext<'_> { + /// `_prep`'s question side: the span-head dispatch and the + /// hallucination-alias label replacement (parts arrive prepared — + /// word units need the original text and are the caller's job). + pub fn prepare_questions( + &self, + questions: &[GenericQuestion], + ) -> Result<(Vec, SpanDispatch), RequestError> { + let span = questions.iter().find(|q| q.kind == "span"); + let dispatch = match span { + Some(question) => { + let labels: HashSet = question.names.iter().cloned().collect(); + span_head_for( + &question.id, + &labels, + question.head_override.as_deref(), + self.router_label_sets, + self.has_broad, + ) + .map_err(|message| crate::contract::runtime_rejection(&message))? + } + None => SpanDispatch { + head: "router", + reason: "", + }, + }; + // The trained `unsupported` label renders in place of a single + // hallucination-alias label (the answer gets the user's name). + let mut adjusted = questions.to_vec(); + if let Some(question) = adjusted.iter_mut().find(|q| q.kind == "span") + && dispatch.head == "router" + && let Some(alias) = halu_alias(&question.names) + && alias != HALU_LABEL + { + question.names = vec![HALU_LABEL.to_string()]; + question.descriptions = vec![self.halu_desc.clone()]; + } + Ok((adjusted, dispatch)) + } + + /// `_render` on one prepared row: the parts pass and every block, + /// with the budget applied first. + pub fn render( + &self, + parts: &[PreparedPart], + questions: &[GenericQuestion], + dispatch: &SpanDispatch, + ) -> Result { + let ids_of = |text: &str| self.encoder.ids(text); + let roles: Vec = parts.iter().map(|p| p.role.clone()).collect(); + // Question blocks and their schema costs. + struct RenderedQ { + qid: String, + qtype: String, + names: Vec, + otoks: Vec>, + has_abs: bool, + head: Vec, + suffix: Vec, + abstain_tokens: Vec, + len: usize, + } + let mut rendered_qs: Vec = Vec::new(); + let mut el: Vec<(String, Vec)> = Vec::new(); // span labels + let mut span_question: Option<&GenericQuestion> = None; + for question in questions { + if question.kind == "span" { + span_question = Some(question); + for (name, desc) in question.names.iter().zip(&question.descriptions) { + let tokens = ids_of(&option_block(name, desc, "label")); + el.push((name.clone(), tokens.clone())); + } + continue; + } + let suffix = match question.kind.as_str() { + "set" => SUFFIX_SET, + _ => SUFFIX_CHOICE_SCORE, // choice and score share the wording + }; + let has_abs = question.kind == "choice"; // SystemOne: abstain defaults true + let head = ids_of(&q_head( + &question.kind, + &question.over, + &question.text, + false, + )); + let suffix = ids_of(suffix); + let abstain_tokens = if has_abs { + ids_of(&option_block(ABS_KEY, ABS_DESC, "option")) + } else { + Vec::new() + }; + let mut otoks = Vec::with_capacity(question.names.len()); + let mut len = + 1 + head.len() + suffix.len() + abstain_tokens.len() + usize::from(has_abs); + for (name, desc) in question.names.iter().zip(&question.descriptions) { + let tokens = ids_of(&option_block(name, desc, "option")); + len += 1 + tokens.len(); + otoks.push(tokens); + } + rendered_qs.push(RenderedQ { + qid: question.id.clone(), + qtype: question.kind.clone(), + names: question.names.clone(), + otoks, + has_abs, + head, + suffix, + abstain_tokens, + len, + }); + } + let span_over: Option = span_question.map(|question| question.over[0].clone()); + let mut overs: HashSet = HashSet::new(); + for question in questions { + overs.extend(question.over.iter().cloned()); + } + if let Some(over) = &span_over { + overs.insert(over.clone()); + } + let part_of = |role: &str| parts.iter().find(|p| p.role == role); + let shrink = roles.iter().find(|role| !overs.contains(*role)).cloned(); + let layout = match &span_over { + Some(over) if part_of(over).is_some_and(|p| p.ids.len() <= HYBRID_RMAX) => "c", + Some(_) => "a", + None => "", + }; + // The schema overhead the budget does not see. + let mut budget = ids_of(PARTS_HEAD).len(); + for role in &roles { + budget += ids_of(&seg_open(role)).len() + ids_of(SEG_CLOSE).len(); + } + if let Some(over) = &span_over { + let question = span_question.expect("span question"); + let head = ids_of(&q_head("span", &question.over, &question.text, true)); + let suffix = ids_of(SUFFIX_SPAN); + budget += head.len() + suffix.len(); + if layout == "c" { + let span_len = part_of(over).expect("span part").ids.len(); + budget += ids_of(TEXT_HEAD).len() + + ids_of(&seg_open(over)).len() + + ids_of(SEG_CLOSE).len(); + let headroom = self.max_length.saturating_sub(budget); + budget += span_len.min(headroom / 2); + } + } + let q_lens: Vec = rendered_qs.iter().map(|q| q.len).collect(); + let el_lens: Vec = el.iter().map(|(_, tokens)| 1 + tokens.len()).collect(); + let mut segs: Vec<(String, usize)> = parts + .iter() + .map(|p| (p.role.clone(), p.ids.len())) + .collect(); + let (seg_lens, trunc) = assemble_budget( + &q_lens, + &el_lens, + &mut segs, + 64.max(self.max_length - budget), + &overs, + shrink.as_deref(), + ) + .map_err(|()| too_long(self.max_length))?; + // The parts pass, in part order (not the sorted map). + let mut p_ids = ids_of(PARTS_HEAD); + let mut start: HashMap = HashMap::new(); + for part in parts { + let keep = seg_lens[&part.role]; + let open = ids_of(&seg_open(&part.role)); + start.insert(part.role.clone(), p_ids.len() + open.len()); + p_ids.extend(open); + p_ids.extend(part.ids.iter().take(keep)); + p_ids.extend(ids_of(SEG_CLOSE)); + } + // Question blocks. + let mut blocks: Vec = Vec::new(); + for q in &rendered_qs { + let mut ids = q.head.clone(); + let mut ends = Vec::with_capacity(q.names.len() + usize::from(q.has_abs)); + for tokens in &q.otoks { + ids.extend(tokens); + ends.push(ids.len() - 1); + } + if q.has_abs { + ids.extend(q.abstain_tokens.clone()); + ends.push(ids.len() - 1); + } + ids.extend(q.suffix.clone()); + let query = ids.len() - 1; + blocks.push(Block::Question { + ids, + ends, + query, + qid: q.qid.clone(), + qtype: q.qtype.clone(), + names: q.names.clone(), + has_abs: q.has_abs, + }); + } + // The span block. + let mut row_names = None; + let mut row_w_offs = None; + let mut row_w_pos = None; + if let Some(over) = &span_over + && !el.is_empty() + { + let question = span_question.expect("span question"); + let mut ids = ids_of(&q_head("span", &question.over, &question.text, true)); + let mut ends = Vec::new(); + let mut starts = Vec::new(); + for (_, tokens) in &el { + starts.push(ids.len()); + ids.extend(tokens); + ends.push(ids.len() - 1); + } + let part = part_of(over).expect("span part"); + let n = seg_lens[over]; + let (word_offsets, first_tokens) = part.words.as_ref().expect("span words"); + // Word indices whose first token survives the kept prefix; + // indices, not token values — two words can share one. + let keep: Vec = first_tokens + .iter() + .enumerate() + .filter(|&(_, &t)| t < n) + .map(|(index, _)| index) + .collect(); + let words_in_block = layout == "c"; + if words_in_block { + ids.extend(ids_of(TEXT_HEAD)); + ids.extend(ids_of(&seg_open(over))); + let c0 = ids.len(); + ids.extend(part.ids.iter().take(n)); + ids.extend(ids_of(SEG_CLOSE)); + row_w_pos = Some(keep.iter().map(|&i| c0 + first_tokens[i]).collect()); + } else { + let base = start[over]; + row_w_pos = Some(keep.iter().map(|&i| base + first_tokens[i]).collect()); + } + ids.extend(ids_of(SUFFIX_SPAN)); + let query = ids.len() - 1; + row_names = Some(el.iter().map(|(name, _)| name.clone()).collect()); + row_w_offs = Some(keep.iter().map(|&i| word_offsets[i]).collect()); + let label_ranges: Vec<(usize, usize)> = + starts.into_iter().zip(ends.iter().copied()).collect(); + blocks.push(Block::Span { + ends, + label_ranges, + words_in_block, + ids, + query, + w_pos: row_w_pos.clone().expect("w_pos"), + }); + } + let n_tokens = p_ids.len() + blocks.iter().map(block_len).sum::(); + Ok(RenderedRow { + p_ids, + blocks, + trunc, + seg_lens, + layout: if span_over.is_some() { + Some(layout.to_string()) + } else { + None + }, + names: row_names, + w_offs: row_w_offs, + w_pos: row_w_pos, + span_over, + n_tokens, + head: dispatch.head.to_string(), + head_reason: if dispatch.reason.is_empty() { + None + } else { + Some(dispatch.reason.to_string()) + }, + window: false, + }) + } +} + +fn block_len(block: &Block) -> usize { + match block { + Block::Question { ids, .. } => ids.len(), + Block::Span { ids, .. } => ids.len(), + } +} diff --git a/src/models/vela/native/src/state.rs b/src/models/vela/native/src/state.rs new file mode 100644 index 00000000..d33e42bb --- /dev/null +++ b/src/models/vela/native/src/state.rs @@ -0,0 +1,235 @@ +//! DEV2.0 canonical JSON and the state → typed-parts mapping, mirroring +//! the pinned runtime's `canonical_json`, `content_text` and +//! `system_one_state` exactly (the frozen `native-plan-*` fixtures are +//! the parity target). + +use serde_json::Value; +use std::collections::BTreeMap; + +use crate::contract::RequestError; + +/// `json.dumps(ensure_ascii=False, sort_keys=True, separators=(",", ":"))` +/// — key-sorted compact JSON, non-ASCII literal. +pub fn canonical(value: &Value) -> String { + match value { + Value::Object(map) => { + let mut keys: Vec<&String> = map.keys().collect(); + keys.sort(); + let parts: Vec = keys + .iter() + .map(|key| { + format!( + "{}:{}", + serde_json::to_string(key).unwrap(), + canonical(&map[*key]) + ) + }) + .collect(); + format!("{{{}}}", parts.join(",")) + } + Value::Array(items) => { + let parts: Vec = items.iter().map(canonical).collect(); + format!("[{}]", parts.join(",")) + } + other => serde_json::to_string(other).unwrap(), + } +} + +/// JSON content → model text: strings as they are, anything else as +/// canonical JSON. +pub fn content_text(value: &Value) -> String { + match value { + Value::String(text) => text.clone(), + other => canonical(other), + } +} + +/// The state-key → part-role table (unknown keys land in `context`). +pub fn key_role(key: &str) -> &'static str { + match key.to_ascii_lowercase().as_str() { + "request" | "user" | "prompt" => "user", + "answer" | "response" => "answer", + _ => "context", + } +} + +/// One rendered state part, in user / context / answer order. +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +pub struct Part { + pub r#type: String, + pub text: String, +} + +/// A named state field's span inside its part's text (Unicode code +/// points, as on the reference). +#[derive(Debug, Clone, Copy, PartialEq)] +pub struct FieldRange { + pub role: &'static str, + pub start: usize, + pub end: usize, +} + +#[derive(Debug)] +pub struct StateParts { + pub parts: Vec, + pub fields: BTreeMap, +} + +fn state_error(msg: &str) -> RequestError { + RequestError::envelope(&["state"], msg, "value_error") +} + +/// The SystemOne state → (parts, fields) mapping, mirroring +/// `system_one_state`: a plain string is one user part; a JSON array is +/// canonicalized into one; an object groups its keys by role (request / +/// user / prompt → user; source / context / document / tools / +/// previous_answer → context; answer / response → answer; unknown keys +/// → context) in user / context / answer order — one known-key entry +/// per role renders bare, several (or an unknown key) render as +/// `"key:\n"` blocks joined by blank lines. +pub fn system_one_state(state: &Value) -> Result { + // A string holding a JSON object is read as that object. + let state = match state { + Value::String(text) => { + let stripped = text.trim_start(); + if stripped.starts_with('{') { + if let Value::Object(object) = + serde_json::from_str::(stripped).unwrap_or(Value::Null) + { + Value::Object(object) + } else { + state.clone() + } + } else { + state.clone() + } + } + other => other.clone(), + }; + match &state { + Value::String(text) => { + if text.trim().is_empty() { + return Err(state_error("state must not be empty or whitespace")); + } + let mut fields = BTreeMap::new(); + fields.insert( + "request".into(), + FieldRange { + role: "user", + start: 0, + end: text.chars().count(), + }, + ); + Ok(StateParts { + parts: vec![Part { + r#type: "user".into(), + text: text.clone(), + }], + fields, + }) + } + Value::Array(_) => { + let text = canonical(&state); + let mut fields = BTreeMap::new(); + fields.insert( + "request".into(), + FieldRange { + role: "user", + start: 0, + end: text.chars().count(), + }, + ); + Ok(StateParts { + parts: vec![Part { + r#type: "user".into(), + text, + }], + fields, + }) + } + Value::Object(object) if !object.is_empty() => { + // Group per role, keeping the object's insertion order inside + // each role and remembering which entries had a known key. + let mut by_role: [Vec<(&String, &Value, bool)>; 3] = + [Vec::new(), Vec::new(), Vec::new()]; + for (key, value) in object { + let lower = key.to_ascii_lowercase(); + let known = matches!( + lower.as_str(), + "request" + | "user" + | "prompt" + | "source" + | "context" + | "document" + | "tools" + | "previous_answer" + | "answer" + | "response" + ); + let slot = match key_role(&lower) { + "user" => 0, + "answer" => 2, + _ => 1, + }; + by_role[slot].push((key, value, known)); + } + let mut parts = Vec::new(); + let mut fields = BTreeMap::new(); + for (role, items) in [ + ("user", &by_role[0]), + ("context", &by_role[1]), + ("answer", &by_role[2]), + ] { + if items.is_empty() { + continue; + } + let mut text = String::new(); + let single = items.len() == 1 && items[0].2; + for (index, (key, value, _)) in items.iter().enumerate() { + let rendered = content_text(value); + if single { + fields.insert( + (*key).clone(), + FieldRange { + role, + start: 0, + end: rendered.chars().count(), + }, + ); + text = rendered; + } else { + if index > 0 { + text.push_str("\n\n"); + } + let head = format!("{key}:\n"); + let start = text.chars().count() + head.chars().count(); + fields.insert( + (*key).clone(), + FieldRange { + role, + start, + end: start + rendered.chars().count(), + }, + ); + text.push_str(&head); + text.push_str(&rendered); + } + } + if text.trim().is_empty() { + return Err(state_error(&format!( + "the {role} part of the state is empty" + ))); + } + parts.push(Part { + r#type: role.into(), + text, + }); + } + Ok(StateParts { parts, fields }) + } + _ => Err(state_error( + "state must be a non-empty string, JSON object or JSON array", + )), + } +} diff --git a/src/models/vela/native/src/words.rs b/src/models/vela/native/src/words.rs new file mode 100644 index 00000000..c26dcac7 --- /dev/null +++ b/src/models/vela/native/src/words.rs @@ -0,0 +1,119 @@ +//! Word units and first-token mapping, mirroring the pinned runtime's +//! `schema_lib_r4` `_WORD` splitter (GLiNER2 whitespace splitter + CJK +//! one unit per character + the r4 URL/email/handle rule) and +//! `word_first_tokens`. Offsets are Unicode code points everywhere, as +//! on the reference. + +use onig::Regex; + +/// The CJK ranges of the reference `_WORD` pattern, verbatim. +const CJK: &str = "⺀-⿿　-〿぀-ヿ㄀-ㇿ㐀-䶿一-鿿ꀀ-꓏가-힯豈-﫿︰-﹏＀-￯"; +/// Trailing punctuation the URL rule strips. +const TRAIL: &str = ".,;:!?)\\]}>\"'\u{201d}\u{2019}\u{bb}"; + +fn word_pattern() -> Regex { + let pattern = concat!( + "(?:https?://|www\\.)[^\\s{cjk}]+?(?=[{trail}]*(?![^\\s{cjk}]))", + "|[a-z0-9._%+-]+@[a-z0-9.-]+\\.[a-z]{2,}", + "|@[a-z0-9_]+", + "|[{cjk}]", + "|[^\\W{cjk}]+(?:[-_][^\\W{cjk}]+)*", + "|\\S", + ); + let pattern = pattern.replace("{cjk}", CJK).replace("{trail}", TRAIL); + Regex::with_options( + &pattern, + onig::RegexOptions::REGEX_OPTION_IGNORECASE, + onig::Syntax::ruby(), + ) + .expect("the reference word pattern must compile") +} + +/// The (start, end) word ranges of `text`, in code points. +pub fn split_words(text: &str) -> Vec<(usize, usize)> { + let regex = word_pattern(); + // Byte offsets → code-point offsets. + let char_of_byte: Vec = text + .char_indices() + .map(|(byte, _)| byte) + .chain(std::iter::once(text.len())) + .collect(); + let to_char = |byte: usize| -> usize { char_of_byte.partition_point(|&start| start < byte) }; + regex + .find_iter(text) + .map(|(start, end)| (to_char(start), to_char(end))) + .collect() +} + +/// (word char offsets (W, 2), each word's first overlapping sub-word +/// token index), mirroring `word_first_tokens`: the first token whose +/// cumulative end passes the word start, skipping empty tokens. +pub fn word_first_tokens( + text: &str, + offsets: &[(usize, usize)], +) -> (Vec<(usize, usize)>, Vec) { + let words = split_words(text); + if words.is_empty() || offsets.is_empty() { + return (Vec::new(), Vec::new()); + } + let valid: Vec = offsets.iter().map(|(s, e)| e > s).collect(); + let mut cummax_end: Vec = Vec::with_capacity(offsets.len()); + let mut running: i64 = -1; + for (index, (_start, end)) in offsets.iter().enumerate() { + if valid[index] { + running = running.max(*end as i64); + } + cummax_end.push(running); + } + let mut word_offsets = Vec::new(); + let mut first_tokens = Vec::new(); + for (a, b) in words { + let mut t = cummax_end.partition_point(|&end| end <= a as i64); + while t < offsets.len() && !valid[t] { + t += 1; + } + if t < offsets.len() && offsets[t].0 < b { + word_offsets.push((a, b)); + first_tokens.push(t); + } + } + (word_offsets, first_tokens) +} + +/// The reference's CJK class as a range test (the same ranges the word +/// splitter carries). +pub fn is_cjk_char(ch: char) -> bool { + // The reference class has one contiguous run from U+8C48 to + // U+FAFF and ends the Yi block at U+A4CF (not U+A48F). + matches!(ch as u32, + 0x2E80..=0x2FFF | 0x3000..=0x303F | 0x3040..=0x30FF | 0x3100..=0x31FF + | 0x3400..=0x4DBF | 0x4E00..=0x9FFF | 0xA000..=0xA4CF | 0xAC00..=0xD7AF + | 0x8C48..=0xFAFF | 0xFE30..=0xFE4F | 0xFF00..=0xFFEF) +} + +/// The reference's `_UNIT` split (decode-time units): URL bodies, runs +/// of word characters (excluding CJK, `_` excluded by `[^\W_]`) plus +/// `@._-+`, or any non-space char. Returns each char's unit id, -1 +/// outside units — the decode's `u` array. +pub fn unit_ids(chars: &[char]) -> Vec { + let mut ids = vec![-1i64; chars.len()]; + let text: String = chars.iter().collect(); + let pattern = concat!( + "(?:https?://|www\\.)[^\\s\\]\\)\\}>「」『』\"'“”{cjk}]+?(?=[.,;:!?]*(?![^\\s\\]\\)\\}>「」『』\"'“”{cjk}]))", + "|(?:(?![{cjk}])[^\\W_]|[@._\\-+])+", + "|\\S", + ) + .replace("{cjk}", CJK); + let regex = Regex::with_options( + &pattern, + onig::RegexOptions::REGEX_OPTION_IGNORECASE, + onig::Syntax::ruby(), + ) + .expect("the reference unit pattern must compile"); + for (unit, (start, end)) in regex.find_iter(&text).enumerate() { + for id in ids.iter_mut().take(end).skip(start) { + *id = unit as i64; + } + } + ids +} diff --git a/tests/vela/native_contract_unit.rs b/tests/vela/native_contract_unit.rs new file mode 100644 index 00000000..e2a60834 --- /dev/null +++ b/tests/vela/native_contract_unit.rs @@ -0,0 +1,14 @@ +//! Private-item tests for the native crate's wire contract, loaded by +//! the `#[path]` wiring in `src/models/vela/native/src/contract.rs`. + +use super::*; + +#[test] +fn duplicate_keys_mirror_the_reference_message() { + let error = normalize_parse_error("request body is not valid JSON: duplicate key \"state\""); + assert_eq!(error.status, 400); + assert_eq!( + error.body, + serde_json::json!