llama_index
Milvus
| llama_index | Milvus | |
|---|---|---|
| 76 | 109 | |
| 32,542 | 27,747 | |
| 4.2% | 3.2% | |
| 10.0 | 10.0 | |
| 4 days ago | 2 days ago | |
| Python | Go | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
llama_index
- Show HN: Route your prompts to the best LLM
- LlamaIndex: A data framework for your LLM applications
- FLaNK AI - 01 April 2024
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Show HN: Ragdoll Studio (fka Arthas.AI) is the FOSS alternative to character.ai
For anyone curious llamaindex's "prompt mixins", they're actually dead simple: https://github.com/run-llama/llama_index/blob/8a8324008764a7... - and maybe no longer supported.
I basically reinvented this wheel in ragdoll but made it more dynamic: https://github.com/bennyschmidt/ragdoll/blob/master/src/util...
- LlamaIndex is a data framework for your LLM applications
- How to verify that a snippet of Python code doesn't access protected members
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🆓 Local & Open Source AI: a kind ollama & LlamaIndex intro
Being able to plug third party frameworks (Langchain, LlamaIndex) so you can build complex projects
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I made an app that runs Mistral 7B 0.2 LLM locally on iPhone Pros
Mistral Instruct does use a system prompt.
You can see the raw format here: https://www.promptingguide.ai/models/mistral-7b#chat-templat... and you can see how LllamaIndex uses it here (as an example): https://github.com/run-llama/llama_index/blob/1d861a9440cdc9...
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Top 5 Vector Database Videos of 2023 🎥
Learn how to use Milvus as persistent vector storage with LlamaIndex in under 5 minutes.
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What's going on in the Zilliz Universe? December 2023
▶️ Read Blog 📷 Watch Demo 🦙 Notebook using Pipelines inside LlamaIndex
Milvus
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Recapping the AI, Machine Learning and Data Science Meetup - May 30, 2024
Milvus open source vector database
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Using Milvus-Lite Now
If you saw my recent newsletter you can see I joined Zilliz to work on the Open Source AI Database, Milvus.
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AIM Weekly 27 May 2024
🎥 Playlist: Unstructured Data Meetup https://www.meetup.com/unstructured-data-bay-area/events/ 🖥️ Website: https://www.youtube.com/@MilvusVectorDatabase/videos X Twitter - / milvusio https://x.com/milvusio 🔗 Linkedin: / zilliz https://www.linkedin.com/company/zilliz/ 😺 GitHub: https://github.com/milvus-io/milvus 🦾 Invitation to join discord: / discord https://discord.com/invite/FjCMmaJng6
- FLaNK-AIM: 20 May 2024 Weekly
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Computer Vision Meetup: Develop a Legal Search Application from Scratch using Milvus and DSPy!
Legal practitioners often need to find specific cases and clauses across thousands of dense documents. While traditional keyword-based search techniques are useful, they fail to fully capture semantic content of queries and case files. Vector search engines and large language models provide an intriguing alternative. In this talk, I will show you how to build a legal search application using the DSPy framework and the Milvus vector search engine.
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Ask HN: Who is hiring? (April 2024)
Zilliz (zilliz.com) | Hybrid/ONSITE (SF, NYC) | Full-time
I am part of the hiring team for DevRel
NYC - https://boards.greenhouse.io/zilliz/jobs/4307910005
SF - https://boards.greenhouse.io/zilliz/jobs/4317590005
Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus), the most starred vector database on GitHub. Milvus is a distributed vector database that shines in 1B+ vector use cases. Examples include autonomous driving, e-commerce, and drug discovery. (and, of course, RAG)
We are also hiring for other roles that I am not personally involved in the hiring process for such as product managers, software engineers, and recruiters.
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Unlock Advanced Search Capabilities with Milvus and Read about RAG
Get started with Milvus on GitHub.
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Milvus VS pgvecto.rs - a user suggested alternative
2 projects | 13 Mar 2024
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How to choose the right type of database
Milvus: An open-source vector database designed for AI and ML applications. It excels in handling large-scale vector similarity searches, making it suitable for recommendation systems, image and video retrieval, and natural language processing tasks.
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Simplifying the Milvus Selection Process
Selecting the right version of open-source Milvus is important to the success of any project leveraging vector search technology. With Milvus offering different versions of its vector database tailored to varying requirements, understanding the significance of selecting the correct version is key for achieving desired outcomes.
What are some alternatives?
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
pgvector - Open-source vector similarity search for Postgres
langchain - 🦜🔗 Build context-aware reasoning applications
faiss - A library for efficient similarity search and clustering of dense vectors.
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
chatgpt-retrieval-plugin - The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
gpt-llama.cpp - A llama.cpp drop-in replacement for OpenAI's GPT endpoints, allowing GPT-powered apps to run off local llama.cpp models instead of OpenAI.
Face Recognition - The world's simplest facial recognition api for Python and the command line