# Apply Technique: Comprehensive Guide to Generative AI Agent Techniques
## What This Is
This is a comprehensive library of tutorials and code examples for building Generative AI agents. It provides developers with the knowledge to create everything from simple conversational bots to complex, multi-agent systems for task automation.
Source: https://github.com/NirDiamant/GenAI_Agents
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and directory structure
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
- Whether this repository or a similar tool is already cloned or installed
Then ask me before proceeding:
1. Which AI provider/API should this use? (Use whatever I already have configured, or ask me to set one up — options include direct provider APIs or a unified service like OpenRouter)
2. Where in my project should this be integrated?
3. Are there any customizations I need (model preferences, naming conventions, constraints)?
## Fetch the Source
Clone or inspect the repository to understand what needs to be installed:
```bash
gh repo clone NirDiamant/GenAI_Agents
```
Review the README, directory structure, and any install instructions before proceeding.
## What to Implement
This is an **AI Technique** — a pattern or methodology for working with AI models.
- Explain how this technique applies to my current project and what benefit it provides
- Implement it in a way that fits my existing codebase — suggest concrete files to modify or create
- If it requires specific model capabilities (structured output, function calling, etc.), verify my current provider supports them
- Show me a working example I can test immediately
## Additional Context
- Clone the repository `https://github.com/NirDiamant/GenAI_Agents.git` into the user's workspace to access all tutorials and code examples.
- Scan the root directory and selected tutorial subdirectories for `requirements.txt` files. Create and activate a Python virtual environment, then install all required dependencies.
- Analyze a tutorial notebook selected by the user to identify required API keys (e.g., OPENAI_API_KEY). Check the user's environment for existing keys, and if not found, prompt the user to add them to a `.env` file for the project.
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it