https://github.com/thomasjanssen-tech/agno-tutorial
This Agno (formerly Phidata) tutorial shows how you can build a finance agent, an agentic RAG and a multi-agent system in just 7 minutes!
https://github.com/thomasjanssen-tech/agno-tutorial
agent agno phidata rag retrieval-augmented-generation
Last synced: 3 months ago
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This Agno (formerly Phidata) tutorial shows how you can build a finance agent, an agentic RAG and a multi-agent system in just 7 minutes!
- Host: GitHub
- URL: https://github.com/thomasjanssen-tech/agno-tutorial
- Owner: ThomasJanssen-tech
- Created: 2025-06-02T15:08:40.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-02T15:51:17.000Z (4 months ago)
- Last Synced: 2025-06-03T04:37:29.720Z (4 months ago)
- Topics: agent, agno, phidata, rag, retrieval-augmented-generation
- Language: Python
- Homepage: https://thomasjanssen.tech/
- Size: 161 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
README
Agno (formerly Phidata) Tutorial
Watch the full tutorial on my YouTube Channel
Prerequisites
- Python 3.11+
Installation
1. Clone the repository:
```
git clone https://github.com/ThomasJanssen-tech/Agno-Tutorial
cd Agno-Tutorial
```
2. Create a virtual environment
```
python -m venv venv
```
3. Activate the virtual environment
```
venv\Scripts\Activate
(or on Mac): source venv/bin/activate
```
4. Install libraries
```
pip install -r requirements.txt
```
5. Add your OpenAI API Key
- Aadd an OpenAI API key
Executing the scripts
- Open a terminal in VS Code
- Execute the following command:
```
python run finance-agent.py
python run agentic-rag.py
python run multi-agent.py
```
Further reading
- https://docs.agno.com/introduction