https://github.com/algsoch/bodhai
The vicky_server.py module powers the Vicky Data Science Assistant by executing solutions dynamically based on query patterns. With extensive pattern recognition and specialized solvers, it provides an efficient and scalable approach to answering data science queries.
https://github.com/algsoch/bodhai
action chatbot fastaapi html-css-javascript python requests requets uvicorn
Last synced: about 1 month ago
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The vicky_server.py module powers the Vicky Data Science Assistant by executing solutions dynamically based on query patterns. With extensive pattern recognition and specialized solvers, it provides an efficient and scalable approach to answering data science queries.
- Host: GitHub
- URL: https://github.com/algsoch/bodhai
- Owner: algsoch
- License: mit
- Created: 2025-04-03T15:47:12.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-04-11T08:05:45.000Z (about 1 month ago)
- Last Synced: 2025-04-12T20:54:01.739Z (about 1 month ago)
- Topics: action, chatbot, fastaapi, html-css-javascript, python, requests, requets, uvicorn
- Language: Python
- Homepage: https://app.algsoch.tech/
- Size: 500 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🎯 IIT MADRAS TDS PROBLEM SOLVER
---
## 🚀 System Architecture & Technology Stack
### 🏗 Core Components
- **Backend Architecture**: Python-based with FastAPI framework
- **Frontend**: Responsive single-page application using HTML5, CSS3, and vanilla JavaScript
- **Integration Layer**: Webhook support for Discord, Slack, and Telegram notifications
- **Data Processing**: Python core libraries with specialized modules for file handling
- **Question Processing Engine**: Pattern matching algorithm with specialized solvers
---
## 📁 Core Files
- 🖥 **vicky_app.py**: Web server, API endpoints, HTML rendering, and system management
- 🧠 **vicky_server.py**: Question analysis, pattern matching, and solution generation
---
## 🔍 Technical Implementation Details
### 📡 Communication Infrastructure
#### 1️⃣ Webhook Integration System
The webhook system uses a buffering mechanism to batch notifications, preventing overload while maintaining detailed logs.
🔹 **Supported Platforms:**
✅ **Discord**: Rich message formatting with embedded content
✅ **Telegram**: Direct messages to specified chat IDs
✅ **Slack**: Interactive messages through incoming webhooks
### 🧩 Pattern Matching Engine
The engine uses regex patterns for:
- 📌 **Contextual Understanding**: Detecting specific question types
- 🏷 **Command Recognition**: Identifying code commands and parameters
- 📑 **Assignment Classification**: Routing questions to GA1-GA5 solvers
- 📂 **File Association**: Linking relevant uploaded files
### 📂 File Management System
- 🔑 **Generates Unique IDs**: 8-character identifiers for each file
- 🏷 **Stores Metadata**: Tracks filenames, timestamps, and file types
- 🔗 **Provides Contextual Access**: Allows referencing files by ID
- 📌 **Type-Specific Handling**: Different processing for ZIP archives vs. README files
### 🎨 Base64 Image Decoder/Encoder
- 🔒 **Client-side implementation** for security and performance
- 🏷 **Intelligent Format Detection** for automatic prefix correction
- 🚀 **Robust Error Handling** for malformed Base64 data
- 📋 **Clipboard Integration** for direct image pasting
### 🌍 HTML Viewer with CORS Proxy
- 🔓 **Bypass CORS Restrictions** via third-party proxy
- 📜 **Render Live Content** in sandboxed iframe
- 📖 **Provide Source Viewing** for analysis
- ✂ **Enable HTML Copying** for modification
### ⚡ API Layer & Documentation
- 🔹 **Multiple Response Formats**: JSON and HTML output
- 🔹 **File Upload Support**: Process questions with attached files
- 🔹 **Notification Integration**: Webhook notifications for API calls
- 🔹 **Security Features**: IP logging, optional rate limiting
### 🔐 Authentication and Security
- 🛡 **IP Logging**: Tracks API and UI interactions
- 🔑 **Admin Endpoints**: Secure access to logs and analytics
- 🔒 **Environment Variables**: Sensitive values stored securely
- ⚠ **XSS Protection**: HTML escaping for user-generated content
- ✅ **Input Validation**: Thorough validation of user inputs
---
