Esmeralda Agentic: Multi-Turn Conversations Generated by LLMs

A collection of multi-turn conversational interactions generated by various large language models (LLMs). Each row represents a single conversation consisting of an ordered array of messages together with the originating model. The dataset was created by Locutusque and was last updated on Hugging Face in May 2026.

Use Cases

• Analyze instruction-following capabilities based on multi-turn conversational interactions.
• Study tool-calling behavior in LLMs based on the structured message arrays.
• Research reasoning traces and model performance across different LLM sources.

Strengths

• Conversations include an ordered array of messages, suggesting a structured format for analysis.
• Each conversation is labeled with its originating LLM source, enabling model-specific comparisons.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Hugging Face dataset repository by Locutusque.

Collection Method

Generated by various large language models (LLMs).

Freshness

Last updated 2026-05-25 19:43:41; freshness should be verified.