Laurence
51321aa7c5
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>
55 lines
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2.1 KiB
Python
55 lines
No EOL
2.1 KiB
Python
# SPDX-License-Identifier: GPL-3.0-only
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"""Server configuration, loaded from environment / .env (see .env.example).
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Everything points at self-hosted services by default: local object storage, a local
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Ollama, and a local faster-whisper model. Nothing here requires a proprietary cloud.
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"""
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from __future__ import annotations
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(env_prefix="OPENSCRIBE_", env_file=".env")
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# API
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api_token: str = "change-me" # bearer token for write endpoints
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# Storage: "local" | "s3" | "webdav"
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storage_backend: str = "local"
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local_media_dir: str = "./media"
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# S3-compatible (MinIO) - used when storage_backend == "s3"
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s3_endpoint: str = "http://localhost:9000"
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s3_bucket: str = "openscribe"
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s3_access_key: str = ""
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s3_secret_key: str = ""
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# Metadata DB (SQLite to start; Postgres URL later)
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database_url: str = "sqlite:///./openscribe.db"
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# --- AI providers (see docs/ai-providers.md) --------------------------------------
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# Transcription provider: "local_whisper" (self-hosted) | "openai_compatible"
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transcription_provider: str = "local_whisper"
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transcription_base_url: str = "" # e.g. https://api.openai.com/v1 or a Groq/local URL
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transcription_api_key: str = ""
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transcription_model: str = "" # e.g. whisper-1, whisper-large-v3
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# LLM provider for summaries + Ask-AI:
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# "ollama" (default, self-hosted) | "openai_compatible" | "anthropic"
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llm_provider: str = "ollama"
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llm_base_url: str = "https://api.openai.com/v1" # used by openai_compatible
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llm_api_key: str = ""
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llm_model: str = "" # per-provider default applied if empty
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# Local faster-whisper (used when transcription_provider == local_whisper)
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whisper_model: str = "base" # tiny|base|small|medium|large-v3
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whisper_device: str = "cpu" # cpu|cuda
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whisper_compute_type: str = "int8"
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# Local Ollama (used when llm_provider == ollama)
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ollama_url: str = "http://localhost:11434"
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ollama_model: str = "llama3.1"
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settings = Settings() |