On Thu, Aug 3, 2023 at 7:16 AM Chris Albon <calbon(a)wikimedia.org> wrote: > Hi everybody, > > TL;DR We would like users of ORES models to migrate to our new open > source ML infrastructure, Lift Wing, within the next five months. We are > available to help you do that, from advice to making code commits. It is > important to note: All ML models currently accessible on ORES are also > currently accessible on Lift Wing. > > As part of the Machine Learning Modernization Project ( > https://www.mediawiki.org/wiki/Machine_Learning/Modernization), the > Machine Learning team has deployed a Wikimedia’s new machine learning > inference infrastructure, called Lift Wing ( > https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing). Lift > Wing brings a lot of new features such as support for GPU-based models, > open source LLM hosting, auto-scaling, stability, and ability to host a > larger number of models. > This sounds quite exciting! What's the best place to read up on that planned support for GPU-based models and open source LLMs? (I also saw in the recent NYT article[1] that the team is "in the process of adapting A.I. models that are 'off the shelf; — essentially models that have been made available by researchers for anyone to freely customize — so that Wikipedia’s editors can use them for their work.") I'm aware of the history[2] of not being able to use NVIDIA GPUs due to their CUDA drivers being proprietary. It was mentioned recently in the Wikimedia AI Telegram group that this is still a serious limitation, despite some new explorations with AMD GPUs[3] - to the point that e.g. the WMF's Language team has resorted to using models without GPU support (CPU only).[4] It sounds like there is reasonable hope that this situation could change fairly soon? Would it also mean both at the same time, i.e. open source LLMs running with GPU support (considering that at least some well-known ones appear to require torch.cuda.is_available() == True for that)? Regards, Tilman [1] https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html [2] https://techblog.wikimedia.org/2020/04/06/saying-no-to-proprietary-code-in-… [3] https://phabricator.wikimedia.org/T334583 etc. [4] https://diff.wikimedia.org/2023/06/13/mint-supporting-underserved-languages… or https://thottingal.in/blog/2023/07/21/wikiqa/ (experimental but, I understand, written to be deployable on WMF infrastructure) > > With the creation of Lift Wing, the team is turning its attention to > deprecating the current machine learning infrastructure, ORES. ORES served > us really well over the years, it was a successful project but it came > before radical changes in technology like Docker, Kubernetes and more > recently MLOps. The servers that run ORES are at the end of their planned > lifespan and so to save cost we are going to shut them down in early 2024. > > We have outlined a deprecation path on Wikitech ( > https://wikitech.wikimedia.org/wiki/ORES), please read the page if > you are a maintainer of a tool or code that uses the ORES endpoint > https://ores.wikimedia.org/). If you have any doubt or if you need > assistance in migrating to Lift Wing, feel free to contact the ML team via: > > - Email: ml(a)wikimedia.org > - Phabricator: #Machine-Learning-Team tag > - IRC (Libera): #wikimedia-ml > > The Machine Learning team is available to help projects migrate, from > offering advice to making code commits. We want to make this as easy as > possible for folks. > > High Level timeline: > > **By September 30th 2023: *Infrastructure powering the ORES API > endpoint will be migrated from ORES to Lift Wing. For users, the API > endpoint will remain the same, and most users won’t notice any change. > Rather just the backend services powering the endpoint will change. > > Details: We'd like to add a DNS CNAME that points ores.wikimedia.org > to ores-legacy.wikimedia.org, a new endpoint that offers a almost > complete replacement of the ORES API calling Lift Wing behind the scenes. > In an ideal world we'd migrate all tools to Lift Wing before > decommissioning the infrastructure behind ores.wikimedia.org, but it > turned out to be really challenging so to avoid disrupting users we chose > to implement a transition layer/API. > > To summarize, if you don't have time to migrate before September to > Lift Wing, your code/tool should work just fine on > ores-legacy.wikimedia.org and you'll not have to change a line in > your code thanks to the DNS CNAME. The ores-legacy endpoint is not a 100% > replacement for ores, we removed some very old and not used features, so we > highly recommend at least test the new endpoint for your use case to avoid > surprises when we'll make the switch. In case you find anything weird, > please report it to us using the aforementioned channels. > > **September to January: *We will be reaching out to every user of > ORES we can identify and working with them to make the migration process as > easy as possible. > > **By January 2024: *If all goes well, we would like zero traffic on > the ORES API endpoint so we can turn off the ores-legacy API. > > If you want more information about Lift Wing, please check > https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing > > Thanks in advance for the patience and the help! > > Regards, > > The Machine Learning Team > _______________________________________________ > Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org > To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org > > https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ _______________________________________________ Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/

