WebScout Exact: Match 4 Retrieval Agent

WebScout Exact is my entry for Match 4 of the AMD AI League (Intelligent Web Information Retrieval). The agent takes a natural-language question, optionally with a starting URL, and returns one exact value plus the source page it came from, not a summary or a list of links. It runs as a single Docker container built on the official ROCm PyTorch image, so it works on AMD Instinct GPUs. Pipeline: the question is classified into an answer type (number, date, version, price, name, phone and so on); the agent fetches the given URL or searches the web, follows the most relevant links, and cleans each page into plain text. Candidate values are extracted with rules for each answer type and checked by a local Qwen3-4B-Instruct model served from the container on the AMD GPU, which picks the value that best matches the question. The answer is normalised the way the grader compares answers and written to a JSON file with the answer, source URL and confidence. If the model is not available, a rule-based path still answers. Each query is designed to finish well under 30 seconds and the model loads during the startup window. On my own held-out test set it answers 7 of 8 questions correctly. No API keys are used: all reasoning runs locally on AMD hardware. Image: ghcr.io/solar-depin-hub/amd-match4-agent:v1