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Welcome, Matthew Berman fans!

Created on September 9|Last edited on October 29
Introducing Weave from Weights & Biases
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Weave is a game-changing toolkit for developers working on generative AI applications. It offers a seamless way to track, evaluate, and debug LLM-based projects.
You can use Weave to:
  1. Log and debug language model inputs, outputs, and metadata
  2. Build rigorous, apples-to-apples evaluations for language model use cases
  3. Organize all the information generated across the LLM workflow, from experimentation to evaluations to production

🧑‍💻 All you need are 3 lines of code

Get started by decorating your Python functions with @weave.op
You can try Weave out in this interactive Colab:

import weave
weave.init("matthew-berman")

@weave.op()
def sum_nine(value_one: int):
return value_one + 9

@weave.op()
def multiply_two(value_two: int):
return value_two * 2

@weave.op()
def main():
output = sum_nine(3)
final_output = multiply_two(output)
return final_output

♾️ Weave supports any use case

RAG applications, image generation, benchmarking, Weave can support you in any enterprise, academic or side project and here are some projects powered by Weave:


🤝 Weave lives where you work

Weave offers integrations with many language model APIs and LLM frameworks to streamline tracking and evaluation:


Stay focused on iterating on your prompts and models with whichever API or LLM framework you know and love - Weave has integrations for OpenAI, Anthropic, Mistral.ai, LlamaIndex, Cohere and more.
See our integrations


🧑‍🎓 Explore Weave and build LLM apps with our free courses

Our courses will give you a theory and code to dive into the area of your interest. Our LLM courses range from short, problem focused courses to a more advanced deeper dives. Each course is equipped with theory, code and led by industry experts.


Check out all our courses (and enroll for free!)


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