Hi Chris, On Mon, Aug 7, 2023 at 11:51 AM Chris Albon <calbon(a)wikimedia.org> wrote: > Hi Tilman, > > Most of the work is still very experimental. We have hosted a few LLMs > on Lift Wing already (StarCoder for example) but they were just running on > CPU, far too slow for real use cases. But it proves that we can easily host > LLMs on Lift Wing. We have been pretty quiet about it while we focus on the > ORES migration, but it is our next big project. More soon hopefully! > Understood. Looking forward to learning more later! > Where we are now is that we have budget for a big GPU purchase (~10-20 > GPUs depending on cost), the question we will try to answer after the ORES > migration is complete is: what GPUs should we purchase? We are trying to > balance our strong preference to stay open source (i.e. AMD mROC) in a > world dominated by a single closed source vendor (i.e. Nvidia). In > addition, do we go for a few expensive GPUs better suited to LLMs (A1000, > H100, etc) or a mix of big and small? We will need to figure out all this. > I see. On that matter, what do you folks make of the recent announcements of AMD's partnerships with Hugging Face and Pytorch[5]? (which, I understand, came after the ML team had already launched the aforementioned new AMD explorations) "Open-source AI: AMD looks to Hugging Face and Meta spinoff PyTorch to take on Nvidia [...] Both partnerships involve AMD’s ROCm AI software stack, the company’s answer to Nvidia’s proprietary CUDA platform and application-programming interface. AMD called ROCm an open and portable AI system with out-of-the-box support that can port to existing AI models. [...B]oth AMD and Hugging Face are dedicating engineering resources to each other and sharing data to ensure that the constantly updated AI models from Hugging Face, which might not otherwise run well on AMD hardware, would be “guaranteed” to work on hardware like the MI300X. [...] AMD said PyTorch will fully upstream the ROCm software stack and “provide immediate ‘day zero’ support for PyTorch 2.0 with ROCm release 5.4.2 on all AMD Instinct accelerators,” which is meant to appeal to those customers looking to switch from Nvidia’s software ecosystem." In their own announcement, Hugging Face offered further details, including a pretty impressive list of models to be supported:[6] "We intend to support state-of-the-art transformer architectures for natural language processing, computer vision, and speech, such as BERT, DistilBERT, ROBERTA, Vision Transformer, CLIP, and Wav2Vec2. Of course, generative AI models will be available too (e.g., GPT2, GPT-NeoX, T5, OPT, LLaMA), including our own BLOOM and StarCoder models. Lastly, we will also support more traditional computer vision models, like ResNet and ResNext, and deep learning recommendation models, a first for us. [..] We'll do our best to test and validate these models for PyTorch, TensorFlow, and ONNX Runtime for the above platforms. [...] We will integrate the AMD ROCm SDK seamlessly in our open-source libraries, starting with the transformers library." Do you think this may promise too much, or could it point to a possible solution of the Foundation's conundrum? In any case, this seems to be an interesting moment where many in AI are trying to move away from Nvidia's proprietary CUDA platform. Most of them probably more for financial and availability reasons though, given the current GPU shortages[7] (which the ML team is undoubtedly aware of already; mentioning this as context for others on this list. See also Marketwatch's remarks about current margins[5]). Regards, Tilman [5] https://archive.ph/2023.06.15-173527/https://www.marketwatch.com/amp/story/… [6] https://huggingface.co/blog/huggingface-and-amd [7] See e.g. https://gpus.llm-utils.org/nvidia-h100-gpus-supply-and-demand/ (avoid playing the song though. Don't say I didn't warn you) > I wouldn't characterize WMF's Language Team using CPU as because of > AMD, rather at the time we didn't have the budget for GPUs so Lift Wing > didn't have any. Since then we have moved two GPUs onto Lift Wing for > testing but they are pretty old (2017ish). Once we make the big GPU > purchase Lift Wing will gain a lot of functionality for LLM and similar > models. > > Chris > > On Sun, Aug 6, 2023 at 9:57 PM Tilman Bayer <haebwiki(a)gmail.com> > wrote: > >> On Thu, Aug 3, 2023 at 7:16 AM Chris Albon <calbon(a)wikimedia.org> >> wrote: >> >>> Hi everybody, >>> >>> TL;DR We would like users of ORES models to migrate to our new open >>> source ML infrastructure, Lift Wing, within the next five months. We are >>> available to help you do that, from advice to making code commits. It is >>> important to note: All ML models currently accessible on ORES are also >>> currently accessible on Lift Wing. >>> >>> As part of the Machine Learning Modernization Project ( >>> https://www.mediawiki.org/wiki/Machine_Learning/Modernization), the >>> Machine Learning team has deployed a Wikimedia’s new machine learning >>> inference infrastructure, called Lift Wing ( >>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing). >>> Lift Wing brings a lot of new features such as support for GPU-based >>> models, open source LLM hosting, auto-scaling, stability, and ability to >>> host a larger number of models. >>> >> >> This sounds quite exciting! What's the best place to read up on that >> planned support for GPU-based models and open source LLMs? (I also saw in >> the recent NYT article[1] that the team is "in the process of adapting A.I. >> models that are 'off the shelf; — essentially models that have been made >> available by researchers for anyone to freely customize — so that >> Wikipedia’s editors can use them for their work.") >> >> I'm aware of the history[2] of not being able to use NVIDIA GPUs due >> to their CUDA drivers being proprietary. It was mentioned recently in the >> Wikimedia AI Telegram group that this is still a serious limitation, >> despite some new explorations with AMD GPUs[3] - to the point that e.g. the >> WMF's Language team has resorted to using models without GPU support (CPU >> only).[4] >> It sounds like there is reasonable hope that this situation could >> change fairly soon? Would it also mean both at the same time, i.e. open >> source LLMs running with GPU support (considering that at least some >> well-known ones appear to require torch.cuda.is_available() == True for >> that)? >> >> Regards, Tilman >> >> [1] >> https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html >> [2] >> https://techblog.wikimedia.org/2020/04/06/saying-no-to-proprietary-code-in-… >> [3] https://phabricator.wikimedia.org/T334583 etc. >> [4] >> https://diff.wikimedia.org/2023/06/13/mint-supporting-underserved-languages… >> or https://thottingal.in/blog/2023/07/21/wikiqa/ (experimental but, >> I understand, written to be deployable on WMF infrastructure) >> >> >>> >>> With the creation of Lift Wing, the team is turning its attention to >>> deprecating the current machine learning infrastructure, ORES. ORES served >>> us really well over the years, it was a successful project but it came >>> before radical changes in technology like Docker, Kubernetes and more >>> recently MLOps. The servers that run ORES are at the end of their planned >>> lifespan