feat: LLM router with local (Ollama) and cloud (OpenAI) backends

- lyra.config.load() reads env into a frozen Config dataclass
- lyra.llm.complete(messages, backend) routes to Ollama /api/chat or
  OpenAI chat completions
- lyra.llm.embed(texts) calls OpenAI embeddings
- .env.example switched from Anthropic to OpenAI to match available key

lyra/config.py

@@ -0,0 +1,31 @@
+"""Environment-driven configuration."""
+from __future__ import annotations
+
+import os
+from dataclasses import dataclass
+from pathlib import Path
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+
+@dataclass(frozen=True)
+class Config:
+    local_base_url: str
+    local_model: str
+    openai_api_key: str
+    cloud_model: str
+    embed_model: str
+    db_path: Path
+
+
+def load() -> Config:
+    return Config(
+        local_base_url=os.getenv("LOCAL_BASE_URL", "http://localhost:11434"),
+        local_model=os.getenv("LOCAL_MODEL", "qwen2.5:7b-instruct"),
+        openai_api_key=os.getenv("OPENAI_API_KEY", ""),
+        cloud_model=os.getenv("CLOUD_MODEL", "gpt-4o-mini"),
+        embed_model=os.getenv("EMBED_MODEL", "text-embedding-3-small"),
+        db_path=Path(os.getenv("LYRA_DB_PATH", "data/lyra.db")),
+    )