({"detail": "duplicate JSON key 'state'"}) + ); +} diff --git a/tests/vela/native_processing.rs b/tests/vela/native_processing.rs new file mode 100644 index 00000000..917a423c --- /dev/null +++ b/tests/vela/native_processing.rs @@ -0,0 +1,137 @@ +//! Processing tests against the frozen token-plan fixtures. +//! +//! The mapping tests (state → parts, SystemOne → predict, plan) run +//! everywhere with no tokenizer and no weights. The full render parity +//! — rows and window rows byte-for-byte against the fixtures — needs +//! the exported bundle's tokenizer and is opt-in: +//! +//! VELA_NATIVE_BUNDLE=weights/vela-2.0-0.8b-native \ +//! cargo test -p omni-vela-native --test vela_native_processing -- --nocapture + +use std::path::PathBuf; + +use omni_vela_native::questions::system_one_to_predict; +use omni_vela_native::state::system_one_state; +use serde_json::Value; + +const CASES: [&str; 5] = [ + "example-request", + "example-request-set-threshold", + "example-request-cjk", + "example-request-score", + "long-span-windowed", +]; + +fn fixture(case: &str) -> Value { + let root = PathBuf::from(env!("CARGO_MANIFEST_DIR")).join("../../../../tests/vela/fixtures"); + serde_json::from_str( + &std::fs::read_to_string(root.join(format!("native-plan-{case}.json"))) + .expect("fixture present; record it with recipe/vela/export_token_plan.py"), + ) + .expect("fixture JSON") +} + +// ------------------------------------------------------- mapping (no tokens) + +fn mapped(case: &str) -> Value { + let fix = fixture(case); + let request = fix["request"].as_object().expect("request"); + let state = system_one_state(&request["state"]).expect("state maps"); + let questions = request["questions"].as_object().expect("questions"); + let mapped = system_one_to_predict(state, questions).expect("maps"); + serde_json::json!({ + "predict_request": serde_json::to_value(&mapped.request).unwrap(), + "plan": serde_json::to_value(&mapped.plan).unwrap(), + }) +} + +#[test] +fn the_predict_mapping_matches_every_fixture() { + for case in CASES { + let got = mapped(case); + let fix = fixture(case); + assert_eq!( + got["predict_request"], fix["predict_request"], + "predict_request differs for {case}" + ); + assert_eq!(got["plan"], fix["plan"], "plan differs for {case}"); + } +} + +#[test] +fn an_invalid_question_reports_the_pinned_triples() { + let state = system_one_state(&serde_json::json!("s")).expect("state"); + let questions = serde_json::json!({ + "q": {"type": "choice", "instructions": "ok?", "criteria": {"a": "x"}} + }); + let error = system_one_to_predict(state, questions.as_object().unwrap()).unwrap_err(); + assert_eq!( + error.body, + serde_json::json!({"detail": [{"loc": ["body", "questions", "q", "criteria"], + "msg": "choice criteria must be an object with 2 to 255 entries", "type": "value_error"}]}) + ); + + let state = system_one_state(&serde_json::json!("s")).expect("state"); + let questions = serde_json::json!({ + "q": {"type": "span", "instructions": "which?", "criteria": {"a": "x"}, + "head": "other", "over": "request"} + }); + let error = system_one_to_predict(state, questions.as_object().unwrap()).unwrap_err(); + assert_eq!( + error.body["detail"][0]["loc"], + serde_json::json!(["body", "questions", "q", "head"]) + ); + assert_eq!(error.body["detail"][0]["type"], "literal_error"); +} + +#[test] +fn a_set_label_collision_is_rejected_after_the_walk() { + let state = system_one_state(&serde_json::json!("s")).expect("state"); + let questions = serde_json::json!({ + "issues": {"type": "set", "instructions": "which?", "criteria": {"billing": "b"}}, + "issues.billing": {"type": "noul", "instructions": "which?"} + }); + let error = system_one_to_predict(state, questions.as_object().unwrap()).unwrap_err(); + assert_eq!( + error.body["detail"][0]["msg"], + "collides with the Noul view of a set label" + ); +} + +// ------------------------------------------------- full render (opt-in) + +fn bundle_dir() -> Option { + let value = std::env::var("VELA_NATIVE_BUNDLE").ok()?; + let path = PathBuf::from(value); + path.is_dir().then_some(path) +} + +#[test] +fn the_rendered_rows_match_every_fixture() { + let Some(bundle) = bundle_dir() else { + eprintln!("skipping: set VELA_NATIVE_BUNDLE to an exported bundle for render parity"); + return; + }; + let processor = omni_vela_native::processing::Processor::load(&bundle) + .expect("processor loads the exported bundle"); + for case in CASES { + let fix = fixture(case); + let request = fix["request"].as_object().expect("request"); + let planned = match processor.plan(request) { + Ok(planned) => planned, + Err(error) => panic!( + "plan failed for {case}: {}", + serde_json::to_string(&error.body).unwrap() + ), + }; + let got = serde_json::json!({ + "rows": serde_json::to_value(&planned.rows).unwrap(), + "window_rows": serde_json::to_value(&planned.window_rows).unwrap(), + }); + assert_eq!(got["rows"], fix["rows"], "rows differ for {case}"); + assert_eq!( + got["window_rows"], fix["window_rows"], + "window rows differ for {case}" + ); + } +} diff --git a/tests/vela/native_units.rs b/tests/vela/native_units.rs new file mode 100644 index 00000000..e117fdea --- /dev/null +++ b/tests/vela/native_units.rs @@ -0,0 +1,97 @@ +//! Unit tests for the native crate's state mapping and word splitter, +//! extracted from the modules per the repository's test-placement +//! rule (the private contract test lives in native_contract_unit.rs, +//! loaded by the `#[path]` wiring in contract.rs). + +use omni_vela_native::state::system_one_state; +use omni_vela_native::words::{split_words, word_first_tokens}; +use serde_json::json; + +// ------------------------------------------------------------- state + +#[test] +fn a_plain_string_is_one_user_part() { + let parts = system_one_state(&json!("hello")).expect("parts"); + assert_eq!(parts.parts.len(), 1); + assert_eq!(parts.parts[0].r#type, "user"); + assert_eq!(parts.fields["request"].end, 5); +} + +#[test] +fn typed_keys_group_into_ordered_parts_with_field_ranges() { + let parts = system_one_state(&json!({ + "answer": "A", "request": "R", "source": "S", "extra": "E", + })) + .expect("parts"); + let roles: Vec<&str> = parts.parts.iter().map(|p| p.r#type.as_str()).collect(); + assert_eq!(roles, ["user", "context", "answer"]); + let context = &parts.parts[1]; + assert_eq!(context.text, "source:\nS\n\nextra:\nE"); + assert_eq!(parts.fields["source"].start, "source:\n".chars().count()); + assert_eq!( + parts.fields["extra"].start, + "source:\nS\n\nextra:\n".chars().count() + ); +} + +#[test] +fn an_empty_role_part_is_rejected() { + let error = system_one_state(&json!({"request": " "})).unwrap_err(); + assert_eq!( + error.body["detail"][0]["msg"], + serde_json::json!("the user part of the state is empty") + ); +} + +#[test] +fn a_string_holding_a_json_object_is_read_as_that_object() { + let parts = system_one_state(&json!("{\"request\": \"text\"}")).expect("parts"); + assert_eq!(parts.parts.len(), 1); + assert_eq!(parts.fields["request"].end, 4); +} + +// ------------------------------------------------------------- words + +#[test] +fn words_split_like_the_reference() { + let text = "Hi, I'm Tom Baker (tom.baker@example.com)."; + let words: Vec = split_words(text) + .iter() + .map(|(a, b)| text.chars().skip(*a).take(b - a).collect()) + .collect(); + assert_eq!( + words, + vec![ + "Hi", + ",", + "I", + "'", + "m", + "Tom", + "Baker", + "(", + "tom.baker@example.com", + ")", + "." + ] + ); +} + +#[test] +fn cjk_characters_are_one_unit_each() { + let text = "追踪 parcel 仓库"; + let words: Vec = split_words(text) + .iter() + .map(|(a, b)| text.chars().skip(*a).take(b - a).collect()) + .collect(); + assert_eq!(words, vec!["追", "踪", "parcel", "仓", "库"]); +} + +#[test] +fn first_tokens_skip_empty_tokens() { + let text = "alpha beta"; + let offsets = vec![(0, 0), (0, 5), (6, 10)]; + let (word_offsets, first) = word_first_tokens(text, &offsets); + assert_eq!(word_offsets, vec![(0, 5), (6, 10)]); + assert_eq!(first, vec![1, 2]); +} From 7391de2a1035fb9a07af3d13ef4a997e0002ab48 Mon Sep 17 00:00:00 2001 From: "Mr.Dong" <1042542469@qq.com> Date: Sun, 25 Oct 2026 02:34:48 +0800 Subject: [PATCH 03/32] vela: add the 0.8B native token-level processing MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The Rust processing of the native path, mirrored from the pinned runtime and checked field-for-field against the five frozen token plans (opt-in render parity with the exported bundle's tokenizer): - state.rs: the state -> typed-parts mapping (role grouping, field ranges, canonical DEV2.0 JSON) with the pinned rejection triples; - questions.rs: the SystemOne -> predict mapping — the validation walk and order, Noul folded into a two-option choice (choice renders [ABS], the reference's abstain default), over resolution, threshold/head carried, the set-label collision check; - words.rs: the GLiNER2/CJK _WORD splitter and the first-token word mapping; - render.rs: the encoder (char-offset tokens, memoized), the six-rule span-head dispatch with the hallucination-alias label replacement, the truncation budget, the DEV2.0 rendering (parts pass, question blocks with option ends and query positions, span layout a/c with word positions) and the window rows (head only, as the reference); - processing.rs: the Processor over the exported bundle. Also: the envelope error locs are flat arrays, matching the reference triples exactly. Checks: cargo test (26 tests) + fmt/clippy clean + opt-in render parity (5/5 fixtures). --- Cargo.lock | 3 + README.md | 2 +- docs/supported-models.md | 2 +- recipe/vela/native.md | 44 +- src/models/vela/README.md | 17 +- src/models/vela/native/Cargo.toml | 18 +- src/models/vela/native/examples/parity.rs | 87 +++ src/models/vela/native/src/contract.rs | 15 +- src/models/vela/native/src/lib.rs | 12 +- src/models/vela/native/src/processing.rs | 274 ++++++++ src/models/vela/native/src/questions.rs | 441 ++++++++++++ src/models/vela/native/src/render.rs | 794 ++++++++++++++++++++++ src/models/vela/native/src/state.rs | 235 +++++++ src/models/vela/native/src/words.rs | 119 ++++ tests/vela/native_contract_unit.rs | 14 + tests/vela/native_processing.rs | 137 ++++ tests/vela/native_units.rs | 97 +++ 17 files changed, 2277 insertions(+), 34 deletions(-) create mode 100644 src/models/vela/native/examples/parity.rs create mode 100644 src/models/vela/native/src/processing.rs create mode 100644 src/models/vela/native/src/questions.rs create mode 100644 src/models/vela/native/src/render.rs create mode 100644 src/models/vela/native/src/state.rs create mode 100644 src/models/vela/native/src/words.rs create mode 100644 tests/vela/native_contract_unit.rs create mode 100644 tests/vela/native_processing.rs create mode 100644 tests/vela/native_units.rs diff --git a/Cargo.lock b/Cargo.lock index 2a269f64..bd63bd1c 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -1295,8 +1295,11 @@ version = "0.1.0" dependencies = [ "anyhow", "omni-qwen3-5-native", + "onig", + "serde", "serde_json", "sha2 0.11.1", + "tokenizers 0.22.2", ] [[package]] diff --git a/README.md b/README.md index cbfce500..a68b0fd2 100644 --- a/README.md +++ b/README.md @@ -183,7 +183,7 @@ extensions) on each checkpoint's own pinned runtime: | OmniJev-4B v1.1 | [Checkpoint export and CPU contract](recipe/omnijev/README.md) only; the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | | D3 (Decision 3.0) | [Python reference worker](recipe/d3/reference.md) on the checkpoint's pinned runtime; `choice`/`noul`/`score` text state, media inputs refused; author-run on A100 (evidence in the integration PR) | | Vela 2.0 0.3B | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; all five kinds (`choice`/`noul`/`score`/`span`/`set`) for text state; CPU FP32 validated (author-run, evidence in the integration PR) | -| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; [native library](recipe/vela/native.md) (bundle export, wire contract); CPU FP32 parity recorded in the integration PR | +| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; [native library](recipe/vela/native.md) (bundle export, wire contract, token-level processing); CPU FP32 parity recorded in the integration PR | [Supported models and hardware](docs/supported-models.md) lists the devices and where each worker has been run. diff --git a/docs/supported-models.md b/docs/supported-models.md index 30a52c6b..399ea09a 100644 --- a/docs/supported-models.md +++ b/docs/supported-models.md @@ -25,7 +25,7 @@ Models that are being added are also tracked in issues labeled [new model](https | OmniJev-4B v1.1 | None yet: [checkpoint export and CPU contract](../recipe/omnijev/README.md); the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | Request contract, preparation, heads and finishing checked against the reference ([#120](https://github.com/ThinkFlowLab/system1-omni/pull/120)); no inference | Not yet | Not supported | Python 3.10 reference environment for the export and fixtures | | D3 (Decision 3.0) | [Python reference worker](../recipe/d3/reference.md) running the checkpoint's pinned runtime | Unverified | Author-run on NVIDIA A100 (sm_80): three-kind serving smoke with byte-identical frontend forwarding and reference parity (exact decisions, max delta 0.0, 348 == 348 tokens); evidence in the integration PR. Owner: @MrDongsls. | Unverified | Python 3.12, the [pinned runtime requirements](../recipe/d3/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/d3) (~52 GB) | | Vela 2.0 0.3B | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime | **CPU FP32 validated** (author-run, x86 WSL2, 24 cores): startup with all-kind warmup, the four example requests plus five synthetic rejections, and exact-match reference parity against the pinned upstream server on all nine (four 200s byte-equal incl. key order, agreed 422/413); byte-identical frontend forwarding; evidence in the integration PR. Owner: @MrDongsls. | Unverified (bf16-autocast is an untested deployment option) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.3B) (1.24 GB FP32 weights; ~4.4 GB with ONNX/assets) | -| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B); [native library](../recipe/vela/native.md) — bundle export, wire contract | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | +| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B); [native library](../recipe/vela/native.md) — bundle export, wire contract, token-level processing | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | - **Validated:** covered by the recipe on `main` or by the checks in the linked merged pull request. - **Author-run:** recorded by the recipe author on the stated hardware and not independently reproduced; the row names its owner. diff --git a/recipe/vela/native.md b/recipe/vela/native.md index a9328003..4c3cefa3 100644 --- a/recipe/vela/native.md +++ b/recipe/vela/native.md @@ -2,8 +2,9 @@ The native implementation for [vllm-sr/Vela-2.0-0.8B](https://huggingface.co/vllm-sr/Vela-2.0-0.8B): -the exported-bundle gate and the wire contract, mirrored from the -pinned runtime. This is a library; serving runs through the +the exported-bundle gate, the wire contract, and the token-level +processing — all mirrored from the pinned runtime and checked against +frozen fixtures. This is a library; serving runs through the [reference recipe](reference.md)'s Python worker. Run the commands from the repository root with the same `.venv` and @@ -28,22 +29,45 @@ tokenizer, and `vela_native_manifest.json` pinning the source revision, the gate's file table, the tensor inventory and every file's SHA-256. +## Freeze the token-plan fixtures (opt-in, needs the package) + +~~~sh +PYTHONPATH=src .venv/bin/python recipe/vela/export_token_plan.py \ + --model weights/vela-2.0-0.8b --out tests/vela/fixtures/ +~~~ + +The token plans record what the pinned runtime feeds the backbone (the +predict mapping, the per-row decomposition, the rendered `p_ids`, +blocks and readout positions, truncation, a windowed long-span case). +The example-request token plan totals 1,041 tokens, matching the +oracle fixture's `usage.input_tokens`. + ## Checks ~~~sh cargo test -p omni-vela-native cargo fmt --all --check cargo clippy -p omni-vela-native --all-targets -- -D warnings +VELA_NATIVE_BUNDLE="$PWD/weights/vela-2.0-0.8b-native" \ + cargo test -p omni-vela-native --test vela_native_processing -- --nocapture ~~~ -15 tests, no weights, no GPU: the wire contract against the pinned -runtime's 422/400 bodies and the bundle manifest gate against a -synthetic bundle. +26 tests run everywhere with no weights and no GPU: the wire contract +against the pinned runtime's 422/400 bodies, the bundle manifest gate, +and the predict-mapping/plan parity on every frozen fixture. The +opt-in render check replays the five token plans through the Rust +processing field-for-field. For a field-level diff of one case: + +~~~sh +VELA_NATIVE_BUNDLE="$PWD/weights/vela-2.0-0.8b-native" \ + cargo run -p omni-vela-native --example parity -- example-request +~~~ ## Scope and limits -- Implemented: the bundle export + manifest gate and the wire - admission. -- Not implemented: token-level processing, the F32 heads, scoring, - backbone execution, and an HTTP worker. No performance claims are - made. +- Implemented: the bundle export + manifest gate, the wire admission, + and the token-level processing (state mapping, predict mapping with + the validation triples, word units, span-head dispatch, the DEV2.0 + rendering, the truncation budget, window rows). +- Not implemented: the F32 heads, scoring and span decoding, backbone + execution, and an HTTP worker. No performance claims are made. diff --git a/src/models/vela/README.md b/src/models/vela/README.md index 888658fc..92fc4f82 100644 --- a/src/models/vela/README.md +++ b/src/models/vela/README.md @@ -246,8 +246,19 @@ The native implementation lives in [`native/`](native/) as the - `native/src/contract.rs` is the wire admission, mirroring `protocol.py` and the pinned runtime's preamble with byte-equal 422/400 bodies. +- `native/src/{state,questions,words,render,processing}.rs` are the + token-level processing: the state → parts mapping, the SystemOne → + predict mapping with the pinned runtime's validation triples (Noul + folded into a two-option choice; choice renders `[ABS]`, the + reference's abstain default), the GLiNER2/CJK word splitter, the + six-rule span-head dispatch with the hallucination-alias label + replacement, the DEV2.0 prompt rendering (parts pass, question + blocks with option end and query positions, span layout a/c with + word positions, the truncation budget, the 16,384-window 413) and + the long-target window rows. All five frozen token plans + (`tests/vela/fixtures/native-plan-*.json`) match field-for-field. -Token-level processing, the F32 heads, backbone execution and an HTTP -worker are not implemented. Checks: `cargo test -p omni-vela-native` -(15 tests, no weights, no GPU; see +The F32 heads, scoring, backbone execution and an HTTP worker are not +implemented. Checks: `cargo test -p omni-vela-native` (26 tests, no +weights, no GPU; render parity opt-in with `VELA_NATIVE_BUNDLE`; see [recipe/vela/native.md](../../recipe/vela/native.md)). diff --git a/src/models/vela/native/Cargo.toml b/src/models/vela/native/Cargo.toml index 814d32b0..a69e15b6 100644 --- a/src/models/vela/native/Cargo.toml +++ b/src/models/vela/native/Cargo.toml @@ -3,15 +3,15 @@ name = "omni-vela-native" version = "0.1.0" edition = "2024" publish = false -description = "Native library for vllm-sr/Vela-2.0-0.8B: bundle gate and wire contract" +description = "Native library for vllm-sr/Vela-2.0-0.8B: bundle gate, wire contract and token-level processing" [dependencies] anyhow = "1.0.100" +onig = { version = "6", default-features = false } omni-qwen3-5-native = { path = "../../qwen3_5/native" } -serde_json = { version = "1.0.149", features = ["preserve_order"] } -sha2 = "0.11" - -[dev-dependencies] +serde = { version = "1", features = ["derive"] } +tokenizers = { version = "=0.22.2", default-features = false, features = ["onig"] } +serde_json = { version = "1.0.149", features = ["float_roundtrip", "preserve_order"] } sha2 = "0.11" [lib] @@ -24,3 +24,11 @@ path = "../../../../tests/vela/native_contract.rs" [[test]] name = "vela_native_bundle" path = "../../../../tests/vela/native_bundle.rs" + +[[test]] +name = "vela_native_processing" +path = "../../../../tests/vela/native_processing.rs" + +[[test]] +name = "vela_native_units" +path = "../../../../tests/vela/native_units.rs" diff --git a/src/models/vela/native/examples/parity.rs b/src/models/vela/native/examples/parity.rs new file mode 100644 index 00000000..071d0f52 --- /dev/null +++ b/src/models/vela/native/examples/parity.rs @@ -0,0 +1,87 @@ +//! Debug helper: compare the rendered rows against one fixture and +//! print the first differing field. Run with: +//! +//! VELA_NATIVE_BUNDLE=/abs/path cargo run -p omni-vela-native --example parity -- example-request + +use std::path::PathBuf; + +use serde_json::Value; + +fn main() { + let case = std::env::args().nth(1).unwrap_or("example-request".into()); + let bundle = PathBuf::from( + std::env::var("VELA_NATIVE_BUNDLE").expect("VELA_NATIVE_BUNDLE points at the export"), + ); + let fixture: Value = serde_json::from_str( + &std::fs::read_to_string( + PathBuf::from(env!