diff --git a/data/apps.json b/data/apps.json index 07a1b10434e3c5cfe42b21a2c7a52964d413bd35..3982905316fe5f0748b4de1ca77859af7adb9c7f 100644 --- a/data/apps.json +++ b/data/apps.json @@ -2388,7 +2388,7 @@ "issueTracker": "https://github.com/nextcloud/assistant/issues", "website": "https://github.com/nextcloud/assistant", "created": "2023-08-21T11:46:53.737268Z", - "lastModified": "2025-01-08T09:42:47.588634Z", + "lastModified": "2025-01-22T10:23:03.349014Z", "releases": [ { "version": "1.1.0", @@ -4371,7 +4371,7 @@ "issueTracker": "https://github.com/nextcloud/calendar/issues", "website": "https://github.com/nextcloud/calendar/", "created": "2016-10-01T12:40:39.060903Z", - "lastModified": "2025-01-16T16:08:19.743118Z", + "lastModified": "2025-01-22T18:08:16.087879Z", "releases": [ { "version": "4.7.16", @@ -6835,7 +6835,7 @@ "issueTracker": "https://github.com/nextcloud/contacts/issues", "website": "https://github.com/nextcloud/contacts#readme", "created": "2016-10-30T14:00:58.922766Z", - "lastModified": "2025-01-09T15:56:41.212616Z", + "lastModified": "2025-01-22T17:57:13.584713Z", "releases": [ { "version": "6.0.2", @@ -21674,7 +21674,7 @@ "issueTracker": "https://github.com/nextcloud/integration_openai/issues", "website": "https://github.com/nextcloud/integration_openai", "created": "2023-02-07T00:02:04.311790Z", - "lastModified": "2025-01-08T11:41:34.959635Z", + "lastModified": "2025-01-22T14:34:26.453310Z", "releases": [ { "version": "2.0.3", @@ -21824,7 +21824,7 @@ "en": { "name": "OpenAI and LocalAI integration", "summary": "Integration of OpenAI and LocalAI services", - "description": "⚠️ The smart pickers have been removed from this app\nas they are now included in the [Assistant app](https://apps.nextcloud.com/apps/assistant).\n\nThis app implements:\n\n* Text generation providers: Free prompt, Summarize, Headline, Context Write, Chat, and Reformulate (using any available large language model)\n* A Translation provider (using any available language model)\n* A SpeechToText provider (using Whisper)\n* An image generation provider\n\n⚠️ Context Write, Summarize, Headline and Reformulate have mainly been tested with OpenAI.\nThey might work when connecting to other services, without any guarantee.\n\nInstead of connecting to the OpenAI API for these, you can also connect to a self-hosted [LocalAI](https://localai.io) instance or [Ollama](https://ollama.com/) instance\nor to any service that implements an API similar to the OpenAI one, for example: [Plusserver](https://www.plusserver.com/en/ai-platform/) or [MistralAI](https://mistral.ai).\n\n⚠️ This app is mainly tested with OpenAI. We do not guarantee it works perfectly\nwith other services that implement OpenAI-compatible APIs with slight differences.\n\n## Improve AI task pickup speed\n\nTo avoid task processing execution delay, setup at 4 background job workers in the main server (where Nextcloud is installed). The setup process is documented here: https://docs.nextcloud.com/server/latest/admin_manual/ai/overview.html#improve-ai-task-pickup-speed\n\n## Ethical AI Rating\n### Rating for Text generation using ChatGPT via the OpenAI API: 🔴\n\nNegative:\n* The software for training and inference of this model is proprietary, limiting running it locally or training by yourself\n* The trained model is not freely available, so the model can not be run on-premises\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model's performance and CO2 usage.\n\n\n### Rating for Translation using ChatGPT via the OpenAI API: 🔴\n\nNegative:\n* The software for training and inference of this model is proprietary, limiting running it locally or training by yourself\n* The trained model is not freely available, so the model can not be run on-premises\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model's performance and CO2 usage.