feat: Add Simple Multi-Agent Researcher tutorial for google ADK course

ai_agent_framework_crash_course/google_adk_crash_course/8_simple_multi_agent/README.md

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+# 🎯 Tutorial 8: Simple Multi‑Agent Researcher (Runs with ADK)
+
+## 🎯 What You'll Learn
+- **Multi‑agent orchestration** using a coordinator agent with specialized sub‑agents
+- **Sequential workflow** where agents build upon each other's outputs
+- **Web search integration** for real-time research capabilities
+- **Running with ADK Web** to interactively test the multi‑agent system
+
+## 🧠 Core Concept: Multi-Agent Research Pipeline
+A coordinator `LlmAgent` orchestrates three specialized agents in a sequential workflow: Research → Summarize → Critique. Each agent contributes to building a comprehensive research report.
+
+```
+User Query → Coordinator Agent
+                │
+                ├──▶ Research Agent (web search + analysis)
+                │           │
+                │           └──▶ Research Findings
+                │
+                ├──▶ Summarizer Agent (synthesis)
+                │           │
+                │           └──▶ Key Insights
+                │
+                └──▶ Critic Agent (quality analysis)
+                            │
+                            └──▶ Final Report with Recommendations
+```
+
+## 📁 Project Structure
+```
+8_simple_multi_agent/
+├── README.md                    # This file
+├── requirements.txt             # Dependencies
+├── multi_agent_researcher/      # Main implementation
+│   ├── agent.py                # Multi-agent system (exports root_agent)
+└── .env                        # Environment variables (create this)
+```
+
+## 🚀 Getting Started
+
+### 1. Install Dependencies
+Navigate to the `8_simple_multi_agent` folder and install the required libraries:
+```bash
+cd 8_simple_multi_agent
+pip install -r requirements.txt
+```
+
+### 2. Set Up Environment
+Create a `.env` file in the `8_simple_multi_agent` folder:
+```bash
+# Create .env file
+echo "GOOGLE_API_KEY=your_ai_studio_key_here" > .env
+```
+
+**Important**: Replace `your_ai_studio_key_here` with your actual Google AI Studio API key from [https://aistudio.google.com/](https://aistudio.google.com/)
+
+### 3. Run with ADK Web (Recommended)
+From the `8_simple_multi_agent` folder:
+```bash
+adk web
+```
+
+**ADK Web Setup:**
+- Open the local URL printed in the terminal
+- In the import section, use this path:
+  ```
+  ai_agent_framework_crash_course.google_adk_crash_course.8_simple_multi_agent.multi_agent_researcher
+  ```
+- Select the `root_agent` object
+- Start chatting with your multi-agent researcher!
+
+## 🧪 Sample Prompts to Try
+
+### **Comprehensive Research Query:**
+```
+Research the future of renewable energy integration in smart cities, including current technologies, implementation challenges, economic feasibility, and policy requirements. Provide a critique and suggestions.
+```
+
+### **Other Test Queries:**
+```
+"Research the current state of AI regulation in the European Union and its impact on business innovation"
+```
+
+```
+"Investigate the latest developments in CRISPR gene editing technology and its potential applications in medicine"
+```
+
+```
+"Research the effectiveness of personalized learning platforms in K-12 education, including current implementations and learning outcomes"
+```
+
+## 🔍 How It Works
+
+### **Research Agent:**
+- Conducts comprehensive web research using Google Search
+- Gathers current information, trends, and developments
+- Provides structured findings with sources and outlines
+
+### **Summarizer Agent:**
+- Synthesizes research into clear, actionable insights
+- Creates executive summaries and key bullet points
+- Identifies critical patterns and takeaways
+
+### **Critic Agent:**
+- Performs quality analysis and gap identification
+- Provides risk assessment and opportunity analysis
+- Gives actionable recommendations and next steps
+
+### **Coordinator:**
+- Orchestrates the entire research workflow
+- Ensures proper sequence: Research → Summarize → Critique
+- Integrates all outputs into a cohesive final report
+
+## 📝 Tips for Best Results
+- **Be specific** in your research queries for better agent coordination
+- **Allow completion** of the full workflow for comprehensive results
+- The system automatically follows the research pipeline for thorough analysis
+- Each agent builds upon the previous agent's work for better insights
+
+## 🔗 Next Steps
+After mastering this tutorial, explore:
+- **Tutorial 9**: Workflow Agents (Sequential, Parallel, Branching)
+- **Advanced Patterns**: Custom tools and agent communication
+- **Integration**: Connect with external data sources and APIs
+
+## 🚨 Troubleshooting
+- **API Key Issues**: Ensure your `.env` file is in the correct location and contains a valid `GOOGLE_API_KEY`
+- **Import Errors**: Make sure you're using the exact import path shown above
+- **Agent Not Found**: Verify that `root_agent` is properly exported from the module

ai_agent_framework_crash_course/google_adk_crash_course/8_simple_multi_agent/multi_agent_researcher/.env.example

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+# If using Gemini via Google AI Studio
+GOOGLE_GENAI_USE_VERTEXAI=False
+GOOGLE_API_KEY="your-api-key"

ai_agent_framework_crash_course/google_adk_crash_course/8_simple_multi_agent/multi_agent_researcher/__init__.py

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+from .agent import root_agent  

ai_agent_framework_crash_course/google_adk_crash_course/8_simple_multi_agent/multi_agent_researcher/agent.py

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+import os
+from dotenv import load_dotenv
+from google.adk.agents import LlmAgent
+from google.adk.tools.agent_tool import AgentTool
+from google.adk.tools import google_search
+
+# Load environment variables
+load_dotenv()
+
+# --- Sub-agents ---
+research_agent = LlmAgent(
+    name="research_agent",
+    model="gemini-2.0-flash",
+    description="Finds key information and outlines for a given topic.",
+    instruction=(
+        "You are a focused research specialist. Given a user topic or goal, "
+        "conduct thorough research and produce:\n"
+        "1. A comprehensive bullet list of key facts and findings\n"
+        "2. Relevant sources and references (when available)\n"
+        "3. A structured outline for approaching the topic\n"
+        "4. Current trends or recent developments\n\n"
+        "Keep your research factual, well-organized, and comprehensive. "
+        "Use the google_search tool to find current information when needed."
+    ),
+    tools=[google_search]
+)
+
+summarizer_agent = LlmAgent(
+    name="summarizer_agent",
+    model="gemini-2.5-flash",
+    description="Summarizes research findings clearly and concisely.",
+    instruction=(
+        "You are a skilled summarizer. Given research findings, create:\n"
+        "1. A concise executive summary (2-3 sentences)\n"
+        "2. 5-7 key bullet points highlighting the most important information\n"
+        "3. A clear takeaway message\n"
+        "4. Any critical insights or patterns you notice\n\n"
+        "Focus on clarity, relevance, and actionable insights. "
+        "Avoid repetition and maintain the logical flow of information."
+    ),
+)
+
+critic_agent = LlmAgent(
+    name="critic_agent",
+    model="gemini-2.5-flash",
+    description="Provides constructive critique and improvement suggestions.",
+    instruction=(
+        "You are a thoughtful analyst and critic. Given research and summaries, provide:\n"
+        "1. **Gap Analysis**: Identify missing information or areas that need more research\n"
+        "2. **Risk Assessment**: Highlight potential risks, limitations, or biases\n"
+        "3. **Opportunity Identification**: Suggest areas for further exploration or improvement\n"
+        "4. **Quality Score**: Rate the overall research quality (1-10) with justification\n"
+        "5. **Actionable Recommendations**: Provide specific next steps or improvements\n\n"
+        "Be constructive, thorough, and evidence-based in your analysis."
+    ),
+)
+
+# --- Coordinator (root) agent ---
+root_agent = LlmAgent(
+    name="multi_agent_researcher",
+    model="gemini-2.5-flash",
+    description="Advanced multi-agent research coordinator that orchestrates research, analysis, and critique.",
+    instruction=(
+        "You are an advanced research coordinator managing a team of specialized agents.\n\n"
+        "**Your Research Team:**\n"
+        "- **research_agent**: Conducts comprehensive research using web search and analysis\n"
+        "- **summarizer_agent**: Synthesizes findings into clear, actionable insights\n"
+        "- **critic_agent**: Provides quality analysis, gap identification, and recommendations\n\n"
+        "**Research Workflow:**\n"
+        "1. **Research Phase**: Delegate to research_agent to gather comprehensive information\n"
+        "2. **Synthesis Phase**: Use summarizer_agent to distill findings into key insights\n"
+        "3. **Analysis Phase**: Engage critic_agent to evaluate quality and identify opportunities\n"
+        "4. **Integration**: Combine all outputs into a cohesive research report\n\n"
+        "**For Each Research Request:**\n"
+        "- Always start with research_agent to gather information\n"
+        "- Then use summarizer_agent to create clear summaries\n"
+        "- Finally, engage critic_agent for quality analysis and recommendations\n"
+        "- Present the final integrated research report to the user\n\n"
+        "**Output Format:**\n"
+        "Provide a structured response that includes:\n"
+        "- