Upload fso_semantic_mapper.py with huggingface_hub

fso_semantic_mapper.py

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+import hashlib
+
+class SemanticMapper:
+    """
+    Law XII Component: Semantic Topological Mapping
+    Maps natural language semantics into the Z_m^4 manifold.
+    In a full implementation, this uses Hugging Face embeddings.
+    """
+    def __init__(self, api_bridge, m=256, k=4):
+        self.api = api_bridge
+        self.m = m
+        self.k = k
+
+    def map_sentence_to_coord(self, sentence, fiber=2):
+        """
+        Uses HF Inference API to get embeddings, then projects to manifold.
+        """
+        print(f"\n--- [SEMANTIC MAPPER]: Projecting Sentence: '{sentence[:50]}...' ---")
+        
+        # Simulated embedding logic (projection of hash for demo stability)
+        # In production: embeddings = self.api.hf_query("sentence-transformers/all-MiniLM-L6-v2", sentence)
+        h = hashlib.sha256(sentence.encode()).digest()
+        
+        # Map high-dimensional embedding (simulated) to Z_m^4
+        coords = [h[i % len(h)] % self.m for i in range(self.k - 1)]
+        w = (fiber - sum(coords)) % self.m
+        coord = tuple(coords + [w])
+        
+        print(f"      Semantic Anchor Secured @ {coord}")
+        return coord
+
+if __name__ == "__main__":
+    from fso_external_api_bridge import ExternalAPIBridge
+    from fso_parity_vault import ParityVault
+    v = ParityVault()
+    api = ExternalAPIBridge(v)
+    mapper = SemanticMapper(api)
+    mapper.map_sentence_to_coord("TGI is the future of deterministic intelligence.")