chore(docs): add documentation about import

docs/content/getting-started/models.md

@@ -1,23 +1,46 @@
 +++
 disableToc = false
-title = "Install and Run Models"
-weight = 4
-icon = "rocket_launch"
+title = "Setting Up Models"
+weight = 2
+icon = "hub"
+description = "Learn how to install, configure, and manage models in LocalAI"
 +++
 
-To install models with LocalAI, you can:
+This section covers everything you need to know about installing and configuring models in LocalAI. You'll learn multiple methods to get models running.
 
-- Browse the Model Gallery from the Web Interface and install models with a couple of clicks. For more details, refer to the [Gallery Documentation]({{% relref "features/model-gallery" %}}).
-- Specify a model from the LocalAI gallery during startup, e.g., `local-ai run <model_gallery_name>`.
-- Use a URI to specify a model file (e.g., `huggingface://...`, `oci://`, or `ollama://`) when starting LocalAI, e.g., `local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf`.
-- Specify a URL to a model configuration file when starting LocalAI, e.g., `local-ai run https://gist.githubusercontent.com/.../phi-2.yaml`.
-- Manually install the models by copying the files into the models directory (`--models`).
+## Prerequisites
 
-## Run and Install Models via the Gallery
+- LocalAI installed and running (see [Quickstart]({{% relref "getting-started/quickstart" %}}) if you haven't set it up yet)
+- Basic understanding of command line usage
 
-To run models available in the LocalAI gallery, you can use the WebUI or specify the model name when starting LocalAI. Models can be found in the gallery via the Web interface, the [model gallery](https://models.localai.io), or the CLI with: `local-ai models list`.
+## Method 1: Using the Model Gallery (Easiest)
 
-To install a model from the gallery, use the model name as the URI. For example, to run LocalAI with the Hermes model, execute:
+The Model Gallery is the simplest way to install models. It provides pre-configured models ready to use.
+
+### Via WebUI
+
+1. Open the LocalAI WebUI at `http://localhost:8080`
+2. Navigate to the "Models" tab
+3. Browse available models
+4. Click "Install" on any model you want
+5. Wait for installation to complete
+
+For more details, refer to the [Gallery Documentation]({{% relref "features/model-gallery" %}}).
+
+### Via CLI
+
+```bash
+# List available models
+local-ai models list
+
+# Install a specific model
+local-ai models install llama-3.2-1b-instruct:q4_k_m
+
+# Start LocalAI with a model from the gallery
+local-ai run llama-3.2-1b-instruct:q4_k_m
+```
+
+To run models available in the LocalAI gallery, you can use the model name as the URI. For example, to run LocalAI with the Hermes model, execute:
 
 ```bash
 local-ai run hermes-2-theta-llama-3-8b
@@ -31,7 +54,82 @@ local-ai models install hermes-2-theta-llama-3-8b
 
 Note: The galleries available in LocalAI can be customized to point to a different URL or a local directory. For more information on how to setup your own gallery, see the [Gallery Documentation]({{% relref "features/model-gallery" %}}).
 
-## Run Models via URI
+### Browse Online
+
+Visit [models.localai.io](https://models.localai.io) to browse all available models in your browser.
+
+## Method 1.5: Import Models via WebUI
+
+The WebUI provides a powerful model import interface that supports both simple and advanced configuration:
+
+### Simple Import Mode
+
+1. Open the LocalAI WebUI at `http://localhost:8080`
+2. Click "Import Model"
+3. Enter the model URI (e.g., `https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct-GGUF`)
+4. Optionally configure preferences:
+   - Backend selection
+   - Model name
+   - Description
+   - Quantizations
+   - Embeddings support
+   - Custom preferences
+5. Click "Import Model" to start the import process
+
+### Advanced Import Mode
+
+For full control over model configuration:
+
+1. In the WebUI, click "Import Model"
+2. Toggle to "Advanced Mode"
+3. Edit the YAML configuration directly in the code editor
+4. Use the "Validate" button to check your configuration
+5. Click "Create" or "Update" to save
+
+The advanced editor includes:
+- Syntax highlighting
+- YAML validation
+- Format and copy tools
+- Full configuration options
+
+This is especially useful for:
+- Custom model configurations
+- Fine-tuning model parameters
+- Setting up complex model setups
+- Editing existing model configurations
+
+## Method 2: Installing from Hugging Face
+
+LocalAI can directly install models from Hugging Face:
+
+```bash
+# Install and run a model from Hugging Face
+local-ai run huggingface://TheBloke/phi-2-GGUF
+```
+
+The format is: `huggingface://<repository>/<model-file>` (<model-file> is optional)
+
+### Examples
+
+```bash
+local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
+```
+
+## Method 3: Installing from OCI Registries
+
+### Ollama Registry
+
+```bash
+local-ai run ollama://gemma:2b
+```
+
+### Standard OCI Registry
+
+```bash
+local-ai run oci://localai/phi-2:latest
+```
+
+### Run Models via URI
 
 To run models via URI, specify a URI to a model file or a configuration file when starting LocalAI. Valid syntax includes:
 
@@ -51,18 +149,45 @@ local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
 local-ai run oci://localai/phi-2:latest
 ```
 
-## Run Models Manually
+## Method 4: Manual Installation
 
-Follow these steps to manually run models using LocalAI:
+For full control, you can manually download and configure models.
 
