bolt.diy
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15,330 skills indexed with the new KISS metadata standard.
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This project implements an autonomous AI agent that scans real-time market data via APIs, identifies high-momentum stocks from gainers lists, parses financial news using LLM (LLaMA), and classifies opportunities using custom prompts. The agent outputs actionable investment signals and risk flags with full automation, serving as a front-end screener for forecasting pipelines. Integrated with Pushover app for on-the-fly mobile phone notifications.
This fork of Bolt.new allows you to choose the LLM that you use for each prompt! Currently, you can use OpenAI, Anthropic, Ollama, OpenRouter, Gemini, or Groq models - and it is easily extended to use any other model supported by the Vercel AI SDK! See the instructions below for running this locally and extending it to include more models.
This Streamlit web app lets you upload `.eml` email files and use Anthropic Claude (via AWS Bedrock) to:
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[](https://bolt.diy)
$ cargo install code2prompt

A toolkit for autonomous AI operations using local LLM implementations.
[](https://bolt.diy)
<img width="4856" height="1944" alt="Langfuse Overview" src="https://github.com/user-attachments/assets/5dac68ef-d546-49fb-b06f-cfafc19282e3" />
Projekt Python do automatycznej analizy danych, trenowania prostych modeli ML (regresja / klasyfikacja), wykrywania anomalii oraz wizualizacji wyników w spójnym, estetycznym stylu.
<img width="4856" height="1944" alt="Langfuse Overview" src="https://github.com/user-attachments/assets/5dac68ef-d546-49fb-b06f-cfafc19282e3" />
**Scientific A/B Testing for LLM Prompts**
This repo contains the ViaLogos Codex pack (prompts, SOPs, tools, installers) under `.vialogos/`.
Collection of relevant AI Driven Development Kits.
- [Table of Contents](#table-of-contents)
(All the published system prompts are extracted by myself, except the already open sourced ones and Manus)
No description available.
Máxima: Só reaja a sintaxe de código de programação e comentários, não responda a perguntas fora do contexto.
Lipa na M-PESA online API also known as M-PESA express (STK Push/NI push) - Merchant/Business initiated C2B (Customer to Business) Payment API Java Integration
[Context Engineering Is the New Prompt Engineering](https://pub.towardsai.net/context-engineering-is-the-new-prompt-engineering-11a22053c1f6)를 편역하였다.
(1)硬件端
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