("CARGO_MANIFEST_DIR")) + .join("../../../../tests/vela/fixtures") + .join(format!("native-plan-{case}.json")), + ) + .expect("fixture"), + ) + .expect("fixture json"); + + let processor = omni_vela_native::processing::Processor::load(&bundle).expect("load"); + let request = fixture["request"].as_object().expect("request"); + match processor.plan(request) { + Ok(planned) => { + let got = serde_json::json!({ + "rows": serde_json::to_value(&planned.rows).unwrap(), + "window_rows": serde_json::to_value(&planned.window_rows).unwrap(), + }); + compare( + "rows", + got["rows"].as_array().unwrap(), + fixture["rows"].as_array().unwrap(), + ); + if !fixture["window_rows"].is_null() { + compare( + "window_rows", + got["window_rows"].as_array().unwrap(), + fixture["window_rows"].as_array().unwrap(), + ); + } + println!("parity: no field differences found"); + } + Err(error) => println!( + "plan error: {}", + serde_json::to_string(&error.body).unwrap() + ), + } +} + +fn compare(name: &str, got: &[Value], want: &[Value]) { + println!("{name}: {} vs {} row(s)", got.len(), want.len()); + for (index, (a, b)) in got.iter().zip(want).enumerate() { + let (Some(a), Some(b)) = (a.as_object(), b.as_object()) else { + continue; + }; + for key in b.keys() { + if a.get(key) != b.get(key) { + println!("row {index} field {key}: differs"); + println!( + " want: {}", + serde_json::to_string(&b[key]) + .unwrap() + .chars() + .take(300) + .collect::() + ); + println!( + " got: {}", + serde_json::to_string(&a[key]) + .unwrap() + .chars() + .take(300) + .collect::() + ); + } + } + for key in a.keys() { + if !b.contains_key(key) { + println!("row {index} field {key}: extra in ours"); + } + } + } +} diff --git a/src/models/vela/native/src/contract.rs b/src/models/vela/native/src/contract.rs index 06a3de95..734dcb25 100644 --- a/src/models/vela/native/src/contract.rs +++ b/src/models/vela/native/src/contract.rs @@ -56,7 +56,7 @@ pub fn parse_body(raw: &[u8]) -> Result, RequestError> { /// Mirror the reference worker's 400 messages: duplicate keys verbatim, /// everything else the shared generic message. -fn normalize_parse_error(error: &str) -> RequestError { +pub(crate) fn normalize_parse_error(error: &str) -> RequestError { if let Some(rest) = error.split("duplicate key ").nth(1) { // serde appends its position suffix after the quoted key. if let Some(key) = rest @@ -129,14 +129,5 @@ pub fn runtime_rejection(message: &str) -> RequestError { } #[cfg(test)] -mod tests { - use super::*; - - #[test] - fn duplicate_keys_mirror_the_reference_message() { - let error = - normalize_parse_error("request body is not valid JSON: duplicate key \"state\""); - assert_eq!(error.status, 400); - assert_eq!(error.body, json!({"detail": "duplicate JSON key 'state'"})); - } -} +#[path = "../../../../../tests/vela/native_contract_unit.rs"] +mod tests; diff --git a/src/models/vela/native/src/lib.rs b/src/models/vela/native/src/lib.rs index 32f64c4f..1d849284 100644 --- a/src/models/vela/native/src/lib.rs +++ b/src/models/vela/native/src/lib.rs @@ -1,5 +1,13 @@ -//! Native library for vllm-sr/Vela-2.0-0.8B: the exported-bundle gate -//! and the wire contract, mirrored from the pinned runtime. +//! Native library for vllm-sr/Vela-2.0-0.8B: the exported-bundle gate, +//! the wire contract, and the token-level processing (state → parts, +//! the SystemOne → predict mapping with the pinned runtime's validation +//! triples, word units, the DEV2.0 prompt rendering — mirrored against +//! the frozen `native-plan-*` fixtures). pub mod bundle; pub mod contract; +pub mod processing; +pub mod questions; +pub mod render; +pub mod state; +pub mod words; diff --git a/src/models/vela/native/src/processing.rs b/src/models/vela/native/src/processing.rs new file mode 100644 index 00000000..12370856 --- /dev/null +++ b/src/models/vela/native/src/processing.rs @@ -0,0 +1,274 @@ +//! The processor: one admitted request body → predict mapping, plan, +//! and rendered rows, mirroring the reference path +//! (`system_one_to_predict` → `_to_generic` → `_predict`'s row split → +//! `_prep`/`_render`, plus the long-target window rows). Everything the +//! frozen `native-plan-*` fixtures record. + +use std::collections::HashSet; +use std::path::Path; + +use anyhow::{Context, Result}; +use serde_json::{Map, Value}; + +use crate::contract::RequestError; +use crate::questions::{PredictQuestion, system_one_to_predict}; +use crate::render::{ + Encoder, GenericQuestion, HALU_LABEL, PreparedPart, RMAX, RenderContext, RenderedRow, + window_part, +}; +use crate::state::system_one_state; + +pub struct Processor { + encoder: Encoder, + max_length: usize, + router_label_sets: Vec>, + has_broad: bool, + halu_desc: String, +} + +pub struct Planned { + pub predict_request: Value, + pub plan: Value, + pub rows: Vec, + pub window_rows: Vec, +} + +impl Processor { + /// Load from an exported native bundle (tokenizer + calibration; + /// the manifest gate runs first). + pub fn load(bundle: &Path) -> Result { + let manifest = crate::bundle::Bundle::load(bundle)?; + let calibration: Value = serde_json::from_slice( + &std::fs::read(bundle.join("calibration.json")).context("calibration.json")?, + ) + .context("calibration.json must be JSON")?; + let broad = calibration.get("broad_head").filter(|b| !b.is_null()); + let router_label_sets: Vec> = broad + .and_then(|b| b.get("router_label_sets")) + .and_then(Value::as_array) + .filter(|sets| !sets.is_empty()) + .map(|sets| { + sets.iter() + .filter_map(Value::as_array) + .map(|labels| { + labels + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect() + }) + .collect() + }) + .unwrap_or_else(|| { + vec![ + calibration["pii_types"].as_array().map(|types| { + types + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect() + }), + calibration["halu_schema"]["labels"] + .as_object() + .map(|labels| labels.keys().cloned().collect()), + ] + .into_iter() + .flatten() + .collect() + }); + let has_broad = broad.is_some(); // the bundle gate pinned the broad tensors + let halu_desc = calibration["halu_schema"]["labels"][HALU_LABEL] + .as_str() + .unwrap_or("a claim not supported by the context") + .to_owned(); + Ok(Self { + encoder: Encoder::load(&bundle.join("tokenizer.json"))?, + max_length: manifest.max_length(), + router_label_sets, + has_broad, + halu_desc, + }) + } + + /// The full planning path for one admitted request body. + pub fn plan(&self, body: &Map) -> Result { + let state = system_one_state(&body["state"])?; + let questions = body["questions"] + .as_object() + .ok_or_else(crate::questions::empty_questions_error)?; + let mapped = system_one_to_predict(state, questions)?; + let predict_request = serde_json::to_value(&mapped.request).expect("serializable"); + let plan = serde_json::to_value(&mapped.plan).expect("serializable"); + let state_parts = mapped.request.parts.clone(); + + // `_to_generic`: predict questions → generic render questions + // (Noul is already folded; choice always carries [ABS]). + let generic: Vec = + mapped.request.questions.iter().map(to_generic).collect(); + // `_predict`'s row split: non-span questions plus the first span + // in one row, every further span its own row. + let spans: Vec<&GenericQuestion> = generic.iter().filter(|q| q.kind == "span").collect(); + let rest: Vec = generic + .iter() + .filter(|q| q.kind != "span") + .cloned() + .collect(); + let mut rows: Vec> = Vec::new(); + if !rest.is_empty() || !spans.is_empty() { + let mut first = rest.clone(); + if let Some(span) = spans.first() { + first.push((*span).clone()); + } + rows.push(first); + for span in spans.iter().skip(1) { + rows.push(vec![(*span).clone()]); + } + } + let context = RenderContext { + encoder: &self.encoder, + max_length: self.max_length, + router_label_sets: &self.router_label_sets, + has_broad: self.has_broad, + halu_desc: self.halu_desc.clone(), + }; + let span_roles: HashSet = + spans.iter().flat_map(|q| q.over.iter().cloned()).collect(); + let mut rendered = Vec::new(); + let mut window_rows = Vec::new(); + let mut parts_by_role = std::collections::HashMap::new(); + for part in self.prepared_parts(&state_parts, &span_roles) { + parts_by_role.insert(part.role.clone(), part); + } + for row in rows { + if row.is_empty() { + continue; + } + let (adjusted, dispatch) = context.prepare_questions(&row)?; + let parts: Vec = state_parts + .iter() + .map(|part| { + parts_by_role + .get(&part.r#type) + .cloned() + .expect("prepared part") + }) + .collect(); + let record = context.render(&parts, &adjusted, &dispatch)?; + // `_window_rows`: a span target beyond RMAX becomes one row + // per window (the full-render span block stays on the row). + let span = row.iter().find(|q| q.kind == "span"); + if let Some(span) = span { + let index = parts.iter().position(|p| p.role == span.over[0]); + if let Some(index) = index { + let part = &parts[index]; + let has_words = part.words.is_some(); + if part.ids.len() > RMAX && has_words { + let (_, first_tokens) = part.words.as_ref().expect("words"); + for (a, b) in crate::render::span_windows(first_tokens, part.ids.len()) { + let mut windowed_parts = parts.clone(); + windowed_parts[index] = window_part(part, a, b); + let (w_adjusted, w_dispatch) = context.prepare_questions(&row)?; + let mut record = + context.render(&windowed_parts, &w_adjusted, &w_dispatch)?; + // The runtime's window rows carry the head only. + record.window = true; + window_rows.push(record); + } + } + } + } + rendered.push(record); + } + Ok(Planned { + predict_request, + plan, + rows: rendered, + window_rows, + }) + } + + /// The prepared parts for one request: tokens everywhere, offsets + /// and word units on span-target parts. + fn prepared_parts( + &self, + state_parts: &[crate::state::Part], + span_roles: &HashSet, + ) -> Vec { + state_parts + .iter() + .map(|part| { + let (ids, offsets) = self.encoder.ids_offsets(&part.text); + if span_roles.contains(&part.r#type) { + let words = crate::words::word_first_tokens(&part.text, &offsets); + PreparedPart { + role: part.r#type.clone(), + ids, + offsets: Some(offsets), + words: Some(words), + } + } else { + PreparedPart { + role: part.r#type.clone(), + ids, + offsets: None, + words: None, + } + } + }) + .collect() + } +} + +/// `_to_generic` for the SystemOne path: options/labels carry over in +/// order (score levels have empty descriptions), the target part is the +/// resolved `over`, choice always carries `[ABS]` (the reference's +/// `abstain` default is true and the mapper never sets it), and span +/// keeps its threshold and head override. +fn to_generic(question: &PredictQuestion) -> GenericQuestion { + let over: Vec = match &question.target_part { + Value::String(role) => vec![role.clone()], + Value::Array(roles) => roles + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect(), + _ => Vec::new(), + }; + let (names, descriptions) = match (&question.labels, &question.options) { + (Some(labels), _) => ( + labels.iter().map(|n| n.name.clone()).collect(), + labels.iter().map(|n| n.description.clone()).collect(), + ), + (None, Some(Value::Array(items))) => { + // Objects carry name/description; score levels are strings. + let mut names = Vec::new(); + let mut descriptions = Vec::new(); + for item in items { + match item { + Value::String(name) => { + names.push(name.clone()); + descriptions.push(String::new()); + } + Value::Object(named) => { + names.push(named["name"].as_str().unwrap_or_default().to_owned()); + descriptions + .push(named["description"].as_str().unwrap_or_default().to_owned()); + } + _ => {} + } + } + (names, descriptions) + } + _ => (Vec::new(), Vec::new()), + }; + GenericQuestion { + id: question.id.clone(), + kind: question.kind.clone(), + over, + text: question.text.clone(), + names, + descriptions, + threshold: question.threshold, + head_override: question.head.clone(), + } +} diff --git a/src/models/vela/native/src/questions.rs b/src/models/vela/native/src/questions.rs new file mode 100644 index 00000000..4c095032 --- /dev/null +++ b/src/models/vela/native/src/questions.rs @@ -0,0 +1,441 @@ +//! The SystemOne (state, questions) → predict-request mapping, mirroring +//! the pinned runtime's `system_one_to_predict` exactly: the validation +//! walk and its whole-request error triples, the Noul folding into a +//! two-option choice, and the per-question plan used to build responses. + +use serde_json::{Map, Value}; + +use crate::contract::RequestError; +use crate::state::{Part, StateParts, content_text}; + +/// The `questions` container rejection shared by the mapping and the +/// processor's body walk. +pub fn empty_questions_error() -> RequestError { + qerror( + &["questions"], + "questions must be a non-empty object of named questions", + ) +} + +pub const SYSTEM_ONE_TYPES: [&str; 5] = ["noul", "choice", "score", "span", "set"]; +pub const NOUL_DEFAULT_NO: &str = "No. The statement or question is not satisfied."; +pub const NOUL_DEFAULT_YES: &str = "Yes. The statement or question is satisfied."; + +/// One option / label of a predict question (name, description). +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +pub struct Named { + pub name: String, + pub description: String, +} + +/// The predict-level question, exactly as it serializes into the frozen +/// fixtures: Noul questions arrive here already folded into a choice. +#[derive(Debug, Clone, serde::Serialize)] +pub struct PredictQuestion { + pub id: String, + #[serde(rename = "type")] + pub kind: String, + pub text: String, + pub target_part: Value, + #[serde(skip_serializing_if = "Option::is_none")] + pub labels: Option>, + #[serde(skip_serializing_if = "Option::is_none")] + pub options: Option, + #[serde(skip_serializing_if = "Option::is_none")] + pub threshold: Option, + #[serde(skip_serializing_if = "Option::is_none")] + pub head: Option, +} + +#[derive(Debug, Clone, serde::Serialize)] +pub struct PredictRequest { + pub parts: Vec, + pub questions: Vec, +} + +/// The response-side plan entry for one original question. +#[derive(Debug, Clone, serde::Serialize)] +pub struct PlanEntry { + pub qid: String, + #[serde(rename = "type")] + pub kind: String, + pub criteria: Value, + pub range: Option<(usize, usize)>, + pub part: Value, +} + +#[derive(Debug)] +pub struct Mapped { + pub request: PredictRequest, + pub plan: Vec, +} + +fn qerror(loc: &[&str], msg: &str) -> RequestError { + RequestError::envelope(loc, msg, "value_error") +} + +fn nonblank(value: &Value) -> bool { + match value { + Value::String(text) => !text.trim().is_empty(), + _ => true, + } +} + +/// `over` (state key | part name | list) → (target part(s), field range). +fn resolve_over( + over: &Value, + parts: &StateParts, + qloc: &[&str], +) -> Result<(Value, Option<(usize, usize)>), RequestError> { + let roles: Vec<&str> = parts.parts.iter().map(|p| p.r#type.as_str()).collect(); + let items: Vec<&Value> = match over { + Value::Array(list) => list.iter().collect(), + single => vec![single], + }; + let mut out: Vec<&str> = Vec::new(); + let mut range = None; + for item in items { + let Some(name) = item.as_str() else { + return Err(qerror( + &[qloc[0], qloc[1], "over"], + "over must be a state key, a part name or a list of them", + )); + }; + if let Some(field) = parts.fields.get(name) { + if !over.is_array() { + range = Some((field.start, field.end)); + } + if !out.contains(&field.role) { + out.push(field.role); + } + } else if roles.contains(&name) { + if !out.contains(&name) { + out.push(name); + } + } else { + let role = crate::state::key_role(name); + if roles.contains(&role) && !out.contains(&role) { + out.push(role); + } else { + return Err(qerror( + &[qloc[0], qloc[1], "over"], + &format!( + "'{name}' is not a field of the state (fields: [{fields}], parts: [{roles}])", + fields = parts + .fields + .keys() + .map(|k| format!("'{k}'")) + .collect::>() + .join(", "), + roles = roles.join(", "), + ), + )); + } + } + } + if out.is_empty() { + return Err(qerror( + &[qloc[0], qloc[1], "over"], + "over must not be empty", + )); + } + // Sequence order, so the pooled range covers exactly these parts. + let ordered: Vec<&str> = roles + .iter() + .filter(|role| out.contains(role)) + .copied() + .collect(); + let target = match ordered.len() { + 1 => Value::String(ordered[0].into()), + _ => Value::Array( + ordered + .into_iter() + .map(|r| Value::String(r.into())) + .collect(), + ), + }; + Ok((target, range)) +} + +/// The full mapping. `state` and `questions` are the admitted request's +/// fields; validation runs in the pinned runtime's order so error +/// precedence matches. +pub fn system_one_to_predict( + state_parts: StateParts, + questions: &Map, +) -> Result { + if questions.is_empty() { + return Err(qerror( + &["questions"], + "questions must be a non-empty object of named questions", + )); + } + let roles: Vec<&str> = state_parts + .parts + .iter() + .map(|p| p.r#type.as_str()) + .collect(); + let mut predict = Vec::new(); + let mut plan = Vec::new(); + for (qid, question) in questions { + if qid.trim().is_empty() { + return Err(qerror( + &["questions"], + "question IDs must not be empty or whitespace", + )); + } + let Some(question) = question.as_object() else { + return Err(qerror( + &["questions", qid], + "a question must be an object with a type", + )); + }; + let loc = ["questions", qid]; + let kind = question.get("type").and_then(Value::as_str).unwrap_or(""); + if !SYSTEM_ONE_TYPES.contains(&kind) { + return Err(RequestError::envelope( + &[loc[0], loc[1], "type"], + "type must be one of ['noul', 'choice', 'score', 'span', 'set']", + "literal_error", + )); + } + let mut allowed: Vec<&str> = vec!