Compare commits
5 Commits
v0.1.9
...
use-albertine
| Author | SHA1 | Date | |
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| 4b03946028 | |||
| 68b919c189 | |||
| c5544e87d6 | |||
| 4b4f16e93f | |||
| 3e3f964ac5 |
+1
-1
Submodule secrets updated: 142e7a70b1...f5aea0c251
@@ -7,7 +7,7 @@ build-backend = "setuptools.build_meta"
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[project]
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name = "meet"
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version = "0.1.9"
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version = "0.1.10"
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authors = [{ "name" = "DINUM", "email" = "dev@mail.numerique.gouv.fr" }]
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classifiers = [
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"Development Status :: 5 - Production/Stable",
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Generated
+2
-2
@@ -1,12 +1,12 @@
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{
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"name": "meet",
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"version": "0.1.9",
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"version": "0.1.10",
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"lockfileVersion": 3,
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"requires": true,
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"packages": {
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"": {
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"name": "meet",
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"version": "0.1.9",
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"version": "0.1.10",
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"dependencies": {
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"@livekit/components-react": "2.6.9",
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"@livekit/components-styles": "1.1.4",
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@@ -1,7 +1,7 @@
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{
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"name": "meet",
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"private": true,
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"version": "0.1.9",
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"version": "0.1.10",
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"type": "module",
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"scripts": {
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"dev": "panda codegen && vite",
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@@ -125,6 +125,9 @@ summary:
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AWS_S3_ACCESS_KEY_ID: meet
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AWS_S3_SECRET_ACCESS_KEY: password
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OPENAI_API_KEY: password
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OPENAI_BASE_URL: https://albertine.beta.numerique.gouv.fr:32222/v1
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OPENAI_ASR_MODEL: openai/whisper-large-v3
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OPENAI_LLM_MODEL: meta-llama/Llama-3.1-8B-Instruct
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AWS_S3_SECURE_ACCESS: False
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WEBHOOK_API_TOKEN: password
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WEBHOOK_URL: https://www.mock-impress.com/webhook/
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@@ -155,6 +158,9 @@ celery:
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AWS_S3_ACCESS_KEY_ID: meet
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AWS_S3_SECRET_ACCESS_KEY: password
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OPENAI_API_KEY: password
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OPENAI_BASE_URL: https://albertine.beta.numerique.gouv.fr:32222/v1
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OPENAI_ASR_MODEL: openai/whisper-large-v3
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OPENAI_LLM_MODEL: meta-llama/Llama-3.1-8B-Instruct
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AWS_S3_SECURE_ACCESS: False
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WEBHOOK_API_TOKEN: password
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WEBHOOK_URL: https://www.mock-impress.com/webhook/
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@@ -1,7 +1,7 @@
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image:
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repository: lasuite/meet-backend
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pullPolicy: Always
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tag: "v0.1.9"
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tag: "v0.1.10"
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backend:
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migrateJobAnnotations:
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@@ -129,7 +129,7 @@ frontend:
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image:
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repository: lasuite/meet-frontend
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pullPolicy: Always
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tag: "v0.1.9"
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tag: "v0.1.10"
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ingress:
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enabled: true
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@@ -165,3 +165,9 @@ posthog:
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cert-manager.io/cluster-issuer: letsencrypt
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nginx.ingress.kubernetes.io/upstream-vhost: eu-assets.i.posthog.com
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nginx.ingress.kubernetes.io/backend-protocol: https
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summary:
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replicas: 0
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celery:
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replicas: 0
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@@ -216,6 +216,9 @@ summary:
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secretKeyRef:
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name: summary
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key: OPENAI_API_KEY
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OPENAI_BASE_URL: https://albertine.beta.numerique.gouv.fr:32222/v1
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OPENAI_ASR_MODEL: openai/whisper-large-v3
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OPENAI_LLM_MODEL: meta-llama/Llama-3.1-8B-Instruct
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WEBHOOK_API_TOKEN:
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secretKeyRef:
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name: summary
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Generated
+2
-2
@@ -1,12 +1,12 @@
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{
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"name": "mail_mjml",
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"version": "0.1.9",
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"version": "0.1.10",
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"lockfileVersion": 3,
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"requires": true,
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"packages": {
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"": {
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"name": "mail_mjml",
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"version": "0.1.9",
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"version": "0.1.10",
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"license": "MIT",
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"dependencies": {
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"@html-to/text-cli": "0.5.4",
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@@ -1,6 +1,6 @@
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{
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"name": "mail_mjml",
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"version": "0.1.9",
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"version": "0.1.10",
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"description": "An util to generate html and text django's templates from mjml templates",
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"type": "module",
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"dependencies": {
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@@ -1,6 +1,7 @@
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"""Celery workers."""
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import json
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import os
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import tempfile
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from pathlib import Path
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@@ -28,6 +29,7 @@ celery = Celery(
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)
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if settings.sentry_dsn and settings.sentry_is_enabled:
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@signals.celeryd_init.connect
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def init_sentry(**_kwargs):
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"""Initialize sentry."""
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@@ -100,15 +102,20 @@ def process_audio_transcribe_summarize(filename: str, email: str, sub: str):
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api_key=settings.openai_api_key, base_url=settings.openai_base_url
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)
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logger.debug("Querying transcription …")
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with open(temp_file_path, "rb") as audio_file:
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transcription = openai_client.audio.transcriptions.create(
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model=settings.openai_asr_model, file=audio_file
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)
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try:
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logger.debug("Querying transcription …")
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with open(temp_file_path, "rb") as audio_file:
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transcription = openai_client.audio.transcriptions.create(
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model=settings.openai_asr_model, file=audio_file
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)
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transcription = transcription.text
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transcription = transcription.text
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logger.debug("Transcription: \n %s", transcription)
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logger.debug("Transcription: \n %s", transcription)
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finally:
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if os.path.exists(temp_file_path):
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os.remove(temp_file_path)
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logger.debug("Temporary file removed: %s", temp_file_path)
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instructions = get_instructions(transcription)
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summary_response = openai_client.chat.completions.create(
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