docs: add whisper-server to docker-compose.yml
- Add commented-out whisper-server service to docker-compose.yml - Update README to show both manual docker run and docker-compose options
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@@ -189,7 +189,7 @@ audio:
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Without an `audio` config, voice messages from non-audio-capable models will display an error message to the user. For local transcription, you can run a whisper.cpp server:
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Without an `audio` config, voice messages from non-audio-capable models will display an error message to the user. For local transcription, you can run a whisper.cpp server:
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```bash
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```bash
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# Start whisper.cpp server with OpenAI-compatible endpoint
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# Option 1: Manual docker run
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docker run -d \
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docker run -d \
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--name whisper-server \
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--name whisper-server \
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-p 18801:8080 \
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-p 18801:8080 \
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@@ -200,6 +200,9 @@ docker run -d \
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--convert \
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--convert \
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--language en \
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--language en \
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--inference-path /v1/audio/transcriptions
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--inference-path /v1/audio/transcriptions
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# Option 2: Using docker-compose (uncomment whisper-server service in docker-compose.yml)
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# docker compose up -d
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```
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```
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## Telegram Commands
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## Telegram Commands
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@@ -30,5 +30,27 @@ services:
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start_period: 15s
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start_period: 15s
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retries: 3
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retries: 3
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# Optional: Whisper server for audio transcription
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# Uncomment and adjust as needed for voice message support
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# whisper-server:
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# image: ghcr.io/ggml-org/whisper.cpp:main
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# container_name: whisper-server
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# restart: unless-stopped
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# ports:
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# - "18801:8080"
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# command: whisper-server
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# --model /app/models/ggml-base.en.bin
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# --host 0.0.0.0
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# --port 8080
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# --convert
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# --language en
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# --inference-path /v1/audio/transcriptions
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# healthcheck:
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# test: ["CMD-SHELL", "curl", "-f", "http://localhost:8080/"]
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# interval: 30s
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# timeout: 5s
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# start_period: 15s
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# retries: 3
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volumes:
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volumes:
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flynn-data:
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flynn-data:
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