## 🎨 User Interface Components
### 💬 1. Chat Interface
- 💾 **Message History**: Displays assistant conversation
- 📝 **Code Formatting**: Syntax highlighting
- 📂 **File Uploads**: Drag-and-drop and button-based
- 📋 **Copy Functionality**: One-click copying of code blocks
### 📌 2. Question Categories & Navigation
- 🏷 **Tab-Based Navigation** for easy category switching
- 🔄 **Dynamic Content Loading** based on selection
- 🎯 **Active State Tracking** for visual feedback
### 📂 3. File Management UI
- 📜 **File Listing**: Shows all uploaded files with metadata
- ⚙ **File Actions**: Use or delete files
- 📤 **Upload Interface**: Simple form-based upload
---
## 🔗 Integration Architecture
### 🔄 1. Server-Client Communication
- 🌍 **RESTful API Pattern** with:
- 📜 Form Data: `multipart/form-data` for file uploads
- 📡 JSON Responses: Structured data
- 📄 HTML Responses: Rendered content
- 📢 **Status Updates** for real-time monitoring
### 🔧 2. External Service Integration
- ✅ **Discord**: Webhook notifications--whenever anybody hit [api](https://app.algsoch.tech/api)
- ✅ **Slack**: Incoming webhook events--whenever anybody hit [api](https://app.algsoch.tech/api)
- ✅ **CORS Proxy**: Third-party service for HTML viewing
- ✅ **Local File System**: Persistent storage for uploads
---
## 🔀 Data Flow Architecture
1️⃣ **User Input**: Question text + optional file upload
2️⃣ **Pattern Analysis**: Classification of intent
3️⃣ **Solver Selection**: Routing to correct solver function
4️⃣ **Response Generation**: Formatted answer creation
5️⃣ **Data Enrichment**: Code blocks and structured formatting
6️⃣ **Client Delivery**: Rendering in chat interface
---
## 📊 Administrative Features
- 📈 **Usage Analytics**: Feature usage statistics
- 🔍 **IP Logs**: System access records
- 📊 **API Statistics**: Endpoint usage data
- 📌 **Tool Usage Tracking**: Popularity insights
- 🚨 **Error Monitoring**: Centralized logging
---
## 🏆 Conclusion
The **Vicky Data Science Assistant Platform** is a **multi-layered system** integrating modern web technologies with an advanced Python backend. The **modular architecture** ensures scalability and easy maintenance, while the **comprehensive API** enables external integrations. Its emphasis on **user experience** and **powerful data processing** makes it a **robust tool for data science education and assistance**. 🚀
---
# 📜 vicky_server.py Documentation
## 🔍 Overview
**vicky_server.py** is the core component of the **Vicky Data Science Assistant Platform**, responsible for **question processing, pattern matching, and executing specialized solution functions** for assignments GA1-GA5.
### 📂 Module Structure
- 🧩 **GA1 Solutions**: Data processing and file handling
- 🛠 **GA2 Solutions**: API integration, Docker, FastAPI, and deployment
- 🔍 **GA3 Solutions**: Network requests, text processing, data manipulation
- 🌐 **GA4 Solutions**: Web scraping, data extraction, automation
- 📊 **GA5 Solutions**: Advanced data analysis and cleaning operations
Each function follows a **consistent structure**, with docstrings documenting parameters, return values, and purpose.
---
## 📝 Sample Implementations
### 🏞 GA2: Image Compression
```python
# Compress an image losslessly to be under 1,500 bytes
def ga2_second_solution(query=None):
import os
from PIL import Image
default_image_path = "E:\\data science tool\\GA2\\iit_madras.png"
image_path = file_manager.get_file(default_image_path, query, "image")
max_bytes = 1500
with Image.open(image_path) as img:
compressed_path = "compressed_output.png"
img.save(compressed_path, format="PNG", optimize=True, compress_level=9)
return compressed_path
```
### 🎬 GA4: IMDb Web Scraper
```python
# Extract movie data from IMDb within a specified rating range
def ga4_second_solution(query=None):
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
options = Options()
options.add_argument("--headless")
driver = webdriver.Chrome(options=options)
driver.get("https://www.imdb.com/chart/top")
# Scrape and return movies within rating range
```
---
## 🎯 Conclusion
The **vicky_server.py** module powers the **Vicky Data Science Assistant** with **pattern recognition** and **specialized solvers**, providing an **efficient and scalable approach** to data science queries. 🚀