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docs/troubleshooting.md
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docs/troubleshooting.md
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# Troubleshooting
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Issues specific to Llamactl deployment and operation.
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## Configuration Issues
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### Invalid Configuration
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**Problem:** Invalid configuration preventing startup
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**Solutions:**
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1. Use minimal configuration:
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```yaml
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server:
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host: "0.0.0.0"
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port: 8080
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instances:
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port_range: [8000, 9000]
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```
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2. Check data directory permissions:
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```bash
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# Ensure data directory is writable (default: ~/.local/share/llamactl)
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mkdir -p ~/.local/share/llamactl/{instances,logs}
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```
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## Instance Management Issues
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### Model Loading Failures
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**Problem:** Instance fails to start with model loading errors
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**Common Solutions:**
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- **llama-server not found:** Ensure `llama-server` binary is in PATH
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- **Wrong model format:** Ensure model is in GGUF format
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- **Insufficient memory:** Use smaller model or reduce context size
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- **Path issues:** Use absolute paths to model files
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### Memory Issues
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**Problem:** Out of memory errors or system becomes unresponsive
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**Solutions:**
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1. **Reduce context size:**
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```json
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{
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"n_ctx": 1024
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}
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```
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2. **Use quantized models:**
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- Try Q4_K_M instead of higher precision models
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- Use smaller model variants (7B instead of 13B)
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### GPU Configuration
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**Problem:** GPU not being used effectively
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**Solutions:**
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1. **Configure GPU layers:**
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```json
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{
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"n_gpu_layers": 35
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}
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```
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### Advanced Instance Issues
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**Problem:** Complex model loading, performance, or compatibility issues
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Since llamactl uses `llama-server` under the hood, many instance-related issues are actually llama.cpp issues. For advanced troubleshooting:
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**Resources:**
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- **llama.cpp Documentation:** [https://github.com/ggml/llama.cpp](https://github.com/ggml/llama.cpp)
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- **llama.cpp Issues:** [https://github.com/ggml/llama.cpp/issues](https://github.com/ggml/llama.cpp/issues)
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- **llama.cpp Discussions:** [https://github.com/ggml/llama.cpp/discussions](https://github.com/ggml/llama.cpp/discussions)
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**Testing directly with llama-server:**
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```bash
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# Test your model and parameters directly with llama-server
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llama-server --model /path/to/model.gguf --port 8081 --n-gpu-layers 35
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```
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This helps determine if the issue is with llamactl or with the underlying llama.cpp/llama-server.
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## API and Network Issues
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### CORS Errors
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**Problem:** Web UI shows CORS errors in browser console
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**Solutions:**
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1. **Configure allowed origins:**
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```yaml
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server:
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allowed_origins:
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- "http://localhost:3000"
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- "https://yourdomain.com"
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```
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## Authentication Issues
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**Problem:** API requests failing with authentication errors
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**Solutions:**
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1. **Disable authentication temporarily:**
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```yaml
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auth:
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require_management_auth: false
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require_inference_auth: false
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```
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2. **Configure API keys:**
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```yaml
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auth:
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management_keys:
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- "your-management-key"
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inference_keys:
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- "your-inference-key"
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```
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3. **Use correct Authorization header:**
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```bash
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curl -H "Authorization: Bearer your-api-key" \
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http://localhost:8080/api/v1/instances
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```
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## Remote Node Issues
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### Node Configuration
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**Problem:** Remote instances not appearing or cannot be managed
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**Solutions:**
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1. **Verify node configuration:**
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```yaml
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local_node: "main" # Must match a key in nodes map
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nodes:
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main:
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address: "" # Empty for local node
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worker1:
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address: "http://worker1.internal:8080"
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api_key: "secure-key" # Must match worker1's management key
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```
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2. **Check node name consistency:**
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- `local_node` on each node must match what other nodes call it
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- Node names are case-sensitive
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3. **Test remote node connectivity:**
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```bash
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curl -H "Authorization: Bearer remote-node-key" \
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http://remote-node:8080/api/v1/instances
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```
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## Debugging and Logs
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### Viewing Instance Logs
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```bash
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# Get instance logs via API
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curl http://localhost:8080/api/v1/instances/{name}/logs
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# Or check log files directly
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tail -f ~/.local/share/llamactl/logs/{instance-name}.log
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```
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### Enable Debug Logging
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```bash
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export LLAMACTL_LOG_LEVEL=debug
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llamactl
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```
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## Getting Help
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When reporting issues, include:
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1. **System information:**
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```bash
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llamactl --version
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```
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2. **Configuration file** (remove sensitive keys)
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3. **Relevant log output**
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4. **Steps to reproduce the issue**
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