Weights & Biases Weave
Trace, debug, and evaluate LLM apps — a lightweight toolkit for developing generative AI software.
About
Weave is Weights & Biases' toolkit for the experimental loop of building LLM applications: trace every model call, debug the trace tree when something goes wrong, and run rigorous apples-to-apples evaluations before you ship. The core interaction is one decorator — @weave.op() on any function — and suddenly you have a full trace of inputs, outputs, and latencies across OpenAI, Anthropic, Google, Hugging Face, and your own code.
It slots into the agent stack rather than competing with it: NVIDIA's NeMo Agent Toolkit documents Weave as its tracing backend, and the evaluation harness is the part teams keep once the novelty of tracing wears off. The repo is Apache-2.0 and actively maintained, though at ~1,100 stars the standalone community is small — most users arrive via the W&B platform itself. You need a (free) W&B account, and the hosted dashboard is where the traces live, so this is open-core rather than fully self-hostable.
What it can do
- One-decorator tracing (`@weave.op()`) for any Python function
- Trace trees across OpenAI, Anthropic, Google, Hugging Face, and custom code
- Apples-to-apples evaluation harness for models and prompts
- Debug view of every model input, output, and latency
- Native integration as the tracing backend for NVIDIA NeMo Agent Toolkit
- Organizes experiments, traces, and evals per project
Setup
- Create a free Weights & Biases account at wandb.ai.
- Install:
pip install weave(Python 3.10+). - In your code:
import weave; weave.init("my-project"). - Decorate functions to trace:
@weave.op()— traces appear in the W&B dashboard. - Build evaluations with Weave's eval harness to compare models and prompts apples-to-apples.
Prerequisites
Python 3.10+; a free Weights & Biases account (traces are viewed in the hosted dashboard).
Use cases
Works with
Trust score — 8/10
Scored 8/10 (metrics tier, metrics-v1). Evidence: 1,141 GitHub stars (GitHub API), Apache-2.0, pushed Oct 15 2026; NVIDIA's NeMo Agent Toolkit release notes document Weave as its tracing backend, corroborating real production use beyond W&B's own marketing. Strengths: W&B backing, genuinely open client, the `@weave.op()` model is the simplest tracing story in the category. Docked for: (1) small standalone community — adoption rides on the W&B platform; (2) traces live in the hosted dashboard, so it is open-core not fully self-hostable; (3) requires a W&B account even for local experiments. License: Apache-2.0.
★ 1,141 GitHub stars
How the trust score is built
Full methodology →- Adoption · stars/downloads, log-scaled vs peers
- 6.0/10
- Maintenance · recency, releases, issue load
- 10.0/10
- Openness · license + docs
- 10.0/10
- Manual review · sanity read + red-flag check
- 8.0/10
- · Adoption 6: starScore from 1,141 stars on wandb/weave — small standalone community, most users arrive via the W&B platform
- · Maintenance 10: pushed 2026-10-15 (recency 10)
- · Openness 10: Apache-2.0 + docs verified (wandb.me/weave)
- · Manual 8: NVIDIA NeMo Agent Toolkit release notes document Weave as its tracing backend, corroborating real production use; docked for platform-dependent adoption, hosted-dashboard traces (open-core, not self-hostable), W&B account requirement
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.