Agentic Student Assistant

🌟 Overview

Agentic Student Assistant is an intelligent academic companion built with LangGraph, OpenAI, and modern AI infrastructure. It empowers students and researchers with specialized AI agents for career intelligence, academic research, and curated reading recommendations.

Our toolkit consists of the following intelligent agents:

• Talk2Jobs: Real-time global job market intelligence with regional optimization for Germany, USA, Mexico, India, Japan, and more.
• Talk2Papers: Multi-tier academic search across ArXiv, Semantic Scholar, CORE, and OpenReview with deep-dive Q&A capabilities.
• Talk2Books: Curated reading recommendations from Open Library and Google Books with academic focus.

🏗️ Architecture

The system leverages a sophisticated multi-agent orchestration pattern using LangGraph, featuring semantic caching with Redis and comprehensive monitoring via Google Cloud Logging.

🛠️ Tech Stack

• Orchestration: LangGraph (ReAct)
• Intelligence: OpenAI GPT-4
• Infrastructure: Redis (Semantic Cache), Google Cloud Logging
• Interface: Streamlit (Dashboard)
• Language: Python 3.10+

🌟 Key Features

1. Advanced Academic Research (Talk2Papers) 📑

A high-fidelity research tool that queries the world's leading academic databases in parallel:

• Multi-Tier Search: ArXiv + Semantic Scholar + CORE + OpenReview.net
• Deep-Dive Q&A: Ask follow-up questions about specific papers' methodology or findings
• Robust Fallback: Automatically switches sources if an API is rate-limited or forbidden
• Semantic Similarity: Local embedding-based semantic caching for instant similar query responses

2. Reading Recommendations (Talk2Books) 📚

Curated reading lists using Open Library and Google Books:

• Academic Focus: Filters for reputable publishers and academic sources
• Detailed Summaries: Provides insights into core contributions and target audience

3. Global Job Market Intelligence (Talk2Jobs) 💼

Precision search across international regions:

• Regional Intelligence: Specific optimizations for Mexico, Germany, Japan, India, USA, and more
• Language Aware: Automatically adjusts search parameters (hl, gl, google_domain) for local results

4. Smart Caching System 🧠

Redis-based persistent caching with local semantic similarity:

• Exact Match: Hash-based instant retrieval
• Semantic Match: SentenceTransformer-powered similarity search (threshold: 0.88)
• Zero API Cost: Completely local embedding generation
• 80-90% Latency Reduction: Through intelligent response caching

Clone and enter the repository

git clone https://github.com/yourusername/Agentic_Student_Assistant
cd Agentic_Student_Assistant

Install dependencies

Installation with uv

1. Install uv if you haven't already.
2. Sync dependencies:

uv sync

Set up .env with your API keys (OpenAI, SerpAPI, etc.)

Create a .env file in the root directory:

OPENAI_API_KEY=your_openai_key
SERPAPI_API_KEY=your_serpapi_key
# Optional (for enhanced features)
CORE_API_KEY=your_core_key
SEMANTIC_SCHOLAR_API_KEY=your_ss_key
REDIS_HOST=your_redis_host
REDIS_PORT=6379
REDIS_DB=0
REDIS_PASSWORD=your_redis_password
GROQ_API_KEY=your_groq_key  # For free LLM alternative```

Launch the dashboard

streamlit run app/frontend/streamlit_app.py

📖 Usage

Example Queries

Job Search:

"Find data science jobs in Berlin"
"Show me machine learning positions in Tokyo"

Paper Research:

"Papers about transformer architecture"
"Explain the BioBridge paper"

Book Recommendations:

"Books on deep learning for beginners"
"Academic texts on quantum computing"

📊 Performance Metrics

• Routing Accuracy: ~98%
• Cache Hit Rate: 80-90% (with Redis + Semantic Matching)
• Average Latency: <2s (cached), 5-8s (fresh query)
• Supported Databases: 7 (ArXiv, Semantic Scholar, CORE, OpenReview, Open Library, Google Books, Google Jobs)

Built with ❤️ for students and researchers worldwide 🌍🎓