and so to save cost we are going to shut them down in early 2024. >>> >>> We have outlined a deprecation path on Wikitech ( >>> https://wikitech.wikimedia.org/wiki/ORES), please read the page if >>> you are a maintainer of a tool or code that uses the ORES endpoint >>> https://ores.wikimedia.org/). If you have any doubt or if you need >>> assistance in migrating to Lift Wing, feel free to contact the ML team via: >>> >>> - Email: ml(a)wikimedia.org >>> - Phabricator: #Machine-Learning-Team tag >>> - IRC (Libera): #wikimedia-ml >>> >>> The Machine Learning team is available to help projects migrate, >>> from offering advice to making code commits. We want to make this as easy >>> as possible for folks. >>> >>> High Level timeline: >>> >>> **By September 30th 2023: *Infrastructure powering the ORES API >>> endpoint will be migrated from ORES to Lift Wing. For users, the API >>> endpoint will remain the same, and most users won’t notice any change. >>> Rather just the backend services powering the endpoint will change. >>> >>> Details: We'd like to add a DNS CNAME that points ores.wikimedia.org >>> to ores-legacy.wikimedia.org, a new endpoint that offers a almost >>> complete replacement of the ORES API calling Lift Wing behind the scenes. >>> In an ideal world we'd migrate all tools to Lift Wing before >>> decommissioning the infrastructure behind ores.wikimedia.org, but >>> it turned out to be really challenging so to avoid disrupting users we >>> chose to implement a transition layer/API. >>> >>> To summarize, if you don't have time to migrate before September to >>> Lift Wing, your code/tool should work just fine on >>> ores-legacy.wikimedia.org and you'll not have to change a line in >>> your code thanks to the DNS CNAME. The ores-legacy endpoint is not a 100% >>> replacement for ores, we removed some very old and not used features, so we >>> highly recommend at least test the new endpoint for your use case to avoid >>> surprises when we'll make the switch. In case you find anything weird, >>> please report it to us using the aforementioned channels. >>> >>> **September to January: *We will be reaching out to every user of >>> ORES we can identify and working with them to make the migration process as >>> easy as possible. >>> >>> **By January 2024: *If all goes well, we would like zero traffic on >>> the ORES API endpoint so we can turn off the ores-legacy API. >>> >>> If you want more information about Lift Wing, please check >>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing >>> >>> Thanks in advance for the patience and the help! >>> >>> Regards, >>> >>> The Machine Learning Team >>> _______________________________________________ >>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>> To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org >>> >>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >> >> _______________________________________________ >> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >> To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org >> >> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ > > _______________________________________________ > Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org > To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org > > https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ _______________________________________________ Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/

Hello! As a next step in the deprecation process of ORES https://wikitech.wikimedia.org/wiki/ORES the Machine Learning team will switch the backend of ores.wikimedia.org to ores-legacy, a k8s application meant to provide a compatibility layer between ORES and Lift Wing so users that have not yet migrated to Lift Wing will be transparently migrated. Ores-legacy is an application that has the same API as ORES but in the background makes requests to Lift Wing, allowing us to decommission the ORES servers until all clients have moved. This change is planned to take place on Monday 25th of September. If you have a client/application that is still using ORES we expect that this switch is going to be transparent for you. However keep in mind that ores-legacy is not a 100% replacement for ORES as some old and unused features are no longer supported. If you see anything out of the ordinary, feel free to contact the Machine Learning team: IRC libera: #wikimedia-ml Phabricator: Machine-Learning-team tag Thank you! On Wed, Aug 9, 2023 at 1:22 PM Chaloemphon Praphuchakang < yoshrakpraphu(a)gmail.com&gt; wrote: > > On Tue, 8 Aug 2023, 10:45 Tilman Bayer, &lt;haebwiki(a)gmail.com&gt; wrote: > >> >> Hi Chris, >> >> On Mon, Aug 7, 2023 at 11:51 AM Chris Albon &lt;calbon(a)wikimedia.org&gt; >> wrote: >> >>> Hi Tilman, >>> >>> Most of the work is still very experimental. We have hosted a few >>> LLMs on Lift Wing already (StarCoder for example) but they were just >>> running on CPU, far too slow for real use cases. But it proves that we can >>> easily host LLMs on Lift Wing. We have been pretty quiet about it while we >>> focus on the ORES migration, but it is our next big project. More soon >>> hopefully! >>> >> Understood. Looking forward to learning more later! >> >> >>> Where we are now is that we have budget for a big GPU purchase >>> (~10-20 GPUs depending on cost), the question we will try to answer after >>> the ORES migration is complete is: what GPUs should we purchase? We are >>> trying to balance our strong preference to stay open source (i.e. AMD mROC) >>> in a world dominated by a single closed source vendor (i.e. Nvidia). In >>> addition, do we go for a few expensive GPUs better suited to LLMs (A1000, >>> H100, etc) or a mix of big and small? We will need to figure out all this. >>> >> I see. On that matter, what do you folks make of the recent >> announcements of AMD's partnerships with Hugging Face and Pytorch[5]? >> (which, I understand, came after the ML team had already launched the >> aforementioned new AMD explorations) >> >> "Open-source AI: AMD looks to Hugging Face and Meta spinoff PyTorch >> to take on Nvidia [...] >> Both partnerships involve AMD’s ROCm AI software stack, the company’s >> answer to Nvidia’s proprietary CUDA platform and application-programming >> interface. AMD called ROCm an open and portable AI system with >> out-of-the-box support that can port to existing AI models. [...B]oth AMD >> and Hugging Face are dedicating engineering resources to each other and >> sharing data to ensure that the constantly updated AI models from Hugging >> Face, which might not otherwise run well on AMD hardware, would be >> “guaranteed” to work on hardware like the MI300X. [...] AMD said PyTorch >> will fully upstream the ROCm software stack and “provide immediate ‘day >> zero’ support for PyTorch 2.0 with ROCm release 5.4.2 on all AMD Instinct >> accelerators,” which is meant to appeal to those customers looking to >> switch from Nvidia’s software ecosystem." >> >> >> In their own announcement, Hugging Face offered further details, >> including a pretty impressive list of models to be supported:[6] >> >> >> "We intend to support state-of-the-art transformer architectures for >> natural language processing, computer vision, and speech, such as BERT, >> DistilBERT, ROBERTA, Vision Transformer, CLIP, and Wav2Vec2. Of course, >> generative AI models will be available too (e.g., GPT2, GPT-NeoX, T5, OPT, >> LLaMA), including our own BLOOM and StarCoder models. Lastly, we will also >> support more traditional computer vision models, like ResNet and ResNext, >> and deep learning recommendation models, a first for us. [..] We'll do our >> best to test and validate these models for PyTorch, TensorFlow, and ONNX >> Runtime for the above platforms. [...] We will integrate the AMD ROCm SDK >> seamlessly in our open-source libraries, starting with the transformers >> library." >> >> >> Do you think this may promise too much, or could it point to a >> possible solution of the Foundation's conundrum? >> In any case, this seems to be an interesting moment where many in AI >> are trying to move away from Nvidia's proprietary CUDA platform. Most of >> them probably more for financial and availability reasons though, given the >> current GPU shortages[7] (which the ML team is undoubtedly aware of >> already; mentioning this as context for others on this list. See also >> Marketwatch's remarks about current margins[5]). >> >> Regards, Tilman >> >> >> [5] >> https://archive.ph/2023.06.15-173527/https://www.marketwatch.com/amp/story/… >> [6] https://huggingface.co/blog/huggingface-and-amd >> [7] See e.g. >> https://gpus.llm-utils.org/nvidia-h100-gpus-supply-and-demand/ >> (avoid playing the song though. Don't say I didn't warn you) >> >> >>> I wouldn't characterize WMF's Language Team using CPU as because of >>> AMD, rather at the time we didn't have the budget for GPUs so Lift Wing >>> didn't have any. Since then we have moved two GPUs onto Lift Wing for >>> testing but they are pretty old (2017ish). Once we make the big GPU >>> purchase Lift Wing will gain a lot of functionality for LLM and similar >>> models. >>> >>> Chris >>> >>> On Sun, Aug 6, 2023 at 9:57 PM Tilman Bayer &lt;haebwiki(a)gmail.com&gt; >>> wrote: >>> >>>> On Thu, Aug 3, 2023 at 7:16 AM Chris Albon &lt;calbon(a)wikimedia.org&gt; >>>> wrote: >>>> >>>>> Hi everybody, >>>>> >>>>> TL;DR We would like users of ORES models to migrate to our new >>>>> open source ML infrastructure, Lift Wing, within the next five months. We >>>>> are available to help you do that, from advice to making code commits. It >>>>> is important to note: All ML models currently accessible on ORES are also >>>>> currently accessible on Lift Wing. >>>>> >>>>> As part of the Machine Learning Modernization Project ( >>>>> https://www.mediawiki.org/wiki/Machine_Learning/Modernization), >>>>> the Machine Learning team has deployed a Wikimedia’s new machine learning >>>>> inference infrastructure, called Lift Wing ( >>>>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing). >>>>> Lift Wing brings a lot of new features such as support for GPU-based >>>>> models, open source LLM hosting, auto-scaling, stability, and ability to >>>>> host a larger number of models. >>>>> >>>> >>>> This sounds quite exciting! What's the best place to read up on >>>> that planned support for GPU-based models and open source LLMs? (I also saw >>>> in the recent NYT article[1] that the team is "in the process of adapting >>>> A.I. models that are 'off the shelf; — essentially models that have been >>>> made available by researchers for anyone to freely customize — so that >>>> Wikipedia’s editors can use them for their work.") >>>> >>>> I'm aware of the history[2] of not being able to use NVIDIA >>>> GPUs due to their CUDA drivers being proprietary. It was mentioned recently >>>> in the Wikimedia AI Telegram group that this is still a serious limitation, >>>> despite some new explorations with AMD GPUs[3] - to the point that e.g. the >>>> WMF's Language team has resorted to using models without GPU support (CPU >>>> only).[4] >>>> It sounds like there is reasonable hope that this situation could >>>> change fairly soon? Would it also mean both at the same time, i.e. open >>>> source LLMs running with GPU support (considering that at least some >>>> well-known ones appear to require torch.cuda.is_available() == True for >>>> that)? >>>> >>>> Regards, Tilman >>>> >>>> [1] >>>> https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html >>>> [2] >>>> https://techblog.wikimedia.org/2020/04/06/saying-no-to-proprietary-code-in-… >>>> [3] https://phabricator.wikimedia.org/T334583 etc. >>>> [4] >>>> https://diff.wikimedia.org/2023/06/13/mint-supporting-underserved-languages… >>>> or https://thottingal.in/blog/2023/07/21/wikiqa/ (experimental >>>> but, I understand, written to be deployable on WMF infrastructure) >>>> >>>> >>>>> >>>>> With the creation of Lift Wing, the team is turning its attention >>>>> to deprecating the current machine learning infrastructure, ORES. ORES >>>>> served us really well over the years, it was a successful project but it >>>>> came before radical changes in technology like Docker, Kubernetes and more >>>>> recently MLOps. The servers that run ORES are at the end of their planned >>>>> lifespan and so to save cost we are going to shut them down in early 2024. >>>>> >>>>> We have outlined a deprecation path on Wikitech ( >>>>> https://wikitech.wikimedia.org/wiki/ORES), please read the page >>>>> if you are a maintainer of a tool or code that uses the ORES endpoint >>>>> https://ores.wikimedia.org/). If you have any doubt or if you >>>>> need assistance in migrating to Lift Wing, feel free to contact the ML team >>>>> via: >>>>> >>>>> - Email: ml(a)wikimedia.org >>>>> - Phabricator: #Machine-Learning-Team tag >>>>> - IRC (Libera): #wikimedia-ml >>>>> >>>>> The Machine Learning team is available to help projects