Update fusion context embeddings

README.md

@@ -1,8 +1,8 @@
 # ailab-bio/TACK-Context-Encoding
 
 PCA-reduced context embedding tables for the `tackai` fusion surrogates (`tackai.fusion`):
-one lookup table plus a PCA side-file per block (assay (8-d), cell (47-d), e3 (7-d), poi (51-d)), and `manifest.json` recording
-each file's sha256, byte size and dimensions. Published from a `protein_space="combined"` encoder; `from_pretrained` reproduces that by default.
+one lookup table plus a PCA side-file per block (assay (8-d), cell (53-d), e3 (24-d), poi (77-d)), and `manifest.json` recording
+each file's sha256, byte size and dimensions.
 
 These tables are **inputs** to every fusion model, never the output of one — a fitted
 ensemble is only meaningful against the exact tables it was built with, so this repo is
@@ -14,7 +14,7 @@ versioned by commit rather than by file content.
 from tackai.fusion.data import FusionData
 
 data = FusionData.from_pretrained("ailab-bio/TACK-Context-Encoding")
-context = data.encode_context({"poi_seq": ..., "e3_seq": ..., "cell_id": ..., "assay": ...})
+context = data.transform_context({"poi_seq": ..., "e3_seq": ..., "cell_id": ..., "assay": ...})
 ```
 
 `from_pretrained` installs these files into `TACKAI_CACHE` and verifies them against this

assay_embeddings_vocab=open26_model=all-mpnet-base-v1_pooling=mean_pca8.npz

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manifest.json

@@ -1,101 +1,216 @@
 {
- "format": "tack-fusion-context/v1",
+ "format": "tack-context-encoding/v1",
  "tackai_version": "1.0.0",
- "protein_space": "combined",
+ "protein_space": null,
  "block_dims": {
   "assay_time": 1,
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-  "poi": 51,
-  "e3": 7,
+  "poi": 77,
+  "e3": 24,
+  "cell": 53,
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  },
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+ "combined_dim": 85,
  "models": {
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   "poi": "facebook/esm2_t30_150M_UR50D",
-  "e3": "facebook/esm2_t30_150M_UR50D"
+  "e3": "facebook/esm2_t30_150M_UR50D",
+  "combined": "facebook/esm2_t30_150M_UR50D",
+  "cell": "sentence-transformers/all-mpnet-base-v1",
+  "assay": "sentence-transformers/all-mpnet-base-v1"
  },
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  }
 }

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