Textgrad

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TextGrad is an open-source Coding & Development tool that enables automatic "differentiation" via text, using large language models to backpropagate textual gradients. It offers a PyTorch-like API for optimizing variables with text feedback.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is textgrad?

TextGrad is an open-source framework designed for automatic "differentiation" via text, leveraging large language models (LLMs) to backpropagate textual gradients. It provides a powerful and intuitive API, similar to PyTorch, allowing users to define loss functions and optimize them using text feedback. The tool supports optimizing various variables, including code snippets, solutions to problems, molecules, and prompts. Recent updates introduce a new engine based on LiteLLM, expanding compatibility to models like Bedrock, Together, and Gemini, and enabling caching. TextGrad has been published in Nature, highlighting its significance in the field.

Best used for

Ideal for researchers and developers who need to optimize LLM outputs, refine text-based solutions, and improve prompt engineering strategies. Especially valuable for those working on complex AI systems requiring iterative textual feedback and gradient-based optimization.

Common actions

optimize LLM responses

refine text-based solutions

improve prompt engineering

backpropagate textual gradients

deepfakecollaborationlow-code/no-codeopen-sourceautomated workflowface swappinggithub copilot"AI Agents"workflows

Capabilities

Key features

Textual gradient backpropagation
PyTorch-like API
LLM text feedback optimization
Prompt optimization
Solution optimization
Supports multiple LLM engines
Caching capabilities

Target Audience

professordeveloperresearcher

Integrations

litellm

Pricing & Plans

Open Source

Free

FAQs

What kind of variables can TextGrad optimize?

TextGrad can optimize various unstructured variables, including text-based solutions to problems, code snippets, molecules, and prompts. Its flexible framework allows for applying textual gradients to improve a wide range of textual outputs from LLMs.

How does TextGrad's API compare to PyTorch?

TextGrad's API is designed to be similar to PyTorch, making it intuitive for users familiar with deep learning frameworks. It allows defining loss functions and optimizers, and performing forward and backward passes using textual gradients, mirroring PyTorch's autograd engine.

Which LLM engines are supported by TextGrad?

TextGrad supports various LLM engines, including OpenAI's GPT-4o and gpt-3.5-turbo. With its experimental LiteLLM-based engine, it also extends compatibility to models from Bedrock, Together, and Gemini, offering broad flexibility in model choice.

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Open Source & Models Code Assistants DevOps & Infrastructure No-Code / Low-Code Testing & QA Backend & APIs

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Also listed in

This tool also appears in

Research & Education › Academic Research AI Agents & Automation › AI Frameworks & Infra

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