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feat(server): pluggable AI providers - any open-standard or commercial AI
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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>
This commit is contained in:
Laurence 2026-07-03 18:56:58 +01:00
parent 34eb17abbc
commit 51321aa7c5
12 changed files with 380 additions and 13 deletions
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5
state/ARCHITECTURE.md
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@ -56,8 +56,11 @@ Three sync paths, exactly as specified:
- Pipeline: ingest (from cloud store or direct upload) -> store raw audio (object store)
-> transcribe (faster-whisper) -> summarise (Ollama LLM) -> index metadata (DB) ->
expose REST API + exports (audio, TXT, SRT, VTT, Markdown, JSON).
- AI is provider-pluggable (`server/app/providers/`, see docs/ai-providers.md): transcription
and the LLM each target a configured provider - open-standard (OpenAI-compatible / local
faster-whisper / Ollama) or commercial (OpenAI, Anthropic, Gemini). No lock-in.
- Depends on: object storage (MinIO or local FS), a DB (SQLite to start, Postgres later),
faster-whisper, Ollama. All self-hostable.
and whichever AI providers are configured (default: self-hosted faster-whisper + Ollama).
- Why this way: keeps the device cheap and low-power (no on-device AI); all heavy compute
runs on hardware the user owns; every step swappable and open.