feat: local AI server scaffolding (FastAPI, RAG, embeddings). Port policy (>=26000), README/API docs, scripts.

server/config.py

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+from __future__ import annotations
+
+import os
+from dataclasses import dataclass
+
+
+@dataclass(frozen=True)
+class Settings:
+    ollama_host: str = os.getenv("OLLAMA_HOST", "http://localhost:11434")
+    base_model: str = os.getenv("BASE_MODEL", "qwen2.5:7b-instruct")
+    boost_model: str = os.getenv("BOOST_MODEL", "qwen2.5:14b-instruct")
+    embedding_model: str = os.getenv("EMBEDDING_MODEL", "nomic-embed-text")
+    index_path: str = os.getenv("INDEX_PATH", "data/index.jsonl")
+
+    # Paperless (user will provide API details)
+    paperless_base_url: str = os.getenv("PAPERLESS_BASE_URL", "")
+    paperless_token: str = os.getenv("PAPERLESS_TOKEN", "")
+
+
+settings = Settings()
+