migrate, >>>>> from offering advice to making code commits. We want to make this as easy >>>>> as possible for folks. >>>>> >>>>> High Level timeline: >>>>> >>>>> **By September 30th 2023: *Infrastructure powering the ORES API >>>>> endpoint will be migrated from ORES to Lift Wing. For users, the API >>>>> endpoint will remain the same, and most users won’t notice any change. >>>>> Rather just the backend services powering the endpoint will change. >>>>> >>>>> Details: We'd like to add a DNS CNAME that points >>>>> ores.wikimedia.org to ores-legacy.wikimedia.org, a new endpoint >>>>> that offers a almost complete replacement of the ORES API calling Lift Wing >>>>> behind the scenes. In an ideal world we'd migrate all tools to Lift Wing >>>>> before decommissioning the infrastructure behind >>>>> ores.wikimedia.org, but it turned out to be really challenging so >>>>> to avoid disrupting users we chose to implement a transition layer/API. >>>>> >>>>> To summarize, if you don't have time to migrate before September >>>>> to Lift Wing, your code/tool should work just fine on >>>>> ores-legacy.wikimedia.org and you'll not have to change a line in >>>>> your code thanks to the DNS CNAME. The ores-legacy endpoint is not a 100% >>>>> replacement for ores, we removed some very old and not used features, so we >>>>> highly recommend at least test the new endpoint for your use case to avoid >>>>> surprises when we'll make the switch. In case you find anything weird, >>>>> please report it to us using the aforementioned channels. >>>>> >>>>> **September to January: *We will be reaching out to every user of >>>>> ORES we can identify and working with them to make the migration process as >>>>> easy as possible. >>>>> >>>>> **By January 2024: *If all goes well, we would like zero traffic >>>>> on the ORES API endpoint so we can turn off the ores-legacy API. >>>>> >>>>> If you want more information about Lift Wing, please check >>>>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing >>>>> >>>>> Thanks in advance for the patience and the help! >>>>> >>>>> Regards, >>>>> >>>>> The Machine Learning Team >>>>> _______________________________________________ >>>>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>>>> To unsubscribe send an email to >>>>> wikitech-l-leave(a)lists.wikimedia.org >>>>> >>>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>>> >>>> _______________________________________________ >>>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>>> To unsubscribe send an email to >>>> wikitech-l-leave(a)lists.wikimedia.org >>>> >>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>> >>> _______________________________________________ >>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>> To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org >>> >>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >> >> _______________________________________________ >> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >> To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org >> >> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ > > _______________________________________________ > Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org > To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org > > https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ _______________________________________________ Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/

Hi Aaron! Thanks for following up. The API is almost compatible with what ORES currently does, but there are limitations (like the max number of revisions in a batch etc..). The API clearly states when something is not supported, so you can check its compatibility now making some requests to: https://ores-legacy.wikimedia.org If you open a task with a list of systems that you need to migrate we can definitely take a look and help. So far the traffic being served by ORES has been reduced to few clients, and all of them don't run with recognizable UAs (see https://meta.wikimedia.org/wiki/User-Agent_policy) so we'll try our best to support them. The migration to Lift Wing has been widely publicized, a lot of documentation is available to migrate. We'd suggest trying Lift Wing for your systems instead (see https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing/Usage). The Machine Learning plan is to eventually deprecate ores-legacy too, to maintain only one system (namely Lift Wing). There is no final date yet, we'll try to reach out to all remaining users first, so if you plan to keep using ores-legacy please follow up with us first :) Thanks! Luca (on behalf of the ML Team) On Fri, Sep 22, 2023 at 5:10 PM Aaron Halfaker < aaron.halfaker(a)gmail.com&gt; wrote: > Does the new ores-legacy support the same feature set. E.g. features > output, injection, and threshold optimizations. Or is it just prediction? > This will affect some of the systems I need to migrate. > > On Fri, Sep 22, 2023, 06:21 Ilias Sarantopoulos < > isarantopoulos(a)wikimedia.org&gt; wrote: > >> Hello! >> >> >> As a next step in the deprecation process of ORES >> https://wikitech.wikimedia.org/wiki/ORES the Machine Learning team will >> switch the backend of ores.wikimedia.org to ores-legacy, a k8s >> application meant to provide a compatibility layer between ORES and Lift >> Wing so users that have not yet migrated to Lift Wing will be >> transparently migrated. Ores-legacy is an application that has the same API >> as ORES but in the background makes requests to Lift Wing, allowing us to >> decommission the ORES servers until all clients have moved. >> >> This change is planned to take place on Monday 25th of September. If >> you have a client/application that is still using ORES we expect that this >> switch is going to be transparent for you. >> >> However keep in mind that ores-legacy is not a 100% replacement for >> ORES as some old and unused features are no longer supported. >> >> If you see anything out of the ordinary, feel free to contact the >> Machine Learning team: >> >> IRC libera: #wikimedia-ml >> >> Phabricator: Machine-Learning-team tag >> >> Thank you! >> >> >> On Wed, Aug 9, 2023 at 1:22 PM Chaloemphon Praphuchakang < >> yoshrakpraphu(a)gmail.com&gt; wrote: >> >>> >>> On Tue, 8 Aug 2023, 10:45 Tilman Bayer, &lt;haebwiki(a)gmail.com&gt; wrote: >>> >>>> >>>> Hi Chris, >>>> >>>> On Mon, Aug 7, 2023 at 11:51 AM Chris Albon &lt;calbon(a)wikimedia.org&gt; >>>> wrote: >>>> >>>>> Hi Tilman, >>>>> >>>>> Most