Integrate Mistral Nemo with LlamaIndex for Context

Integrate Mistral Nemo via LlamaIndex into your control system to provide intelligent assistance. The LLM should be able to interpret the current robot state (e.g., joint positions, force-torque sensor data), environmental context (e.g., object locations, obstacle maps, task goal descriptions), and operator queries to provide context-aware suggestions or warnings. Explain your RAG strategy using LlamaIndex to query relevant robot documentation, task manuals, or past successful task logs to enhance the LLM's knowledge base.