HF pulling model docs (#3273)

Ticket:CVS-166548

Author: atobiszei

docs/pull_hf_models.md

@@ -0,0 +1,150 @@
+*Note:*
+This functionality is a work in progress
+
+# Pulling the models {#ovms_pul}
+
+There is a special mode to make OVMS pull the model from Hugging Face before starting the service:
+
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest --pull_hf_model --source_model <model_name_in_HF> --model_repository <path_where_to_store_model_files> --model_name <external_model_name> --task <task> --task_params <task_params>
+```
+
+| option               | description                                                                                   |
+|----------------------|-----------------------------------------------------------------------------------------------|
+| `--pull`             | Instructs the server to run in pulling mode to get the model from the Hugging Face repository |
+| `--source_model`     | Specifies the model name in the Hugging Face model repository (optional - if empty model_name is used) |
+| `--model_repository` | Directory where all required model files will be saved                                        |
+| `--model_name`       | Name of the model as exposed externally by the server                                         |
+| `--task`             | Defines the task the model will support (e.g., text_generation/embedding, rerank, etc.)                       |
+| `--task_params`      | Task-specific parameters in a format to be determined (TBD FIXME)                             |
+
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest \
+--model_path <path_to_model> --model_name <model_name> --port 9000 --rest_port 8000 --log_level DEBUG
+```
+
+It will prepare all needed configuration files to support LLMS with OVMS in model repository
+
+# Starting the mediapipe graph or LLM models
+Now you can start server with single mediapipe graph, or LLM model that is already present in local filesystem with:
+
+```
+docker run -d --rm -v <models_repository>:/models -p 9000:9000 -p 8000:8000 openvino/model_server:latest \
+--model_path <path_to_model> --model_name <model_name> --port 9000 --rest_port 8000
+```
+
+Server will detect the type of requested servable (model or mediapipe graph) and load it accordingly. This detection is based on the presence of a `.pbtxt` file, which defines the Mediapipe graph structure.
+
+*Note*: There is no online model modification nor versioning capability as of now for graphs, LLM like models.
+
+# Starting the LLM model from HF directly
+
+In case you do not want to prepare model repository before starting the server in one command you can run OVMS with:
+
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest --source_model <model_name_in_HF> --model_repository <path_where_to_store_model_files> --model_name <ovms_servable_name> --task <task> --task_params <task_params>
+```
+
+It will download required model files, prepare configuration for OVMS and start serving the model.
+
+# Starting the LLM model from local storage
+
+In case you have predownloaded the model files from HF but you lack OVMS configuration files you can start OVMS with
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest --source_model <model_name_in_HF> --model_repository <path_where_to_store_ovms_config_files> --model_path <model_files_path> --model_name <external_model_name> --task <task> --task_params <task_params>
+```
+
+# Simplified mediapipe graphs and LLM models loading
+
+Now there is an easier way to specify LLM configurations in `config.json`. In the `model_config` section, it is sufficient to specify `model_name` and `base_path`, and the server will detect if there is a graph configuration file (`.pbtxt`) present and load the servable accordingly. 
+
+For example, the `model_config` section in `config.json` could look like this:
+
+```json
+{
+    "model_config_list": [
+        {
+            "config": {
+                "name": "text_generation_model",
+                "base_path": "/models/text_generation_model"
+            }
+        },
+        {
+            "config": {
+                "name": "embedding_model",
+                "base_path": "/models/embedding_model"
+            }
+        },
+        {
+            "config": {
+                "name": "mediapipe_graph",
+                "base_path": "/models/mediapipe_graph"
+            }
+        }
+    ]
+}
+```
+# List models
+
+To check what models are servable from specified model repository:
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest \
+--models_repository /models --list_models
+```
+
+For following directory structure:
+```
+/models
+├── meta
+│   ├── llama4
+│   │   └── graph.pbtxt
+│   ├── llama3.1
+│   │   └── graph.pbtxt
+├── LLama3.2
+│   └── graph.pbtxt
+└── resnet
+    └── 1
+        └── saved_model.pb
+```
+
+The output would be:
+```
+meta/llama4
+meta/llama3.1
+LLama3.2
+resnet
+```
+
+# Enable model
+
+To add model to ovms configuration file with specific model use either:
+
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest \
+--models_repository /models/<model_path> --add_to_config <config_file_path> --model_name <name>
+```
+
+When model is directly inside `/models`.
+
+Or
+
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest \
+--add_to_config <config_file_path> --model_name <name> --model_path <model_path>
+```
+when there is no model_repository specified.
+
+# Disable model
+
+If you want to remove model from configuration file you can do it either manually or use command:
+
+```
+docker run -d --rm -v <models_repository>:/models openvino/model_server:latest \
+--remove_from_config <config_file_path> --model_name <name>
+```
+
+FIXME TODO TBD
+- adjust existing documentation to link with this doc
+- task, task_params to be updated explained
+- do we want to allow in pulling mode separately specifying model_path/repository?
+- we should explain the relevance of config.json to model repository (ie that config.json will work with specific dir)