[{"data":1,"prerenderedAt":431},["ShallowReactive",2],{"project-36667374":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":10,"maker":11,"posted_at":12,"year":13,"points":14,"comments":15,"rank_in_year":16,"shown_in_year":17,"top":18,"tier":19,"category":20,"subcategory":21,"format":22,"keywords":23,"reception":28,"sentiment":29,"stance_mix":30,"scored_comments":35,"aspects":36,"strip":45,"post_text":48,"what":49,"said":97,"maker_in_thread":208,"shape":220,"grid":224,"attempts":389,"same_week":394,"maker_shows":42,"maker_hidden":423,"reader_version":424,"card":425},"36667374","Danswer","Open-source question answering across all your docs","title","Show HN: Danswer – Open-source question answering across all your docs","https:\u002F\u002Fgithub.com\u002Fdanswer-ai\u002Fdanswer","github.com","Weves",1689000926,2023,189,66,298,3109,10,"notable","ai","enterprise search","web_app",[21,24,25,26,27],"question answering","self-hosted","llm document search","open source","curious",-0.083,{"positive":31,"neutral":32,"mixed":33,"critical":34},4,14,2,7,27,{"execution":37,"privacy":39,"idea":41,"performance":43,"design":44},{"positive":38,"critical":38},0,{"positive":38,"critical":40},6,{"positive":33,"critical":42},1,{"positive":38,"critical":38},{"positive":38,"critical":38},[46,38,38,38,46,42,46,42,46,46,46,42,47,46,38,46,42,46,47,38,38,46,47,42,47,38,46,46,46,46,42,38,38,38,38,38,38,38,38,38],3,5,"My friend and I have been feeling frustrated at how inefficient it is to find information at work. There are so many tools (Slack, Confluence, GitHub, Jira, Google Drive, etc.) and they provide different (often not great) ways to find information. We thought maybe LLMs could help, so over the last couple months we've been spending a bit of time on the side to build Danswer.\n\nIt is an open source, self-hosted search tool that allows you to ask questions and get answers across common workspace apps AND your personal documents (via file upload \u002F web scraping)! Full demo here: https:\u002F\u002Fwww.youtube.",{"problem":50,"audience":56,"pricing":64,"motivation":65,"time_to_build":64,"stack":69,"openness":94,"stage":95,"team_size":96},{"value":51,"source":52,"evidence":53},"Finding information across scattered workplace tools like Slack, Confluence, GitHub, Jira and Drive is inefficient","maker",[54],{"id":55},"post",{"value":57,"source":58,"evidence":59},"Workers and enterprises searching internal documents and workplace apps","inferred",[60,61],{"id":55},{"id":62,"by":11,"text":63},"36672652","Native support for the Microsoft suite of tools is something we plan to add fairly soon! We're a small team, and currently swamped with connector\u002Ffeature requests so no promises…",null,{"value":66,"source":52,"evidence":67},"Frustration with inefficient information finding at work",[68],{"id":55},[70,76,86],{"value":71,"source":52,"evidence":72},"OpenAI models for generation",[73],{"id":74,"by":11,"text":75},"36703108","Right now, Danswer does send data to OpenAI. Once we support locally hosted, open source generative models that will change. If you go with that option, your data won't be sent…",{"value":77,"source":52,"evidence":78},"Qdrant vector database",[79,83],{"id":80,"by":81,"text":82},"36671792","andre-z","We at Qdrant are glad to be a part of this awesome solution, providing the Vector Database resource for Danswer. https:\u002F\u002Fgithub.com\u002Fqdrant\u002Fqdrant",{"id":84,"by":11,"text":85},"36672709","Amazing foundational tools like Qdrant make building in this space so much easier \u003C3",{"value":87,"source":88,"evidence":89},"Next.js frontend","commenter",[90],{"id":91,"by":92,"text":93},"36676144","quickthrower2","Cool, written in NextJS! Are you taking on new contributors? I would be interested in adding Azure OpenAI support and OneNote support.","open_source","beta","team",{"praise":98,"objections":106,"requests":136,"questions":170,"alternatives":192},[99],{"value":100,"source":88,"evidence":101},"Accurate answers with source links in testing",[102],{"id":103,"by":104,"text":105},"36667949","ssddanbrown","I maintain an open source documentation platform, for which I had received a few queries about AI tooling. I'm not into the AI world of development, and my tech stack &…",[107,122,132],{"value":108,"source":88,"evidence":109},"Only works with OpenAI, so sending company data externally is a blocker",[110,114,118],{"id":111,"by":112,"text":113},"36667981","danpetrov","Sadly completely unusuable for our usecase - if you are targeting