mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
Mathieu Virbel
ad56165b54
* fix: remove unused settings and utils files * fix: remove migration done * fix: remove outdated scripts * fix: removing deployment of hermes, not used anymore * fix: partially remove secret, still have to understand frontend.
98 lines
2.8 KiB
Plaintext
98 lines
2.8 KiB
Plaintext
#
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# This file serve as an example of possible configuration
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# All the settings are described here: reflector/settings.py
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#
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## =======================================================
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## User authentication
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## =======================================================
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## Using jwt/authentik
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AUTH_BACKEND=jwt
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AUTH_JWT_AUDIENCE=
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## =======================================================
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## Transcription backend
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##
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## Check reflector/processors/audio_transcript_* for the
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## full list of available transcription backend
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## =======================================================
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## Using local whisper
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#TRANSCRIPT_BACKEND=whisper
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## Using serverless modal.com (require reflector-gpu-modal deployed)
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#TRANSCRIPT_BACKEND=modal
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#TRANSCRIPT_URL=https://xxxxx--reflector-transcriber-web.modal.run
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#TRANSLATE_URL=https://xxxxx--reflector-translator-web.modal.run
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#TRANSCRIPT_MODAL_API_KEY=xxxxx
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TRANSCRIPT_BACKEND=modal
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TRANSCRIPT_URL=https://monadical-sas--reflector-transcriber-web.modal.run
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TRANSCRIPT_MODAL_API_KEY=
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## =======================================================
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## Transcription backend
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##
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## Only available in modal atm
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## =======================================================
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TRANSLATE_URL=https://monadical-sas--reflector-translator-web.modal.run
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## =======================================================
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## LLM backend
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##
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## Responsible for titles and short summary
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## Check reflector/llm/* for the full list of available
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## llm backend implementation
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## =======================================================
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## Using serverless modal.com (require reflector-gpu-modal deployed)
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LLM_BACKEND=modal
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LLM_URL=https://monadical-sas--reflector-llm-web.modal.run
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LLM_MODAL_API_KEY=
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ZEPHYR_LLM_URL=https://monadical-sas--reflector-llm-zephyr-web.modal.run
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## Using OpenAI
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#LLM_BACKEND=openai
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#LLM_OPENAI_KEY=xxx
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#LLM_OPENAI_MODEL=gpt-3.5-turbo
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## Using GPT4ALL
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#LLM_BACKEND=openai
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#LLM_URL=http://localhost:4891/v1/completions
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#LLM_OPENAI_MODEL="GPT4All Falcon"
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## Default LLM MODEL NAME
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#DEFAULT_LLM=lmsys/vicuna-13b-v1.5
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## Cache directory to store models
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CACHE_DIR=data
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## =======================================================
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## Summary LLM configuration
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## =======================================================
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## Context size for summary generation (tokens)
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SUMMARY_LLM_CONTEXT_SIZE_TOKENS=16000
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SUMMARY_LLM_URL=
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SUMMARY_LLM_API_KEY=sk-
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SUMMARY_MODEL=
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## =======================================================
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## Diarization
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##
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## Only available on modal
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## To allow diarization, you need to expose expose the files to be dowloded by the pipeline
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## =======================================================
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DIARIZATION_ENABLED=false
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DIARIZATION_URL=https://monadical-sas--reflector-diarizer-web.modal.run
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## =======================================================
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## Sentry
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## =======================================================
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## Sentry DSN configuration
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#SENTRY_DSN=
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