khoj
qdrant
khoj | qdrant | |
---|---|---|
50 | 141 | |
4,858 | 17,943 | |
2.8% | 3.4% | |
9.9 | 9.9 | |
about 17 hours ago | 3 days ago | |
Python | Rust | |
GNU Affero General Public License v3.0 | 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.
khoj
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Show HN: I made an app to use local AI as daily driver
There are already several RAG chat open source solutions available. Two that immediately come to mind are:
Danswer
https://github.com/danswer-ai/danswer
Khoj
https://github.com/khoj-ai/khoj
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
I'm a fan of Khoj. Been using it for months. https://github.com/khoj-ai/khoj
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You probably don’t need to fine-tune LLMs
https://github.com/khoj-ai/khoj
This is the easiest I found, on here too.
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Show HN: Khoj – Chat Offline with Your Second Brain Using Llama 2
Thanks for the feedback. Does your machine have a GPU? 32GB CPU RAM should be enough but GPU speeds up response time.
We have fixes for the seg fault[1] and improvement to the query speed[2] that should be released by end of day today[3].
Update khoj to version 0.10.1 with pip install --upgrade khoj-assistant to see if that improves your experience.
The number of documents/pages/entries doesn't scale memory utilization as quickly and doesn't affect the search, chat response time as much
[1]: The seg fault would occur when folks sent multiple chat queries at the same time. A lock and some UX improvements fixed that
[2]: The query time improvements are done by increasing batch size, to trade-off increased memory utilization for more speed
[3]: The relevant pull request for reference: https://github.com/khoj-ai/khoj/pull/393
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A Review: Using Llama 2 to Chat with Notes on Consumer Hardware
We recently integrated Llama 2 into Khoj. I wanted to share a short real-world evaluation of using Llama 2 for the chat with docs use-cases and hear which models have worked best for you all. The standard benchmarks (ARC, HellaSwag, MMLU etc.) are not tuned for evaluating this
- FLaNK Stack Weekly for 17 July 2023
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An open source AI search + chat assistant for your Notion workspace
Self-host your Notion assistant using the instructions here. You'll need Python >= 3.8 to get started.
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When will we get JARVIS?
Here's an early example: https://github.com/khoj-ai/khoj
qdrant
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Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain
Great. Now that we have the embeddings, we need to store them in a vector database. We will be using Qdrant for this purpose. Qdrant is an open-source vector database that allows you to store and query high-dimensional vectors. The easiest way to get started with the Qdrant database is using the docker.
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Boost Your Code's Efficiency: Introducing Semantic Cache with Qdrant
I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours.
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Ask HN: Has Anyone Trained a personal LLM using their personal notes?
I'm currently looking to implement locally, using QDrant [1] for instance.
I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2].
[1]. https://qdrant.tech/
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Show HN: A fast HNSW implementation in Rust
Also compare with qdrant's Rust implementation; they tout their performance. https://github.com/qdrant/qdrant/tree/master/lib/segment/src...
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pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
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Open-source Rust-based RAG
There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb
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Qdrant 1.8.0 - Major Performance Enhancements
For more information, see our release notes. Qdrant is an open source project. We welcome your contributions; raise issues, or contribute via pull requests!
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Perform Image-Driven Reverse Image Search on E-Commerce Sites with ImageBind and Qdrant
Initialize the Qdrant Client with in-memory storage. The collection name will be “imagebind_data” and we will be using cosine distance.
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7 Vector Databases Every Developer Should Know!
Qdrant is an open-source vector search engine optimized for performance and flexibility. It supports both exact and approximate nearest neighbor search, providing a balance between accuracy and speed for various AI and ML applications.
- Ask HN: Who is hiring? (February 2024)
What are some alternatives?
obsidian-smart-connections - Chat with your notes & see links to related content with AI embeddings. Use local models or 100+ via APIs like Claude, Gemini, ChatGPT & Llama 3
Milvus - A cloud-native vector database, storage for next generation AI applications
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
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.
llama-cpp-python - Python bindings for llama.cpp
faiss - A library for efficient similarity search and clustering of dense vectors.
obsidian-ava - Quickly format your notes with ChatGPT in Obsidian
pgvector - Open-source vector similarity search for Postgres
logseq-plugin-gpt3-openai - A plugin for GPT-3 AI assisted note taking in Logseq
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
danswer - Gen-AI Chat for Teams - Think ChatGPT if it had access to your team's unique knowledge.
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.