Enterprise, you should know better than to use OpenAI models as the only LLM available. For now I will stick to…",{"id":115,"by":116,"text":117},"36668637","Intox","Another great tool solving the exact problem we're willing to solve using an external service we can't use. No company at a decent size (those who actually reach some complexity…",{"id":119,"by":120,"text":121},"36674848","TeMPOraL","From FAQ: > Danswer provides Docker containers that you can run anywhere, so data never has to leave your PVC. The one exception is using GPT for inference but we are working on…",{"value":123,"source":88,"evidence":124},"Access control is basic; private docs leak to all users",[125,129],{"id":126,"by":127,"text":128},"36668505","lmeyerov","How are you thinking about the \"document level access control\" to make this viable for business environments? Ex: If a connected gdrive document gets indexed, but then someone…",{"id":130,"by":11,"text":131},"36673151","Great question! Right now, our access control is very basic. When admins setup connectors to other apps, all documents indexed are accessible by all (meant to be public documents…",{"value":133,"source":88,"evidence":134},"Heavy to run, long docker build",[135],{"id":103,"by":104,"text":105},[137,149,156,163],{"value":138,"source":88,"evidence":139},"Support for local open source models",[140,141,145],{"id":111,"by":112,"text":113},{"id":142,"by":143,"text":144},"36669530","XCSme","Wait, this is not local? Why use OpenAI third-party requests instead of a local model?",{"id":146,"by":147,"text":148},"36672389","lastdong","Noooooooo, not openAI! It looks perfect, just allow to run models like Vicuna or Llama locally - well, since it’s open source anyone can contribute to make this happen. Thank you…",{"value":150,"source":88,"evidence":151},"Azure OpenAI support",[152,153],{"id":119,"by":120,"text":121},{"id":154,"by":120,"text":155},"36674870","At the very least, I'd start with adding support for the Azure flavor of OpenAI API. It's literally the same models, but the difference is that it's your company deploying those…",{"value":157,"source":88,"evidence":158},"Microsoft 365, SharePoint and OneDrive connectors",[159],{"id":160,"by":161,"text":162},"36668774","TommyCat","Looks great and will test it out, but for enterprises definitely needs support for Azure\u002FOffice 365 integration to index Word, Excel, etc. Lots of docs are stored in Onedrive,…",{"value":164,"source":88,"evidence":165},"Notion connector",[166],{"id":167,"by":168,"text":169},"36671163","tibanne","This looks interesting. Thank you for making public. I made something similar that uses data from only Notion. Do you happen to have \u002F be developing a Notion connector?",[171,178,185],{"value":172,"source":88,"evidence":173},"How does it compare to llama-index",[174],{"id":175,"by":176,"text":177},"36670423","nbulka","how does this compare to llama-index",{"value":179,"source":88,"evidence":180},"Why not build on LangChain or similar frameworks",[181],{"id":182,"by":183,"text":184},"36669963","kaismh","The video looks impressive, well done. Why didn't you build it on top of langchain or other similar frameworks?",{"value":186,"source":88,"evidence":187},"Business model",[188],{"id":189,"by":190,"text":191},"36667786","sixhobbits","I've seen a few of these, and this one looks like it is more feature complete than many (e.g. including web scraping I think is an important component). Looks nice! Curious about…",[193,197,201],{"value":194,"source":88,"evidence":195},"PrivateGPT and LocalGPT",[196],{"id":111,"by":112,"text":113},{"value":198,"source":88,"evidence":199},"llama-index",[200],{"id":175,"by":176,"text":177},{"value":202,"source":88,"evidence":203},"osschat.io",[204],{"id":205,"by":206,"text":207},"36674445","ChrisPzilla","Check this out. Built on a vector database (https:\u002F\u002Fgithub.com\u002Fmilvus-io\u002Fmilvus) and a semantic cache (https:\u002F\u002Fgithub.com\u002Fzilliztech\u002FGPTCache) https:\u002F\u002Fosschat.io\u002F",{"comments":32,"answered":209,"key":210},9,[211,214,217],{"id":212,"text":213},"36673336","Agree with the point about intelligent chunking being very important! Each individual app connector can choose how it wants to split each `document` into `section`s (important…",{"id":215,"text":216},"36668270","Yea, that's good feedback - we've gotten requests for open source model support from a lot from people we've talked about. It's one of our highest priorities, and should be…",{"id":218,"text":219},"36677532","That's