Reka Research – A SOTA research agent
Hi HN, We built something new! It is an AI agent that can: - iterate through up to a dozen sources (web or GDrive) - reason between hops in natural language (exposed in the trace) - generate structured JSON so downstream code can consume results deterministically It not only delivers state-of-the-art performance on both SimpleQA and Reka Research-Eval, but also shatters the notion that cutting-edge AI must come at a premium, being significantly more affordable than alternatives. Tech stack highlights - Base model: Reka Flash 3.1 (trained from scratch, post-trained with RL on verifiable…
What it does
In the maker’s words, at launch
Hi HN, We built something new! It is an AI agent that can: - iterate through up to a dozen sources (web or GDrive) - reason between hops in natural language (exposed in the trace) - generate structured JSON so downstream code can consume results deterministically It not only delivers state-of-the-art performance on both SimpleQA and Reka Research-Eval, but also shatters the notion that cutting-edge AI must come at a premium, being significantly more affordable than alternatives. Tech stack highlights - Base model: Reka Flash 3.1 (trained from scratch, post-trained with RL on verifiable rewards) - Flat pricing: $0.025/query (no extra token usage cost) - Public REST API (OpenAI-style), plus on-prem / VPC options for enterprises Product Page: https://reka.ai/products/research Documentation: https://docs.reka.ai/research
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I have built many AI agents, and all frameworks felt so bloated, slow, and unpredictable. Therefore, I hacked together a minimal library that works with JSON/dict/kwargs definitions for each step, allowing you a simpler way to define reproducible agents. It supports concurrency for up to 1000 calls/min, giving you speed and predictability in your workflows. Install pip install flashlearn Input is a list of dictionaries Simply take user inputs, API responses, and calculations from other tools and feed them to FlashLearn. user_inputs = [{"query": "When was python launched?"}]…
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Today marks ten years, 3653 consecutive days, of running at least one mile every day under the USRSA rules [1]. To celebrate, I built an interactive dashboard that turns a decade of GPX files into charts you can explore. Running has truly changed my life: I've made lifelong friends, explored beautiful places, and more importantly invested into my own health and fitness, which I'm starting to see the positive benefits as I get older. The stack is pretty simple: a NextJS app, with a Postgres database to keep all my running data, and all the stats are pre-computed and cached in Redis, so I…
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