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W&B Weave
A Framework for Developing and Deploying LLM-Based Applications

W&B Weave
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Home: https://weave-docs.wandb.ai

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What is W&B Weave?

Weights & Biases (W&B) Weave is a flexible and scalable framework designed to support every stage of your LLM application development workflow. Weave offers comprehensive solutions from tracing and monitoring to experimentation and evaluation.

Weave allows integration with existing development stacks through the Python SDK, TypeScript SDK, and Service API. It provides support for many LLM providers, local models, frameworks, and other third-party services. This enables developers to efficiently manage the whole life circle of LLM app creation.

Features

  • Tracing & Monitoring: Track LLM calls and application logic.
  • Systematic Iteration: Refine prompts, datasets, and models.
  • Experimentation: Utilize the LLM Playground for model and prompt testing.
  • Evaluation: Assess performance with custom or pre-built scorers.
  • Guardrails: Implement safeguards for content moderation and prompt safety.
  • Integrations: Use with popular LLM providers, local models and frameworks.

Use Cases

  • Debugging and analyzing LLM application performance in production systems.
  • Iteratively improving prompts, datasets, and models.
  • Conducting experiments with various models and prompts.
  • Systematically evaluating and enhancing the performance of LLM applications.
  • Implementing safety measures for content moderation and prompt engineering.

FAQs

  • What LLM providers does Weave support?
    Weave supports numerous LLM providers, local models, frameworks, and third-party services.

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