Complete component dependency and attribution metadata

CLIP_LICENSE

@@ -0,0 +1,22 @@
+MIT License
+
+Copyright (c) 2021 OpenAI
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+

README.md

@@ -31,3 +31,5 @@ This release follows the official enhanced-decoder reconstruction script with `t
 Native classes are pinned to source revision `9812da01c0695f4989060cc4eea053715e9e4441`. The two adaptations are documented: parameter device/dtype helper compatibility, and construction of the already-checkpointed CLIP branch without its redundant network download. Original tensor computation classes are retained. See `source_reconstruction.sh`, `code_provenance.json` and `validation.json`.
 
 Validation covers all source tensor payload hashes, strict loading, nine-scale ID geometry and bounds, residual lookup reconstruction, finite semantic/RGB outputs, and exact decode-code parity with canonical lookup decoding. Synthetic reconstruction does not establish image quality or full MLLM/VQA/text-to-image performance. Weight-card MIT terms and source-code Apache-2.0 terms are recorded separately in `LICENSE` and `CODE_LICENSE`; original copyright notices remain in the native files.
+
+`CLIP_LICENSE` separately preserves the original OpenAI MIT license and attribution for the bundled CLIP-derived visual transformer.

code_provenance.json

@@ -30,5 +30,11 @@
     "url": "https://raw.githubusercontent.com/ByteVisionLab/TokenFlow/9812da01c0695f4989060cc4eea053715e9e4441/tokenflow/scripts/reconstruction_vq.sh",
     "original_sha256": "281dbe6d9adead48626a3e590843ac6b12a1cc8308141c3ad56d08f90dd48fc0",
     "modifications": []
+  },
+  "CLIP_LICENSE": {
+    "url": "https://raw.githubusercontent.com/openai/CLIP/d05afc436d78f1c48dc0dbf8e5980a9d471f35f6/LICENSE",
+    "original_sha256": "987e63b32f6c89ff5160e429458a872ff048e6860b590a3912e938f9da8f14db",
+    "modifications": [],
+    "purpose": "Preserve the original OpenAI CLIP attribution for the bundled derived visual transformer."
   }
 }

release_manifest.json

@@ -6,8 +6,8 @@
       "sha256": "8452aa13b93e9e0bb2ca9935b0a935de98c8d1b79c5e015484b29cd56a99075d"
     },
     "code_provenance.json": {
-      "size": 1870,
-      "sha256": "4c3e90e3b5a6c1add98a3251a94e48350347661e83750b3eeceb19eb8fc88c1c"
+      "size": 2227,
+      "sha256": "e7f683099d76b929f54cb23167fe7a03218f6d167554d0ecc3433b8b1c745922"
     },
     "LICENSE": {
       "size": 1192,
@@ -22,8 +22,8 @@
       "sha256": "051d7086fadaff33fc6c2178fc85e4e25db1d71ada609ab07a89a1eac4da1a38"
     },
     "README.md": {
-      "size": 2481,
-      "sha256": "d6a1fb8d2a3d6c354272f10b2149d4c56bc9b0d1ec34264dc087de45d106a4e1"
+      "size": 2615,
+      "sha256": "c7a1c8132304a6382d1788ab804478214bb307bf0321699c258f9a3056678b4b"
     },
     "source_reconstruction.sh": {
       "size": 1150,
@@ -76,6 +76,10 @@
     "native/clip/model.py": {
       "size": 22258,
       "sha256": "81a18829854b081a67b96244b574a0149284cb59f1aedd3fd025a0006ef69765"
+    },
+    "CLIP_LICENSE": {
+      "size": 1064,
+      "sha256": "987e63b32f6c89ff5160e429458a872ff048e6860b590a3912e938f9da8f14db"
     }
   }
 }