A collection of AI/ML projects exploring generative models, NLP, and database interactions. Includes Streamlit apps for real-world use cases.

• SQL Chat App
• AI Resume & JD Analyzer
• AI Travel Planner

A Streamlit application that allows users to ask questions about SQL databases using natural language. Leverages Groq LLM for query generation and LangChain for database interaction.

• Real-time SQL query generation
• Schema-aware responses
• Error handling for database interactions
• Context-aware conversations

• Python | Streamlit | LangChain | Groq LLM | MySQL

git clone https://github.com/vivekpathania/ai-experiments
cd sqlchatbot

Virtual Environment:

pip install virtualenv
python3 -m venv env
source env/bin/activate

Install dependencies:

pip install -r requirements.txt

Create .env file: env

DB_URI=mysql+pymysql://username:password@localhost/dbname
GROQ_API_KEY=your_groq_api_key_here

Run the app:

streamlit run sqlchatbot.py

Automatically evaluate candidate fit for job roles using Groq LLM and Streamlit. Generates match scores, personalized improvement suggestions, and ATS-compliant CV rewrites.

• Score-Based Recommendations:
  • Score ≥8: CV is aligned; no changes needed.
  • 5 ≤ Score <8: Receive improvement suggestions and CV rewrite.
  • Score <5: Redirected to refine or find a better-fitting role.
• Real-Time Analysis: Instant feedback on CV-JD alignment.
• ATS-Compliant CV Rewrite: Structured for applicant tracking systems.
• Loading Spinners: Visual feedback during LLM processing.
• Dynamic UI: Tailored experiences based on evaluation scores.

• Python | Streamlit | LangChain | Groq LLM | PyMuPDF

git clone https://github.com/vivekpathania/ai-experiments
cd hrapp

Virtual Environment:

pip install virtualenv
python3 -m venv env
source env/bin/activate

Install dependencies:

 pip install -r requirements.txt

Run the app:

streamlit run app.py

• Upload Files: Drag-and-drop PDFs for the job description and CV.
• Select Mode: Choose between Hiring or Candidate Mode.
• Evaluate Fit: Click "Evaluate Fit" to generate a report.
• Improve CV: Review suggestions and generate an updated CV (Score ≥5).

This project is licensed under the Apache License.

• Streamlit
• GROQ
• LangChain
• PyMuPDF

A conversational travel planning application that generates customized itineraries using AI. Supports both business and leisure trips with tailored recommendations.

• Conversational Interface: Natural language interaction to gather trip details
• Real-Time Data Integration: Uses Tavily/SerpApi to fetch up-to-date travel information
• Customized Itineraries: Generates Markdown-formatted itineraries with flight options, hotel recommendations, and daily schedules
• Multi-Tool Support: Integrates Groq LLM, Tavily, and SerpApi for comprehensive data processing
• Visual Formatting: Uses emojis, tables, and bullet points for clear presentation

• Python | Streamlit | Agno | Groq LLM | Tavily/SerpApi

git clone https://github.com/vivekpathania/ai-experiments
cd travel-agent

Virtual Environment:

pip install virtualenv
python3 -m venv env
source env/bin/activate

Install dependencies:

 pip install -r requirements.txt

Run the app:

streamlit run app.py

1. Enter API Keys: Provide Groq and Tavily/SerpApi keys in the sidebar
2. Describe Your Trip: Use natural language to specify trip details (e.g., "Family holiday from London to Paris for 4 days")
3. Generate Itinerary: The AI will create a detailed itinerary with options for flights, hotels, and activities

Business trip from New York to Tokyo from 2024-05-10 to 2024-05-15 for 1 traveler. Budget: $3000. Needs conference venues and after-work dining options.

# **Tokyo Business Trip Itinerary**

## Trip Summary
- **Type:** Business
- **Dates:** May 10 - May 15, 2024
- **Travelers:** 1
- **Budget:** $3,000

## Flight Options
| Airline          | Price (Adult) | Details                  |
|------------------|---------------|--------------------------|
| JAL              | $1,200        | Non-stop, 8 AM departure |
| ANA              | $1,150        | 1 layover in Seoul       |

## Accommodation
| Hotel                | Price/Night | Amenities                |
|----------------------|-------------|--------------------------|
| Park Hyatt Tokyo     | $350        | Business center, WiFi    |
| Mandarin Oriental    | $290        | Fitness center, breakfast|

## Daily Schedule
- **May 10**: Business meeting at Conference Center X (10 AM)
- **May 11**: Networking dinner at Robata-tei (7 PM)

## Important Tips
- **Transportation**: Use the Tokyo Metro for easy access to business districts.
- **Culture**: Familiarize yourself with Japanese business etiquette.

This project is licensed under the MIT License.

• Streamlit
• Groq
• Tavily
• SerpApi