Provide Rust abstractions for composing LLM chains with streaming and typed errors.
npx skills add https://github.com/wesichain/wesichain --skill wesichain-core
Please help me install this Agent Skill. Skill: wesichain-core Source: https://github.com/wesichain/wesichain/tree/main/.claude/skills/wesichain-core Command: npx skills add https://github.com/wesichain/wesichain --skill wesichain-core
This Skill provides the foundational building blocks for creating robust, composable, and type-safe LLM applications in Rust, enabling developers to build complex agentic workflows with ease.
.then() for LCEL-style pipelines.WesichainError for robust error management.Use the wesichain-core skill to create a chain by composing a prompt template with a dummy LLM and a simple parser.
High-intent search queries and answers about installing and using this skill.
To build composable LLM pipelines in Rust, you implement the Runnable trait for modular components and link them together using the `.then()` method via RunnableExt. This enables LCEL-style chaining for complex agentic workflows.
LCEL-style chaining is a pipeline pattern for LLM applications that links modular components sequentially. In Rust, it works by implementing the Runnable trait and using RunnableExt to compose type-safe pipelines with `.then()`.
Yes, you can stream output and handle errors in Rust LLM chains. The framework supports streaming output and provides a unified WesichainError type for robust, type-safe error management across composed components.
You create a ReAct agent in Rust by composing modular components into a single type-safe chain. Implement the Runnable trait for tool retrieval, prompt formatting, and LLM summarization, then link them using RunnableExt.
No external dependencies are required to use these core abstractions. The framework provides the foundational Runnable trait and RunnableExt internally, allowing you to build robust LLM applications without external library dependencies.
The best way to manage type safety in Rust LLM applications is using core abstractions like the Runnable trait. This ensures modular components compose safely, while a unified WesichainError handles errors robustly across complex chains.
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