

Inductor Custom Playgrounds
Overview :
Inductor Custom Playgrounds is a platform designed for developers to accelerate the development process, shorten time to market, and create more effective LLM applications and features through the automation of generating shareable LLM application development environments. The platform supports developers in rapid iteration and experimentation, building high-quality LLM applications through collaborative and data-driven approaches.
Target Users :
Inductor Custom Playgrounds is targeted towards developers, especially teams who need to rapidly build, test, and iterate on LLM applications. It is suitable for enterprises who require using private data and internal systems in a secure environment, as well as developers who need to quickly gather feedback and collaboratively optimize applications.
Use Cases
Development and testing of AI chatbots.
Development of document assistant functionality to help users quickly find information.
Implementation of text-to-SQL features to simplify database query processes.
Features
Automatically generates a custom user interface integrated directly with specific LLM applications.
Runs directly in the user environment, supporting the use of private data and internal systems.
Supports secure collaboration, allowing team members to share work, collect feedback, and leverage collective expertise within the playground.
Accelerates development through features like UI auto-generation, hot reloading, automatic logging, and integration testing suite management.
Provides rapid prototyping and system evaluation for LLM applications or features.
Supports specific features for multi-turn dialogue applications, such as `inductor.ChatSession` type annotations.
How to Use
1. Install the Inductor CLI tool by executing the command `pip install inductor`.
2. Execute the command `inductor playground my.module:my_function` in the terminal, where `my.module:my_function` is the Python function entry point for the LLM application.
3. If developing a multi-turn chat application, add a `inductor.ChatSession` type annotation before the entry function.
4. Refer to the documentation for more information on how to use Custom Playgrounds.
5. After generating the playground, you can immediately share the LLM application with technical or non-technical colleagues to collect feedback.
6. Utilize interactive development with hot reloading, logging, and playback features to continuously evolve the LLM application.
7. Convert interactions into repeatable test suites for system evaluation.
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