Скачать или смотреть How to use callbacks in Google ADK ? Google Agent Development Kit for Beginners (Part 7)

Time to super charge Google ADK agents! In Part 7 of our Beginners series, we dive into the 6 essential ADK callback types. Learn to build more robust, secure, user-friendly, and efficient AI agents with 5 practical, real-world callback examples from our GitHub repo.
We'll walk through each example in the 7-agents-and-callbacks folder, explaining the Python code (agent.py) and demonstrating how to test them using adk web.

Discover how to implement:
Agent Lifecycle Logging (example_01_...):
Use before_agent_callback & after_agent_callback for session tracking, interaction timing, and request counting.
Model Input Sanitization (example_02_...):
Employ before_model_callback to redact sensitive mock PII (like credit card numbers) before data reaches the LLM.
Model Response Enhancement (example_03_...):
Leverage after_model_callback to parse LLM outputs, extract structured data (e.g., flight details), and add helpful quick links.
Tool Argument Validation & Modification (example_04_...):
Utilize before_tool_callback to validate tool arguments (e.g., date formats for a meeting scheduler) and standardize them for consistency.
Tool Response Transformation & Caching (example_05_...):
Combine before_tool_callback for caching external API calls (like currency conversion) and after_tool_callback to format tool outputs for a better user experience, managing cache expiry.

In this hands-on tutorial, you'll master:
The six main ADK callback types and their practical applications.
- before_agent_callback & after_agent_callback for comprehensive agent lifecycle management.
- before_model_callback for crucial input preprocessing, sanitization, and security.
- after_model_callback for powerful output post-processing, data extraction, - - and response enrichment.
- before_tool_callback for robust tool argument validation, modification, and efficient API call caching.
- after_tool_callback for transforming raw tool responses into user-friendly formats.
Modifying agent state (callback_context.state, tool_context.state) effectively within callbacks.
Intercepting and dynamically altering LLM requests and responses.
Strategically skipping tool executions based on validation logic or cache hits.

This video provides a clear path to building more sophisticated, reliable, and production-ready AI agents with Google ADK.

🔗 Resources:
Get the Code: https://github.com/AhsanAyaz/ai-agent... (Folder: 7-agents-and-callbacks/)

Google ADK Callbacks Docs: https://google.github.io/adk-docs/cal...
Google ADK State Docs: https://google.github.io/adk-docs/ses...

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What are you building with Google ADK callbacks? Share your ideas or ask questions in the comments! If this video helped, please hit the like button and share.

🕒 Major Timestamps:
00:00 - Intro: The Power of Callbacks in Google ADK
00:19 - Overview: Understanding Tools & Callbacks in AI Agents
00:28 - Setup: Cloning Repo & Navigating to 7-agents-and-callbacks
00:57 - Introducing the 5 Callback Examples
01:03 - Examples and demos
02:30 - Example 1 - before_agent_callback & after_agent_callback
08:15 - Running example 1
10:27 - Example 2 - before_model_callback
12:19 - Running example 2
13:40 - Example 3 - after_model_callback
16:29 - Running example 3
18:20 - Example 4 - before_tool_callback
20:55 - Running example 5
24:40 - Example 5 - before_tool_callback & after_tool_callback
30:20 - Running example 5
35:10 - Summary and outro


Hashtags:
#GoogleADK #ADKCallbacks #AIAgents #AgentDevelopmentKit #GoogleCloud #Python #GenAI #AIProgramming #LLM #ArtificialIntelligence #DeveloperTools #SoftwareDevelopment #AIPatterns #SecureAI #EfficientAI #UserFriendlyAI #StateManagement #APICaching