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lakshaybamel / repository
agno-agentic-ai
A collection of Agentic AI applications using AGNO, Gemini, multi-agent workflows, memory, and Streamlit.
#agentic-ai#agno#ai-agents#generative-ai#google-gemini#llm
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README preview
🤖 Agentic AI Projects using AGNO
A collection of Agentic AI applications built using the AGNO Framework and Google Gemini Models.
This repository demonstrates:
- AI Agents
- Multi-Agent Systems
- Tool Calling
- AI Memory
- Financial Analysis Agents
- YouTube Content Analysis
- Streamlit-based AI Applications
🚀 Features
✈️ Travel Agent
An AI travel assistant that provides:
- Travel guidance
- Real-time information
- Safety insights
- Destination recommendations
Tools Used
- DuckDuckGo Search
- Google Gemini
📈 Finance Agent
An intelligent finance assistant capable of:
- Stock price analysis
- Analyst recommendations
- Financial insights
- Market research
Tools Used
- Yahoo Finance
- DuckDuckGo Search
- Google Gemini
🌍 Multi-Agent Translation Team
A collaborative multi-agent system where:
- One agent responds in English
- One agent responds in Hindi
- One agent responds in Chinese
Demonstrates:
- Team-based AI workflows
- Multi-agent communication
- Language translation
🧠 Memory Agent
An AI assistant with persistent memory using SQLite.
Features
- Stores conversation context
- Remembers previous interactions
- Uses memory-aware responses
Database
- SQLite (
agno.db)
🎥 YouTube Video Analyzer
An AI-powered YouTube content analyzer with:
- Video summaries
- Timestamp generation
- Topic segmentation
- Key insights extraction
Includes a Streamlit UI for interactive usage.
🛠️ Tech Stack
| Technology | Usage |
|---|---|
| Python | Core Programming |
| AGNO | Agent Framework |
| Google Gemini | LLM |
| Streamlit | Frontend UI |
| SQLite | Memory Storage |
| DuckDuckGo Tools | Web Search |
| Yahoo Finance | Financial Data |
📂 Project Structure
agno-agentic-ai/
│
├── agent.py
├── finance.py
├── memory.py
├── team.py
├── youtube_analyzer.py
├── ui.py
│
├── agno.db
├── requirements.txt
├── README.md
├── .gitignore
└── .env
⚙️ Installation
1️⃣ Clone Repository
git clone https://github.com/lakshaybamel/agno-agentic-ai.git
cd agno-agentic-ai
2️⃣ Create Virtual Environment
Windows
python -m venv venv
venv\Scripts\activate
Linux / macOS
python3 -m venv venv
source venv/bin/activate
3️⃣ Install Dependencies
pip install -r requirements.txt
4️⃣ Setup Environment Variables
Create a .env file:
GOOGLE_API_KEY=your_google_api_key
Get your API key from:
🔗 https://aistudio.google.com/api-keys/
▶️ Running the Projects
✈️ Travel Agent
python agent.py
📈 Finance Agent
python finance.py
🌍 Team Agent
python team.py
🧠 Memory Agent
python memory.py
🎥 Streamlit YouTube Analyzer
streamlit run ui.py
Then open:
http://localhost:8501
📚 Learning Outcomes
This project helped in understanding:
- AI Agent Architectures
- Tool Calling
- Multi-Agent Systems
- AI Memory Systems
- LLM Application Development
- Streamlit Deployment
- Real-time AI Applications
👨💻 Author
Lakshay Bamel
MCA Student @ BIT Mesra
⭐ Support
If you found this project useful, consider giving it a ⭐ on GitHub!