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| title: ChronoQuery | |
| emoji: 🏆 | |
| colorFrom: red | |
| colorTo: blue | |
| sdk: streamlit | |
| sdk_version: 1.50.0 | |
| pinned: false | |
| short_description: Unlock the past — ask about any historical event and get ins | |
| **ChronoQuery** is an intelligent, AI-powered historical event explainer that allows users to explore the past interactively. | |
| Just type in a historical event, figure, or question — and get **instant, research-backed insights** compiled from reliable sources like **Wikipedia** and **DuckDuckGo Search**, all refined through **Google’s Gemini AI**. | |
| --- | |
| ## 🧠 What It Is | |
| ChronoQuery is an **AI history assistant** built with **Streamlit** and **LangChain**, powered by **Google’s Gemini 2.5 Flash model**. | |
| It’s designed to help users learn about historical topics effortlessly — whether you’re a student, researcher, or just curious about world events. | |
| --- | |
| ## ⚙️ What It Does | |
| ✅ Takes any historical question or event as input | |
| ✅ Automatically identifies the **core topic or event** using an AI-based topic extractor | |
| ✅ Fetches relevant content from **Wikipedia** and **DuckDuckGo** | |
| ✅ Combines and refines the data using **Gemini AI** for an accurate, contextualized answer | |
| ✅ Displays results in an elegant, user-friendly Streamlit interface | |
| --- | |
| ## 🔍 How It Works | |
| ChronoQuery uses a modular AI workflow powered by **LangChain Runnables**: | |
| 1. **User Query → Topic Extraction** | |
| - The app identifies the main topic or event using Gemini’s language understanding. | |
| 2. **Knowledge Retrieval** | |
| - Fetches relevant summaries from **Wikipedia** (via `WikipediaRetriever`). | |
| - Collects additional web context using **DuckDuckGo Search**. | |
| 3. **Data Combination** | |
| - Both Wikipedia and web data are merged into a unified context string. | |
| 4. **AI Reasoning & Summarization** | |
| - The combined data is sent to **Gemini 2.5 Flash**, which formulates a detailed, coherent response. | |
| 5. **Output Rendering** | |
| - Streamlit displays the results beautifully, allowing users to query multiple times interactively. | |
| --- | |
| ## 🧩 Technologies Used | |
| | Component | Technology / Library | Purpose | | |
| |------------|----------------------|----------| | |
| | 🧱 Framework | **Streamlit** | Builds the interactive web interface | | |
| | 🧠 AI Model | **Google Gemini 2.5 Flash (via `google.generativeai`)** | Generates contextual answers | | |
| | 🔗 Orchestration | **LangChain (core, community)** | Manages chains, prompts, and data flow | | |
| | 📚 Knowledge Base | **WikipediaRetriever** | Retrieves factual content | | |
| | 🌐 Web Search | **DuckDuckGoSearchRun** | Adds recent or broader information | | |
| | 🧩 Utilities | **RunnableLambda, RunnableParallel, StrOutputParser** | Custom data pipelines and parsing | | |
| | 💾 Language | **Python 3.10+** | Main development language | | |
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