what is HistorIQ?
HistorIQ is an AI-driven platform for generating historical novels based on the Model Context Protocol (MCP) architecture. It integrates Retrieval-Augmented Generation (RAG), AI Agents, and locally deployed large language models (LLMs) to allow users to ask questions about historical events, figures, and cultural themes, generating contextually relevant answers through multi-stage reasoning and knowledge retrieval.
how to use HistorIQ?
Users can interact with HistorIQ by inputting their queries in natural language regarding historical topics, and the system will generate responses in the form of chapters of a historical novel.
key features of HistorIQ?
- MCP Architecture: Modular and scalable design separating Client, Server, Agent, and RAG.
- Historical Novel Generation: AI acts as a historical novelist, automatically crafting chapters and narratives.
- Chapter-based Narrative Structure: Each generation includes 4-6 chapters with coherent themes and literary quality.
- Cultural Enrichment: AI incorporates classical quotes and poetry to enhance the reading experience.
- Full Traditional Chinese Design: The interface and content are designed for local cultural reading habits.
- Voice Reading and Highlight Animation: Supports story reading with synchronized highlighting and background music.
- Interactive Features: Users can extend stories, rewrite styles, or summarize content interactively.
- RAG Integration: Incorporates retrieval-based generation to supplement background knowledge.
use cases of HistorIQ?
- Generating engaging historical narratives for educational purposes.
- Assisting writers in creating historically accurate fiction.
- Providing interactive storytelling experiences for users interested in history.
FAQ from HistorIQ?
- Can HistorIQ generate novels on any historical topic?
Yes! HistorIQ can generate content on a wide range of historical events and figures.
- Is there a cost to use HistorIQ?
HistorIQ is free to use for all users.
- How accurate are the historical details in the generated content?
The accuracy depends on the input queries and the underlying data used for generation.