Introducing Prompts: LLM Monitoring
W&B Prompts – LLM Monitoring provides large language model usage monitoring and diagnostics. Start simply, then customize and evolve your monitoring analytics over time.
Out of the box usage insights, customizable analytics
- Organizations can track and manage prompts usage statistics like cost per prompt request, number of prompt tokens, and prompt latency
- Individuals can filter and drill down to analyze prompt performance, observe all inputs sent to the prompt, and track experiments over time
- Analyze trade offs between performance, latency, and costs to optimize project ROI
A single system of record for LLMs with one centralized API gateway
- Shared and secure data artifacts and API keys with role based access controls and TTL policies
- Manage and monitor access to LLMs using our enterprise API gateway
- Immediately compare and contrast LLM performance with exploratory plots, graphs, and fine-grain activity details
- Adaptive charts to group by users, model, or any custom LLM attribute
Prompt engineering productivity, streaming LLM analysis
- Bring your own data with stream logging with a few lines of code
- Quickly create panels, add controls, and stay in sync
- Generate custom evaluation in Python or through the visual interface
Example use cases
- Build document extraction pipelines with LLMs
- Create Q&A chatbots for internal or product documentation
- Structured data extraction from text, image, and video files
- Generate customer success or sales outreach emails
Ecosystem
W&B LLM Monitoring works with the tools you’re using already. This includes everything from OpenAI Evals and Anyscale Endpoints to Azure OpenAI and HuggingFace, plus thousands of popular open source repositories.