["type", "instructions", "criteria", "over"]; + if kind == "span" || kind == "set" { + allowed.push("threshold"); + } + if kind == "span" { + allowed.push("head"); + } + let extra: Vec<&String> = question + .keys() + .filter(|key| !allowed.contains(&key.as_str())) + .collect(); + if let Some(first) = extra.first() { + return Err(RequestError::envelope( + &[loc[0], loc[1], first], + "Extra inputs are not permitted", + "extra_forbidden", + )); + } + let instructions = question.get("instructions").unwrap_or(&Value::Null); + if !nonblank(instructions) { + return Err(qerror( + &[loc[0], loc[1], "instructions"], + "instructions must not be empty or whitespace", + )); + } + let text = match instructions { + Value::Null => String::new(), + other => content_text(other), + }; + let criteria = question.get("criteria").unwrap_or(&Value::Null); + // Target part: the resolved `over`, the span default, or all parts. + let (target_part, range) = match question.get("over") { + Some(Value::Null) | None => { + if kind == "span" { + let role = if roles.contains(&"answer") { + "answer" + } else if roles.contains(&"user") { + "user" + } else { + roles[0] + }; + (Value::String(role.into()), None) + } else if roles.len() == 1 { + (Value::String(roles[0].into()), None) + } else { + ( + Value::Array(roles.iter().map(|r| Value::String((*r).into())).collect()), + None, + ) + } + } + Some(over) => resolve_over(over, &state_parts, &loc)?, + }; + let mut predict_question = PredictQuestion { + id: qid.clone(), + kind: kind.to_string(), + text: text.clone(), + target_part: target_part.clone(), + labels: None, + options: None, + threshold: None, + head: None, + }; + let mut plan_criteria = criteria.clone(); + match kind { + "noul" => { + if !criteria.is_null() + && (!criteria.is_object() + || criteria + .as_object() + .is_some_and(|map| map.keys().any(|k| k != "true" && k != "false"))) + { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "noul criteria is an object with optional true / false", + )); + } + let map = criteria.as_object().cloned().unwrap_or_default(); + for key in ["true", "false"] { + if let Some(value) = map.get(key) + && !nonblank(value) + { + return Err(qerror( + &[loc[0], loc[1], "criteria", key], + "Noul criterion must not be empty or whitespace", + )); + } + } + let no = match map.get("false") { + Some(Value::Null) | None => NOUL_DEFAULT_NO.to_string(), + Some(value) => content_text(value), + }; + let yes = match map.get("true") { + Some(Value::Null) | None => NOUL_DEFAULT_YES.to_string(), + Some(value) => content_text(value), + }; + predict_question.kind = "choice".into(); + predict_question.options = Some(serde_json::json!([ + {"name": "no", "description": no}, + {"name": "yes", "description": yes}, + ])); + } + "choice" | "set" | "span" => { + let (lo, hi) = if kind == "choice" { (2, 255) } else { (1, 255) }; + let Some(map) = criteria.as_object() else { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + &format!("{kind} criteria must be an object with {lo} to {hi} entries"), + )); + }; + if !(lo..=hi).contains(&map.len()) { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + &format!("{kind} criteria must be an object with {lo} to {hi} entries"), + )); + } + let mut named = Vec::new(); + for (name, value) in map { + if name.trim().is_empty() || !nonblank(value) { + return Err(qerror( + &[loc[0], loc[1], "criteria", name], + "option names and descriptions must not be empty or whitespace", + )); + } + let description = match value { + Value::Null => String::new(), + other => content_text(other), + }; + named.push(Named { + name: name.clone(), + description, + }); + } + if kind == "span" { + predict_question.labels = Some(named); + } else { + predict_question.options = Some(serde_json::to_value(&named).unwrap()); + } + } + _ => { + // score + let Some(levels) = criteria.as_array() else { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "score criteria must be a list of 2 to 10 levels", + )); + }; + if !(2..=10).contains(&levels.len()) { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "score criteria must be a list of 2 to 10 levels", + )); + } + let mut names = Vec::new(); + for (index, value) in levels.iter().enumerate() { + if value.is_null() || !nonblank(value) { + return Err(qerror( + &[loc[0], loc[1], "criteria", &index.to_string()], + "Score criterion must not be empty or whitespace", + )); + } + names.push(content_text(value)); + } + if names.iter().collect::>().len() != names.len() { + return Err(qerror( + &[loc[0], loc[1], "criteria"], + "score levels must be distinct", + )); + } + predict_question.options = Some(serde_json::to_value(&names).unwrap()); + } + } + if let Some(threshold) = question.get("threshold") + && !threshold.is_null() + { + match threshold.as_f64().filter(|_| threshold.is_number()) { + Some(value) if (0.0..=1.0).contains(&value) => { + predict_question.threshold = Some(value); + } + _ => { + return Err(qerror( + &[loc[0], loc[1], "threshold"], + "threshold must be a number in [0, 1]", + )); + } + } + } + if kind == "span" + && let Some(head) = question.get("head") + && !head.is_null() + { + match head.as_str() { + Some(value @ ("router" | "broad")) => { + predict_question.head = Some(value.to_string()); + } + _ => { + return Err(RequestError::envelope( + &[loc[0], loc[1], "head"], + "head must be one of ['router', 'broad']", + "literal_error", + )); + } + } + } + // Python's plan keeps `crit`; noul normalized null -> {} earlier. + if kind == "noul" && plan_criteria.is_null() { + plan_criteria = serde_json::json!({}); + } + predict.push(predict_question); + plan.push(PlanEntry { + qid: qid.clone(), + kind: kind.to_string(), + criteria: plan_criteria, + range, + part: target_part, + }); + } + // The Noul views of set labels must not overwrite a question. + for entry in &plan { + if entry.kind == "set" + && let Value::Object(map) = &entry.criteria + { + for label in map.keys() { + if questions.contains_key(&format!("{}.{}", entry.qid, label)) { + return Err(qerror( + &["questions", &format!("{}.{}", entry.qid, label)], + "collides with the Noul view of a set label", + )); + } + } + } + } + Ok(Mapped { + request: PredictRequest { + parts: state_parts.parts, + questions: predict, + }, + plan, + }) +} diff --git a/src/models/vela/native/src/render.rs b/src/models/vela/native/src/render.rs new file mode 100644 index 00000000..ed3d11fd --- /dev/null +++ b/src/models/vela/native/src/render.rs @@ -0,0 +1,794 @@ +//! Prompt rendering, mirroring the pinned runtime's `_prep` + `_render` +//! (the DEV2.0 decoder layout): the parts pass, per-question blocks +//! with option end and query positions, the span block in layout a/c +//! with word positions, the truncation budget, and the long-target +//! windows. Output structs serialize exactly like the frozen +//! `native-plan-*` fixtures. + +use std::cell::RefCell; +use std::collections::{HashMap, HashSet}; +use std::path::Path; + +use std::collections::BTreeMap; +use tokenizers::Tokenizer; + +use crate::contract::RequestError; +use crate::state::canonical; + +pub const SUFFIX_CHOICE_SCORE: &str = + "\n\nSelect the single option best supported by the context and instructions.\nDecision:"; +pub const SUFFIX_SET: &str = + "\n\nSelect every option supported by the context and instructions.\nDecision:"; +pub const SUFFIX_SPAN: &str = + "\n\nMark every span of the target text that carries one of the labels.\nSpans:"; +pub const ABS_KEY: &str = "[ABS]"; +pub const ABS_DESC: &str = "None of the shown options applies."; +pub const PARTS_HEAD: &str = "Context:\n"; +pub const SEG_CLOSE: &str = "\n\n"; +pub const TEXT_HEAD: &str = "\n\nText:\n"; +pub const HYBRID_RMAX: usize = 2048; +pub const WIN: usize = 1800; +pub const STRIDE: usize = 1536; +pub const RMAX: usize = 2048; + +pub const ROUTER_SPAN_IDS: [&str; 3] = ["pii", "halu", "toxic"]; +pub const HALU_LABEL: &str = "unsupported"; +pub const HALU_ALIASES: [&str; 9] = [ + "unsupported", + "unsupportedclaim", + "hallucinated", + "hallucination", + "hallucinatedspan", + "notsupported", + "unsupportedspan", + "fabricated", + "fabrication", +]; +pub const PII_TYPES: [&str; 17] = [ + "AGE", + "CREDIT_CARD", + "DATE_TIME", + "DOMAIN_NAME", + "EMAIL_ADDRESS", + "GPE", + "IBAN_CODE", + "IP_ADDRESS", + "NRP", + "ORGANIZATION", + "PERSON", + "PHONE_NUMBER", + "STREET_ADDRESS", + "TITLE", + "US_DRIVER_LICENSE", + "US_SSN", + "ZIP_CODE", +]; + +fn seg_open(role: &str) -> String { + format!("\n") +} + +fn option_block(key: &str, desc: &str, tag: &str) -> String { + format!( + "\n<{tag}>\n{}\n", + canonical(&serde_json::json!({"key": key, "description": desc})) + ) +} + +fn q_head(kind: &str, over: &[String], text: &str, span: bool) -> String { + let target = over.join(", "); + format!( + "\n\nTask type: {kind}\nTarget: {target}\nQuestion:\n{text}\n{}", + if span { "Labels:" } else { "Options:" } + ) +} + +// ------------------------------------------------------------------ tokenizer + +/// The pinned tokenizer, with the reference's memoized plain-`ids` view +/// and char-offset encodings (the tokenizers crate reports byte +/// offsets; the reference works in Unicode code points). +/// Ids plus char offsets, the encoder cache entry. +type Encoded = (Vec, Vec<(usize, usize)>); + +pub struct Encoder { + tokenizer: Tokenizer, + cache: RefCell>, +} + +impl Encoder { + pub fn load(path: &Path) -> anyhow::Result { + let tokenizer = Tokenizer::from_file(path).map_err(anyhow::Error::msg)?; + Ok(Self { + tokenizer, + cache: RefCell::new(HashMap::new()), + }) + } + + fn encode(&self, text: &str) -> (Vec, Vec<(usize, usize)>) { + if let Some(hit) = self.cache.borrow().get(text) { + return hit.clone(); + } + let encoding = match self.tokenizer.encode(text, false) { + Ok(encoding) => encoding, + Err(error) => { + // The pinned tokenizer should never fail on valid UTF-8 + // input; surface the error instead of panicking so a + // wrapping worker can map it. + unreachable!("the pinned tokenizer failed on valid input: {error}") + } + }; + let byte_offsets = encoding.get_offsets(); + // Byte → code-point offsets. + let char_starts: Vec = text + .char_indices() + .map(|(byte, _)| byte) + .chain(std::iter::once(text.len())) + .collect(); + let to_char = |byte: usize| char_starts.partition_point(|&start| start < byte); + let offsets: Vec<(usize, usize)> = byte_offsets + .iter() + .map(|(start, end)| (to_char(*start), to_char(*end))) + .collect(); + let entry = (encoding.get_ids().to_vec(), offsets); + self.cache + .borrow_mut() + .insert(text.to_owned(), entry.clone()); + entry + } + + /// Memoized token ids of a whole string (the reference's `_ids`). + pub fn ids(&self, text: &str) -> Vec { + self.encode(text).0 + } + + /// Ids and char offsets (the reference's `_ids_offs`). + pub fn ids_offsets(&self, text: &str) -> (Vec, Vec<(usize, usize)>) { + self.encode(text) + } +} + +// ------------------------------------------------------------- span dispatch + +/// `[\s_\-]+` removed, lower-cased — the reference's `_norm_label`. +pub fn norm_label(name: &str) -> String { + let mut out = String::with_capacity(name.len()); + for ch in name.chars() { + if !ch.is_whitespace() && ch != '_' && ch != '-' { + out.extend(ch.to_lowercase()); + } + } + out +} + +/// The user's label when the span question has exactly one label that +/// is a hallucination alias, else none. +pub fn halu_alias(names: &[String]) -> Option { + if names.len() == 1 && HALU_ALIASES.contains(&norm_label(&names[0]).as_str()) { + Some(names[0].clone()) + } else { + None + } +} + +pub struct SpanDispatch { + pub head: &'static str, + pub reason: &'static str, +} + +/// The reference's six-rule dispatch, in order: `"head"` override, +/// trained ids, an exact router label set, a non-empty subset of the 17 +/// PII types, one hallucination alias, else broad (router when the +/// broad head is not loaded). +pub fn span_head_for( + id: &str, + labels: &HashSet, + head_override: Option<&str>, + router_label_sets: &[HashSet], + broad_available: bool, +) -> Result { + if let Some(head) = head_override { + if !matches!(head, "router" | "broad") { + return Err(format!( + "head must be one of ['router', 'broad'], got '{head:?}'" + )); + } + if head == "broad" && !broad_available { + return Err("the broad span head is not loaded (needs broad_head.safetensors)".into()); + } + return Ok(SpanDispatch { + head: if head == "broad" { "broad" } else { "router" }, + reason: "override", + }); + } + if ROUTER_SPAN_IDS.contains(&id) { + return Ok(SpanDispatch { + head: "router", + reason: "id", + }); + } + if router_label_sets.iter().any(|set| set == labels) { + return Ok(SpanDispatch { + head: "router", + reason: "label_set", + }); + } + let pii: HashSet<&str> = PII_TYPES.into_iter().collect(); + if !labels.is_empty() && labels.iter().all(|label| pii.contains(label.as_str())) { + return Ok(SpanDispatch { + head: "router", + reason: "pii_subset", + }); + } + if halu_alias(&labels.iter().cloned().collect::>()).is_some() { + return Ok(SpanDispatch { + head: "router", + reason: "halu_alias", + }); + } + if !broad_available { + return Ok(SpanDispatch { + head: "router", + reason: "broad_unavailable", + }); + } + Ok(SpanDispatch { + head: "broad", + reason: "default", + }) +} + +// ------------------------------------------------------------------ rendering + +/// One generic-contract question at render time (Noul is already folded +/// into a two-option choice; choice always carries `[ABS]` on the +/// SystemOne path — the reference's `_to_generic` defaults abstain to +/// true and the mapper never sets it). +#[derive(Clone)] +pub struct GenericQuestion { + pub id: String, + pub kind: String, + pub over: Vec, + pub text: String, + pub names: Vec, + pub descriptions: Vec, + pub threshold: Option, + pub head_override: Option, +} + +/// One prepared part: tokens, and for span-target parts also char +/// offsets and word units. +/// Word char offsets and each word's first token index. +pub type WordUnits = (Vec<(usize, usize)>, Vec); + +#[derive(Clone)] +pub struct PreparedPart { + pub role: String, + pub ids: Vec, + pub offsets: Option>, + pub words: Option, +} + +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +pub struct TruncRecord { + pub shrink_cut: usize, + pub protected_cut: usize, +} + +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +#[serde(tag = "kind")] +pub enum Block { + #[serde(rename = "q")] + Question { + ids: Vec, + ends: Vec, + query: usize, + qid: String, + qtype: String, + names: Vec, + has_abs: bool, + }, + #[serde(rename = "span")] + Span { + ends: Vec, + label_ranges: Vec<(usize, usize)>, + words_in_block: bool, + ids: Vec, + query: usize, + w_pos: Vec, + }, +} + +#[derive(Debug, Clone, PartialEq)] +pub struct RenderedRow { + pub p_ids: Vec, + pub blocks: Vec, + pub trunc: TruncRecord, + pub seg_lens: BTreeMap, + pub layout: Option, + pub names: Option>, + pub w_offs: Option>, + pub w_pos: Option>, + pub span_over: Option, + pub n_tokens: usize, + pub head: String, + pub head_reason: Option, + /// The runtime's window rows carry the head only — no head_reason + /// key at all (predict_raw assigns head alone). + pub window: bool, +} + +/// Serialize exactly like the frozen fixtures: main rows always carry +/// `head_reason` (null when the row has no span); window rows omit it. +impl serde::Serialize for RenderedRow { + fn serialize(&self, serializer: S) -> Result + where + S: serde::Serializer, + { + serialize_row(self, serializer) + } +} + +fn serialize_row(row: &RenderedRow, serializer: S) -> Result +where + S: serde::Serializer, +{ + use serde::ser::SerializeMap; + let mut map = serializer.serialize_map(None)?; + macro_rules! put { + ($key:literal, $value:expr) => { + map.serialize_entry($key, &$value)? + }; + } + put!("p_ids", row.p_ids); + put!("blocks", row.blocks); + put!("trunc", row.trunc); + put!("seg_lens", row.seg_lens); + put!("layout", row.layout); + if let Some(names) = &row.names { + put!("names", names); + } + if let Some(w_offs) = &row.w_offs { + put!("w_offs", w_offs); + } + if let Some(w_pos) = &row.w_pos { + put!("w_pos", w_pos); + } + if let Some(span_over) = &row.span_over { + put!("span_over", span_over); + } + put!("n_tokens", row.n_tokens); + put!("head", row.head); + if !row.window { + put!("head_reason", row.head_reason); + } + map.end() +} + +/// Everything the renderer needs beyond tokens. +pub struct RenderContext<'a> { + pub encoder: &'a Encoder, + pub max_length: usize, + pub router_label_sets: &'a [HashSet], + pub has_broad: bool, + pub halu_desc: String, +} + +/// The whole-request 413: questions plus schema alone do not fit. +pub fn too_long(max_length: usize) -> RequestError { + RequestError { + status: 413, + body: serde_json::json!({"detail": [{"loc": ["body", "questions"], + "msg": format!("the questions alone do not fit the {max_length}-token window"), + "type": "too_long"}]}), + } +} + +/// `schema_lib_r4.assemble`, eval path: the truncation order on the +/// decoder's token costs. Returns kept segment lengths and the record. +fn assemble_budget( + q_lens: &[usize], + el_lens: &[usize], + segs: &mut [(String, usize)], + max_len: usize, + protected: &HashSet, + shrink: Option<&str>, +) -> Result<(BTreeMap, TruncRecord), ()> { + let fixed = 2 + 1 + segs.len(); + fn over( + q_lens: &[usize], + el_lens: &[usize], + segs: &[(String, usize)], + fixed: usize, + max_len: usize, + ) -> i64 { + fixed as i64 + + q_lens.iter().sum::() as i64 + + el_lens.iter().sum::() as i64 + + segs.iter().map(|(_, n)| *n).sum::() as i64 + - max_len as i64 + } + let mut trunc = TruncRecord { + shrink_cut: 0, + protected_cut: 0, + }; + let shrink_index = shrink.and_then(|role| segs.iter().position(|(r, _)| r == role)); + for floor in [64, 1] { + if over(q_lens, el_lens, segs, fixed, max_len) > 0 + && let Some(index) = shrink_index + { + let full = segs[index].1; + let excess = over(q_lens, el_lens, segs, fixed, max_len).max(0) as usize; + let keep = full.min(floor.max(full.saturating_sub(excess))); + trunc.shrink_cut += full - keep; + segs[index].1 = keep; + } + } + if over(q_lens, el_lens, segs, fixed, max_len) > 0 { + for index in 0..segs.len() { + if over(q_lens, el_lens, segs, fixed, max_len) > 0 && protected.contains(&segs[index].0) + { + let full = segs[index].1; + let excess = over(q_lens, el_lens, segs, fixed, max_len).max(0) as usize; + let keep = 1.max(full.saturating_sub(excess)); + trunc.protected_cut += full - keep; + segs[index].1 = keep; + } + } + } + if over(q_lens, el_lens, segs, fixed, max_len) > 0 { + return Err(()); + } + let seg_lens: BTreeMap = + segs.iter().map(|(role, n)| (role.clone(), *n)).collect(); + Ok((seg_lens, trunc)) +} + +/// Token windows [a, b) over a part of n tokens, starting and cut at +/// word starts (`schema_lib_d3_20261001.windows`). +pub fn span_windows(first_tokens: &[usize], n: usize) -> Vec<(usize, usize)> { + let mut starts: Vec = first_tokens.to_vec(); + starts.sort_unstable(); + starts.dedup(); + if starts.is_empty() { + return vec![(0, n)]; + } + let mut out = Vec::new(); + let mut a = starts[0]; + loop { + let limit = a + WIN; + let next: Vec = starts + .iter() + .copied() + .filter(|&s| s > a && s < limit) + .collect(); + let b = if limit >= n { + n + } else if !next.is_empty() { + *starts + .iter() + .filter(|&&s| s < limit && s > a) + .max() + .unwrap() + } else { + n.min(limit) + }; + out.push((a, b)); + if b >= n { + break; + } + let candidate: Vec = starts + .iter() + .copied() + .filter(|&s| s >= a + STRIDE && s < b) + .collect(); + a = candidate.first().copied().unwrap_or(b); + } + out +} + +/// A windowed copy of a prepared part: tokens [a, b) and the words that +/// start inside them. +pub fn window_part(part: &PreparedPart, a: usize, b: usize) -> PreparedPart { + let (word_offsets, first_tokens) = part.words.as_ref().expect("windowed parts carry words"); + let selected: Vec = first_tokens + .iter() + .enumerate() + .filter(|&(_, &t)| t >= a && t < b) + .map(|(index, _)| index) + .collect(); + let kept_offsets: Vec<(usize, usize)> = selected.iter().map(|&i| word_offsets[i]).collect(); + PreparedPart { + role: part.role.clone(), + ids: part.ids[a..b].to_vec(), + offsets: part.offsets.as_ref().map(|offs| offs[a..b].to_vec()), + words: Some(( + kept_offsets, + selected.iter().map(|&i| first_tokens[i] - a).collect(), + )), + } +} + +impl