Alternatives
Products that do what Advanced LLM Voice Mode but on your own database does
Hey there! We've been working on something pretty cool lately, and I'm excited to share it with you. It's called Zing Advanced Voice Mode, and it's designed to make data analysis more intuitive, accessible, and efficient. With Zing Advanced Voice Mode, you can simply ask a question in plain English, and the tool will instantly provide a clear, concise answer, along with a visual representation of the query. No more struggling with complex syntax or spending hours writing intricate SQL statements. It works with google sheets, excel files, csvs, postgres, mysql, Databricks, SQL Server,…
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I built a voice agent from scratch that averages ~400ms end-to-end latency (phone stop → first syllable). That’s with full STT → LLM → TTS in the loop, clean barge-ins, and no precomputed responses. What moved the needle: Voice is a turn-taking problem, not a transcription problem. VAD alone fails; you need semantic end-of-turn detection. The system reduces to one loop: speaking vs listening. The two transitions - cancel instantly on barge-in, respond instantly on end-of-turn - define the experience. STT → LLM → TTS must stream. Sequential pipelines are dead on arrival for natural…
Mar 2026 · ntik.me
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Hey HN, we've just finished building a dynamic router for LLMs, which takes each prompt and sends it to the most appropriate model and provider. We'd love to know what you think! Here is a quick(ish) screen-recroding explaining how it works: https://youtu.be/ZpY6SIkBosE Best results when training a custom router on your own prompt data: https://youtu.be/9JYqNbIEac0 The router balances user preferences for quality, speed and cost. The end result is higher quality and faster LLM responses at lower cost. The quality for each candidate LLM is predicted ahead of time…
2024 · unify.ai
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2023 · github.com
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I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…
2023 · github.com
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Hi HN. I've gotten pretty tired of needing to learn a custom programming language for a tool I use once a week or less. So I figured, it might be easier to pick up if `jq` used a programming language I already know. Voila, gq.
2022 · github.com
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I played around with GPT-3 to build this demo. Select a public BigQuery dataset and describe your query in natural English, then edit the generated SQL as needed and execute it. https://app.tabbydata.com/sql-assistant-demo
2021
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Hey everyone on HN! We recently spent the past couple of weeks building out an end-to-end platform which can plug-in multiple models (both open/closed-source) to create voice driven conversational applications. We've tried to make the process simple & concise through documentation. Feel free to try it out and provide feedback. We will be launching a dashboard in the coming week for monitoring and analytics alongwith more open source models. Let us know what you all think. (if you want to contribute, we have tons of features planned - do let us know)
2023 · github.com
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2017 · github.com
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We're excited to announce the launch of ZenStack V1 after a year of refinement. With ZenStack, we introduce ZModel, a domain-specific language (DSL) that simplifies the definition of data and access rules, bringing it closer to the database level. This eliminates the need for extensive, repetitive coding on the application side. We would love to hear your feedback and opinions on it. Thank you!
2023 · github.com
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Hey everyone! Along with my team, I've developed a reinforcement learning system that automatically optimizes LLM prompts, complete with a visualization feature to track both prompt structure and learning progress over time. Take a look here: https://nomadic-ml.github.io/nomadic/cookbooks/Nomadic_Promp... Check out our website too:https://www.nomadicml.com/ In terms of how this visualization works: The RL Prompt Optimizer employs a reinforcement learning framework to iteratively improve prompts used for language model evaluations. At each episode, the…
2024 · nomadic-ml.github.io
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Zep is a long-term memory store designed for conversational AI applications built using modern LLMs. It handles the storage, summarization, embedding, indexing, and enrichment of chat histories, and offers developers a simple, low-latency API to this data. Chat history storage is an infrastructure challenge all developers and enterprises face as they look to move from prototypes to deploying conversational AI applications that provide rich and intimate experiences to users. Key features include long-term memory persistence, auto-summarization, vector search, auto-token counting, and Python…
2023
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2025 · github.com
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I’ve been working on AnyModal, a framework for integrating different data types (like images and audio) with LLMs. Existing tools felt too limited or task-specific, so I wanted something more flexible. AnyModal makes it easy to combine modalities with minimal setup—whether it’s LaTeX OCR, image captioning, or chest X-ray interpretation. You can plug in models like ViT for image inputs, project them into a token space for your LLM, and handle tasks like visual question answering or audio captioning. It’s still a work in progress, so feedback or contributions would be great. GitHub:…
2024 · github.com
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When I heard about Google's clone of Claude Code this morning I tried out my 2 week old MCP server and instantly had two way voice conversation with it. Gemini seemed a bit confused by this. :-) https://youtu.be/HC6BGxjCVnM?feature=shared&t=36 It's a FOSS MCP server I created a couple of weeks ago: - https://getvoicemode.com - https://github.com/mbailey/voicemode # Installation (~/.gemini/settings.json) { "theme": "Dracula", "selectedAuthType": "oauth-personal", "mcpServers": { "voice-mode": { "command": "uvx", "args": [ "voice-mode" ] }…
2025 · getvoicemode.com
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