of the work is still very experimental. We have hosted a few >>>>> LLMs on Lift Wing already (StarCoder for example) but they were just >>>>> running on CPU, far too slow for real use cases. But it proves that we can >>>>> easily host LLMs on Lift Wing. We have been pretty quiet about it while we >>>>> focus on the ORES migration, but it is our next big project. More soon >>>>> hopefully! >>>>> >>>> Understood. Looking forward to learning more later! >>>> >>>> >>>>> Where we are now is that we have budget for a big GPU purchase >>>>> (~10-20 GPUs depending on cost), the question we will try to answer after >>>>> the ORES migration is complete is: what GPUs should we purchase? We are >>>>> trying to balance our strong preference to stay open source (i.e. AMD mROC) >>>>> in a world dominated by a single closed source vendor (i.e. Nvidia). In >>>>> addition, do we go for a few expensive GPUs better suited to LLMs (A1000, >>>>> H100, etc) or a mix of big and small? We will need to figure out all this. >>>>> >>>> I see. On that matter, what do you folks make of the recent >>>> announcements of AMD's partnerships with Hugging Face and Pytorch[5]? >>>> (which, I understand, came after the ML team had already launched the >>>> aforementioned new AMD explorations) >>>> >>>> "Open-source AI: AMD looks to Hugging Face and Meta spinoff PyTorch >>>> to take on Nvidia [...] >>>> Both partnerships involve AMD’s ROCm AI software stack, the >>>> company’s answer to Nvidia’s proprietary CUDA platform and >>>> application-programming interface. AMD called ROCm an open and portable AI >>>> system with out-of-the-box support that can port to existing AI models. >>>> [...B]oth AMD and Hugging Face are dedicating engineering resources to each >>>> other and sharing data to ensure that the constantly updated AI models from >>>> Hugging Face, which might not otherwise run well on AMD hardware, would be >>>> “guaranteed” to work on hardware like the MI300X. [...] AMD said PyTorch >>>> will fully upstream the ROCm software stack and “provide immediate ‘day >>>> zero’ support for PyTorch 2.0 with ROCm release 5.4.2 on all AMD Instinct >>>> accelerators,” which is meant to appeal to those customers looking to >>>> switch from Nvidia’s software ecosystem." >>>> >>>> >>>> In their own announcement, Hugging Face offered further details, >>>> including a pretty impressive list of models to be supported:[6] >>>> >>>> >>>> "We intend to support state-of-the-art transformer architectures >>>> for natural language processing, computer vision, and speech, such as BERT, >>>> DistilBERT, ROBERTA, Vision Transformer, CLIP, and Wav2Vec2. Of course, >>>> generative AI models will be available too (e.g., GPT2, GPT-NeoX, T5, OPT, >>>> LLaMA), including our own BLOOM and StarCoder models. Lastly, we will also >>>> support more traditional computer vision models, like ResNet and ResNext, >>>> and deep learning recommendation models, a first for us. [..] We'll do our >>>> best to test and validate these models for PyTorch, TensorFlow, and ONNX >>>> Runtime for the above platforms. [...] We will integrate the AMD ROCm SDK >>>> seamlessly in our open-source libraries, starting with the transformers >>>> library." >>>> >>>> >>>> Do you think this may promise too much, or could it point to a >>>> possible solution of the Foundation's conundrum? >>>> In any case, this seems to be an interesting moment where many in >>>> AI are trying to move away from Nvidia's proprietary CUDA platform. Most of >>>> them probably more for financial and availability reasons though, given the >>>> current GPU shortages[7] (which the ML team is undoubtedly aware of >>>> already; mentioning this as context for others on this list. See also >>>> Marketwatch's remarks about current margins[5]). >>>> >>>> Regards, Tilman >>>> >>>> >>>> [5] >>>> https://archive.ph/2023.06.15-173527/https://www.marketwatch.com/amp/story/… >>>> [6] https://huggingface.co/blog/huggingface-and-amd >>>> [7] See e.g. >>>> https://gpus.llm-utils.org/nvidia-h100-gpus-supply-and-demand/ >>>> (avoid playing the song though. Don't say I didn't warn you) >>>> >>>> >>>>> I wouldn't characterize WMF's Language Team using CPU as because >>>>> of AMD, rather at the time we didn't have the budget for GPUs so Lift Wing >>>>> didn't have any. Since then we have moved two GPUs onto Lift Wing for >>>>> testing but they are pretty old (2017ish). Once we make the big GPU >>>>> purchase Lift Wing will gain a lot of functionality for LLM and similar >>>>> models. >>>>> >>>>> Chris >>>>> >>>>> On Sun, Aug 6, 2023 at 9:57 PM Tilman Bayer &lt;haebwiki(a)gmail.com&gt; >>>>> wrote: >>>>> >>>>>> On Thu, Aug 3, 2023 at 7:16 AM Chris Albon &lt;calbon(a)wikimedia.org&gt; >>>>>> wrote: >>>>>> >>>>>>> Hi everybody, >>>>>>> >>>>>>> TL;DR We would like users of ORES models to migrate to our new >>>>>>> open source ML infrastructure, Lift Wing, within the next five months. We >>>>>>> are available to help you do that, from advice to making code commits. It >>>>>>> is important to note: All ML models currently accessible on ORES are also >>>>>>> currently accessible on Lift Wing. >>>>>>> >>>>>>> As part of the Machine Learning Modernization Project ( >>>>>>> https://www.mediawiki.org/wiki/Machine_Learning/Modernization), >>>>>>> the Machine Learning team has deployed a Wikimedia’s new machine learning >>>>>>> inference infrastructure, called Lift Wing ( >>>>>>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing). >>>>>>> Lift Wing brings a lot of new features such as support for GPU-based >>>>>>> models, open source LLM hosting, auto-scaling, stability, and ability to >>>>>>> host a larger number of models. >>>>>>> >>>>>> >>>>>> This sounds quite exciting! What's the best place to read up on >>>>>> that planned support for GPU-based models and open source LLMs? (I also saw >>>>>> in the recent NYT article[1] that the team is "in the process of adapting >>>>>> A.I. models that are 'off the shelf; — essentially models that have been >>>>>> made available by researchers for anyone to freely customize — so that >>>>>> Wikipedia’s editors can use them for their work.") >>>>>> >>>>>> I'm aware of the history[2] of not being able to use NVIDIA >>>>>> GPUs due to their CUDA drivers being proprietary. It was mentioned recently >>>>>> in the Wikimedia AI Telegram group that this is still a serious limitation, >>>>>> despite some new explorations with AMD GPUs[3] - to the point that e.g. the >>>>>> WMF's Language team has resorted to using models without GPU support (CPU >>>>>> only).