LLMuse vs Qdrant Viewer

Track tokens. Ship faster. LLMuse helps developers track Claude, Codex, and Copilot usage quotas in real time — with a clean iPhone experience built to keep you in flow. Stop guessing how much quota you have left. Stop getting surprised mid-session. Stay focused while llmuse keeps your usage visible. What you can do Track usage quotas across multiple LLM providers Monitor session / weekly usage (depending on provider) Get alerts before you hit your limits Track reset timing and usage windows Stay updated with Dynamic Island and Live Activity View everything in a fast, minimal, developer-friendly UI Built for developers Whether you’re coding in long sessions, switching between tools, or watching premium usage closely, llmuse gives you a quick way to stay in control without breaking focus. LLMuse Pro Multi-provider dashboard Custom alerts and thresholds Reset tracking and advanced monitoring Personalized widgets / display options (as available) Never hit the limit blind.

Qdrant Viewer is a client app for connecting directly from your iPhone to vector databases hosted either self-hosted or on Qdrant Cloud, allowing you to inspect collections and perform semantic searches. Key Features: - Built-in Demo Environment: Immediately try vector search with approximately 30,000 MeSH (Medical Subject Headings) vectors, with no configuration required. - Flexible Connection Settings: Supports connection via REST API, including authentication with api-key, Bearer tokens, and custom headers. - Collection Information Display: View the number of points, segments, vector dimensions, and distance function. Alias names are prioritized if set. - Semantic Search: Perform vector searches using natural language. Adjust the number of results and score threshold for each search. - Flexible Result Display: Select and list any field within the payload (supports nested structures). Detailed inspection in JSON format is also available. - 3D Visualization: Project search results into a three-dimensional space to visually explore the distance relationships between vectors. - Multiple Embedding Engines: Supports Qdrant Built-in, OpenAI, Google, Hugging Face, Cohere, and custom APIs. - Data Source: Uses MeSH (U.S. National Library of Medicine, public domain) as demo data. The embedding model is intfloat/multilingual-e5-small, licensed under the MIT License.