Alternatives
Products that do what Open-source Perplexity clone one file back end, streaming answers does
I built an open-source research agent. You ask a question, it searches the web via Tavily, synthesizes an answer with an LLM, and shows the sources it used. Answers stream in real-time. The interesting part is the backend. It's a single JS file (~100 lines) that handles web search, LLM streaming, and per-user conversation history. No vector database, no Redis, no separate storage service. It runs inside a cell — an isolated environment with a built-in database, search index, and filesystem. The cell handles persistence and streaming natively, so the agent code only has to deal with the…
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hey hn, I built an open-source Perplexity clone that can run local LLMs and cloud LLMs. It's fully self-hostable through Docker and uses ollama to support local LLMs. The demo video in the repository shows me running it locally with llama3 on my M1 Macbook Pro. I'm open to any suggestions or feedback, thanks!
2024 · github.com
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I've been working in the couple of months on an experiment, trying to make GPT-4 much more useful for web development / React, writing production code that is relevant to any repository without copy pasta from ChatGPT or having small snippets of auto-complete from Copilot that are not in your context. The agent is taking a user story text and generating and composing multiple react components to generate the relevant screens, based on atomic design principles, with Typescript, TailwindCSS and RadixUI. Is is still experimental but very interesting results, I would like to get your…
2023 · github.com
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LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!
2023 · github.com
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Hey guys, I am think of building an open-source version of Perplexity to let devs play around with it. But with all the existing tools available what features would you want? Anything specific? What is missing? Currently working on - 1. Streaming text 2. Citations sources 3. Image and file upload 4. Chat history and storage 5. Temperature and custom instructions If you are in marketing or growth can anyone help me with what to focus on while building such an app? Also here is a very first version. Probably will break and most of the buttons also don’t work, built it in 3 days using Bing and…
2024 · omniplex.vercel.app
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Built an AI code reviewer using Letta (Python) that I can call natively from Rust applications. The interesting part: real-time streaming works perfectly across the language boundary with zero hassle using RunAgent. The agent runs in Python with persistent memory, leverages the best in house agentic memory management with Letta (Pythonic AI agent framework), and my rust code just uses it (kinda) natively, though Letta has no Rust bindings. And, streaming works like magic. No FFI, no complex bridges - just native async/streaming that feels like calling any Rust librar, but without…
2025 · medium.com
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Hi HN, I've been working with LLMs in production for a while both as a solo dev building apps for clients and working at an AI startup. The one thing that always was a pain was to pay OpenAI/Gemini/Anthropic a few dollars a month just for me to say "test" or have a CI runner validate some UI code. So I built this server called ChunkBack, that mocks the popular llm provider's functionality but allows you to type in a deterministic language: `SAY "cheese"` or `TOOLCALL "tool_name" {} "tool response"` I've had to work in some test environments and give good results for experimenting…
Nov 2025 · github.com
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Hey HN! For that last 8 months I've been trying to make agents that can hack web applications to find vulnerabilities in them - An AI Security Tester. The system has 29 agents in total, a custom LLM Orchestration framework which works on the task-subtask architecture (old-school but works amazingly for my use case, and is pretty reliable) with custom agent calling mechanism. No Auo-Gen, Langchain and Crew AI - Everything custom built for pentesting. Each test runs in an isolated Kali linux environment (on AWS Fargate), where the agents have full access to the environment to undertake any…
2025
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The first ever AI peer reviewed research article just got approved. It’s kinda crazy how advanced AI have come to replace researchers. I've just been using Deep Research on ChatGPT and Perplexity a lot to write and research complex technical reports for my boss. He loves the reports and it has decreased my workload a ton but I still have some frustrations with it. None of them provide an API that gets me the same quality of output you would with the applications. I wanted something with more control on the LLMs, swappable with the reasoning new models that came out. Not just prompt →…
2025 · github.com
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Built this because I was tired of every AI tool shipping my data to someone else server n0x runs the full stack LLM inference via WebGPU, autonomous ReAct agents, RAG over your own docs, sandboxed Python execution via Pyodide all inside a single browser tab. No account No keys No backend Models download once, cache in IndexedDB permanently. Biggest challenge was context window budgeting for the agent loop and making the WASM vector search non-blocking. Happy to talk architecture. GitHub: https://github.com/ixchio/n0x | Live demo: https://n0x-three.vercel.app
Mar 2026 · n0xth.vercel.app
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Hey HN! I built Experiment to solve a common frustration in LLM development: the lack of proper tools for prompt engineering experimentation. Here's what makes it different: Key Features: - Load and edit chat completion logs from CSV files - Fork and modify specific conversation entries - Run inference via Anthropic, Mistral, and OpenAI - Define custom tools using JSONSchema format - Visual tool usage analysis with collapsible, sorted key-value pairs - Full mobile support and available as installable PWA Technical Highlights: - Built with React using custom isomorphic architecture -…
2025 · github.com
