Feat/improve

.config/store.json

@@ -0,0 +1,17 @@
+{
+  "users": {
+    "1711055629": {
+      "name": "Ayush",
+      "roll": "6372373",
+      "uni": "IIITM Gwalior"
+    }
+  },
+  "sessions": {
+    "1711055629": {
+      "step": "AWAITING_PLATFORM",
+      "context": "Make a assignment for bubble sort and give me pdf withe rhr code and code op screenshot",
+      "solution": "Assignment: Implementation and Performance Analysis of Bubble Sort Algorithm\nStudent Name: Ayush\nRoll Number: 6372373\nUniversity: IIITM Gwalior\nDate: 4/1/2026\n\n1. Objective\nThe objective of this assignment is to implement the Bubble Sort algorithm, document the step-by-step logic, provide the source code, and analyze its time complexity in the context of sorting an array of integers.\n\n2. Problem Statement\nWrite a program to sort an array of $n$ elements using the Bubble Sort technique. The program must:\na) Accept input size $n$ and an array of $n$ integers from the user.\nb) Perform the sort by repeatedly stepping through the list, comparing adjacent elements, and swapping them if they are in the wrong order.\nc) Display the sorted array.\n\n3. Algorithm Description\nBubble Sort is a comparison-based algorithm where each pair of adjacent elements is compared, and elements are swapped if they are not in order. This process repeats until the array is sorted.\n- Time Complexity: O(n²) in the worst and average cases.\n- Space Complexity: O(1) as it is an in-place sorting algorithm.\n\n4. Source Code (Python)\n```python\ndef bubble_sort(arr):\n    n = len(arr)\n    for i in range(n):\n        for j in range(0, n - i - 1):\n            if arr[j] > arr[j + 1]:\n                arr[j], arr[j + 1] = arr[j + 1], arr[j]\n    return arr\n\n# Driver code\nif __name__ == \"__main__\":\n    data = [64, 34, 25, 12, 22, 11, 90]\n    print(\"Original array:\", data)\n    sorted_data = bubble_sort(data)\n    print(\"Sorted array:\", sorted_data)\n```\n\n5. Output Screenshot Placeholder\n[Insert Screenshot of Program Execution Here]\n\n6. Conclusion\nThe implementation confirms that Bubble Sort is effective for smaller datasets but inefficient for large-scale data due to its quadratic time complexity. Proper documentation of the swapping mechanism demonstrates the fundamental working principle of the algorithm.",
+      "format": "Pdf with code op"
+    }
+  }
+}

.env

@@ -0,0 +1 @@
+TELEGRAM_BOT_TOKEN=8606625998:AAGuNWcFKDyXBSBITEie_NCSqZ2j2GZ6dC4

.gitignore

@@ -64,20 +64,17 @@ web_modules/
 
 # Yarn Integrity file
 .yarn-integrity
-
-# dotenv environment variable files
-.env
-.env.*
-!.env.example
+.config
 
 # parcel-bundler cache (https://parceljs.org/)
 .cache
 .parcel-cache
 
 # Next.js build output
 .next
+.env
 out
-
+.config
 # Nuxt.js build / generate output
 .nuxt
 dist

README.md

@@ -1 +1,71 @@
-# scholarsync
+# ScholarSync: Openclaw for students 🎓
+
+ScholarSync is an automated study and assignment agent that you interact with directly through your favorite messaging platforms. By providing assignment prompts and specific platform instructions, ScholarSync will solve, format, and upload your academic coursework exactly how you need it.
+
+---
+
+## 🚀 Key Features
+
+### 💬 Multi-Platform Messaging Integration
+
+Interact with ScholarSync easily on:
+
+- **Telegram**
+- **WhatsApp** *(Coming soon)*
+- **Slack** *(Coming soon)*
+
+### 📝 Seamless Onboarding
+
+The first time you interact with the bot, you will be onboarded to specify your permanent details:
+
+- **Roll Number**
+- **Name**
+- **University / College**  
+These details are automatically attached and formatted into your generated assignments.
+
+### 📚 Complete Assignment Solving
+
+Provide the bot with all required details to solve your assignment (e.g. prompt text, PDF documents, or images via OCR). ScholarSync analyzes the requirements and processes the solution precisely.
+
+### 📤 Custom Upload Destinations
+
+Tell ScholarSync which platform to upload the finished assignment to (e.g., Moodle, Canvas, Github Classroom, or a custom university portal) and the bot will handle the final submission via browser automation.
+
+### 🗂️ Flexible Output Formats
+
+Tell the bot *exactly* what you need. ScholarSync can provide and format:
+
+- **PDF Documents** (theory and conceptual answers).
+- **Source Code** files (`.js`, `.py`, `.cpp`, etc.).
+- **Code Output** text files.
+- **Code Execution Screenshots** (Visual proof that your code executed successfully).
+
+### 🧠 Bring Your Own Model (Local & API)
+
+Running an open-source model like Llama locally? Or prefer using an external API? ScholarSync allows you to run a local model as well through API keys, giving you complete control over costs, privacy, and the intelligence engine behind the solver.
+
+---
+
+## 🛠️ Built With
+
+- **Node.js**: As the core backend environment.
+- **Telegraf**: For Telegram integration.
+- **Puppeteer**: For headless browser automation (capturing output screenshots, uploading assignments).
+- **PDF-Parse & Tesseract.js**: For parsing and reading assignment documents and images.
+- **Googleapis**: For integrating with Drive or external storages.
+
+## 🚀 Getting Started
+
+1. Set up your `.env` file with the necessary API Keys (Telegram Bot Token, LLM Config, etc.).
+2. Depending on your needs, you can start the service as a CLI tool or a background Bot Daemon.
+3. Install dependencies:
+
+   ```bash
+   npm install
+   ```
+
+4. Run the development environment:
+
+   ```bash
+   npm start # (Ensure you configure standard start scripts in package.json to run src/index.ts)
+   ```