Chroma @trychroma
the AI-native open-source embedding database https://t.co/lNBGVvILsE https://t.co/CBw8N9F5MW discord.gg/MMeYNTmh3x Joined March 2022-
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join Chroma We’re looking for curious people who are dedicated to becoming world-class at their craft to join our team. There is a lot of important work to do. Join us. careers.trychroma.com
I have just released a new cut of the @trychroma Ruby client. It is just a maintenance release. Jupyter notebook includes an example to create embedding using @ollama and Nomic embed text model. github.com/mariochavez/ch…
check out the list here: enterprisetech30.com
lots to do. we are hiring: trychroma.notion.site/careers-chroma…
but the most valuable ai applications have yet to be discovered. chroma's role in the ecosystem is to enable as much experimentation as possible by making retrieval 'just work', while constantly improving the quality of retrieved results. x.com/atroyn/status/…
but the most valuable ai applications have yet to be discovered. chroma's role in the ecosystem is to enable as much experimentation as possible by making retrieval 'just work', while constantly improving the quality of retrieved results. x.com/atroyn/status/…
we're doing important work. ai applications process new kinds of data in new ways, which means they need new data infrastructure to be invented. in fact this data infra is how you get ai into your organization. x.com/atroyn/status/…
we're doing important work. ai applications process new kinds of data in new ways, which means they need new data infrastructure to be invented. in fact this data infra is how you get ai into your organization. x.com/atroyn/status/…
chroma has been nominated to @Wing_VC's annual 'enterprise tech 30' list, highlighting 'the most promising private companies in enterprise technology'. i'm not usually big on industry lists but we're in good company on this one. ai applications are a big deal!
Chroma Community Town Halls are back March 27 - 10:30am pacific - 1:30pm eastern lu.ma/yplm9s5d
we are interested in effective demonstrations of these capabilities, far more than full-fledged products. take voyager as your inspiration: voyager.minedojo.org look into the future of what might be possible, even as a toy, rather than what might be commercially viable today.
*multi-modal systems* - llms are now capable of processing not just text, but also images, and audio. chroma supports multi-modal retrieval, and we want to see exciting applications of these capabilities.
*systems that explore* - programs that are capable of recognizing when knowledge is not yet available, and either ask for help, or autonomously seek out relevant new knowledge as needed. they might use retrieval to figure out what they don't yet know, and where to find out.
*systems that learn* - programs which improve and adapt either implicitly through use, or explicitly by being taught and then remembering skills they've learned at the right time. they might use retrieval to store and remember skills and tools.
*autonomous ai systems* - programs backed by llms which are capable of operating on their own, without direct human prompting, to run a process, gather information, or accomplish a goal. They might use retrieval for their working memory.
by popular demand, chroma is supporting backdrop build v3. we have grants available for excellent projects in the following categories:
by popular demand, chroma is supporting backdrop build v3. we have grants available for excellent projects in the following categories:
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oh god website went viral and i now have a 600$ @posthog bill
I recorded a tutorial on how to build a #RAG pipeline to chat with your PDFs locally. Here's what I used: 🚀 @ollama → for local models 🔗 @LangChainAI & @UnstructuredIO → simplifies PDF processing and chat 🕸️ @nomic_ai → embedding model nomic-embed-text 🤖 @AIatMeta →…
So how long does it take to build a RAG app in pure Typescript? Try 5 minutes. Just add a dash of @ollama and a pinch of @trychroma and you are set. youtu.be/8rz9axIzIy4 But if the sad state of PDF conversion triggers you, stay away.
There are three ways to run @trychroma for your @ollama #RAG app. This short video will show you how:
Creating a #RAG app is pretty simple when using @ollama and @trychroma. With this video you can write the basics in #Python in just a few minutes and start asking questions to your documents: youtu.be/GxLoMquHynY #llm #ai #localai #Pythonprogramming
Anant (@indstryoutsider) is documenting the Renaissance movement happening in San Francisco like no one else. you can check his work at anantsinha dot xyz.
This is a nice schematic diagram from @lambdaEranga on the step-by-step process for building RAG with local models (with @llama_index, @ollama, @huggingface embeddings, and @trychroma), and wrapping it all in a Flask server. It’s one of the most detailed starter guides for full…
@soleio @trychroma omgggg their hacker in residence program looks so good! 🫣🥲
If you use @GoogleColab and dev env togethher, juicefs is a easy way to share your data. Run @trychroma on the juicefs is a nice try
💪Overcome #GoogleDrive's limitations for persistent #DataStorage with this guide. This post shares how to persist data in #Colab using #JuiceFS. It also offers examples of saving SD models for #Fooocus and storing the #Chroma vector database. Learn more👇 juicefs.com/en/blog/usage-…
Did you know @springboot service connections for @testcontainers is arriving to Spring AI? Try version 1.0.0-SNAPSHOT for @trychroma @milvusio @ollama @qdrant_engine @Redisinc @weaviate_io docs.spring.io/spring-ai/refe…
@EdduMelendez @asaikali @springboot @testcontainers @trychroma @milvusio @ollama @qdrant_engine @Redisinc @weaviate_io Nice! I have done this for Chroma and PGVector by providing the docker-compose.yaml file myself, but this is gonna be way easier.
📢 Come join us for a meetup on March 13 in Sunnyvale, CA, together with our friends from @RisingWaveLabs and @trychroma . Tune in for 📷 tech talks by @strlen , @ProductPasha and Liquan Pei and 📷 Save your seat: meetup.com/sf-stream-proc…
@johnowhitaker @benjamin_warner @lancedb @lancedb is fantastic, definitely my vector db of choice along with @trychroma when I need something (single-vector) that's hassle-free but needs a bit more features than Voyager (which I'll forever plug spotify.github.io/voyager/)
I think I need both @trychroma and @zep_ai and some sleep
If you're looking ideas that would make a splash in AI, look no further than this thread from @atroyn (founder @trychroma) Grants available from Chroma for excellent products in these categories 🚀
by popular demand, chroma is supporting backdrop build v3. we have grants available for excellent projects in the following categories:
Incredible "request for project" list — hard to find someone more plugged into where to build next in AI than @atroyn of @trychroma If you're interested to ship something in any of these categories, we'd love to support you! Grants available from Chroma for excellent projects.
by popular demand, chroma is supporting backdrop build v3. we have grants available for excellent projects in the following categories:
by popular demand, chroma is supporting backdrop build v3. we have grants available for excellent projects in the following categories:
Builders keep asking for @trychroma so we’re thrilled to have them in V3. Chroma is the open source vector retrieval system for AI applications. It's the easiest way to give your AI applications knowledge, state, and memory.
*autonomous ai systems* - programs backed by llms which are capable of operating on their own, without direct human prompting, to run a process, gather information, or accomplish a goal. They might use retrieval for their working memory.
*systems that learn* - programs which improve and adapt either implicitly through use, or explicitly by being taught and then remembering skills they've learned at the right time. they might use retrieval to store and remember skills and tools.
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