Drop native offline chat support with llama-cpp-python

It is recommended to chat with open-source models by running an
open-source server like Ollama, Llama.cpp on your GPU powered machine
or use a commercial provider of open-source models like DeepInfra or
OpenRouter.

These chat model serving options provide a mature Openai compatible
API that already works with Khoj.

Directly using offline chat models only worked reasonably with pip
install on a machine with GPU. Docker setup of khoj had trouble with
accessing GPU. And without GPU access offline chat is too slow.

Deprecating support for an offline chat provider directly from within
Khoj will reduce code complexity and increase developement velocity.
Offline models are subsumed to use existing Openai ai model provider.

tests/conftest.py

@@ -196,17 +196,6 @@ def default_openai_chat_model_option():
     return chat_model
 
 
-@pytest.mark.django_db
-@pytest.fixture
-def offline_agent():
-    chat_model = ChatModelFactory()
-    return Agent.objects.create(
-        name="Accountant",
-        chat_model=chat_model,
-        personality="You are a certified CPA. You are able to tell me how much I've spent based on my notes. Regardless of what I ask, you should always respond with the total amount I've spent. ALWAYS RESPOND WITH A SUMMARY TOTAL OF HOW MUCH MONEY I HAVE SPENT.",
-    )
-
-
 @pytest.mark.django_db
 @pytest.fixture
 def openai_agent():
@@ -516,40 +505,6 @@ def client(
     return TestClient(app)
 
 
-@pytest.fixture(scope="function")
-def client_offline_chat(search_config: SearchConfig, default_user2: KhojUser):
-    # Initialize app state
-    state.config.search_type = search_config
-    state.SearchType = configure_search_types()
-
-    LocalMarkdownConfig.objects.create(
-        input_files=None,
-        input_filter=["tests/data/markdown/*.markdown"],
-        user=default_user2,
-    )
-
-    all_files = fs_syncer.collect_files(user=default_user2)
-    configure_content(default_user2, all_files)
-
-    # Initialize Processor from Config
-    ChatModelFactory(
-        name="bartowski/Meta-Llama-3.1-3B-Instruct-GGUF",
-        tokenizer=None,
-        max_prompt_size=None,
-        model_type="offline",
-    )
-    UserConversationProcessorConfigFactory(user=default_user2)
-
-    state.anonymous_mode = True
-
-    app = FastAPI()
-
-    configure_routes(app)
-    configure_middleware(app)
-    app.mount("/static", StaticFiles(directory=web_directory), name="static")
-    return TestClient(app)
-
-
 @pytest.fixture(scope="function")
 def new_org_file(default_user: KhojUser, content_config: ContentConfig):
     # Setup