[4] >>>>>> It sounds like there is reasonable hope that this situation could >>>>>> change fairly soon? Would it also mean both at the same time, i.e. open >>>>>> source LLMs running with GPU support (considering that at least some >>>>>> well-known ones appear to require torch.cuda.is_available() == True for >>>>>> that)? >>>>>> >>>>>> Regards, Tilman >>>>>> >>>>>> [1] >>>>>> https://www.nytimes.com/2023/07/18/magazine/wikipedia-ai-chatgpt.html >>>>>> [2] >>>>>> https://techblog.wikimedia.org/2020/04/06/saying-no-to-proprietary-code-in-… >>>>>> [3] https://phabricator.wikimedia.org/T334583 etc. >>>>>> [4] >>>>>> https://diff.wikimedia.org/2023/06/13/mint-supporting-underserved-languages… >>>>>> or https://thottingal.in/blog/2023/07/21/wikiqa/ (experimental >>>>>> but, I understand, written to be deployable on WMF infrastructure) >>>>>> >>>>>> >>>>>>> >>>>>>> With the creation of Lift Wing, the team is turning its >>>>>>> attention to deprecating the current machine learning infrastructure, ORES. >>>>>>> ORES served us really well over the years, it was a successful project but >>>>>>> it came before radical changes in technology like Docker, Kubernetes and >>>>>>> more recently MLOps. The servers that run ORES are at the end of their >>>>>>> planned lifespan and so to save cost we are going to shut them down in >>>>>>> early 2024. >>>>>>> >>>>>>> We have outlined a deprecation path on Wikitech ( >>>>>>> https://wikitech.wikimedia.org/wiki/ORES), please read the page >>>>>>> if you are a maintainer of a tool or code that uses the ORES endpoint >>>>>>> https://ores.wikimedia.org/). If you have any doubt or if you >>>>>>> need assistance in migrating to Lift Wing, feel free to contact the ML team >>>>>>> via: >>>>>>> >>>>>>> - Email: ml(a)wikimedia.org >>>>>>> - Phabricator: #Machine-Learning-Team tag >>>>>>> - IRC (Libera): #wikimedia-ml >>>>>>> >>>>>>> The Machine Learning team is available to help projects migrate, >>>>>>> from offering advice to making code commits. We want to make this as easy >>>>>>> as possible for folks. >>>>>>> >>>>>>> High Level timeline: >>>>>>> >>>>>>> **By September 30th 2023: *Infrastructure powering the ORES API >>>>>>> endpoint will be migrated from ORES to Lift Wing. For users, the API >>>>>>> endpoint will remain the same, and most users won’t notice any change. >>>>>>> Rather just the backend services powering the endpoint will change. >>>>>>> >>>>>>> Details: We'd like to add a DNS CNAME that points >>>>>>> ores.wikimedia.org to ores-legacy.wikimedia.org, a new endpoint >>>>>>> that offers a almost complete replacement of the ORES API calling Lift Wing >>>>>>> behind the scenes. In an ideal world we'd migrate all tools to Lift Wing >>>>>>> before decommissioning the infrastructure behind >>>>>>> ores.wikimedia.org, but it turned out to be really challenging >>>>>>> so to avoid disrupting users we chose to implement a transition layer/API. >>>>>>> >>>>>>> To summarize, if you don't have time to migrate before September >>>>>>> to Lift Wing, your code/tool should work just fine on >>>>>>> ores-legacy.wikimedia.org and you'll not have to change a line >>>>>>> in your code thanks to the DNS CNAME. The ores-legacy endpoint is not a >>>>>>> 100% replacement for ores, we removed some very old and not used features, >>>>>>> so we highly recommend at least test the new endpoint for your use case to >>>>>>> avoid surprises when we'll make the switch. In case you find anything >>>>>>> weird, please report it to us using the aforementioned channels. >>>>>>> >>>>>>> **September to January: *We will be reaching out to every user >>>>>>> of ORES we can identify and working with them to make the migration process >>>>>>> as easy as possible. >>>>>>> >>>>>>> **By January 2024: *If all goes well, we would like zero >>>>>>> traffic on the ORES API endpoint so we can turn off the ores-legacy API. >>>>>>> >>>>>>> If you want more information about Lift Wing, please check >>>>>>> https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing >>>>>>> >>>>>>> Thanks in advance for the patience and the help! >>>>>>> >>>>>>> Regards, >>>>>>> >>>>>>> The Machine Learning Team >>>>>>> _______________________________________________ >>>>>>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>>>>>> To unsubscribe send an email to >>>>>>> wikitech-l-leave(a)lists.wikimedia.org >>>>>>> >>>>>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>>>>> >>>>>> _______________________________________________ >>>>>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>>>>> To unsubscribe send an email to >>>>>> wikitech-l-leave(a)lists.wikimedia.org >>>>>> >>>>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>>>> >>>>> _______________________________________________ >>>>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>>>> To unsubscribe send an email to >>>>> wikitech-l-leave(a)lists.wikimedia.org >>>>> >>>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>>> >>>> _______________________________________________ >>>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>>> To unsubscribe send an email to >>>> wikitech-l-leave(a)lists.wikimedia.org >>>> >>>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >>> >>> _______________________________________________ >>> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >>> To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org >>> >>> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ >> >> _______________________________________________ >> Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org >> To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org >> >> https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ > > _______________________________________________ > Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org > To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org > > https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ _______________________________________________ Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/

Managing several hundreds models for goodfaith and damaging is not

(since we have a model for each supported wiki). We (both Research

