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genaiscript

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Basic Information

GenAIScript is a JavaScript and TypeScript toolbox for developers to programmatically assemble prompts and orchestrate large language models, tools, and data as code. It provides a prompt template tag ($) and helper functions like def and defSchema to include files, define schemas, and optimize context for target models. The project supports ingesting PDFs, DOCX, CSV, and XLSX, parsing outputs into files, and previewing changes. It integrates with Visual Studio Code and offers a command-line interface and API for automation. GenAIScript supports multiple model backends including GitHub Models and Copilot, OpenAI and Azure OpenAI, Anthropic, and local models via runtimes like Ollama or LocalAI. It also includes features for registering JavaScript tools, composing agents, vector search for RAG, code interpreter execution, containerized runs, video processing, secret scanning, and built-in content safety system prompts to help build reproducible, testable GenAI workflows.

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2760
App URL
https://github.com/microsoft/genaiscript
Github Repository
https://github.com/microsoft/genaiscript/blob/main/README.md

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App Details

Features
Stylized JavaScript and TypeScript prompting with a $ template tag and helper APIs for defining context and schemas. Fast development loop with editing, debugging, running, and testing in Visual Studio Code or via a CLI. Data schemas and Zod support for structured extraction and validation. Parsers and ingestion for PDFs, DOCX, CSV, and XLSX, plus file search and diffs. LLM tools and MCP tool support via defTool and defAgent to register and compose tools into agents. Built-in RAG/vector search and utilities for composing multiple LLM calls. Support for GitHub Models, Copilot, OpenAI, Azure OpenAI, Anthropic, and local model runtimes. Runtime integrations include a sandboxed code interpreter, Docker containers, video transcription and frame extraction, secret scanning, and content safety checks. Automation via CLI and API and testing/evals support for reliable prompts.
Use Cases
GenAIScript helps developers and teams convert prompting into reproducible code workflows so LLM-powered tasks can be versioned, shared, and automated. It reduces friction by providing helpers to include and optimize file content, define exportable schemas, and automatically parse structured LLM outputs into files. Developers can register and reuse tools, build agents that combine prompts and programmatic actions, and run vector searches for retrieval-augmented generation. Integration with VS Code, a CLI, and an API simplifies iteration and CI automation such as pull request checks. Support for multiple model backends and local runtimes enables portability and offline testing. Built-in safety, secret scanning, tests and evals make deployments safer and more reliable while container and code-execution features allow complex data processing within scripted pipelines.

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