docs: update README and forge documentation
- README: Fixed backend command, added GPU compatibility reference - forge.md: Fixed train CLI (--output-dir), added GPU troubleshooting - Added reference to GPU compatibility guide for RTX 50-series
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@@ -39,6 +39,7 @@ A fully local, privacy-first AI companion trained on your Obsidian vault. Combin
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- Node.js 18+ (for UI)
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- Ollama running locally
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- RTX 5070 or equivalent (12GB+ VRAM for fine-tuning)
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- See [GPU Compatibility Guide](docs/gpu-compatibility.md) for RTX 50-series setup
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### Installation
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@@ -76,7 +77,7 @@ See [docs/config.md](docs/config.md) for full configuration reference.
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**Terminal 1 - Backend:**
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```bash
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python -m uvicorn companion.api:app --host 0.0.0.0 --port 7373
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python -m companion.api
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```
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**Terminal 2 - Frontend:**
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@@ -139,8 +140,9 @@ python -m companion.forge.cli reload ~/.companion/training/final
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| `companion.config` | Configuration management | [docs/config.md](docs/config.md) |
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| `companion.rag` | RAG engine (chunk, embed, search) | [docs/rag.md](docs/rag.md) |
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| `companion.forge` | Fine-tuning pipeline | [docs/forge.md](docs/forge.md) |
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| `companion.api` | FastAPI backend | [docs/api.md](docs/api.md) |
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| `companion.api` | FastAPI backend | This README |
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| `ui/` | React frontend | [docs/ui.md](docs/ui.md) |
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| **GPU Setup** | RTX 50-series compatibility | [docs/gpu-compatibility.md](docs/gpu-compatibility.md) |
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## Project Structure
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@@ -193,22 +193,24 @@ new_path = reload_model(
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```bash
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# Extract training data
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companion.forge.cli extract [--output PATH]
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python -m companion.forge.cli extract [--output PATH]
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# Train model
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companion.forge.cli train \
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[--data PATH] \
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[--output PATH] \
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[--epochs N] \
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[--lr FLOAT]
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python -m companion.forge.train \
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--data PATH \
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--output-dir PATH \
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--epochs N \
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--lr FLOAT
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# Check model status
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companion.forge.cli status
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python -m companion.forge.cli status
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# Reload model
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companion.forge.cli reload MODEL_PATH [--no-backup]
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python -m companion.forge.cli reload MODEL_PATH [--no-backup]
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```
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**Note:** Use `--output-dir` (or `--output`) to specify the training output directory.
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## Training Tips
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**Dataset Size:**
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@@ -243,6 +245,11 @@ Use `gradient_accumulation_steps` to increase effective batch size.
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## Troubleshooting
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**GPU Not Detected / CUDA Not Available**
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- See [GPU Compatibility Guide](gpu-compatibility.md)
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- Common issue on RTX 50-series: Install CUDA-enabled PyTorch: `pip install torch==2.5.1+cu121 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121`
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- Verify: `python -c "import torch; print(torch.cuda.is_available())"`
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**CUDA Out of Memory**
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- Reduce `lora_rank` to 8
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- Reduce `batch_size` to 2
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