Opro

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opro is an AI Agents & Automation tool that provides the official code for the research paper "Large Language Models as Optimizers." It allows users to replicate and experiment with LLMs for optimization tasks, supporting models like text-bison and GPT.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is opro?

opro is the official code repository for the research paper "Large Language Models as Optimizers" by Google DeepMind. This tool provides the foundational codebase for researchers and developers to replicate and further experiment with the findings presented in the paper. It is designed to work with Python 3.10.13 and supports various dependencies including absl-py, google.generativeai, immutabledict, and openai. Users can perform prompt optimization, prompt evaluation, and apply LLMs to specific problems like linear regression and the traveling salesman problem. The repository currently supports text-bison and GPT models, with options to integrate self-served models. It emphasizes careful consideration of API costs for external models.

Best used for

Ideal for developers and data scientists who need to implement and experiment with large language models for optimization tasks, such as prompt optimization and evaluating LLM performance. Especially valuable for researchers looking to replicate the findings of the "Large Language Models as Optimizers" paper or explore new applications of LLMs in problem-solving.

Common actions

optimize prompts

evaluate LLMs

apply LLMs to optimization

replicate research

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Capabilities

Key features

Prompt optimization
Prompt evaluation
Linear regression optimization
Traveling salesman problem optimization
Supports text-bison models
Supports GPT models
Custom model integration

Target Audience

developerdata scientistprofessorstudent

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What programming language and dependencies are required to use opro?

opro is verified to work with Python 3.10.13. Key dependencies include absl-py, google.generativeai, immutabledict, and openai. Users should ensure these are installed to run the code successfully for prompt optimization and evaluation tasks.

Which large language models are supported by opro?

The current version of opro supports text-bison and GPT models for optimization and evaluation tasks. Additionally, the framework is designed to allow users to integrate and utilize their own self-served models by plugging them into the existing prompting APIs.

Are there any cost considerations when using opro?

Yes, calling external APIs like PaLM or GPT for prompt optimization and evaluation can incur significant costs. Users are advised to carefully estimate expenses, start with lighter usage, or consider using self-served models to manage potential charges.

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