Add LLM request queue, streaming chat, and rename ollama_client to llm_client

- Serialize all LLM requests through an asyncio semaphore to prevent
  overloading athena with concurrent requests
- Switch chat() to streaming so the typing indicator only appears once
  the model starts generating (not during thinking/loading)
- Increase LLM timeout from 5 to 10 minutes for slow first loads
- Rename ollama_client.py to llm_client.py and self.ollama to self.llm
  since the bot uses a generic OpenAI-compatible API
- Update embed labels from "Ollama" to "LLM"

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

bot.py

@@ -12,7 +12,7 @@ from dotenv import load_dotenv
 
 from utils.database import Database
 from utils.drama_tracker import DramaTracker
-from utils.ollama_client import LLMClient
+from utils.llm_client import LLMClient
 
 # Load .env
 load_dotenv()
@@ -69,7 +69,7 @@ class BCSBot(commands.Bot):
         llm_base_url = os.getenv("LLM_BASE_URL", "http://athena.lan:11434")
         llm_model = os.getenv("LLM_MODEL", "Qwen3-VL-32B-Thinking-Q8_0")
         llm_api_key = os.getenv("LLM_API_KEY", "not-needed")
-        self.ollama = LLMClient(llm_base_url, llm_model, llm_api_key)
+        self.llm = LLMClient(llm_base_url, llm_model, llm_api_key)
 
         # Drama tracker
         sentiment = config.get("sentiment", {})
@@ -154,7 +154,7 @@ class BCSBot(commands.Bot):
 
     async def close(self):
         await self.db.close()
-        await self.ollama.close()
+        await self.llm.close()
         await super().close()