\n\n### Rating for Image generation using DALL·E via the OpenAI API: 🔴\n\nNegative:\n* The software for training and inferencing of this model is proprietary, limiting running it locally or training by yourself\n* The trained model is not freely available, so the model can not be ran on-premises\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\n\n### Rating for Speech-To-Text using Whisper via the OpenAI API: 🟡\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can run on-premise\n\nNegative:\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\n### Rating for Text generation via LocalAI: 🟢\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can be ran on-premises\n* The training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n\n### Rating for Image generation using Stable Diffusion via LocalAI : 🟡\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can be ran on-premises\n\nNegative:\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\n\n### Rating for Speech-To-Text using Whisper via LocalAI: 🟡\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can be ran on-premises\n\nNegative:\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\nLearn more about the Nextcloud Ethical AI Rating [in our blog](https://nextcloud.com/blog/nextcloud-ethical-ai-rating/)." + "description": "⚠️ The smart pickers have been removed from this app\nas they are now included in the [Assistant app](https://apps.nextcloud.com/apps/assistant).\n\nThis app implements:\n\n* Text generation providers: Free prompt, Summarize, Headline, Context Write, Chat, and Reformulate (using any available large language model)\n* A Translation provider (using any available language model)\n* A SpeechToText provider (using Whisper)\n* An image generation provider\n\n⚠️ Context Write, Summarize, Headline and Reformulate have mainly been tested with OpenAI.\nThey might work when connecting to other services, without any guarantee.\n\nInstead of connecting to the OpenAI API for these, you can also connect to a self-hosted [LocalAI](https://localai.io) instance or [Ollama](https://ollama.com/) instance\nor to any service that implements an API similar to the OpenAI one, for example:\n[IONOS AI Model Hub](https://docs.ionos.com/cloud/ai/ai-model-hub), [Plusserver](https://www.plusserver.com/en/ai-platform/) or [MistralAI](https://mistral.ai).\n\n⚠️ This app is mainly tested with OpenAI. We do not guarantee it works perfectly\nwith other services that implement OpenAI-compatible APIs with slight differences.\n\n## Improve AI task pickup speed\n\nTo avoid task processing execution delay, setup at 4 background job workers in the main server (where Nextcloud is installed). The setup process is documented here: https://docs.nextcloud.com/server/latest/admin_manual/ai/overview.html#improve-ai-task-pickup-speed\n\n## Ethical AI Rating\n### Rating for Text generation using ChatGPT via the OpenAI API: 🔴\n\nNegative:\n* The software for training and inference of this model is proprietary, limiting running it locally or training by yourself\n* The trained model is not freely available, so the model can not be run on-premises\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model's performance and CO2 usage.\n\n\n### Rating for Translation using ChatGPT via the OpenAI API: 🔴\n\nNegative:\n* The software for training and inference of this model is proprietary, limiting running it locally or training by yourself\n* The trained model is not freely available, so the model can not be run on-premises\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model's performance and CO2 usage.\n\n### Rating for Image generation using DALL·E via the OpenAI API: 🔴\n\nNegative:\n* The software for training and inferencing of this model is proprietary, limiting running it locally or training by yourself\n* The trained model is not freely available, so the model can not be ran on-premises\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\n\n### Rating for Speech-To-Text using Whisper via the OpenAI API: 🟡\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can run on-premise\n\nNegative:\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\n### Rating for Text generation via LocalAI: 🟢\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can be ran on-premises\n* The training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n\n### Rating for Image generation using Stable Diffusion via LocalAI : 🟡\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can be ran on-premises\n\nNegative:\n* The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\n\n### Rating for Speech-To-Text using Whisper via LocalAI: 🟡\n\nPositive:\n* The software for training and inferencing of this model is open source\n* The trained model is freely available, and thus can be ran on-premises\n\nNegative:\n* The training data is not freely available, 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