RenderContext<'_> { + /// `_prep`'s question side: the span-head dispatch and the + /// hallucination-alias label replacement (parts arrive prepared — + /// word units need the original text and are the caller's job). + pub fn prepare_questions( + &self, + questions: &[GenericQuestion], + ) -> Result<(Vec, SpanDispatch), RequestError> { + let span = questions.iter().find(|q| q.kind == "span"); + let dispatch = match span { + Some(question) => { + let labels: HashSet = question.names.iter().cloned().collect(); + span_head_for( + &question.id, + &labels, + question.head_override.as_deref(), + self.router_label_sets, + self.has_broad, + ) + .map_err(|message| crate::contract::runtime_rejection(&message))? + } + None => SpanDispatch { + head: "router", + reason: "", + }, + }; + // The trained `unsupported` label renders in place of a single + // hallucination-alias label (the answer gets the user's name). + let mut adjusted = questions.to_vec(); + if let Some(question) = adjusted.iter_mut().find(|q| q.kind == "span") + && dispatch.head == "router" + && let Some(alias) = halu_alias(&question.names) + && alias != HALU_LABEL + { + question.names = vec![HALU_LABEL.to_string()]; + question.descriptions = vec![self.halu_desc.clone()]; + } + Ok((adjusted, dispatch)) + } + + /// `_render` on one prepared row: the parts pass and every block, + /// with the budget applied first. + pub fn render( + &self, + parts: &[PreparedPart], + questions: &[GenericQuestion], + dispatch: &SpanDispatch, + ) -> Result { + let ids_of = |text: &str| self.encoder.ids(text); + let roles: Vec = parts.iter().map(|p| p.role.clone()).collect(); + // Question blocks and their schema costs. + struct RenderedQ { + qid: String, + qtype: String, + names: Vec, + otoks: Vec>, + has_abs: bool, + head: Vec, + suffix: Vec, + abstain_tokens: Vec, + len: usize, + } + let mut rendered_qs: Vec = Vec::new(); + let mut el: Vec<(String, Vec)> = Vec::new(); // span labels + let mut span_question: Option<&GenericQuestion> = None; + for question in questions { + if question.kind == "span" { + span_question = Some(question); + for (name, desc) in question.names.iter().zip(&question.descriptions) { + let tokens = ids_of(&option_block(name, desc, "label")); + el.push((name.clone(), tokens.clone())); + } + continue; + } + let suffix = match question.kind.as_str() { + "set" => SUFFIX_SET, + _ => SUFFIX_CHOICE_SCORE, // choice and score share the wording + }; + let has_abs = question.kind == "choice"; // SystemOne: abstain defaults true + let head = ids_of(&q_head( + &question.kind, + &question.over, + &question.text, + false, + )); + let suffix = ids_of(suffix); + let abstain_tokens = if has_abs { + ids_of(&option_block(ABS_KEY, ABS_DESC, "option")) + } else { + Vec::new() + }; + let mut otoks = Vec::with_capacity(question.names.len()); + let mut len = + 1 + head.len() + suffix.len() + abstain_tokens.len() + usize::from(has_abs); + for (name, desc) in question.names.iter().zip(&question.descriptions) { + let tokens = ids_of(&option_block(name, desc, "option")); + len += 1 + tokens.len(); + otoks.push(tokens); + } + rendered_qs.push(RenderedQ { + qid: question.id.clone(), + qtype: question.kind.clone(), + names: question.names.clone(), + otoks, + has_abs, + head, + suffix, + abstain_tokens, + len, + }); + } + let span_over: Option = span_question.map(|question| question.over[0].clone()); + let mut overs: HashSet = HashSet::new(); + for question in questions { + overs.extend(question.over.iter().cloned()); + } + if let Some(over) = &span_over { + overs.insert(over.clone()); + } + let part_of = |role: &str| parts.iter().find(|p| p.role == role); + let shrink = roles.iter().find(|role| !overs.contains(*role)).cloned(); + let layout = match &span_over { + Some(over) if part_of(over).is_some_and(|p| p.ids.len() <= HYBRID_RMAX) => "c", + Some(_) => "a", + None => "", + }; + // The schema overhead the budget does not see. + let mut budget = ids_of(PARTS_HEAD).len(); + for role in &roles { + budget += ids_of(&seg_open(role)).len() + ids_of(SEG_CLOSE).len(); + } + if let Some(over) = &span_over { + let question = span_question.expect("span question"); + let head = ids_of(&q_head("span", &question.over, &question.text, true)); + let suffix = ids_of(SUFFIX_SPAN); + budget += head.len() + suffix.len(); + if layout == "c" { + let span_len = part_of(over).expect("span part").ids.len(); + budget += ids_of(TEXT_HEAD).len() + + ids_of(&seg_open(over)).len() + + ids_of(SEG_CLOSE).len(); + let headroom = self.max_length.saturating_sub(budget); + budget += span_len.min(headroom / 2); + } + } + let q_lens: Vec = rendered_qs.iter().map(|q| q.len).collect(); + let el_lens: Vec = el.iter().map(|(_, tokens)| 1 + tokens.len()).collect(); + let mut segs: Vec<(String, usize)> = parts + .iter() + .map(|p| (p.role.clone(), p.ids.len())) + .collect(); + let (seg_lens, trunc) = assemble_budget( + &q_lens, + &el_lens, + &mut segs, + 64.max(self.max_length - budget), + &overs, + shrink.as_deref(), + ) + .map_err(|()| too_long(self.max_length))?; + // The parts pass, in part order (not the sorted map). + let mut p_ids = ids_of(PARTS_HEAD); + let mut start: HashMap = HashMap::new(); + for part in parts { + let keep = seg_lens[&part.role]; + let open = ids_of(&seg_open(&part.role)); + start.insert(part.role.clone(), p_ids.len() + open.len()); + p_ids.extend(open); + p_ids.extend(part.ids.iter().take(keep)); + p_ids.extend(ids_of(SEG_CLOSE)); + } + // Question blocks. + let mut blocks: Vec = Vec::new(); + for q in &rendered_qs { + let mut ids = q.head.clone(); + let mut ends = Vec::with_capacity(q.names.len() + usize::from(q.has_abs)); + for tokens in &q.otoks { + ids.extend(tokens); + ends.push(ids.len() - 1); + } + if q.has_abs { + ids.extend(q.abstain_tokens.clone()); + ends.push(ids.len() - 1); + } + ids.extend(q.suffix.clone()); + let query = ids.len() - 1; + blocks.push(Block::Question { + ids, + ends, + query, + qid: q.qid.clone(), + qtype: q.qtype.clone(), + names: q.names.clone(), + has_abs: q.has_abs, + }); + } + // The span block. + let mut row_names = None; + let mut row_w_offs = None; + let mut row_w_pos = None; + if let Some(over) = &span_over + && !el.is_empty() + { + let question = span_question.expect("span question"); + let mut ids = ids_of(&q_head("span", &question.over, &question.text, true)); + let mut ends = Vec::new(); + let mut starts = Vec::new(); + for (_, tokens) in &el { + starts.push(ids.len()); + ids.extend(tokens); + ends.push(ids.len() - 1); + } + let part = part_of(over).expect("span part"); + let n = seg_lens[over]; + let (word_offsets, first_tokens) = part.words.as_ref().expect("span words"); + // Word indices whose first token survives the kept prefix; + // indices, not token values — two words can share one. + let keep: Vec = first_tokens + .iter() + .enumerate() + .filter(|&(_, &t)| t < n) + .map(|(index, _)| index) + .collect(); + let words_in_block = layout == "c"; + if words_in_block { + ids.extend(ids_of(TEXT_HEAD)); + ids.extend(ids_of(&seg_open(over))); + let c0 = ids.len(); + ids.extend(part.ids.iter().take(n)); + ids.extend(ids_of(SEG_CLOSE)); + row_w_pos = Some(keep.iter().map(|&i| c0 + first_tokens[i]).collect()); + } else { + let base = start[over]; + row_w_pos = Some(keep.iter().map(|&i| base + first_tokens[i]).collect()); + } + ids.extend(ids_of(SUFFIX_SPAN)); + let query = ids.len() - 1; + row_names = Some(el.iter().map(|(name, _)| name.clone()).collect()); + row_w_offs = Some(keep.iter().map(|&i| word_offsets[i]).collect()); + let label_ranges: Vec<(usize, usize)> = + starts.into_iter().zip(ends.iter().copied()).collect(); + blocks.push(Block::Span { + ends, + label_ranges, + words_in_block, + ids, + query, + w_pos: row_w_pos.clone().expect("w_pos"), + }); + } + let n_tokens = p_ids.len() + blocks.iter().map(block_len).sum::(); + Ok(RenderedRow { + p_ids, + blocks, + trunc, + seg_lens, + layout: if span_over.is_some() { + Some(layout.to_string()) + } else { + None + }, + names: row_names, + w_offs: row_w_offs, + w_pos: row_w_pos, + span_over, + n_tokens, + head: dispatch.head.to_string(), + head_reason: if dispatch.reason.is_empty() { + None + } else { + Some(dispatch.reason.to_string()) + }, + window: false, + }) + } +} + +fn block_len(block: &Block) -> usize { + match block { + Block::Question { ids, .. } => ids.len(), + Block::Span { ids, .. } => ids.len(), + } +} diff --git a/src/models/vela/native/src/state.rs b/src/models/vela/native/src/state.rs new file mode 100644 index 00000000..d33e42bb --- /dev/null +++ b/src/models/vela/native/src/state.rs @@ -0,0 +1,235 @@ +//! DEV2.0 canonical JSON and the state → typed-parts mapping, mirroring +//! the pinned runtime's `canonical_json`, `content_text` and +//! `system_one_state` exactly (the frozen `native-plan-*` fixtures are +//! the parity target). + +use serde_json::Value; +use std::collections::BTreeMap; + +use crate::contract::RequestError; + +/// `json.dumps(ensure_ascii=False, sort_keys=True, separators=(",", ":"))` +/// — key-sorted compact JSON, non-ASCII literal. +pub fn canonical(value: &Value) -> String { + match value { + Value::Object(map) => { + let mut keys: Vec<&String> = map.keys().collect(); + keys.sort(); + let parts: Vec = keys + .iter() + .map(|key| { + format!( + "{}:{}", + serde_json::to_string(key).unwrap(), + canonical(&map[*key]) + ) + }) + .collect(); + format!("{{{}}}", parts.join(",")) + } + Value::Array(items) => { + let parts: Vec = items.iter().map(canonical).collect(); + format!("[{}]", parts.join(",")) + } + other => serde_json::to_string(other).unwrap(), + } +} + +/// JSON content → model text: strings as they are, anything else as +/// canonical JSON. +pub fn content_text(value: &Value) -> String { + match value { + Value::String(text) => text.clone(), + other => canonical(other), + } +} + +/// The state-key → part-role table (unknown keys land in `context`). +pub fn key_role(key: &str) -> &'static str { + match key.to_ascii_lowercase().as_str() { + "request" | "user" | "prompt" => "user", + "answer" | "response" => "answer", + _ => "context", + } +} + +/// One rendered state part, in user / context / answer order. +#[derive(Debug, Clone, serde::Serialize, PartialEq)] +pub struct Part { + pub r#type: String, + pub text: String, +} + +/// A named state field's span inside its part's text (Unicode code +/// points, as on the reference). +#[derive(Debug, Clone, Copy, PartialEq)] +pub struct FieldRange { + pub role: &'static str, + pub start: usize, + pub end: usize, +} + +#[derive(Debug)] +pub struct StateParts { + pub parts: Vec, + pub fields: BTreeMap, +} + +fn state_error(msg: &str) -> RequestError { + RequestError::envelope(&["state"], msg, "value_error") +} + +/// The SystemOne state → (parts, fields) mapping, mirroring +/// `system_one_state`: a plain string is one user part; a JSON array is +/// canonicalized into one; an object groups its keys by role (request / +/// user / prompt → user; source / context / document / tools / +/// previous_answer → context; answer / response → answer; unknown keys +/// → context) in user / context / answer order — one known-key entry +/// per role renders bare, several (or an unknown key) render as +/// `"key:\n"` blocks joined by blank lines. +pub fn system_one_state(state: &Value) -> Result { + // A string holding a JSON object is read as that object. + let state = match state { + Value::String(text) => { + let stripped = text.trim_start(); + if stripped.starts_with('{') { + if let Value::Object(object) = + serde_json::from_str::(stripped).unwrap_or(Value::Null) + { + Value::Object(object) + } else { + state.clone() + } + } else { + state.clone() + } + } + other => other.clone(), + }; + match &state { + Value::String(text) => { + if text.trim().is_empty() { + return Err(state_error("state must not be empty or whitespace")); + } + let mut fields = BTreeMap::new(); + fields.insert( + "request".into(), + FieldRange { + role: "user", + start: 0, + end: text.chars().count(), + }, + ); + Ok(StateParts { + parts: vec![Part { + r#type: "user".into(), + text: text.clone(), + }], + fields, + }) + } + Value::Array(_) => { + let text = canonical(&state); + let mut fields = BTreeMap::new(); + fields.insert( + "request".into(), + FieldRange { + role: "user", + start: 0, + end: text.chars().count(), + }, + ); + Ok(StateParts { + parts: vec![Part { + r#type: "user".into(), + text, + }], + fields, + }) + } + Value::Object(object) if !object.is_empty() => { + // Group per role, keeping the object's insertion order inside + // each role and remembering which entries had a known key. + let mut by_role: [Vec<(&String, &Value, bool)>; 3] = + [Vec::new(), Vec::new(), Vec::new()]; + for (key, value) in object { + let lower = key.to_ascii_lowercase(); + let known = matches!( + lower.as_str(), + "request" + | "user" + | "prompt" + | "source" + | "context" + | "document" + | "tools" + | "previous_answer" + | "answer" + | "response" + ); + let slot = match key_role(&lower) { + "user" => 0, + "answer" => 2, + _ => 1, + }; + by_role[slot].push((key, value, known)); + } + let mut parts = Vec::new(); + let mut fields = BTreeMap::new(); + for (role, items) in [ + ("user", &by_role[0]), + ("context", &by_role[1]), + ("answer", &by_role[2]), + ] { + if items.is_empty() { + continue; + } + let mut text = String::new(); + let single = items.len() == 1 && items[0].2; + for (index, (key, value, _)) in items.iter().enumerate() { + let rendered = content_text(value); + if single { + fields.insert( + (*key).clone(), + FieldRange { + role, + start: 0, + end: rendered.chars().count(), + }, + ); + text = rendered; + } else { + if index > 0 { + text.push_str("\n\n"); + } + let head = format!("{key}:\n"); + let start = text.chars().count() + head.chars().count(); + fields.insert( + (*key).clone(), + FieldRange { + role, + start, + end: start + rendered.chars().count(), + }, + ); + text.push_str(&head); + text.push_str(&rendered); + } + } + if text.trim().is_empty() { + return Err(state_error(&format!( + "the {role} part of the state is empty" + ))); + } + parts.push(Part { + r#type: role.into(), + text, + }); + } + Ok(StateParts { parts, fields }) + } + _ => Err(state_error( + "state must be a non-empty string, JSON object or JSON array", + )), + } +} diff --git a/src/models/vela/native/src/words.rs b/src/models/vela/native/src/words.rs new file mode 100644 index 00000000..c26dcac7 --- /dev/null +++ b/src/models/vela/native/src/words.rs @@ -0,0 +1,119 @@ +//! Word units and first-token mapping, mirroring the pinned runtime's +//! `schema_lib_r4` `_WORD` splitter (GLiNER2 whitespace splitter + CJK +//! one unit per character + the r4 URL/email/handle rule) and +//! `word_first_tokens`. Offsets are Unicode code points everywhere, as +//! on the reference. + +use onig::Regex; + +/// The CJK ranges of the reference `_WORD` pattern, verbatim. +const CJK: &str = "⺀-⿿　-〿぀-ヿ㄀-ㇿ㐀-䶿一-鿿ꀀ-꓏가-힯豈-﫿︰-﹏＀-￯"; +/// Trailing punctuation the URL rule strips. +const TRAIL: &str = ".,;:!?)\\]}>\"'\u{201d}\u{2019}\u{bb}"; + +fn word_pattern() -> Regex { + let pattern = concat!( + "(?:https?://|www\\.)[^\\s{cjk}]+?(?=[{trail}]*(?![^\\s{cjk}]))", + "|[a-z0-9._%+-]+@[a-z0-9.-]+\\.[a-z]{2,}", + "|@[a-z0-9_]+", + "|[{cjk}]", + "|[^\\W{cjk}]+(?:[-_][^\\W{cjk}]+)*", + "|\\S", + ); + let pattern = pattern.replace("{cjk}", CJK).replace("{trail}", TRAIL); + Regex::with_options( + &pattern, + onig::RegexOptions::REGEX_OPTION_IGNORECASE, + onig::Syntax::ruby(), + ) + .expect("the reference word pattern must compile") +} + +/// The (start, end) word ranges of `text`, in code points. +pub fn split_words(text: &str) -> Vec<(usize, usize)> { + let regex = word_pattern(); + // Byte offsets → code-point offsets. + let char_of_byte: Vec = text + .char_indices() + .map(|(byte, _)| byte) + .chain(std::iter::once(text.len())) + .collect(); + let to_char = |byte: usize| -> usize { char_of_byte.partition_point(|&start| start < byte) }; + regex + .find_iter(text) + .map(|(start, end)| (to_char(start), to_char(end))) + .collect() +} + +/// (word char offsets (W, 2), each word's first overlapping sub-word +/// token index), mirroring `word_first_tokens`: the first token whose +/// cumulative end passes the word start, skipping empty tokens. +pub fn word_first_tokens( + text: &str, + offsets: &[(usize, usize)], +) -> (Vec<(usize, usize)>, Vec) { + let words = split_words(text); + if words.is_empty() || offsets.is_empty() { + return (Vec::new(), Vec::new()); + } + let valid: Vec = offsets.iter().map(|(s, e)| e > s).collect(); + let mut cummax_end: Vec = Vec::with_capacity(offsets.len()); + let mut running: i64 = -1; + for (index, (_start, end)) in offsets.iter().enumerate() { + if valid[index] { + running = running.max(*end as i64); + } + cummax_end.push(running); + } + let mut word_offsets = Vec::new(); + let mut first_tokens = Vec::new(); + for (a, b) in words { + let mut t = cummax_end.partition_point(|&end| end <= a as i64); + while t < offsets.len() && !valid[t] { + t += 1; + } + if t < offsets.len() && offsets[t].0 < b { + word_offsets.push((a, b)); + first_tokens.push(t); + } + } + (word_offsets, first_tokens) +} + +/// The reference's CJK class as a range test (the same ranges the word +/// splitter carries). +pub fn is_cjk_char(ch: char) -> bool { + // The reference class has one contiguous run from U+8C48 to + // U+FAFF and ends the Yi block at U+A4CF (not U+A48F). + matches!(ch as u32, + 0x2E80..=0x2FFF | 0x3000..=0x303F | 0x3040..=0x30FF | 0x3100..=0x31FF + | 0x3400..=0x4DBF | 0x4E00..=0x9FFF | 0xA000..=0xA4CF | 0xAC00..=0xD7AF + | 0x8C48..=0xFAFF | 0xFE30..=0xFE4F | 0xFF00..=0xFFEF) +} + +/// The reference's `_UNIT` split (decode-time units): URL bodies, runs +/// of word characters (excluding CJK, `_` excluded by `[^\W_]`) plus +/// `@._-+`, or any non-space char. Returns each char's unit id, -1 +/// outside units — the decode's `u` array. +pub fn unit_ids(chars: &[char]) -> Vec { + let mut ids = vec![-1i64; chars.len()]; + let text: String = chars.iter().collect(); + let pattern = concat!( + "(?:https?://|www\\.)[^\\s\\]\\)\\}>「」『』\"'“”{cjk}]+?(?=[.,;:!?]*(?![^\\s\\]\\)\\}>「」『』\"'“”{cjk}]))", + "|(?:(?![{cjk}])[^\\W_]|[@._\\-+])+", + "|\\S", + ) + .replace("{cjk}", CJK); + let regex = Regex::with_options( + &pattern, + onig::RegexOptions::REGEX_OPTION_IGNORECASE, + onig::Syntax::ruby(), + ) + .expect("the reference unit pattern must compile"); + for (unit, (start, end)) in regex.find_iter(&text).enumerate() { + for id in ids.iter_mut().take(end).skip(start) { + *id = unit as i64; + } + } + ids +} diff --git a/tests/vela/native_contract_unit.rs b/tests/vela/native_contract_unit.rs new file mode 100644 index 00000000..e2a60834 --- /dev/null +++ b/tests/vela/native_contract_unit.rs @@ -0,0 +1,14 @@ +//! Private-item tests for the native crate's wire contract, loaded by +//! the `#[path]` wiring in `src/models/vela/native/src/contract.rs`. + +use super::*; + +#[test] +fn duplicate_keys_mirror_the_reference_message() { + let error = normalize_parse_error("request body is not valid JSON: duplicate key \"state\""); + assert_eq!(error.status, 400); + assert_eq!( + error.body, + serde_json::json!