a good suggestion! Will look into it, should be fairly easy to support",{"commenters":221,"max_depth":34,"maker_replies":32,"first_comment_mins":222,"lifespan_hours":223},41,30,221,[225,227,231,235,238,241,243,247,250,252,254,258,261,264,265,267,268,269,270,274,277,279,281,283,285,287,288,290,292,295,297,300,301,303,307,311,312,316,318,320,322,324,327,329,332,335,337,340,342,344,346,348,352,355,358,362,365,367,369,372,375,378,380,382,384,387],[103,38,46,226,104,38],"project\u002Fmixed\u002Fexecution",[228,38,38,229,230,38],"36673214","commenter\u002Fneutral\u002Fnone","gardnr",[232,38,38,233,234,38],"36675376","other\u002Fneutral\u002Fnone","sodality2",[236,38,38,233,237,38],"36675580","mikeravkine",[239,42,38,233,240,38],"36669375","PeterStuer",[212,42,38,242,11,42],"project\u002Fneutral\u002Fdesign",[244,42,46,245,246,38],"36674522","maker\u002Fneutral\u002Fexecution","darkteflon",[248,42,38,233,249,38],"36674330","andy99",[111,33,42,251,112,38],"project\u002Fcritical\u002Fprivacy",[215,33,38,253,11,42],"maker\u002Fneutral\u002Fnone",[255,33,46,256,257,38],"36669686","project\u002Fneutral\u002Fnone","adr1an",[259,33,42,251,260,38],"36668509","jagtstronaut",[262,33,42,251,263,38],"36679190","avereveard",[154,33,46,256,120,38],[119,46,46,266,120,38],"project\u002Fneutral\u002Fprivacy",[218,46,38,253,11,42],[126,31,46,266,127,38],[130,31,38,266,11,42],[271,47,42,272,273,38],"36669377","project\u002Fcritical\u002Fidea","ttul",[275,47,38,233,276,38],"36676579","Solvency",[80,40,47,278,81,38],"project\u002Fpositive\u002Fnone",[84,40,38,280,11,42],"other\u002Fpositive\u002Fnone",[282,40,46,245,246,38],"36674743",[284,40,38,233,81,38],"36677221",[160,34,46,286,161,38],"project\u002Fmixed\u002Fidea",[62,34,38,253,11,42],[142,289,42,251,143,38],8,[291,289,38,256,11,42],"36671658",[293,289,46,294,120,38],"36674884","project\u002Fneutral\u002Fperformance",[189,209,47,296,190,38],"project\u002Fpositive\u002Fidea",[298,209,38,299,11,42],"36668322","maker\u002Fneutral\u002Fidea",[205,18,38,233,206,38],[302,18,38,233,246,38],"36674699",[304,18,38,305,306,38],"36678059","other\u002Fcritical\u002Fexecution","zX41ZdbW",[308,309,46,266,310,38],"36695802",11,"laylower",[74,309,38,266,11,42],[313,314,47,296,315,38],"36670793",12,"JimmyRuska",[146,317,42,251,147,38],13,[167,32,46,319,168,38],"project\u002Fneutral\u002Fidea",[321,32,38,253,11,42],"36671295",[91,323,47,278,92,38],15,[325,323,38,326,11,42],"36703116","maker\u002Fpositive\u002Fnone",[182,328,46,242,183,38],16,[330,328,38,331,11,42],"36671406","maker\u002Fneutral\u002Fdesign",[333,328,46,245,334,38],"36792355","dadsquad",[175,336,46,256,176,38],17,[338,336,46,256,339,38],"36671395","monkeydust",[341,336,38,242,11,42],"36671622",[343,336,46,331,334,38],"36696919",[345,336,38,331,11,42],"36703131",[115,347,42,251,116,38],18,[349,347,38,350,351,38],"36669929","commenter\u002Fneutral\u002Fprivacy","dimal",[353,347,38,350,354,38],"36670596","nrjames",[356,347,38,229,357,38],"36672077","rolisz",[359,347,38,360,361,38],"36671643","other\u002Fneutral\u002Fprivacy","ixfo",[363,347,38,360,364,38],"36671717","floomk",[366,347,38,350,351,38],"36674365",[368,347,38,350,120,38],"36674712",[370,347,38,350,371,38],"36672343","jsiepkes",[373,347,38,350,374,38],"36673997","curl-up",[376,347,38,350,377,38],"36674316","Epa095",[379,347,38,350,351,38],"36674437",[381,347,38,350,377,38],"36674757",[383,347,38,350,120,38],"36674634",[385,347,38,350,386,38],"36677602","ibestvina",[388,347,38,233,357,38],"36671499",[390,391],{"id":4,"t":12,"points":14,"comments":15},{"id":392,"t":393,"points":46,"comments":38},"42116101",1731424640,[395,400,404,409,413,418],{"id":396,"name":397,"points":398,"category":399},"36662655","Workout.lol",993,"consumer_social",{"id":401,"name":402,"points":403,"category":399},"36686672","LandCamp",348,{"id":405,"name":406,"points":407,"category":408},"36627112","hackernews-personal-blogs",281,"learning_science",{"id":410,"name":411,"points":412,"category":399},"36613727","Blogs.hn",224,{"id":414,"name":415,"points":416,"category":417},"36676415","Laser",218,"games",{"id":419,"name":420,"points":421,"category":422},"36672957","hamt",171,"languages",false,"v2",{"id":426,"name":5,"line":6,"ai":423,"cat":20,"year":13,"points":14,"comments":15,"rec":28,"s":427,"top":18,"kw":428,"maker":11,"domain":10,"tier":19,"attempts":33,"strip":429,"url":9,"mix":430,"praise":100,"objection":108,"sub":21},36667374,-0.08,[21,24,25,26,27],"3000313133315303135003515033331000000000",[31,32,33,34],1794036638252]