Walter Navarro Collao@baneado85

WaltTrace answers short factual questions from mixed engineering documents while returning the exact files needed to support each answer. It parses PDF, Word, Excel, CSV, logs and source files, and uses a local vision-language model to read diagrams, scanned pages and equipment labels. Retrieval follows identifiers between incident reports and lookup tables, allowing answers that require more than one document. Generated quotations are checked against indexed source text; unsupported answers are refused with an empty answer and citation list. Qwen2.5-VL-7B runs on a real AMD GPU through ROCm PyTorch. All weights are embedded in the mandated container base, and the application runs without outbound network access. Indexing starts a resident model behind a private Unix socket so each fresh question process avoids reloading the weights. Malformed, unreadable, encrypted and unsupported files are skipped independently. The development report documents actual GPU timings, memory readings, individual answers and citation checks. Public-sample results are development evidence, not a claim about hidden evaluation scores or League points already awarded.

TradeLix AI is a FastAPI + React trading-agent PoC for the Alpaca AI Trading Agents Hackathon. The system runs a linear multi-agent pipeline: news, sentiment, options context, market features, technical indicators, order blocks, institutional flow, account state, risk, decision, and execution gate. The key design principle is: LLMs propose, deterministic code authorizes. Groq-powered agents and optional ReAct loops can research headlines, inspect compact market signals, reason about BUY/SELL/HOLD, and explain their proposal, but they cannot place trades. Every proposal must pass a deterministic execution gate that checks paper mode, buying power, exposure, duplicate working orders, kill switch, schedule window, and plan validity. Execution is disabled by default and only sends Alpaca paper orders when explicitly armed. The dashboard streams the agent pipeline over SSE, displays candlestick charts and smart-money overlays, shows gate verdicts, supports dry-run previews, and exposes the audit trail so users can inspect why a trade was allowed, blocked, or skipped.

Six Matches. One leaderboard. Build on AMD, earn points and compete for prizes.

🌎 Hybrid Hackathon | 💻 Online Build: 12-17 October 2026 | On-site phase: 17-18 October 2026 To participate in the hackathon, simply click Sign up with AMD. If you are not already a member of the AMD AI Developer Program (ADP), you will need to create an account. The AMD Developer Hackathon: ACT III is a hands-on event for developers, founders, engineers and builders who want to push what’s possible with AI on real infrastructure. 📍 If approved for the on-site experience, you'll also have the opportunity to showcase your project live. Travel and accommodation will not be covered.

🌎 Online Hackathon | 💻 Online Build: Sept 26 - Oct 5, 2026 A virtual, global hackathon. Build from anywhere in the world. Dark Factory is the official hackathon of WeAreDevelopers World Congress North America, presented by BAND, but you don't need to be in San Jose to take part. For one week, you build a software factory in BAND Desktop: a band of coding agents that plans work, implements it and checks its own results. 🎟️ Bonus for sign-ups: you are eligible for a free ticket to WeAreDevelopers World Congress North America in San Jose (Sep 23–25). If you do go, stop by the BAND booth: a surprise is waiting for you.

🌎 Online Hackathon | 💻 Dates: 28 August–4 September 2026 | 🏆 $6,000 Prize Pool Build AI trading agents on Alpaca — autonomous agents and trading apps using Alpaca's Trading API, MCP server and CLI. 🌍 Fully online hackathon. Join and build from anywhere in the world.