Chat-Agent-1M: 919,869 English Chat Conversations with Chain-of-Thought Reasoning

919,869 English chat and agentic conversations are formatted in ChatML (Anthropic-style) Messages. Every assistant turn begins with a short, dense chain-of-thought reasoning tag (<reasoning>) that leads to the final answer. The dataset was created by GasaiAI and is built on top of the curated answers from HuggingFaceTB/smoltalk2, with a last update timestamp of 2026-06-21.

Use Cases

• Fine-tuning language models for structured reasoning based on the chain-of-thought (<reasoning>) format mentioned in the description.
• Training or evaluating agentic AI systems based on the tool-use trajectories (tool availability → call → result → answer) present in ~30% of conversations.
• Studying the structure and patterns of multi-turn, task-oriented dialogues based on the ChatML (Anthropic-style) Messages format.
• Developing benchmarks for grounded reasoning where model responses must integrate external tool results.

Strengths

• Contains 919,869 English conversational records, providing substantial scale for training.
• Every assistant turn includes a structured chain-of-thought (<reasoning>) prefix, explicitly modeling the reasoning process.
• Approximately 30% of conversations include complete tool-use trajectories, offering data for grounded agentic interactions.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is built on another curated source (HuggingFaceTB/smoltalk2); potential biases or limitations from the original source may propagate.

Provenance

Source

GasaiAI, built on HuggingFaceTB/smoltalk2.

Collection Method

Conversations are built on top of curated answers from another dataset, with added chain-of-thought and tool-use trajectories.

Freshness

Last updated 2026-06-21 15:22:36; freshness should be verified.