# DSPy DSPy is an open-source framework for programming language-model applications instead of manually prompting them. Its public repository provides the project code, documentation, tests, issue tracking, and contribution workflow. - Findings24: - Website: - Pricing: Freemium - Categories: AI Agent Infrastructure, AI Developer Tools ## What is DSPy? DSPy is an open-source framework from the Stanford NLP organization for programming language-model applications rather than manually writing prompts. Its public GitHub repository contains the project source, documentation, tests, scripts, configuration, and community development workflow. The available page evidence identifies DSPy’s core positioning, but does not provide enough detail to document specific integrations, installation commands, deployment environments, or model-provider support. ## What can DSPy do? ### Programming-oriented language-model framework DSPy is presented as a framework for programming—not prompting—language models, giving the project a code-centered approach to language-model application development. ### Public source repository The repository is public and includes the main \`dspy\` source directory, allowing users and contributors to inspect the implementation. ### Project documentation A dedicated \`docs\` directory and README are included in the repository, providing the project’s documented entry points. ### Automated test suite The repository includes a \`tests\` directory, which provides a visible place for project validation and regression coverage. ### Contribution and security materials CONTRIBUTING.md and SECURITY.md are present, giving the project documented locations for contribution guidance and security reporting information. ### Built-in open-source development workflow GitHub Issues, pull requests, Discussions, Actions, Projects, and the repository’s branch and tag history support public software development around DSPy. ## Use Cases ### Evaluate a language-model programming framework Developers can review the README, documentation, source tree, and tests to determine whether DSPy fits a language-model application project. ### Prototype from an inspectable codebase Teams that prefer to assess dependencies and implementation details directly can examine the public repository before building on the framework. ### Contribute framework changes Engineers can use the repository’s contribution guidance, issues, pull requests, and discussions to propose or review changes. ### Study implementation and project evolution Researchers and developers can inspect commits, branches, tags, documentation, and tests to follow how the framework changes over time. ## Frequently Asked Questions ### What is DSPy? DSPy is an open-source framework from the Stanford NLP organization whose stated focus is programming—not prompting—language models. ### Where is DSPy developed? DSPy is developed in the public \`stanfordnlp/dspy\` repository on GitHub, which contains its source, documentation, tests, and project-management workflow. ### Can people contribute to DSPy? Yes. The repository includes contribution guidance and exposes issues, pull requests, and discussions for public project participation. ### Does the supplied source list DSPy’s integrations or supported model providers? No. The supplied page evidence does not establish a supported-provider list, integration catalog, installation procedure, or deployment requirements; those details should be verified in the project documentation. ## Quick Facts - **Category**: Developer Tool - **Project type**: Open-source language-model framework - **Repository**: github.com/stanfordnlp/dspy - **Maintainer organization**: Stanford NLP - **Primary workflow**: Programming language-model applications - **Public development**: Issues, pull requests, discussions, tests, and documentation