All fine points. As you can see, I've filed some phab tasks where I saw a clear opportunity to do so. > as mentioned before all the models that currently run on ORES are available in both ores-legacy and Lift Wing. I thought I read that damaging and goodfaith models are going to be replaced. Should I instead read that they are likely to remain available for the foreseeable future? When I asked about a community discussion about the transition from damaging/goodfaith to revertrisk, I was imagining that many people who use those predictions might have an opinion about them going away. E.g. people who use the relevant filters in RecentChanges. Maybe I missed the discussions about that. I haven't seen a mention of the article quality or article topic models in the docs. Are those also going to remain available? I have some user scripts that use these models and are relatively widely used. I didn't notice anyone reaching out. ... So I checked and setting a User-Agent on my user scripts doesn't actually change the User-Agent. I've read that you need to set "Api-User-Agent" instead, but that causes a CORS error when querying ORES. I'll file a bug. On Fri, Sep 22, 2023 at 1:22 PM Luca Toscano &lt;ltoscano(a)wikimedia.org&gt; wrote: > > > On Fri, Sep 22, 2023 at 8:59 PM Aaron Halfaker < > aaron.halfaker(a)gmail.com&gt; wrote: > >> We could definitely file a task. However, it does seem like >> highlighting the features that will no longer be available is an >> appropriate topic for a discussion about migration in a technical mailing >> list. >> > > A specific question related to a functionality is the topic for a > task, I don't think that we should discuss every detail that differs from > the ORES API (Wikitech-l doesn't seem a good medium for it). We are already > following up on Phabricator, let's use tasks if possible to keep the > conversation as light and targeted as possible. > > Is there a good reference for which features have been excluded from >> ores-legacy? It looks like https://wikitech.wikimedia.org/wiki/ORES covers >> some of the excluded features/models, but not all of them. >> > > We spent the last months helping the community to migrate away from > the ORES API (to use Lift Wing instead), the remaining traffic is only > related to few low traffic IPs that we are not able to contact. We didn't > add feature injection or threshold optimization to ores-legacy, for > example, since there was no indication on our logs that users were relying > on it. We have always stated everywhere (including all emails sent in this > mailing list) that we are 100% open to add a functionality if it is backed > up by a valid use case. > > >> I see now that it looks like the RevertRisk model will be replacing >> the *damaging *and *goodfaith *models that differentiate intentional >> damage from unintentional damage. There's a large body of research on why >> this is valuable and important to the social functioning of the wikis. >> This literature also discusses why being reverted is not a very good signal >> for damage/vandalism and can lead to problems when used as a signal for >> patrolling. Was there a community discussion about this deprecation that I >> missed? I have some preliminary results (in press) that demonstrate that >> the RevertRisk model performs significantly worse than the damaging and >> goodfaith models in English Wikipedia for patrolling work. Do you have >> documentation for how you evaluated this model and compared it to >> damaging/goodfaith? >> > > We have model cards related to both Revert Risk models, all of them > linked in the API portal docs (more info: > https://api.wikimedia.org/wiki/Lift_Wing_API). All the community > folks that migrated their bots/tools/etc.. to Revert Risk were very happy > about the change, and we haven't had any request to switch back since then. > > The ML team provides all the models deployed on ORES on Lift Wing, so > any damaging and goodfaith variant is available in the new API. We chose to > not pursue the development of those models for several reasons: > - We haven't had any indication/request from the community about those > models in almost two years, except few Phabricator updates that we followed > up on. > - Managing several hundreds models for goodfaith and damaging is not > very scalable in a modern micro-service architecture like Lift Wing (since > we have a model for each supported wiki). We (both Research and ML) are > oriented on having fewer models that manage more languages at the same > time, and this is the direction that we are following at the moment. It may > not be the perfect one but so far it seems a good choice. If you want to > chime in and provide your inputs we are 100% available in hearing > suggestions/concerns/doubts/recommendations/etc.., please follow up in any > of our channels (IRC, mailing lists, Phabricator for example). > - Last but not the least, most of the damaging/goodfaith models have > been trained with data coming from years ago, and never re-trained. The > efforts to keep several hundreds models up-to-date with recent data versus > doing the same of few models (like revert risk) weights in favor of the > latter for a relatively small team of engineers like us. > > >> FWIW, from my reading of these announcement threads, I believed that >> generally functionality and models would be preserved in >> ores-legacy/LiftWing. This is the first time I've realized the scale of >> what will become unavailable. >> > > This is the part that I don't get, since as mentioned before all the > models that currently run on ORES are available in both ores-legacy and > Lift Wing. What changes is that we don't expose anymore functionality that > logs clearly show are not used, and that would need to be maintained and > improved over time. We are open to improve and add any requirement that the > community needs, the only thing that we ask is to provide a valid use case > to support it. > > I do think that Lift Wing is a great improvement for the community, we > have been working with all the folks that reached out to us, without hiding > anything (including deprecation plans and path forwards). > > Thanks for following up! > > Luca > _______________________________________________ > Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org > To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org > > https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/ _______________________________________________ Wikitech-l mailing list -- wikitech-l(a)lists.wikimedia.org To unsubscribe send an email to wikitech-l-leave(a)lists.wikimedia.org https://lists.wikimedia.org/postorius/lists/wikitech-l.lists.wikimedia.org/