Message Viewer

The Message Viewer ingests chat transcripts in common formats such as JSONL, CSV, or plain text, then normalizes each message into a consistent structure with fields like timestamp, sender, and content. It supports optional metadata such as channel, thread, and message_id. Core capabilities include fast parsing, non-destructive filtering, and simple aggregation to reveal message counts per user, per time window, or per topic. Users can apply text-based search, regular expressions, and lightweight normalization (lowercasing, trimming) to locate relevant exchanges. The tool operates client-side or in isolated environments to minimize data exposure and preserve sensitive content.
Once data is parsed, it builds an in-memory index of messages and supports view modes such as raw, parsed, and summarized views. It exposes outputs like filtered_message_list, total_matches, and exportable datasets in JSON or CSV for downstream processing. Optional features include time-range filtering, user filters, keyword summaries, and quick extraction of metadata. The design emphasizes deterministic results: given the same input and filters, outputs are reproducible, enabling consistent auditing and debugging across teams.
Target users include developers integrating chat features, customer-support teams auditing conversations, QA engineers validating logging pipelines, and researchers analyzing communication patterns. Unique value lies in a focused data-viewing workflow, strict input formats, and export-ready outputs without UI noise. The tool supports compliance-friendly workflows by avoiding server-side processing, logging inputs, and providing clear provenance in exports.