bc7ac32de3
- Campaigns: new table, CRUD API, React context + provider
- Sessions: scoped to campaigns, paths under campaigns/{id}/
- File browser: scoped per campaign, removed copy/paste/autoPlay
- Sidebar: campaign selector dropdown at top
- Transcribe: GPU model cached/released via job counter
- Jobs: status text updates dynamically in real-time
- Auto-redirect: blocked when summarize job is active
68 lines
2.5 KiB
Python
68 lines
2.5 KiB
Python
"""
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App-wide configuration. Everything is either an environment variable (set once,
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at deploy time) or a row in the `settings` table (editable at runtime via the
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setup wizard / settings page) - never a hardcoded path or host.
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"""
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import os
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from pathlib import Path
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# Deploy-time config (env vars) - where things live on disk inside the container.
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DATA_DIR = Path(os.environ.get("APP_DATA_DIR", "/data"))
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UPLOAD_DIR = DATA_DIR / "audio"
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AUDIO_DIR = DATA_DIR / "audio"
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TRANSCRIPT_DIR = DATA_DIR / "transcriptions"
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NOTES_DIR = DATA_DIR / "notes"
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DB_PATH = DATA_DIR / "app.db"
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CAMPAIGNS_DIR = DATA_DIR / "campaigns"
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def campaign_dir(campaign_id: str) -> Path:
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return CAMPAIGNS_DIR / campaign_id
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def campaign_audio_dir(campaign_id: str) -> Path:
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return campaign_dir(campaign_id) / "audio"
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def campaign_transcript_dir(campaign_id: str) -> Path:
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return campaign_dir(campaign_id) / "transcriptions"
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def campaign_notes_dir(campaign_id: str) -> Path:
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return campaign_dir(campaign_id) / "notes"
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for d in (UPLOAD_DIR, AUDIO_DIR, TRANSCRIPT_DIR, NOTES_DIR):
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d.mkdir(parents=True, exist_ok=True)
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# Runtime-editable settings (stored in DB, these are just first-run defaults).
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# NOTE: this flat key/value schema is the single source of truth for settings -
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# it's what every consumer (pipeline/summarize.py, pipeline/transcribe.py,
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# routers/models.py, routers/diagnostics.py) actually reads. The settings
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# router and frontend must mirror these exact keys - a nested schema would
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# silently disconnect the Settings/Setup UI from the pipeline.
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DEFAULT_SETTINGS = {
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# Onboarding
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"onboarding_completed": "false",
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# Transcription
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"whisper_model": "medium", # tiny|base|small|medium|large-v3 - user picks based on their hardware
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"whisper_compute_type": "int8",
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"hf_token": "", # required for diarization (pyannote gated models)
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# Summarization backend: "ollama" (local) or "api" (hosted, OpenAI-compatible)
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"llm_mode": "ollama",
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"ollama_host": "http://localhost:11434",
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"ollama_model": "qwen2.5:7b",
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"api_base_url": "https://api.openai.com/v1",
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"api_key": "",
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"api_model": "gpt-4o-mini",
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# Chunking for long transcripts (map-reduce summarization)
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"chunk_word_target": "2500",
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# Optional world context injected into every summarization prompt
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"world_context": "",
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"world_context_path": "",
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# Player recap style: "story" | "diary" | "bullets" | "custom"
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"player_recap_style": "story",
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"player_recap_custom_prompt": "",
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}
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