feat(server): pluggable AI providers - any open-standard or commercial AI

Lets the owner point transcription and summarisation at any AI: an open-standard
endpoint (OpenAI-compatible / local faster-whisper / Ollama) or a commercial API
(OpenAI, Anthropic, Gemini). Config-driven, self-hostable, no lock-in.

What changed:
- server/app/providers/: provider layer.
  - base.py: Transcriber/Summariser protocols + shared summary prompt + tolerant JSON
    parser (uniform Summary shape across providers).
  - summary.py: OpenAICompatibleSummariser (any /chat/completions - OpenAI, Groq,
    OpenRouter, LocalAI, LM Studio, vLLM, Ollama /v1) and AnthropicSummariser (Claude
    via the official anthropic SDK; Messages API has no OpenAI-compatible endpoint).
  - transcription.py: OpenAICompatibleTranscriber (/audio/transcriptions - OpenAI,
    Groq, self-hosted whisper server) and LocalWhisperTranscriber (faster-whisper,
    execution wired in M5).
  - factory.py: builds the configured providers with per-provider defaults
    (anthropic -> claude-opus-4-8, openai_compatible -> gpt-4o-mini, ollama -> llama3.1).
- config.py + .env.example: transcription_provider / llm_provider selectors + base_url,
  key, model settings; local faster-whisper and Ollama kept as the self-hosted defaults.
- main.py: /health now reports the resolved provider names (no secrets).
- requirements.txt: httpx drives all HTTP providers; anthropic + faster-whisper are
  optional, only for their respective providers.
- docs/ai-providers.md: config recipes for OpenAI, Groq, Anthropic, Gemini, LocalAI,
  LM Studio, Ollama, self-hosted whisper.
- state/: DECISIONS, ARCHITECTURE, TODO updated.

Why:
- The user asked to connect the device to any open standard AI or commercial one; this
  is also the core differentiator vs Plaud's locked cloud.

Notes:
- Anthropic provider uses the official SDK and defaults to claude-opus-4-8 (per the
  claude-api guidance). AI deps are optional per chosen provider. Modules byte-compile
  cleanly; end-to-end wiring into the ingest pipeline lands with M5.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

server/app/main.py

@@ -24,11 +24,20 @@ _recordings: dict[str, Recording] = {}
 
 @app.get("/health")
 def health() -> dict:
+    # Report the resolved provider names (never secrets) so operators can confirm config.
+    from .providers import build_summariser, build_transcriber
+
+    try:
+        summariser = build_summariser().name
+    except Exception as exc:  # e.g. anthropic dep not installed
+        summariser = f"unavailable ({type(exc).__name__})"
     return {
         "status": "ok",
         "storage_backend": settings.storage_backend,
-        "whisper_model": settings.whisper_model,
-        "ollama_model": settings.ollama_model,
+        "transcription_provider": settings.transcription_provider,
+        "transcriber": build_transcriber().name,
+        "llm_provider": settings.llm_provider,
+        "summariser": summariser,
     }