Refactor LLM configuration to remove llamacpp support

- Removed references to llamacpp from configuration files, scripts, and documentation, streamlining the LLM setup process to focus solely on Ollama.
- Updated environment variables and paths to eliminate llamacpp-related entries, ensuring clarity in the configuration.
- Adjusted CLI commands and help messages to reflect the removal of llamacpp, enhancing user experience and reducing confusion.
- Revised documentation to provide clear guidance on using Ollama exclusively, including updates to setup instructions and runtime options.

src/gpu_rent/config.py

@@ -14,7 +14,6 @@ from gpu_rent.paths import (
     default_ssh_key_path,
     env_path,
     extensions_manifest_path,
-    llamacpp_models_manifest_path,
     migrate_legacy_if_needed,
     models_manifest_path,
     ollama_models_manifest_path,
@@ -107,9 +106,7 @@ class Config:
     llm_runtime: str
     enable_swarmui: bool
     ollama_models_manifest: Path
-    llamacpp_models_manifest: Path
     ollama_local_port: int
-    llamacpp_local_port: int
 
     default_flavor_id: str
     flavor_preference: tuple[str, ...]
@@ -185,10 +182,6 @@ def load_config(*, require_auth: bool = True) -> Config:
         (os.environ.get("OLLAMA_MODELS_MANIFEST") or "").strip()
         or str(ollama_models_manifest_path())
     ).expanduser()
-    llamacpp_manifest = Path(
-        (os.environ.get("LLAMACPP_MODELS_MANIFEST") or "").strip()
-        or str(llamacpp_models_manifest_path())
-    ).expanduser()
 
     try:
         llm_runtime = normalize_runtime(os.environ.get("LLM_RUNTIME"))
@@ -243,9 +236,7 @@ def load_config(*, require_auth: bool = True) -> Config:
         llm_runtime=llm_runtime,
         enable_swarmui=enable_swarmui,
         ollama_models_manifest=ollama_manifest,
-        llamacpp_models_manifest=llamacpp_manifest,
         ollama_local_port=_as_int(os.environ.get("OLLAMA_LOCAL_PORT"), 17811),
-        llamacpp_local_port=_as_int(os.environ.get("LLAMACPP_LOCAL_PORT"), 17812),
         default_flavor_id=(os.environ.get("DEFAULT_FLAVOR_ID") or "").strip(),
         flavor_preference=_csv(
             os.environ.get("FLAVOR_PREFERENCE"),