Alternatives
Products that do what Quira does
Cheap, Fast , and Context-Dense RAG Framework for Python
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Hey HN, Matusa here! A friend and I have built Memora. Memora is a vector database with built-in multistage reranking, which can significantly improve search accuracy over semantic search. It also features a proprietary embedding model tailored for RAG use cases — where there's a structural mismatch between the content stored and the query used for searching (hence why HyDE works well). Memora started because we were working on a stealth AI startup where we used an agent that would query into a vector DB, but it would take multiple tries for the agent to find what it needed (20% of the time…
2023 · usememora.app
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2014 · thriftpy.readthedocs.org
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Hello HN! We’ve been working hard on Vanna, our RAG framework for SQL generation and we’ve been updating our documentation. Please have a look — we have a ton of Jupyter notebooks for any combination of desired use cases. At it’s heart, we have abstractions that help you: - “train” a RAG “model” i.e. add metadata for the retrieval augmentation system to reference when constructing the LLM prompt (yes, we know that the terms “train” and “model” are somewhat confusing and we’re open to changing those terms if you can suggest better ones) - “ask” questions, which will generate SQL, run it,…
2023 · github.com
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2015 · amol-mandhane.github.io
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2015 · spacy.io
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Hi HN! Silk is a project I began working on approximately six months ago without any prior experience or knowledge of compiler design, and it's been a frustrating but fun learning experience. It is very much a work in progress, but I would love to hear feedback of any kind!
2020 · ajaymt.github.io
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flect is a Python framework for building full-stack web applications. It constructs user interfaces by utilizing Pydantic models in the backend that correspond to the properties of React components in the frontend. This integration enables quick development of interactive and beautiful UIs using Python.
2024 · github.com
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Hi HN! I lead product at Vectara and we've just released a new LLM in our platform that outperforms GPT4 and Gemini 1.5 Pro on RAG tasks. Vectara is a Retrieval Augmented Generation (RAG) platform primarily deployed as a SaaS service which includes a generous free tier so you can try it for free. The way we've been able to offer a "better but cheaper" is that we focus a lot of our attention on taking smaller models (which can be hosted in a cost efficient way) and fine tuning them to specific tasks: in this case RAG. This ends up with a model that is less capable of arbitrary tasks like…
2024 · vectara.com
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Hi HN, While building RAG agents, I noticed a lot of token budget was wasted on formatting overhead (HTML tags, JSON structure, whitespace). Existing solutions felt too heavy (often requiring torch/transformers), so I wrote this lightweight, zero-dependency library to solve it. It includes strategies for context packing, PII redaction, and tool output compression. Benchmarks show it can save ~15% of tokens with negligible latency overhead (<0.5ms). Happy to answer any questions!
Dec 2025 · github.com
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Smarter RAG with Agentic Retrieval & Context-Aware MCP
Sep 2025
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2012 · blog.fruiapps.com
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