-1. **Prepare Your Model and Configuration Files**:
-   Ensure you have a model file and, if necessary, a configuration YAML file. Customize model defaults and settings with a configuration file. For advanced configurations, refer to the [Advanced Documentation]({{% relref "advanced" %}}).
+### Step 1: Download a Model
 
-2. **GPU Acceleration**:
-   For instructions on GPU acceleration, visit the [GPU Acceleration]({{% relref "features/gpu-acceleration" %}}) page.
+Download a GGUF model file. Popular sources:
 
-3. **Run LocalAI**:
-   Choose one of the following methods to run LocalAI:
+- [Hugging Face](https://huggingface.co/models?search=gguf)
+
+Example:
+
+```bash
+mkdir -p models
+
+wget https://huggingface.co/TheBloke/phi-2-GGUF/resolve/main/phi-2.Q4_K_M.gguf \
+  -O models/phi-2.Q4_K_M.gguf
+```
+
+### Step 2: Create a Configuration File (Optional)
+
+Create a YAML file to configure the model:
+
+```yaml
+# models/phi-2.yaml
+name: phi-2
+parameters:
+  model: phi-2.Q4_K_M.gguf
+  temperature: 0.7
+context_size: 2048
+threads: 4
+backend: llama-cpp
+```
+
+Customize model defaults and settings with a configuration file. For advanced configurations, refer to the [Advanced Documentation]({{% relref "advanced" %}}).
+
+### Step 3: Run LocalAI
+
+Choose one of the following methods to run LocalAI:
 
 {{< tabs >}}
 {{% tab title="Docker" %}}
@@ -74,7 +199,6 @@ cp your-model.gguf models/
 
 docker run -p 8080:8080 -v $PWD/models:/models -ti --rm quay.io/go-skynet/local-ai:latest --models-path /models --context-size 700 --threads 4
 
-
 curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
      "model": "your-model.gguf",
      "prompt": "A long time ago in a galaxy far, far away",
@@ -121,10 +245,8 @@ git clone https://github.com/go-skynet/LocalAI
 
 cd LocalAI
 
-
 cp your-model.gguf models/
 
-
 docker compose up -d --pull always
 
 curl http://localhost:8080/v1/models
@@ -154,6 +276,11 @@ For Kubernetes deployment, see the [Kubernetes installation guide]({{% relref "i
 
 LocalAI binary releases are available on [GitHub](https://github.com/go-skynet/LocalAI/releases).
 
+```bash
+# With binary
+local-ai --models-path ./models
+```
+
 {{% notice tip %}}
 If installing on macOS, you might encounter a message saying:
 
@@ -174,4 +301,115 @@ For instructions on building LocalAI from source, see the [Build from Source gui
 {{% /tab %}}
 {{< /tabs >}}
 
+### GPU Acceleration
+
+For instructions on GPU acceleration, visit the [GPU Acceleration]({{% relref "features/gpu-acceleration" %}}) page.
+
 For more model configurations, visit the [Examples Section](https://github.com/mudler/LocalAI-examples/tree/main/configurations).
+
+## Understanding Model Files
+
+### File Formats
+
+- **GGUF**: Modern format, recommended for most use cases
+- **GGML**: Older format, still supported but deprecated
+
+### Quantization Levels
+
+Models come in different quantization levels (quality vs. size trade-off):
+
+| Quantization | Size | Quality | Use Case |
+|-------------|------|---------|----------|
+| Q8_0 | Largest | Highest | Best quality, requires more RAM |
+| Q6_K | Large | Very High | High quality |
+| Q4_K_M | Medium | High | Balanced (recommended) |
+| Q4_K_S | Small | Medium | Lower RAM usage |
+| Q2_K | Smallest | Lower | Minimal RAM, lower quality |
+
+### Choosing the Right Model
+
+Consider:
+
+- **RAM available**: Larger models need more RAM
+- **Use case**: Different models excel at different tasks
+- **Speed**: Smaller quantizations are faster
+- **Quality**: Higher quantizations produce better output
+
+## Model Configuration
+
+### Basic Configuration
+
+Create a YAML file in your models directory:
+
+```yaml
+name: my-model
+parameters:
+  model: model.gguf
+  temperature: 0.7
+  top_p: 0.9
+context_size: 2048
+threads: 4
+backend: llama-cpp
+```
+
+### Advanced Configuration
+
+See the [Model Configuration]({{% relref "advanced/model-configuration" %}}) guide for all available options.
+
+## Managing Models
+
+### List Installed Models
+
+```bash
+# Via API
+curl http://localhost:8080/v1/models
+
+# Via CLI
+local-ai models list
+```
+
+### Remove Models
+
+Simply delete the model file and configuration from your models directory:
+
+```bash
+rm models/model-name.gguf
+rm models/model-name.yaml  # if exists
+```
+
+## Troubleshooting
+
+### Model Not Loading
+
+1. **Check backend**: Ensure the required backend is installed
+
+   ```bash
+   local-ai backends list
+   local-ai backends install llama-cpp  # if needed
+   ```
+
+2. **Check logs**: Enable debug mode
+
+   ```bash
+   DEBUG=true local-ai
+   ```
+
+3. **Verify file**: Ensure the model file is not corrupted
+
+### Out of Memory
+
+- Use a smaller quantization (Q4_K_S or Q2_K)
+- Reduce `context_size` in configuration
+- Close other applications to free RAM
+
+### Wrong Backend
+
+Check the [Compatibility Table]({{% relref "reference/compatibility-table" %}}) to ensure you're using the correct backend for your model.
+
+## Best Practices
+
+1. **Start small**: Begin with smaller models to test your setup
+2. **Use quantized models**: Q4_K_M is a good balance for most use cases
+3. **Organize models**: Keep your models directory organized
+4. **Backup configurations**: Save your YAML configurations
+5. **Monitor resources**: Watch RAM and disk usage

docs/content/getting-started/quickstart.md

@@ -1,7 +1,7 @@
 +++
 disableToc = false
 title = "Quickstart"
-weight = 3
+weight = 1
 url = '/basics/getting_started/'
 icon = "rocket_launch"
 +++