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/config.py

@@ -28,12 +28,26 @@ class Settings(BaseSettings):
     # Metadata DB (SQLite to start; Postgres URL later)
     database_url: str = "sqlite:///./openscribe.db"
 
-    # Transcription (faster-whisper)
+    # --- AI providers (see docs/ai-providers.md) --------------------------------------
+    # Transcription provider: "local_whisper" (self-hosted) | "openai_compatible"
+    transcription_provider: str = "local_whisper"
+    transcription_base_url: str = ""      # e.g. https://api.openai.com/v1 or a Groq/local URL
+    transcription_api_key: str = ""
+    transcription_model: str = ""         # e.g. whisper-1, whisper-large-v3
+
+    # LLM provider for summaries + Ask-AI:
+    #   "ollama" (default, self-hosted) | "openai_compatible" | "anthropic"
+    llm_provider: str = "ollama"
+    llm_base_url: str = "https://api.openai.com/v1"   # used by openai_compatible
+    llm_api_key: str = ""
+    llm_model: str = ""                   # per-provider default applied if empty
+
+    # Local faster-whisper (used when transcription_provider == local_whisper)
     whisper_model: str = "base"           # tiny|base|small|medium|large-v3
     whisper_device: str = "cpu"           # cpu|cuda
     whisper_compute_type: str = "int8"
 
-    # Summarisation (Ollama, self-hosted)
+    # Local Ollama (used when llm_provider == ollama)
     ollama_url: str = "http://localhost:11434"
     ollama_model: str = "llama3.1"