({"detail": "duplicate JSON key 'state'"}) + ); +} diff --git a/tests/vela/native_processing.rs b/tests/vela/native_processing.rs new file mode 100644 index 00000000..917a423c --- /dev/null +++ b/tests/vela/native_processing.rs @@ -0,0 +1,137 @@ +//! Processing tests against the frozen token-plan fixtures. +//! +//! The mapping tests (state → parts, SystemOne → predict, plan) run +//! everywhere with no tokenizer and no weights. The full render parity +//! — rows and window rows byte-for-byte against the fixtures — needs +//! the exported bundle's tokenizer and is opt-in: +//! +//! VELA_NATIVE_BUNDLE=weights/vela-2.0-0.8b-native \ +//! cargo test -p omni-vela-native --test vela_native_processing -- --nocapture + +use std::path::PathBuf; + +use omni_vela_native::questions::system_one_to_predict; +use omni_vela_native::state::system_one_state; +use serde_json::Value; + +const CASES: [&str; 5] = [ + "example-request", + "example-request-set-threshold", + "example-request-cjk", + "example-request-score", + "long-span-windowed", +]; + +fn fixture(case: &str) -> Value { + let root = PathBuf::from(env!("CARGO_MANIFEST_DIR")).join("../../../../tests/vela/fixtures"); + serde_json::from_str( + &std::fs::read_to_string(root.join(format!("native-plan-{case}.json"))) + .expect("fixture present; record it with recipe/vela/export_token_plan.py"), + ) + .expect("fixture JSON") +} + +// ------------------------------------------------------- mapping (no tokens) + +fn mapped(case: &str) -> Value { + let fix = fixture(case); + let request = fix["request"].as_object().expect("request"); + let state = system_one_state(&request["state"]).expect("state maps"); + let questions = request["questions"].as_object().expect("questions"); + let mapped = system_one_to_predict(state, questions).expect("maps"); + serde_json::json!({ + "predict_request": serde_json::to_value(&mapped.request).unwrap(), + "plan": serde_json::to_value(&mapped.plan).unwrap(), + }) +} + +#[test] +fn the_predict_mapping_matches_every_fixture() { + for case in CASES { + let got = mapped(case); + let fix = fixture(case); + assert_eq!( + got["predict_request"], fix["predict_request"], + "predict_request differs for {case}" + ); + assert_eq!(got["plan"], fix["plan"], "plan differs for {case}"); + } +} + +#[test] +fn an_invalid_question_reports_the_pinned_triples() { + let state = system_one_state(&serde_json::json!("s")).expect("state"); + let questions = serde_json::json!({ + "q": {"type": "choice", "instructions": "ok?", "criteria": {"a": "x"}} + }); + let error = system_one_to_predict(state, questions.as_object().unwrap()).unwrap_err(); + assert_eq!( + error.body, + serde_json::json!({"detail": [{"loc": ["body", "questions", "q", "criteria"], + "msg": "choice criteria must be an object with 2 to 255 entries", "type": "value_error"}]}) + ); + + let state = system_one_state(&serde_json::json!("s")).expect("state"); + let questions = serde_json::json!({ + "q": {"type": "span", "instructions": "which?", "criteria": {"a": "x"}, + "head": "other", "over": "request"} + }); + let error = system_one_to_predict(state, questions.as_object().unwrap()).unwrap_err(); + assert_eq!( + error.body["detail"][0]["loc"], + serde_json::json!(["body", "questions", "q", "head"]) + ); + assert_eq!(error.body["detail"][0]["type"], "literal_error"); +} + +#[test] +fn a_set_label_collision_is_rejected_after_the_walk() { + let state = system_one_state(&serde_json::json!("s")).expect("state"); + let questions = serde_json::json!({ + "issues": {"type": "set", "instructions": "which?", "criteria": {"billing": "b"}}, + "issues.billing": {"type": "noul", "instructions": "which?"} + }); + let error = system_one_to_predict(state, questions.as_object().unwrap()).unwrap_err(); + assert_eq!( + error.body["detail"][0]["msg"], + "collides with the Noul view of a set label" + ); +} + +// ------------------------------------------------- full render (opt-in) + +fn bundle_dir() -> Option { + let value = std::env::var("VELA_NATIVE_BUNDLE").ok()?; + let path = PathBuf::from(value); + path.is_dir().then_some(path) +} + +#[test] +fn the_rendered_rows_match_every_fixture() { + let Some(bundle) = bundle_dir() else { + eprintln!("skipping: set VELA_NATIVE_BUNDLE to an exported bundle for render parity"); + return; + }; + let processor = omni_vela_native::processing::Processor::load(&bundle) + .expect("processor loads the exported bundle"); + for case in CASES { + let fix = fixture(case); + let request = fix["request"].as_object().expect("request"); + let planned = match processor.plan(request) { + Ok(planned) => planned, + Err(error) => panic!( + "plan failed for {case}: {}", + serde_json::to_string(&error.body).unwrap() + ), + }; + let got = serde_json::json!({ + "rows": serde_json::to_value(&planned.rows).unwrap(), + "window_rows": serde_json::to_value(&planned.window_rows).unwrap(), + }); + assert_eq!(got["rows"], fix["rows"], "rows differ for {case}"); + assert_eq!( + got["window_rows"], fix["window_rows"], + "window rows differ for {case}" + ); + } +} diff --git a/tests/vela/native_units.rs b/tests/vela/native_units.rs new file mode 100644 index 00000000..e117fdea --- /dev/null +++ b/tests/vela/native_units.rs @@ -0,0 +1,97 @@ +//! Unit tests for the native crate's state mapping and word splitter, +//! extracted from the modules per the repository's test-placement +//! rule (the private contract test lives in native_contract_unit.rs, +//! loaded by the `#[path]` wiring in contract.rs). + +use omni_vela_native::state::system_one_state; +use omni_vela_native::words::{split_words, word_first_tokens}; +use serde_json::json; + +// ------------------------------------------------------------- state + +#[test] +fn a_plain_string_is_one_user_part() { + let parts = system_one_state(&json!("hello")).expect("parts"); + assert_eq!(parts.parts.len(), 1); + assert_eq!(parts.parts[0].r#type, "user"); + assert_eq!(parts.fields["request"].end, 5); +} + +#[test] +fn typed_keys_group_into_ordered_parts_with_field_ranges() { + let parts = system_one_state(&json!({ + "answer": "A", "request": "R", "source": "S", "extra": "E", + })) + .expect("parts"); + let roles: Vec<&str> = parts.parts.iter().map(|p| p.r#type.as_str()).collect(); + assert_eq!(roles, ["user", "context", "answer"]); + let context = &parts.parts[1]; + assert_eq!(context.text, "source:\nS\n\nextra:\nE"); + assert_eq!(parts.fields["source"].start, "source:\n".chars().count()); + assert_eq!( + parts.fields["extra"].start, + "source:\nS\n\nextra:\n".chars().count() + ); +} + +#[test] +fn an_empty_role_part_is_rejected() { + let error = system_one_state(&json!({"request": " "})).unwrap_err(); + assert_eq!( + error.body["detail"][0]["msg"], + serde_json::json!("the user part of the state is empty") + ); +} + +#[test] +fn a_string_holding_a_json_object_is_read_as_that_object() { + let parts = system_one_state(&json!("{\"request\": \"text\"}")).expect("parts"); + assert_eq!(parts.parts.len(), 1); + assert_eq!(parts.fields["request"].end, 4); +} + +// ------------------------------------------------------------- words + +#[test] +fn words_split_like_the_reference() { + let text = "Hi, I'm Tom Baker (tom.baker@example.com)."; + let words: Vec = split_words(text) + .iter() + .map(|(a, b)| text.chars().skip(*a).take(b - a).collect()) + .collect(); + assert_eq!( + words, + vec![ + "Hi", + ",", + "I", + "'", + "m", + "Tom", + "Baker", + "(", + "tom.baker@example.com", + ")", + "." + ] + ); +} + +#[test] +fn cjk_characters_are_one_unit_each() { + let text = "追踪 parcel 仓库"; + let words: Vec = split_words(text) + .iter() + .map(|(a, b)| text.chars().skip(*a).take(b - a).collect()) + .collect(); + assert_eq!(words, vec!["追", "踪", "parcel", "仓", "库"]); +} + +#[test] +fn first_tokens_skip_empty_tokens() { + let text = "alpha beta"; + let offsets = vec![(0, 0), (0, 5), (6, 10)]; + let (word_offsets, first) = word_first_tokens(text, &offsets); + assert_eq!(word_offsets, vec![(0, 5), (6, 10)]); + assert_eq!(first, vec![1, 2]); +} From dd5064a3a44c60691e52ef5322c030d53d0a3fa9 Mon Sep 17 00:00:00 2001 From: "Mr.Dong" <1042542469@qq.com> Date: Sun, 25 Oct 2026 02:36:06 +0800 Subject: [PATCH 04/32] vela: add the 0.8B native F32 heads, scoring and span decoding MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - heads.rs: CandidateHead (option-end + query hiddens; bilinear + scalar-MLP, [ABS] last), both SpanHeadV2 instances (router and the side-loaded broad head) and set_bias, loaded from the exported bundle's heads.safetensors — plain float32, the reference's own autocast-off setting (erf-based GELU via libm). - scoring.rs: the calibration mirror — per-type temperatures, set thresholds, the PII length rule (log-space interp) and sparse gate, span thresholds by id/label set, softmax/sigmoid, span_decode_r4 (word units, unit vote, fill, edge/URL trim), label aliasing, score value normalization (i/(n-1)), and the window aggregation (mean over covering windows, -30 uncovered). - recipe/vela/export_head_inputs.py and the recorded head-input fixtures: the reference's consumed hidden states, its head logits and its calibrated predict answers for the five frozen cases. Opt-in parity (VELA_NATIVE_BUNDLE): five cases, head-logit drift <= 3.8e-5, predict-answer drift <= 7.3e-7 (the windowed long-span case exact), discrete picks, span structures and threshold rules equal. --- Cargo.lock | 2 + README.md | 2 +- docs/supported-models.md | 2 +- recipe/vela/export_head_inputs.py | 226 +++++++ recipe/vela/native.md | 38 +- src/models/vela/README.md | 16 +- src/models/vela/native/Cargo.toml | 8 +- src/models/vela/native/src/heads.rs | 286 ++++++++ src/models/vela/native/src/lib.rs | 2 + src/models/vela/native/src/scoring.rs | 631 ++++++++++++++++++ .../head-input-example-request-cjk.json | 1 + ...head-input-example-request-cjk.safetensors | Bin 0 -> 254408 bytes .../head-input-example-request-score.json | 1 + ...ad-input-example-request-score.safetensors | Bin 0 -> 41112 bytes ...d-input-example-request-set-threshold.json | 1 + ...-example-request-set-threshold.safetensors | Bin 0 -> 16536 bytes .../fixtures/head-input-example-request.json | 1 + .../head-input-example-request.safetensors | Bin 0 -> 299464 bytes .../head-input-long-span-windowed.json | 1 + .../head-input-long-span-windowed.safetensors | Bin 0 -> 15213024 bytes tests/vela/native_heads.rs | 401 +++++++++++ 21 files changed, 1603 insertions(+), 16 deletions(-) create mode 100644 recipe/vela/export_head_inputs.py create mode 100644 src/models/vela/native/src/heads.rs create mode 100644 src/models/vela/native/src/scoring.rs create mode 100644 tests/vela/fixtures/head-input-example-request-cjk.json create mode 100644 tests/vela/fixtures/head-input-example-request-cjk.safetensors create mode 100644 tests/vela/fixtures/head-input-example-request-score.json create mode 100644 tests/vela/fixtures/head-input-example-request-score.safetensors create mode 100644 tests/vela/fixtures/head-input-example-request-set-threshold.json create mode 100644 tests/vela/fixtures/head-input-example-request-set-threshold.safetensors create mode 100644 tests/vela/fixtures/head-input-example-request.json create mode 100644 tests/vela/fixtures/head-input-example-request.safetensors create mode 100644 tests/vela/fixtures/head-input-long-span-windowed.json create mode 100644 tests/vela/fixtures/head-input-long-span-windowed.safetensors create mode 100644 tests/vela/native_heads.rs diff --git a/Cargo.lock b/Cargo.lock index bd63bd1c..97dcd635 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -1294,8 +1294,10 @@ name = "omni-vela-native" version = "0.1.0" dependencies = [ "anyhow", + "libm", "omni-qwen3-5-native", "onig", + "safetensors 0.8.0", "serde", "serde_json", "sha2 0.11.1", diff --git a/README.md b/README.md index a68b0fd2..6444de28 100644 --- a/README.md +++ b/README.md @@ -183,7 +183,7 @@ extensions) on each checkpoint's own pinned runtime: | OmniJev-4B v1.1 | [Checkpoint export and CPU contract](recipe/omnijev/README.md) only; the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | | D3 (Decision 3.0) | [Python reference worker](recipe/d3/reference.md) on the checkpoint's pinned runtime; `choice`/`noul`/`score` text state, media inputs refused; author-run on A100 (evidence in the integration PR) | | Vela 2.0 0.3B | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; all five kinds (`choice`/`noul`/`score`/`span`/`set`) for text state; CPU FP32 validated (author-run, evidence in the integration PR) | -| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; [native library](recipe/vela/native.md) (bundle export, wire contract, token-level processing); CPU FP32 parity recorded in the integration PR | +| Vela 2.0 0.8B hybrid | [Python reference worker](recipe/vela/reference.md) on the checkpoint's pinned runtime; same surface plus `span_heads`; [native library](recipe/vela/native.md) (bundle export, wire contract, processing, F32 heads); CPU FP32 parity recorded in the integration PR | [Supported models and hardware](docs/supported-models.md) lists the devices and where each worker has been run. diff --git a/docs/supported-models.md b/docs/supported-models.md index 399ea09a..6c07f6ab 100644 --- a/docs/supported-models.md +++ b/docs/supported-models.md @@ -25,7 +25,7 @@ Models that are being added are also tracked in issues labeled [new model](https | OmniJev-4B v1.1 | None yet: [checkpoint export and CPU contract](../recipe/omnijev/README.md); the native worker is in progress ([#114](https://github.com/ThinkFlowLab/system1-omni/issues/114)) | Request contract, preparation, heads and finishing checked against the reference ([#120](https://github.com/ThinkFlowLab/system1-omni/pull/120)); no inference | Not yet | Not supported | Python 3.10 reference environment for the export and fixtures | | D3 (Decision 3.0) | [Python reference worker](../recipe/d3/reference.md) running the checkpoint's pinned runtime | Unverified | Author-run on NVIDIA A100 (sm_80): three-kind serving smoke with byte-identical frontend forwarding and reference parity (exact decisions, max delta 0.0, 348 == 348 tokens); evidence in the integration PR. Owner: @MrDongsls. | Unverified | Python 3.12, the [pinned runtime requirements](../recipe/d3/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/d3) (~52 GB) | | Vela 2.0 0.3B | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime | **CPU FP32 validated** (author-run, x86 WSL2, 24 cores): startup with all-kind warmup, the four example requests plus five synthetic rejections, and exact-match reference parity against the pinned upstream server on all nine (four 200s byte-equal incl. key order, agreed 422/413); byte-identical frontend forwarding; evidence in the integration PR. Owner: @MrDongsls. | Unverified (bf16-autocast is an untested deployment option) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.3B) (1.24 GB FP32 weights; ~4.4 GB with ONNX/assets) | -| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B); [native library](../recipe/vela/native.md) — bundle export, wire contract, token-level processing | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | +| Vela 2.0 0.8B hybrid | [Python reference worker](../recipe/vela/reference.md) running the checkpoint's pinned runtime (same wire layer as 0.3B); [native library](../recipe/vela/native.md) — bundle export, wire contract, processing, F32 heads and scoring | Same surface as 0.3B plus the `span_heads` field (router/broad dispatch); **CPU FP32 parity** (author-run; evidence in the integration PR) | Unverified (bf16-autocast is the evaluated upstream setting but untested here) | Not supported | Python 3.12, the [pinned requirements](../recipe/vela/requirements.txt), the [pinned package](https://huggingface.co/vllm-sr/Vela-2.0-0.8B) (2.02 GB shard + 4.5 MB broad head; ~3 GB FP32 parameters) | - **Validated:** covered by the recipe on `main` or by the checks in the linked merged pull request. - **Author-run:** recorded by the recipe author on the stated hardware and not independently reproduced; the row names its owner. diff --git a/recipe/vela/export_head_inputs.py b/recipe/vela/export_head_inputs.py new file mode 100644 index 00000000..625eadd0 --- /dev/null +++ b/recipe/vela/export_head_inputs.py @@ -0,0 +1,226 @@ +#!/usr/bin/env python3 +"""Freeze the head inputs/outputs of the pinned Vela 2.0 0.8B runtime. + +Records, per frozen case, exactly what +the two F32 heads consume and produce — CandidateHead (option-end +hidden states + the block query hidden) and SpanHeadV2 (word hidden +states + label-mean hiddens), on CPU FP32 with autocast off (the +heads' own setting, bit-deterministic) — so the Rust heads and the +scoring/decode mirror are checked against these without any GPU. Also +records the reference's calibrated predict answers for the same cases +(the scoring target). Hidden matrices go to a per-case safetensors +file; structure, small logits and answers go to JSON next to it. + + PYTHONPATH=src .venv/bin/python recipe/vela/export_head_inputs.py \ + --model weights/vela-2.0-0.8b --out tests/vela/fixtures/ +""" + +from __future__ import annotations + +import argparse +import json +import sys +from pathlib import Path + +import numpy as np +from safetensors.numpy import save_file + +HERE = Path(__file__).resolve().parent +MODEL_NAME = "vllm-sr/Vela-2.0-0.8B" + + + +def parse_args(argv=None): + parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) + parser.add_argument("--model", required=True, help="pinned Vela 2.0 0.8B package directory") + parser.add_argument("--out", default=None, help="fixture output directory") + return parser.parse_args(argv) + + +def long_span_body(): + filler = " ".join(f"Sentence {i} reports a routine delivery event." for i in range(220)) + return { + "model": MODEL_NAME, + "state": {"request": filler}, + "questions": { + "claims": { + "type": "span", + "instructions": "Which spans mention a delivery?", + "criteria": {"delivery": "a delivery event"}, + "over": "request", + } + }, + } + + +def cases(): + named = [ + ("example-request", HERE / "example-request.json"), + ("example-request-set-threshold", HERE / "example-request-set-threshold.json"), + ("example-request-cjk", HERE / "example-request-cjk.json"), + ("example-request-score", HERE / "example-request-score.json"), + ] + loaded = [ + (name, {**json.loads(path.read_text(encoding="utf-8")), "model": MODEL_NAME}) + for name, path in named + ] + loaded.append(("long-span-windowed", long_span_body())) + return loaded + + +def plain(value): + if isinstance(value, dict): + return {key: plain(item) for key, item in value.items()} + if isinstance(value, (list, tuple)): + return [plain(item) for item in value] + if isinstance(value, np.ndarray): + return plain(value.tolist()) + if isinstance(value, (np.integer,)): + return int(value) + if isinstance(value, (np.floating,)): + return float(value) + if isinstance(value, (np.bool_,)): + return bool(value) + return value + + +class Recorder: + """Class-level wrappers around the two heads; records inputs/outputs.""" + + def __init__(self, module, model): + self.calls: list[dict] = [] + self.tensors: dict[str, np.ndarray] = {} + self._on = False + # Tensor names must never collide across rows: the counter keeps + # growing for the whole case. + self.next_index = 0 + self.module = module + self.model = model + original_head = module.CandidateHead.forward + original_span = module.SpanHeadV2.forward + recorder = self + + def head_forward(self, candidates, query): + out = original_head(self, candidates, query) + if recorder._on: + index = recorder.next_index + cname, qname = f"q{index}_cand", f"q{index}_query" + recorder.tensors[cname] = candidates.detach().cpu().numpy().astype(np.float32) + recorder.tensors[qname] = query.detach().cpu().numpy().astype(np.float32) + recorder.next_index = index + 1 + recorder.calls.append( + dict(kind="q", cand=cname, query=qname, + logits=[row.tolist() for row in out.detach().cpu().numpy()]) + ) + return out + + def span_forward(self, words, labels): + out = original_span(self, words, labels) + if recorder._on: + index = recorder.next_index + wname, lname = f"s{index}_words", f"s{index}_labels" + which = "broad" if self is getattr(recorder.model, "span_broad", None) else "router" + recorder.tensors[wname] = words.detach().cpu().numpy().astype(np.float32) + recorder.tensors[lname] = labels.detach().cpu().numpy().astype(np.float32) + recorder.next_index = index + 1 + recorder.calls.append( + dict(kind="span", head=which, words=wname, labels=lname, + logits=out.detach().cpu().numpy().tolist()) + ) + return out + + module.CandidateHead.forward = head_forward + module.SpanHeadV2.forward = span_forward + + +def rows_of(engine, body): + from vela2_inference import system_one_to_predict + + req, plan = system_one_to_predict(body["state"], body["questions"]) + parts, qs, _thr = engine._to_generic(req) + spans = [q for q in qs if q["type"] == "span"] + rest = [q for q in qs if q["type"] != "span"] + rows = [dict(parts=parts, questions=rest + spans[:1])] + [ + dict(parts=parts, questions=[s]) for s in spans[1:] + ] + rendered, preps, windows = [], [], [] + for row in rows: + if not row["questions"]: + continue + prepped = engine._prep(row) + rec = engine._render(prepped) + rec["head"] = prepped["head"] + rec["head_reason"] = prepped["head_reason"] + rec["label_alias"] = plain(prepped.get("label_alias")) + preps.append(prepped) + rendered.append(rec) + for wrow in engine._window_rows(prepped) or []: + wrec = engine._render(wrow) + wrec["head"] = prepped["head"] + windows.append(wrec) + return req, plan, rendered, windows + + +def main(argv=None) -> int: + args = parse_args(argv) + sys.path.insert(0, str(Path(args.model).resolve())) + from vela2_inference import Vela2 + + engine = Vela2.from_pretrained(args.model, backend="torch", device="cpu") + import modeling_vela2 + + recorder = Recorder(modeling_vela2, engine.run.model) + out = Path(args.out) if args.out else HERE.parents[1] / "tests" / "vela" / "fixtures" + out.mkdir(parents=True, exist_ok=True) + + for name, body in cases(): + req, plan, rows, windows = rows_of(engine, body) + # One row per backend call so every recorded head call is + # attributable; question blocks arrive stacked in row order. + calls = [] + tensors: dict[str, np.ndarray] = {} + recorder.calls = [] + recorder.tensors = {} + recorder.next_index = 0 + recorder._on = True + row_of_call: list[int] = [] + try: + for index, rec in enumerate(rows + windows): + # Windows render after the main rows (row index continues). + engine.run([rec]) + for call in recorder.calls: + row_of_call.append(index) + calls.extend(recorder.calls) + tensors.update(recorder.tensors) + recorder.calls = [] + # The reference's calibrated answers for the same request. + predict = plain(engine._predict(req)[0]) + finally: + recorder._on = False + for call, row in zip(calls, row_of_call): + call["row"] = row + save_file(tensors, str(out / f"head-input-{name}.safetensors")) + fixture = { + "case": name, + "request": body, + # The rows block carries the span-head dispatch and alias + # provenance for human inspection; the tests read the + # rendered rows from the native-plan fixtures. + "rows": [ + {key: rec[key] for key in ("head", "head_reason", "label_alias", "n_tokens", "seg_lens") + if key in rec} + for rec in rows + ], + "head_calls": calls, + "predict": predict, + } + (out / f"head-input-{name}.json").write_text( + json.dumps(fixture, ensure_ascii=False) + "\n", encoding="utf-8" + ) + span_calls = sum(1 for call in calls if call["kind"] == "span") + print(f"{name}: {len(rows)} row(s), {len(calls)} head call(s) ({span_calls} span), predict answers: {len(predict['answers'])}") + return 0 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/recipe/vela/native.md b/recipe/vela/native.md index 4c3cefa3..dda168fa 100644 --- a/recipe/vela/native.md +++ b/recipe/vela/native.md @@ -18,6 +18,13 @@ PYTHONPATH=src .venv/bin/python recipe/vela/export_native.py \ --package weights/vela-2.0-0.8b --out weights/vela-2.0-0.8b-native ~~~ +The backbone that executes on CUDA is a uniform-BF16 re-save (every +backbone tensor rounds once at export); the reference's own GPU setting +runs the backbone under bf16 autocast but keeps norm weights and GDN +gate math in FP32, so the uniform export is a slightly lower-precision +profile than either the CPU-FP32 recording or the reference GPU path. +The Vela heads stay F32 on the faithful tensors. + The export re-runs the reference worker's package gate first (provenance), then writes `weights/vela-2.0-0.8b-native/`: the backbone re-keyed `backbone.` → `model.` with **per-tensor dtypes preserved** @@ -34,13 +41,17 @@ SHA-256. ~~~sh PYTHONPATH=src .venv/bin/python recipe/vela/export_token_plan.py \ --model weights/vela-2.0-0.8b --out tests/vela/fixtures/ +PYTHONPATH=src .venv/bin/python recipe/vela/export_head_inputs.py \ + --model weights/vela-2.0-0.8b --out tests/vela/fixtures/ ~~~ The token plans record what the pinned runtime feeds the backbone (the predict mapping, the per-row decomposition, the rendered `p_ids`, blocks and readout positions, truncation, a windowed long-span case). The example-request token plan totals 1,041 tokens, matching the -oracle fixture's `usage.input_tokens`. +oracle fixture's `usage.input_tokens`. The head inputs record the +hidden states the F32 heads consume, the heads' logits and the +calibrated predict answers. ## Checks @@ -49,14 +60,18 @@ cargo test -p omni-vela-native cargo fmt --all --check cargo clippy -p omni-vela-native --all-targets -- -D warnings VELA_NATIVE_BUNDLE="$PWD/weights/vela-2.0-0.8b-native" \ - cargo test -p omni-vela-native --test vela_native_processing -- --nocapture + cargo test -p omni-vela-native --test vela_native_processing \ + --test vela_native_heads -- --nocapture ~~~ -26 tests run everywhere with no weights and no GPU: the wire contract +27 tests run everywhere with no weights and no GPU: the wire contract against the pinned runtime's 422/400 bodies, the bundle manifest gate, and the predict-mapping/plan parity on every frozen fixture. The -opt-in render check replays the five token plans through the Rust -processing field-for-field. For a field-level diff of one case: +opt-in checks replay the fixtures through the Rust implementation: + +- render parity — the token plans match field-for-field (5/5); +- head parity — head-logit drift <= 3.8e-5, predict-answer drift + <= 7.3e-7, discrete picks and span structures equal (5/5). For a field-level diff of one case: ~~~sh VELA_NATIVE_BUNDLE="$PWD/weights/vela-2.0-0.8b-native" \ @@ -66,8 +81,11 @@ VELA_NATIVE_BUNDLE="$PWD/weights/vela-2.0-0.8b-native" \ ## Scope and limits - Implemented: the bundle export + manifest gate, the wire admission, - and the token-level processing (state mapping, predict mapping with - the validation triples, word units, span-head dispatch, the DEV2.0 - rendering, the truncation budget, window rows). -- Not implemented: the F32 heads, scoring and span decoding, backbone - execution, and an HTTP worker. No performance claims are made. + the token-level processing (state mapping, predict mapping with the + validation triples, word units, span-head dispatch, the DEV2.0 + rendering, the truncation budget, window rows), and the F32 heads + with scoring and span decoding (CandidateHead, both SpanHeadV2 + heads, set_bias, temperatures, the PII length rule and sparse gate, + `span_decode_r4`, label aliasing, window aggregation). +- Not implemented: backbone execution and an HTTP worker. No + performance claims are made. diff --git a/src/models/vela/README.md b/src/models/vela/README.md index 92fc4f82..fdca780a 100644 --- a/src/models/vela/README.md +++ b/src/models/vela/README.md @@ -258,7 +258,17 @@ The native implementation lives in [`native/`](native/) as the the long-target window rows. All five frozen token plans (`tests/vela/fixtures/native-plan-*.json`) match field-for-field. -The F32 heads, scoring, backbone execution and an HTTP worker are not -implemented. Checks: `cargo test -p omni-vela-native` (26 tests, no -weights, no GPU; render parity opt-in with `VELA_NATIVE_BUNDLE`; see +- `native/src/{heads,scoring}.rs` are the F32 heads and the scoring + path: CandidateHead, both SpanHeadV2 heads, `set_bias`, the + per-type temperatures, set thresholds, the PII length rule and + sparse gate, `span_decode_r4` (word units, unit vote, fill, + edge/URL trimming), label aliasing, score normalization and the + window aggregation. Replaying the recorded head-input fixtures + (`tests/vela/fixtures/head-input-*`): head-logit drift ≤ 3.8e-5, + predict-answer drift ≤ 7.3e-7, discrete picks and span structures + equal on all five cases. + +Backbone execution and an HTTP worker are not implemented. Checks: +`cargo test -p omni-vela-native` (27 tests, no weights, no GPU; +render and head parity opt-in with `VELA_NATIVE_BUNDLE`; see [recipe/vela/native.md](../../recipe/vela/native.md)). diff --git a/src/models/vela/native/Cargo.toml b/src/models/vela/native/Cargo.toml index 40308a34..753acb62 100644 --- a/src/models/vela/native/Cargo.toml +++ b/src/models/vela/native/Cargo.toml @@ -3,10 +3,12 @@ name = "omni-vela-native" version = "0.1.0" edition = "2024" publish = false -description = "Native library for vllm-sr/Vela-2.0-0.8B: bundle gate, wire contract and token-level processing" +description = "Native library for vllm-sr/Vela-2.0-0.8B: bundle gate, wire contract, processing, F32 heads and scoring" [dependencies] anyhow = "1.0.100" +libm = "0.2" +safetensors = "0.8.0" onig = { package = "onig", version = "6", default-features = false } omni-qwen3-5-native = { path = "../../qwen3_5/native" } serde = { version = "1", features = ["derive"] } @@ -35,3 +37,7 @@ path = "../../../../tests/vela/native_processing.rs" [[test]] name = "vela_native_units" path = "../../../../tests/vela/native_units.rs" + +[[test]] +name = "vela_native_heads" +path = "../../../../tests/vela/native_heads.rs" diff --git a/src/models/vela/native/src/heads.rs b/src/models/vela/native/src/heads.rs new file mode 100644 index 00000000..1381d555 --- /dev/null +++ b/src/models/vela/native/src/heads.rs @@ -0,0 +1,286 @@ +//! The Vela-owned F32 heads, mirrored from the checkpoint's +//! `CandidateHead` and `SpanHeadV2` (the reference computes both with +//! autocast disabled, in float32 — deterministic math). Tensors load +//! from the exported bundle's `heads.safetensors` (37 F32 tensors: +//! CandidateHead, `set_bias`, the router `span2.*` and the side-loaded +//! `span_broad.*`). + +use std::path::Path; + +use anyhow::{Context, Result, ensure}; +use safetensors::SafeTensors; + +const HIDDEN: usize = 1024; +const HEAD_DIM: usize = 256; + +fn gelu(x: f32) -> f32 { + 0.5 * x * (1.0 + libm::erff(x / std::f32::consts::SQRT_2)) +} + +/// One `Linear`: weights row-major `[out, in]`, optional bias. +struct Linear { + weight: Vec, + bias: Option>, + out: usize, + input: usize, +} + +impl Linear { + fn apply(&self, x: &[f32]) -> Vec { + debug_assert_eq!(x.len(), self.input); + let mut out = vec![0.0; self.out]; + for (row, slot) in out.iter_mut().enumerate() { + let mut sum = self.bias.as_ref().map_or(0.0, |b| b[row]); + let base = row * self.input; + for (index, value) in x.iter().enumerate() { + sum += self.weight[base + index] * value; + } + *slot = sum; + } + out + } +} + +/// One `LayerNorm` over the hidden vector (PyTorch defaults, eps 1e-5). +struct LayerNorm { + weight: Vec, + bias: Vec, +} + +impl LayerNorm { + fn apply(&self, x: &[f32]) -> Vec { + let n = x.len() as f32; + let mean = x.iter().sum::() / n; + let var = x.iter().map(|v| (v - mean) * (v - mean)).sum::() / n; + let inv = 1.0 / (var + 1e-5).sqrt(); + x.iter() + .enumerate() + .map(|(i, v)| (v - mean) * inv * self.weight[i] + self.bias[i]) + .collect() + } +} + +/// `SpanHeadV2` (router `span2.*` or broad `span_broad.*`). +pub struct SpanHead { + word_norm: LayerNorm, + label_norm: LayerNorm, + slot: Vec, // [slots, hidden] + slots: usize, + d: usize, + k: Linear, + q: Linear, + m: Linear, + n: Linear, + v: Linear, +} + +impl SpanHead { + /// score (W, L): words (W, H) raw states, labels (L, H) block means. + pub fn forward(&self, words: &[Vec], labels: &[Vec]) -> Vec> { + let mut w: Vec> = words.iter().map(|row| self.word_norm.apply(row)).collect(); + // Per-column mean over the words, subtracted. + if !w.is_empty() { + let mut mean = vec![0.0f32; HIDDEN]; + for row in &w { + for (i, value) in row.iter().enumerate() { + mean[i] += value; + } + } + for value in mean.iter_mut() { + *value /= w.len() as f32; + } + for row in w.iter_mut() { + for (i, value) in row.iter_mut().enumerate() { + *value -= mean[i]; + } + } + } + // Label states: normalized + slot embedding, mean-centered when + // two or more labels. + let mut e: Vec> = labels + .iter() + .enumerate() + .map(|(index, row)| { + let mut state = self.label_norm.apply(row); + let slot = index.min(self.slots - 1); + let base = slot * HIDDEN; + for (i, value) in state.iter_mut().enumerate() { + *value += self.slot[base + i]; + } + state + }) + .collect(); + if e.len() >= 2 { + let mut mean = vec![0.0f32; HIDDEN]; + for row in &e { + for (i, value) in row.iter().enumerate() { + mean[i] += value; + } + } + for value in mean.iter_mut() { + *value /= e.len() as f32; + } + for row in e.iter_mut() { + for (i, value) in row.iter_mut().enumerate() { + *value -= mean[i]; + } + } + } + let scale = 1.0 / (self.d as f32).sqrt(); + let k: Vec> = w.iter().map(|row| self.k.apply(row)).collect(); + let q: Vec> = e.iter().map(|row| self.q.apply(row)).collect(); + let m_rows: Vec> = w.iter().map(|row| self.m.apply(row)).collect(); + let n_rows: Vec> = e.iter().map(|row| self.n.apply(row)).collect(); + w.iter() + .enumerate() + .map(|(wi, _)| { + (0..labels.len()) + .map(|li| { + let mut bil = 0.0f32; + for (a, b) in k[wi].iter().zip(&q[li]) { + bil += a * b; + } + bil *= scale; + let mut summed = vec![0.0f32; HEAD_DIM]; + for (index, value) in summed.iter_mut().enumerate() { + *value = gelu(m_rows[wi][index] + n_rows[li][index]); + } + let mut score = 0.0f32; + for (index, value) in summed.iter().enumerate() { + score += self.v.weight[index] * value; + } + bil + score + }) + .collect() + }) + .collect() + } +} + +/// The two heads plus `set_bias`, loaded from one safetensors file. +pub struct Heads { + candidate_norm: LayerNorm, + query_norm: LayerNorm, + key: Linear, + query: Linear, + candidate_mlp: Linear, + query_mlp: Linear, + scalar: Linear, + pub set_bias: f32, + pub router: SpanHead, + pub broad: SpanHead, +} + +fn tensor<'a>(file: &'a SafeTensors<'a>, name: &str) -> Result> { + let view = file + .tensor(name) + .with_context(|| format!("heads.safetensors is missing {name}"))?; + ensure!( + view.dtype() == safetensors::Dtype::F32, + "{name} must be F32" + ); + Ok(view + .data() + .as_chunks::<4>() + .0 + .iter() + .map(|chunk| f32::from_le_bytes(*chunk)) + .collect()) +} + +fn linear(file: &SafeTensors, prefix: &str, bias: bool, input: usize) -> Result { + let weight = tensor(file, &format!("{prefix}.weight"))?; + let out = weight.len() / input; + ensure!( + weight.len() % input == 0 && out > 0, + "{prefix}.weight shape" + ); + Ok(Linear { + weight, + bias: if bias { + Some(tensor(file, &format!("{prefix}.bias"))?) + } else { + None + }, + out, + input, + }) +} + +fn norm(file: &SafeTensors, prefix: &str) -> Result { + Ok(LayerNorm { + weight: tensor(file, &format!("{prefix}.weight"))?, + bias: tensor(file, &format!("{prefix}.bias"))?, + }) +} + +fn span_head(file: &SafeTensors, prefix: &str, d: usize, slots: usize) -> Result { + let slot = tensor(file, &format!("{prefix}.slot.weight"))?; + Ok(SpanHead { + word_norm: norm(file, &format!("{prefix}.wn"))?, + label_norm: norm(file, &format!("{prefix}.ln"))?, + slots, + slot, + d, + k: linear(file, &format!("{prefix}.K"), false, HIDDEN)?, + q: linear(file, &format!("{prefix}.Q"), false, HIDDEN)?, + m: linear(file, &format!("{prefix}.M"), true, HIDDEN)?, + n: linear(file, &format!("{prefix}.N"), false, HIDDEN)?, + v: linear(file, &format!("{prefix}.v"), false, HEAD_DIM)?, + }) +} + +impl Heads { + pub fn load(bundle: &Path) -> Result { + let raw = std::fs::read(bundle.join("heads.safetensors")).context("heads.safetensors")?; + let file = SafeTensors::deserialize(&raw).context("heads.safetensors must parse")?; + let set_bias = tensor(&file, "set_bias")?; + ensure!(set_bias.len() == 1, "set_bias is a scalar"); + // The span-head geometry ships in the manifest's calibration + // (d 256, slots 64 for this member). + Ok(Self { + candidate_norm: norm(&file, "head.candidate_norm")?, + query_norm: norm(&file, "head.query_norm")?, + key: linear(&file, "head.key", false, HIDDEN)?, + query: linear(&file, "head.query", false, HIDDEN)?, + candidate_mlp: linear(&file, "head.candidate_mlp", true, HIDDEN)?, + query_mlp: linear(&file, "head.query_mlp", false, HIDDEN)?, + scalar: linear(&file, "head.scalar", false, HEAD_DIM)?, + set_bias: set_bias[0], + router: span_head(&file, "span2", HEAD_DIM, 64)?, + broad: span_head(&file, "span_broad", HEAD_DIM, 64)?, + }) + } + + /// CandidateHead: option-end hiddens (W, H) and the block's query + /// hidden (H) -> one logit per option (plus `[ABS]` last when the + /// row carries it — the caller slices). + pub fn forward_candidate(&self, candidates: &[Vec], query: &[f32]) -> Vec { + let global_query = self.query_norm.apply(query); + let q_proj = self.query.apply(&global_query); + let q_mlp = self.query_mlp.apply(&global_query); + let scale = 1.0 / (HEAD_DIM as f32).sqrt(); + candidates + .iter() + .map(|row| { + let candidate = self.candidate_norm.apply(row); + let key = self.key.apply(&candidate); + let mut bilinear = 0.0f32; + for (a, b) in key.iter().zip(&q_proj) { + bilinear += a * b; + } + bilinear *= scale; + let mlp = self.candidate_mlp.apply(&candidate); + let mut summed = vec![0.0f32; HEAD_DIM]; + for (index, value) in summed.iter_mut().enumerate() { + *value = gelu(mlp[index] + q_mlp[index]); + } + let mut nonlinear = 0.0f32; + for (index, value) in summed.iter().enumerate() { + nonlinear += self.scalar.weight[index] * value; + } + bilinear + nonlinear + }) + .collect() + } +} diff --git a/src/models/vela/native/src/lib.rs b/src/models/vela/native/src/lib.rs index 1d849284..3221eeb1 100644 --- a/src/models/vela/native/src/lib.rs +++ b/src/models/vela/native/src/lib.rs @@ -6,8 +6,10 @@ pub mod bundle; pub mod contract; +pub mod heads; pub mod processing; pub mod questions; pub mod render; +pub mod scoring; pub mod state; pub mod words; diff --git a/src/models/vela/native/src/scoring.rs b/src/models/vela/native/src/scoring.rs new file mode 100644 index 00000000..e13fba9e --- /dev/null +++ b/src/models/vela/native/src/scoring.rs @@ -0,0 +1,631 @@ +//! The scoring and decode mirror of the pinned runtime's calibration +//! path (`calibrated`, `span_threshold`, the PII length rule and sparse +//! gate, `span_decode_r4.decode_v2`, `_trim`), turning head logits into +//! predict-level answers. Parity target: the `head-input-*.json` +//! fixtures' `predict.answers`. + + +use serde_json::Value; + +/// The package's `calibration.json` as typed lookup. +pub struct Calibration { + pub data: Value, +} + +pub fn softmax(x: &[f64]) -> Vec { + let max = x.iter().copied().fold(f64::NEG_INFINITY, f64::max); + let e: Vec = x.iter().map(|v| (v - max).exp()).collect(); + let sum: f64 = e.iter().sum(); + e.iter().map(|v| v / sum).collect() +} + +pub fn sigmoid(x: f64) -> f64 { + 1.0 / (1.0 + (-x).exp()) +} + +impl Calibration { + pub fn load(bundle: &std::path::Path) -> anyhow::Result { + Ok(Self { + data: serde_json::from_slice(&std::fs::read(bundle.join("calibration.json"))?)?, + }) + } + + fn temperature(&self, qtype: &str) -> f64 { + self.data["temperature"] + .get(qtype) + .and_then(Value::as_f64) + .unwrap_or(1.0) + } + + pub fn span_temperature(&self, head: &str) -> f64 { + if head == "broad" { + self.data["broad_head"]["temperature"] + .as_f64() + .unwrap_or(1.0) + } else { + self.temperature("span") + } + } + + fn is_pii(&self, qid: &str, names: &[String]) -> bool { + if qid == "pii" { + return true; + } + let types: Vec<&str> = self.data["pii_types"] + .as_array() + .map(|a| a.iter().filter_map(Value::as_str).collect()) + .unwrap_or_default(); + !names.is_empty() && names.iter().all(|n| types.contains(&n.as_str())) + } + + /// log-space piecewise-linear between anchors, constant outside. + fn pii_length_threshold(&self, n_tokens: usize) -> f64 { + let anchors = self.data["pii_length_rule"]["anchors"] + .as_array() + .cloned() + .unwrap_or_default(); + let mut points: Vec<(f64, f64)> = anchors + .iter() + .map(|a| { + ( + a["n_tokens"].as_f64().unwrap_or(1.0).ln(), + a["threshold"].as_f64().unwrap_or(1.0).ln(), + ) + }) + .collect(); + points.sort_by(|a, b| a.0.partial_cmp(&b.0).unwrap()); + let x = (n_tokens.max(1) as f64).ln(); + let (xs, ys): (Vec, Vec) = points.into_iter().unzip(); + interp(&xs, &ys, x).exp() + } + + /// The span threshold and its rule string, before the sparse gate. + pub fn span_threshold( + &self, + qid: &str, + names: &[String], + n_tokens: usize, + head: &str, + ) -> (f64, String) { + if head == "broad" { + return ( + self.data["broad_head"]["threshold"].as_f64().unwrap_or(0.5), + "broad".into(), + ); + } + let th = &self.data["thresholds"]; + if self.is_pii(qid, names) { + if self + .data + .get("pii_length_rule") + .is_some_and(|v| !v.is_null()) + { + return (self.pii_length_threshold(n_tokens), "pii:length".into()); + } + for bucket in self.data["pii_buckets"] + .as_array() + .cloned() + .unwrap_or_default() + { + if n_tokens as f64 <= bucket["max_tokens"].as_f64().unwrap_or(f64::INFINITY) { + return ( + bucket["threshold"].as_f64().unwrap_or(0.5), + format!("pii:{}", bucket["name"].as_str().unwrap_or("")), + ); + } + } + } + for fam in ["halu", "toxic"] { + if qid == fam { + return ( + th[&format!("span:{fam}")].as_f64().unwrap_or(0.5), + fam.into(), + ); + } + } + let specific = format!("span:{qid}"); + if th.get(&specific).is_some() { + (th[&specific].as_f64().unwrap_or(0.5), specific) + } else { + (th["span:*"].as_f64().unwrap_or(0.5), "span:*".into()) + } + } + + pub fn set_threshold(&self, qid: &str) -> f64 { + let th = &self.data["thresholds"]; + th.get(format!("set:{qid}")) + .or_else(|| th.get("set:*")) + .and_then(Value::as_f64) + .unwrap_or(0.5) + } + + /// The PII sparse gate (disabled when K < 0; second decode pass + /// over the same probabilities). + pub fn sparse_gate( + &self, + probs: &[Vec], + offs: &[(usize, usize)], + names: &[String], + text: &str, + thr: f64, + rule: &str, + ) -> (f64, String) { + let gate = &self.data["pii_sparse_gate"]; + let k = gate["K"].as_i64().unwrap_or(-1); + if k < 0 || thr >= gate["t_sparse"].as_f64().unwrap_or(f64::INFINITY) || offs.is_empty() { + return (thr, rule.into()); + } + let probe = gate["probe_threshold"].as_f64().unwrap_or(0.5); + let decoded = decode_spans(probs, offs, names, text, probe); + if decoded.len() as i64 <= k { + ( + gate["t_sparse"].as_f64().unwrap_or(thr), + format!("{rule}+sparse"), + ) + } else { + (thr, rule.into()) + } + } +} + +/// numpy.interp: linear between points, constant outside. +fn interp(xs: &[f64], ys: &[f64], x: f64) -> f64 { + if xs.is_empty() { + return f64::NAN; + } + if x <= xs[0] { + return ys[0]; + } + if x >= xs[xs.len() - 1] { + return ys[ys.len() - 1]; + } + for i in 0..xs.len() - 1 { + if x >= xs[i] && x <= xs[i + 1] { + let t = (x - xs[i]) / (xs[i + 1] - xs[i]); + return ys[i] + t * (ys[i + 1] - ys[i]); + } + } + ys[ys.len() - 1] +} + +// ------------------------------------------------------------ span decoding + +const EDGE: &str = "[](){}<>「」『』【】《》〈》\"'“”‘’«»‹›"; +const URL_TRAIL: &str = ".,;:!?)"; + +fn is_cjk(ch: char) -> bool { + // The reference's CJK class; same ranges as the word splitter. + super::words::is_cjk_char(ch) +} + +fn trim_edges(text: &[char], s: &mut usize, e: &mut usize) { + while *s < *e && (text[*s].is_whitespace() || EDGE.contains(text[*s])) { + *s += 1; + } + while *e > *s && (text[*e - 1].is_whitespace() || EDGE.contains(text[*e - 1])) { + *e -= 1; + } +} + +fn trim_url(text: &[char], s: &mut usize, e: &mut usize) { + // (?:https?://|www\.) at s, case-insensitive. + // The reference regex matches against the full text from s; the + // lookahead is not bounded by the span end. + let head: String = text[*s..(*s + 8).min(text.len())].iter().collect(); + let is_url = { + let lower = head.to_lowercase(); + lower.starts_with("http://") || lower.starts_with("https://") || lower.starts_with("www.") + }; + if !is_url { + return; + } + if let Some(pos) = text[*s..*e].iter().position(|&c| is_cjk(c)) { + *e = *s + pos; + } + while *e > *s + && (URL_TRAIL.contains(text[*e - 1]) + || EDGE.contains(text[*e - 1]) + || text[*e - 1].is_whitespace()) + { + *e -= 1; + } +} + +fn trim(text: &[char], s: usize, e: usize) -> (usize, usize) { + let (mut s, mut e) = (s, e); + trim_edges(text, &mut s, &mut e); + trim_url(text, &mut s, &mut e); + (s, e) +} + +/// `span_decode_r4.decode_v2` with the scorer's arguments +/// (extend=false, trim, no bridge, unit vote + fill on). +#[allow(clippy::too_many_arguments)] +pub fn decode_spans( + probs: &[Vec], + offs: &[(usize, usize)], + names: &[String], + text: &str, + thr: f64, +) -> Vec { + let chars: Vec = text.chars().collect(); + let t_count = offs.len(); + if t_count == 0 { + return Vec::new(); + } + let valid: Vec = offs.iter().map(|(a, b)| b > a).collect(); + let mut lab = vec![-1i64; t_count]; + for t in 0..t_count { + let (k, pk) = argmax(&probs[t]); + if valid[t] && pk as f64 > thr { + lab[t] = k as i64; + } + } + // Unit ids over the text (the reference's `_UNIT`), then per-word + // first-nonspace lookup and alnum test. + let units = super::words::unit_ids(&chars); + let mut tu = vec![-1i64; t_count]; + let mut alnum = vec![false; t_count]; + for t in 0..t_count { + if !valid[t] { + continue; + } + let (a, b) = offs[t]; + let mut f = a; + while f < b && chars[f].is_whitespace() { + f += 1; + } + tu[t] = if f < b && f < chars.len() { + units[f] + } else { + -1 + }; + alnum[t] = chars[a..b].iter().any(|&c| is_alnum(c)); + } + // Unit vote + fill, per run of the same unit. + let mut t = 0; + while t < t_count { + if tu[t] < 0 { + t += 1; + continue; + } + let mut t2 = t; + while t2 + 1 < t_count && (tu[t2 + 1] == tu[t] || !valid[t2 + 1]) { + t2 += 1; + } + let idx: Vec = (t..=t2).filter(|&i| valid[i]).collect(); + let labeled: Vec = idx.iter().copied().filter(|&i| lab[i] >= 0).collect(); + if !labeled.is_empty() { + let distinct: Vec = { + let mut d: Vec = labeled.iter().map(|&i| lab[i]).collect(); + d.sort_unstable(); + d.dedup(); + d + }; + if distinct.len() > 1 { + // The reference picks the first strict maximum in + // labeled-token order; accumulate in a Vec keyed by + // first occurrence, not a HashMap (whose iteration + // order would make ties nondeterministic). + let mut order: Vec = Vec::new(); + let mut scores: Vec = Vec::new(); + for &i in &labeled { + let label = lab[i]; + match order.iter().position(|&l| l == label) { + Some(index) => scores[index] += probs[i][label as usize] as f64, + None => { + order.push(label); + scores.push(probs[i][label as usize] as f64); + } + } + } + let mut winner_index = 0usize; + for (index, score) in scores.iter().enumerate().skip(1) { + if *score > scores[winner_index] { + winner_index = index; + } + } + let winner = order[winner_index]; + for &i in &labeled { + lab[i] = winner; + } + } + let labels: Vec = { + let mut d: Vec = labeled.iter().map(|&i| lab[i]).collect(); + d.sort_unstable(); + d.dedup(); + d + }; + for c in labels { + let pos: Vec = labeled.iter().copied().filter(|&i| lab[i] == c).collect(); + for &i in &idx { + if pos[0] < i && i < pos[pos.len() - 1] && lab[i] < 0 { + lab[i] = c; + } + } + } + } + t = t2 + 1; + } + // Merge consecutive same-label words into spans, trim, mean prob. + let mut spans: Vec<(i64, usize, usize, Vec)> = Vec::new(); + for t in 0..t_count { + if !valid[t] { + continue; + } + let c = lab[t]; + if let Some(last) = spans.last_mut() + && c == last.0 + { + last.2 = offs[t].1; + last.3.push(t); + continue; + } + if c >= 0 { + spans.push((c, offs[t].0, offs[t].1, vec![t])); + } + } + let mut out = Vec::new(); + for (c, s, e, ts) in spans { + let (s, e) = trim(&chars, s, e); + if e <= s { + continue; + } + let mean = ts.iter().map(|&t| probs[t][c as usize] as f64).sum::() / ts.len() as f64; + out.push(serde_json::json!({ + "start": s, "end": e, + "label": names[c as usize], + "probability": mean, + })); + } + out +} + +fn argmax(row: &[f32]) -> (usize, f32) { + let mut best = 0usize; + let mut value = f32::NEG_INFINITY; + for (index, item) in row.iter().enumerate() { + if *item > value { + value = *item; + best = index; + } + } + (best, value) +} + +fn is_alnum(c: char) -> bool { + // The reference's `_ALNUM` = [^\W_]: word characters minus the + // underscore — Rust's alphanumeric already excludes it. + c.is_alphanumeric() +} + +// -------------------------------------------------------- answer assembly + +/// One scored question block: the reference's `raw["qs"]` entry. +pub struct QBlock { + pub qid: String, + pub qtype: String, + pub names: Vec, + pub has_abs: bool, + /// Logits over `names` (plus `[ABS]` last when `has_abs`), + /// **after** run_batch's `set_bias` addition for set blocks. + pub logits: Vec, +} + +/// One scored span: the reference's `raw["span"]` (post aggregation). +pub struct SpanOut { + pub qid: String, + pub over: String, + pub names: Vec, + pub offs: Vec<(usize, usize)>, + pub logits: Vec>, + pub head: String, + pub head_reason: Option, + pub label_alias: Option, + /// The span part's kept token count (the PII length-rule input). + pub n_tokens: usize, +} + +/// `calibrated` for one row: logits -> predict-level answers. +pub fn row_answers( + cal: &Calibration, + blocks: &[QBlock], + span: Option<&SpanOut>, + thresholds: &std::collections::HashMap, + span_text: Option<&str>, +) -> Vec { + let mut answers = Vec::new(); + for block in blocks { + let logits: Vec = block.logits.iter().map(|v| *v as f64).collect(); + let n = block.names.len(); + let temperature = cal.temperature(&block.qtype); + if block.qtype == "set" { + let p: Vec = logits[..n] + .iter() + .map(|v| sigmoid(v / temperature)) + .collect(); + let thr = thresholds + .get(&block.qid) + .copied() + .unwrap_or_else(|| cal.set_threshold(&block.qid)); + let probs: serde_json::Map = block + .names + .iter() + .zip(&p) + .map(|(name, value)| (name.clone(), json_f64(*value))) + .collect(); + let selected: Vec<&String> = block + .names + .iter() + .zip(&p) + .filter(|(_, value)| **value > thr) + .map(|(name, _)| name) + .collect(); + answers.push(serde_json::json!({ + "id": block.qid, "type": "set", + "answer": selected, + "probabilities": probs, + "threshold": thr, + })); + continue; + } + let p = softmax( + &logits[..n] + .iter() + .map(|v| v / temperature) + .collect::>(), + ); + let answer = block.names[argmax_usize(&logits[..n])].clone(); + let probs: serde_json::Map = block + .names + .iter() + .zip(&p) + .map(|(name, value)| (name.clone(), json_f64(*value))) + .collect(); + let mut entry = serde_json::json!({ + "id": block.qid, "type": block.qtype, + "answer": answer, + "probabilities": probs, + }); + if block.has_abs { + let full = softmax(&logits.iter().map(|v| v / temperature).collect::>()); + entry["abstain_probability"] = json_f64(full[full.len() - 1]); + } + if block.qtype == "score" { + let expected: f64 = p.iter().enumerate().map(|(i, v)| i as f64 * v).sum(); + entry["expected_index"] = json_f64(expected); + // The default values normalize the levels to 0..1 + // (i / (n-1)); the SystemOne path never passes explicit ones. + let n = p.len(); + let score: f64 = p + .iter() + .enumerate() + .map(|(i, v)| { + // The reference's default values: i/(n-1), or 0 for + // a single level (never NaN). + let value = if n > 1 { + i as f64 / (n - 1) as f64 + } else { + 0.0 + }; + value * v + }) + .sum(); + entry["score"] = json_f64(score); + } + answers.push(entry); + } + if let Some(span) = span { + let text = span_text.unwrap_or(""); + let head = span.head.as_str(); + // The per-question override wins over the calibrated rule. + let (mut thr, mut rule) = match thresholds.get(&span.qid) { + Some(given) => (*given, "given".to_string()), + None => cal.span_threshold(&span.qid, &span.names, span.n_tokens, head), + }; + let temperature = cal.span_temperature(head); + let probs: Vec> = span + .logits + .iter() + .map(|row| { + row.iter() + .map(|v| sigmoid(*v as f64 / temperature) as f32) + .collect() + }) + .collect(); + if rule.starts_with("pii:") { + let (gated, gated_rule) = + cal.sparse_gate(&probs, &span.offs, &span.names, text, thr, &rule); + thr = gated; + rule = gated_rule; + } + let mut decoded = if span.offs.is_empty() { + Vec::new() + } else { + decode_spans(&probs, &span.offs, &span.names, text, thr) + }; + let chars: Vec = text.chars().collect(); + for entry in decoded.iter_mut() { + let (s, e) = ( + entry["start"].as_u64().unwrap_or(0) as usize, + entry["end"].as_u64().unwrap_or(0) as usize, + ); + entry["text"] = Value::String(chars[s..e].iter().collect()); + if let Some(mapped) = span + .label_alias + .as_ref() + .and_then(Value::as_object) + .and_then(|alias| alias.get(entry["label"].as_str().unwrap_or(""))) + { + entry["label"] = mapped.clone(); + } + } + let mut answer = serde_json::json!({ + "id": span.qid, + "type": "span", + "target_part": span.over, + "spans": decoded, + "threshold": thr, + "threshold_rule": rule, + "head": head, + }); + if let Some(reason) = &span.head_reason { + answer["head_reason"] = Value::String(reason.clone()); + } + answers.push(answer); + } + answers +} + +fn argmax_usize(x: &[f64]) -> usize { + let mut best = 0usize; + let mut value = f64::NEG_INFINITY; + for (index, item) in x.iter().enumerate() { + if *item > value { + value = *item; + best = index; + } + } + best +} + +fn json_f64(value: f64) -> Value { + serde_json::Number::from_f64(value) + .map(Value::Number) + .unwrap_or(Value::Null) +} + +/// `predict_raw`'s window aggregation: sum the window rows' span logits +/// per original word (matched by char offsets), divide by coverage +/// count, uncovered words score -30. +pub fn aggregate_windows( + names: &[String], + original_offs: &[(usize, usize)], + window_logits: &[Vec>], + window_offs: &[Vec<(usize, usize)>], +) -> Vec> { + let labels = names.len(); + // The reference accumulates in float64; the result casts to f32. + let mut acc = vec![vec![0.0f64; labels]; original_offs.len()]; + let mut cnt = vec![0usize; original_offs.len()]; + for (logits, offs) in window_logits.iter().zip(window_offs) { + for ((s, e), row) in offs.iter().zip(logits) { + if let Some(u) = original_offs.iter().position(|(os, oe)| os == s && oe == e) { + for (l, value) in row.iter().enumerate() { + acc[u][l] += *value as f64; + } + cnt[u] += 1; + } + } + } + acc.iter() + .zip(&cnt) + .map(|(row, c)| { + if *c > 0 { + row.iter().map(|v| (*v / *c as f64) as f32).collect() + } else { + vec![-30.0; labels] + } + }) + .collect() +} diff --git a/tests/vela/fixtures/head-input-example-request-cjk.json b/tests/vela/fixtures/head-input-example-request-cjk.json new file mode 100644 index 00000000..3baaa645 --- /dev/null +++ b/tests/vela/fixtures/head-input-example-request-cjk.json @@ -0,0 +1 @@ +{"case": "example-request-cjk", "request": {"model": "vllm-sr/Vela-2.0-0.8B", "state": {"request": "客户张伟（zhang.wei@example.cn）于2026年10月1日在上海市浦东新区世纪大道100号办理了业务，联系电话13800138000。", "source": "客户的业务申请需要在三个工作日内审核完成。", "answer": "客户的业务已经即时完成了。"}, "questions": {"pii": {"type": "span", "instructions": "Which spans are personal information?", "criteria": {"PERSON": "a person's name", "EMAIL_ADDRESS": "an e-mail address", "PHONE_NUMBER": "a telephone number", "STREET_ADDRESS": "a street address or postal address"}, "over": "request"}, "unsupported": {"type": "span", "instructions": "Which spans of the answer are not supported by the context?", "criteria": {"unsupported": "a claim not supported by the context"}}, "billing": {"type": "noul", "instructions": "这个请求是否与账单有关？"}}}, "rows": [{"head": "router", "head_reason": "id", "label_alias": null, "n_tokens": 404, "seg_lens": {"user": 46, "context": 10, "answer": 6}}, {"head": "router", "head_reason": "label_set", "label_alias": null, "n_tokens": 193, "seg_lens": {"user": 46, "context": 10, "answer": 6}}], "head_calls": [{"kind": "q", "cand": "q0_cand", "query": "q0_query", "logits": [[-1.60933518409729, -3.7373664379119873, -10.640555381774902]], "row": 0}, {"kind": "span", "head": "router", "words": "s1_words", "labels": "s1_labels", "logits": [[-23.778533935546875, -35.67962646484375, -29.496707916259766, -35.02517318725586], [-23.778533935546875, -35.67962646484375, -29.496707916259766, -35.02517318725586], [-13.288297653198242, -17.101852416992188, -9.51349925994873, -13.732088088989258], 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b/tests/vela/fixtures/head-input-example-request.json @@ -0,0 +1 @@ +{"case": "example-request", "request": {"model": "vllm-sr/Vela-2.0-0.8B", "state": {"request": "Hi, I'm Tom Baker (tom.baker@example.com). What is the maximum daily dose of paracetamol for an adult?", "source": "For adults, the maximum dose of paracetamol is 4 grams in 24 hours, taken as 500 mg to 1 g every 4 to 6 hours.", "answer": "Adults can take up to 6 grams of paracetamol in 24 hours, in doses of 500 mg to 1 g every 4 to 6 hours."}, "questions": {"pii": {"type": "span", "instructions": "Which spans are personal information?", "criteria": {"AGE": "a person's age", "CREDIT_CARD": "a payment card number", "DATE_TIME": "a date, time or date of birth", "DOMAIN_NAME": "an internet domain name or website address", "EMAIL_ADDRESS": "an e-mail address", "GPE": "a country, city, state or other geopolitical place", "IBAN_CODE": "an international bank account number (IBAN)", "IP_ADDRESS": "an IPv4 or IPv6 address", "NRP": "a nationality, religious or political group", "ORGANIZATION": "the name of a company, institution or other organisation", "PERSON": "a person's name", "PHONE_NUMBER": "a telephone number", "STREET_ADDRESS": "a street address or postal address", "TITLE": "a personal or professional title such as Dr. or Mrs.", "US_DRIVER_LICENSE": "a US driver's licence number", "US_SSN": "a US social security number", "ZIP_CODE": "a postal or ZIP code"}, "over": "request"}, "halu": {"type": "span", "instructions": "Which spans of the answer are not supported by the context?", "criteria": {"unsupported": "a claim not supported by the context"}}, "domain": {"type": "choice", "instructions": "Which subject area is this request about?", "over": "request", "criteria": {"health": "medicine, clinical practice, nutrition, ageing or sexual health", "math": "arithmetic, algebra, geometry, statistics or other mathematics", "other": "a subject that fits none of the listed areas"}}}}, "rows": [{"head": "router", "head_reason": "id", "label_alias": null, "n_tokens": 772, "seg_lens": {"user": 27, "context": 39, "answer": 39}}, {"head": "router", "head_reason": "id", "label_alias": null, "n_tokens": 269, "seg_lens": 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