Update README.md

README.md

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 ---
 title: ChronoQuery
 emoji: 🏆
-colorFrom: yellow
+colorFrom: red
 colorTo: blue
 sdk: streamlit
-sdk_version: 1.46.0
+sdk_version: 1.50.0
 pinned: false
 short_description: Unlock the past — ask about any historical event and get ins
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+**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 |
+
+---