Update README.md

README.md

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-# 🌾 Project Samarth — Intelligent Q&A System
-**Bridging Agriculture & Climate Insights using Live Government Data**
-
----
-
-### 🧠 Overview
-
-**Project Samarth** is an intelligent **Q&A system** built to analyze and answer complex, data-driven questions about **India’s agricultural economy** and its relationship with **climate patterns** — powered entirely by **live datasets from [data.gov.in](https://data.gov.in/)**.
-
-This system fetches real-time data from the:
-- 🏛️ **Ministry of Agriculture & Farmers Welfare**
-- 🌦️ **India Meteorological Department (IMD)**
-
-It integrates both datasets and allows users to query them in **natural language** through a clean **Streamlit-based interface**.
-
----
-
-### 🎯 Problem Statement
-
-Government portals like **data.gov.in** contain thousands of valuable datasets — but they exist in diverse formats across ministries, making it difficult to extract cross-domain insights.
-
-**Your Mission:**  
-To design and build a **functional end-to-end prototype** that:
-1. Fetches live government data using APIs.
-2. Integrates multiple datasets (Agriculture + IMD Rainfall).
-3. Enables users to ask **natural language questions**.
-4. Returns accurate, traceable, and data-backed insights with proper citations.
-
 ---
-
-### 🚀 Features
-
-✅ **Real-Time API Integration**
-- Fetches data directly from `data.gov.in` via official API keys and resource IDs.  
-- Agriculture: Crop production data (1997–2014)  
-- IMD: Sub-divisional rainfall data (1901–2017)
-
-✅ **Data Integration Layer**
-- Automatically merges climate and crop production datasets using cleaned and normalized state names.
-
-✅ **Intelligent Q&A Engine**
-- Understands queries like:
-  - “Compare rainfall and rice production in Bihar and Jharkhand for the last 5 years.”
-  - “Analyze crop trends in Andhra Pradesh.”
-
-✅ **Streamlit Chat Interface**
-- Simple user input box.
-- Clean, markdown-based formatted answers.
-- Auto-citation of data sources.
-
-✅ **Accuracy & Traceability**
-- Every answer is directly backed by the live dataset and cited source.
-
----
-
-### 🧩 System Architecture
-
-User (Streamlit UI)
-│
-▼
-Natural Language Parser (LLM / Keyword Extractor)
-│
-▼
-Query Engine (Pandas Logic)
-│
-▼
-Data Layer (APIs + Local CSV Integration)
-│
-▼
-Answer Generator (Formatter + Citation)
-
-
+title: "🌾 Project Samarth — Intelligent Q&A System"
+emoji: 🌦️
+colorFrom: green
+colorTo: blue
+sdk: streamlit
+sdk_version: "1.38.0"
+app_file: app.py
+pinned: false
+license: mit
 ---
 
-### 🧰 Tech Stack
-
-| Layer | Tools / Libraries |
-|-------|--------------------|
-| Data Fetching | `requests`, `pandas`, `json` |
-| Data Integration | `pandas`, `numpy` |
-| NLP Parsing | Custom keyword parser / rule-based |
-| Visualization | `matplotlib`, `seaborn`, `plotly` |
-| Frontend | `streamlit`, `style.css` |
-| Backend Logic | Python 3.10+ |
-| Source | [data.gov.in](https://data.gov.in) APIs |
+# 🌾 Project Samarth — Intelligent Q&A System
 
----
+An AI-powered Q&A interface that integrates live government data from **data.gov.in**  
+to answer natural language questions about agriculture and climate.  
 
-### ⚙️ Setup Instructions
+## 🧠 Features
+- Real-time data fetching via official APIs (Agriculture + IMD)
+- Automatic data cleaning, merging, and correlation
+- Streamlit chatbot for user-friendly question answering
+- Source citation for every answer
 
-1️⃣ **Clone the Repository**
+## ⚙️ Run Locally
 ```bash
-git clone https://github.com/<your-username>/Project_Samarth.git
-cd Project_Samarth
-
-2️⃣ Create a Virtual Environment
-
-python -m venv venv
-source venv/bin/activate   # (or venv\Scripts\activate on Windows)
-
-
-3️⃣ Install Dependencies
-
 pip install -r requirements.txt
-
-
-4️⃣ Fetch & Integrate Data
-
-python main.py
-
-
-5️⃣ Run the Streamlit Q&A Interface
-
-streamlit run ui/app_streamlit.py
-
-🧠 Example Query
-
-Input:
-
-Compare rainfall and rice production in Andaman and Nicobar Islands for the last 5 years
-
-
-Output:
-
-📊 Analysis for Andaman and Nicobar Islands — Crop: Rice
-
-🌧️ Average Rainfall (mm):
- • Andaman and Nicobar Islands: 1142.46
-
-🌾 Total Production (tonnes):
- • Andaman and Nicobar Islands: 45,451
-
-📚 Data Source: Ministry of Agriculture & Farmers Welfare and India Meteorological Department (IMD), data.gov.in
-
-🧩 Key Dataset References
-Dataset	Ministry	API Resource ID
-District-wise Crop Production Statistics (1997–2014)	Ministry of Agriculture & Farmers Welfare	xxxxx
-Sub-divisional Rainfall Data (1901–2017)	India Meteorological Department (IMD)	xxxxxx
-
-👨‍💻 Developed By
-Satyam Kumar
+streamlit run app.py