fix: add /api prefix to all backend routes

Frontend expects /api/chat but backend had /chat.
Added APIRouter with prefix=/api to fix route mismatch.

docs/gpu-compatibility.md

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+# GPU Compatibility Guide
+
+## RTX 50-Series (Blackwell) Compatibility Notice
+
+### Issue
+NVIDIA RTX 50-series GPUs (RTX 5070, 5080, 5090) use CUDA capability `sm_120` (Blackwell architecture). PyTorch stable releases (up to 2.5.1) only officially support up to `sm_90` (Hopper/Ada).
+
+**Warning you'll see:**
+```
+NVIDIA GeForce RTX 5070 with CUDA capability sm_120 is not compatible with the current PyTorch installation.
+The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90.
+```
+
+### Current Status
+- ✅ PyTorch detects the GPU
+- ✅ CUDA operations generally work
+- ⚠️ Some operations may fail or fall back to CPU
+- ⚠️ Performance may not be optimal
+
+### Workarounds
+
+#### Option 1: Use PyTorch Nightly (Recommended for RTX 50-series)
+```bash
+pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu124
+```
+
+#### Option 2: Use Current Stable with Known Limitations
+Many workloads work fine despite the warning. Test your specific use case.
+
+#### Option 3: Wait for PyTorch 2.7
+Full sm_120 support is expected in the next stable release.
+
+### Installation Steps for KV-RAG with GPU
+
+1. **Install CUDA-enabled PyTorch:**
+   ```bash
+   pip install torch==2.5.1+cu121 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
+   ```
+
+2. **Install unsloth without dependencies:**
+   ```bash
+   pip install unsloth --no-deps
+   pip install unsloth_zoo
+   ```
+
+3. **Install remaining training dependencies:**
+   ```bash
+   pip install bitsandbytes accelerate peft transformers datasets trl
+   ```
+   Note: Skip `xformers` as it may overwrite torch. Unsloth works without it.
+
+### Verify GPU is Working
+
+```python
+import torch
+print(f"CUDA available: {torch.cuda.is_available()}")
+print(f"GPU: {torch.cuda.get_device_name(0)}")
+print(f"CUDA version: {torch.version.cuda}")
+```
+
+### Ollama GPU Status
+
+Ollama runs **natively on Windows** and uses GPU automatically when available:
+- Check with: `nvidia-smi` (look for `ollama.exe` processes)
+- Embedding model (`mxbai-embed-large:335m`) runs on GPU
+- Chat models also use GPU when loaded
+
+### Forge Training GPU Status
+
+The training script uses `unsloth` + `trl` for QLoRA fine-tuning:
+- Requires CUDA-enabled PyTorch
+- Optimized for 12GB VRAM (RTX 5070)
+- Uses 4-bit quantization + LoRA adapters
+- See `src/companion/forge/train.py` for implementation
+
+### Troubleshooting
+
+**Issue:** `CUDA available: False` after installation
+**Fix:** PyTorch was overwritten by a package dependency. Reinstall:
+```bash
+pip install torch==2.5.1+cu121 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 --force-reinstall
+```
+
+**Issue:** `xformers` overwrites torch
+**Fix:** Skip xformers or install matching wheel:
+```bash
+# Skip for now - unsloth works without it
+# Or install specific version matching your torch
+pip install xformers==0.0.28.post3 --index-url https://download.pytorch.org/whl/cu121
+```
+
+### References
+
+- [PyTorch CUDA Compatibility](https://pytorch.org/get-started/locally/)
+- [NVIDIA CUDA Capability Matrix](https://developer.nvidia.com/cuda-gpus)
+- [Unsloth Documentation](https://github.com/unsloth/unsloth)
+- [RTX 50-Series Architecture](https://www.nvidia.com/en-us/geforce/graphics-cards/50-series/)