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rasa-configuring-model-groups

Official

Configure LLM and embedding providers.

Software Engineering#embeddings#llm#configuration#rasa#endpoints.yml#model groups
AuthorRasaHQ
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill simplifies the complex task of configuring model groups in endpoints.yml, enabling seamless integration and routing for various LLM and embedding providers within Rasa.

Core Features & Use Cases

  • Provider Configuration: Set up LLM and embedding providers (OpenAI, Azure, self-hosted, etc.) in endpoints.yml.
  • Multi-Deployment Routing: Configure strategies like least-busy or latency-based routing for multiple model deployments within a single group.
  • Caching & Failover: Implement response caching and define failover mechanisms for robust model group operation.
  • Use Case: When setting up a new Rasa project that requires routing requests to multiple LLM instances for load balancing, use this Skill to define the model_groups in your endpoints.yml.

Quick Start

Configure a model group for OpenAI embeddings in your endpoints.yml file.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: rasa-configuring-model-groups
Download link: https://github.com/RasaHQ/rasa-agent-skills/archive/main.zip#rasa-configuring-model-groups

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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