feat: GPU/TensorCore integration — TensorFlow backend, GPU-accelerated reasoning, training, and memory

- New fusionagi/gpu/ module with TensorBackend protocol abstraction
  - TensorFlowBackend: GPU-accelerated ops with TensorCore mixed-precision
  - NumPyBackend: CPU fallback (always available, no extra deps)
  - Auto-selects best available backend at runtime

- GPU-accelerated operations:
  - Cosine similarity matrix (batched, XLA-compiled)
  - Multi-head attention for consensus scoring
  - Batch hypothesis scoring on GPU
  - Semantic similarity search (pairwise, nearest-neighbor, deduplication)

- New TensorFlowAdapter (fusionagi/adapters/):
  - LLMAdapter for local TF/Keras model inference
  - TensorCore mixed-precision support
  - GPU-accelerated embedding synthesis fallback

- Reasoning pipeline integration:
  - gpu_scoring.py: drop-in GPU replacement for multi_path scoring
  - Super Big Brain: use_gpu config flag, GPU scoring when available

- Memory integration:
  - gpu_search.py: GPU-accelerated semantic search for SemanticGraphMemory

- Self-improvement integration:
  - gpu_training.py: gradient-based heuristic weight optimization
  - Reflective memory training loop with loss tracking

- Dependencies: gpu extra (tensorflow>=2.16, numpy>=1.26)
- 64 new tests (276 total), all passing
- Architecture spec: docs/gpu_tensorcore_integration.md

Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>

fusionagi/adapters/__init__.py

@@ -15,4 +15,16 @@ try:
 except ImportError:
     OpenAIAdapter = None  # type: ignore[misc, assignment]
 
-__all__ = ["LLMAdapter", "StubAdapter", "CachedAdapter", "NativeAdapter", "OpenAIAdapter"]
+try:
+    from fusionagi.adapters.tensorflow_adapter import TensorFlowAdapter
+except ImportError:
+    TensorFlowAdapter = None  # type: ignore[misc, assignment]
+
+__all__ = [
+    "LLMAdapter",
+    "StubAdapter",
+    "CachedAdapter",
+    "NativeAdapter",
+    "OpenAIAdapter",
+    "TensorFlowAdapter",
+]