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How It Works - Offline Indexing: Docs are processed and embedded using the GTE-small model at build time. Browser-Based Magic: - SQLite database (stored in the browser) for vector search. - Local embedding model for query processing. - Local LLaMA model for response generation using WebLLM. - Everything Happens Locally: No data leaves the user’s device. Key Benefits - No API Costs: Everything runs in the browser—zero backend expenses. - Unlimited Chats: No rate limits or usage restrictions. - Privacy-First: Your data stays on your device, always. You can find the code here:…
2024 · docs.akiradocs.ai
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Last night, OpenAI launched Deep Research, a tool for AI-powered deep web searches. In a few hours, I built an open-source alternative using Next.js, Firecrawl, and Vercel's AI SDK. Instead of using a fine-tuned version of o3, this method uses Firecrawl's extract + search with a reasoning model to deep research the web. The system is built using Vercel’s AI SDK for handling requests and streaming data, with an agent-based approach that manages search, extraction, and analysis. It uses Firecrawl to find and extract structured data, which is then processed through a progressive analysis system…
2025 · github.com
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We made human-use. Similar to how browser-use connects agents to the web, human-use connects agents to people all over the world in real-time using the Rapidata API. This allows the LLM to crowdsource human feedback and insights when it deems necessary. Free to use for anyone, you can enable your agent to use humans in real-time to: - Do preference research - Check for hallucinations - Capture sentiment - Get feedback - etc. Whatever you would want from humans. We expose certain parts of the Rapidata API to the agent through the MCP server framework. Additionally we provide a custom client.…
2025 · github.com
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Hey HN! Over the past few weeks, I’ve been working on DataBridge, an open-source solution for data ingestion and querying across text, PDFs, images, and videos. In our latest update, we’ve added a fully local deployment option: - No internet required – Runs entirely offline. - Customizable Models – Supports any LLM and embedding model via Ollama (with options for any other private providers) - Extensibility – You can plug in your own models or tools easily. This local-first approach ensures better privacy, security, and flexibility, especially for teams dealing with sensitive data. You can…
2025 · github.com
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Over this past month I had the idea to build a 100% open-source MIT-licensed tool to simplify sharing code with LLMs, without the vendor lock-in you get from most SDKs. Right now, it’s way too hard to export your data or work freely with models like o1 PRO or Grok 3, especially since they don’t even have API access. So I built OpenRepoPrompt, an open-source tool from wildberry-source that serializes files and folders into XML for LLMs. I coded/designed from 12PM -> 11PM on Saturday and 8AM -> 11PM on Sunday. There are still tons of features missing (I'm working on better file filtering…
2025 · github.com
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I’ve been working on a multi-agent academic research lab, and I wanted to share it here today primarily to give a massive shoutout to the developers behind ZeroClaw. When designing the architecture for this, I needed an autonomous agent runtime that was lightweight, entirely agnostic, and highly secure for local execution. ZeroClaw’s pure Rust implementation provided exactly the zero-overhead foundation the project required. Because they solved the core runtime execution so elegantly, I was able to spend my time building the higher-level orchestration on top of it—like the retrieval graph…
Mar 2026 · rainlabteam.vercel.app
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ChatMyFiles is an open-source alternative to ChatPDF: you upload any PDF or Microsoft Office document and ask questions about it. Unlike other "chat with your documents" solutions, ChatMyFiles can be self hosted using a one-click deploy script that uses Terraform to deploy a - Vector database - Server - (Optional) Open-source LLM such as Falcon, Llama, or GPT4All to your virtual private cloud (VPC). We used Langchain to interface with open source LLMs and Ragstack to deploy to Google Cloud: https://github.com/psychic-api/rag-stack
2023 · chatmyfiles.com
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A few weeks ago I got rejected from a role and the feedback was that I needed a deeper understanding of FAISS and LlamaIndex. So I built triage.flow — an AI assistant that lets you explore and understand GitHub repositories through a chat interface. It clones a repo, indexes it using FAISS + BM25 + tree-sitter parsing, and powers a full UI where you can: - Ask natural-language questions like “how does auth work?” or “explain @src/components/Modal.tsx” - Mention specific files/folders with @filename.ts (autocomplete supported) - See how the agent thinks in real time (Thought →…
2025 · github.com
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I was not getting good cache utilization when including dynamic context in agent threads. After a lot of experimentation, I found a good pattern that minimizes how often long lived conversation history gets modified while still supporting dynamic context. It has flexible hooks for doing things like truncating or summarizing tool outputs when transitioning messages to the long term history. And I'm seeing >>90% of tokens hitting the cache for my agents despite including a lot of dynamic user context. There are a wide range of agent prompting strategies so I'd love to hear where this library…
Jun 2026 · github.com
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Link: https://docs.trysoma.ai/ For the past ~9 months I’ve been building Soma, an open-source AI agent & workflow runtime written in Rust, with a TypeScript SDK (Python coming soon). It’s not a framework; it’s meant to sit underneath whatever agent/tooling code you already write (Vercel AI SDK, LangChain, custom code, etc.). It provides features around your framework + a better DX for building agents. I’ve tried to take a Next.JS model: open-source, good DX, self-deployable. I originally set out to build a vertical back-office/operations product for SMEs. I needed a…
Dec 2025 · docs.trysoma.ai
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