v0.3.0

Added

• CLI entry point (ragmill command) with subcommands: ingest, sync, search, chat, count, serve, export, import, configure.
• REST API server (ragmill serve) with FastAPI — endpoints for ingest, sync, search, chat, export, import, count, health.
• Retrieval-augmented chat via three backends: local GGUF model (ragmill[chat]), Gemini (ragmill[chat-gemini]), OpenAI (ragmill[chat-openai]).
• Standalone config UI (ragmill configure) for setting up cloud backends and chat keys without editing .env by hand.
• Pinecone cloud vector store backend (ragmill[pinecone]).
• Qdrant cloud vector store backend (ragmill[qdrant]).
• JSONL export/import for backup and cross-backend migration.
• RAGMillConfig centralizes all settings in a single dataclass, loaded from env vars / .env.
• Configurable embedding dimension (RAGMILL_EMBEDDING_DIM).
• Batched embedding and upsert operations for better throughput.
• Docker support with docker-compose.yml (SQLite and Qdrant profiles).

Changed

• Default SQLite path is now ./ragmill.db (was :memory:) — data persists across CLI invocations.
• Server binds to 127.0.0.1 by default (was 0.0.0.0) — not exposed to the network unless explicitly configured.
• config-ui extra now includes FastAPI, uvicorn, pydantic, and numpy so ragmill configure works out of the box.
• server extra now includes python-dotenv so .env files are loaded automatically.
• Pinecone RAGMILL_PINECONE_ENVIRONMENT is now honored (parses region from formats like us-west-2, us-west1-gcp).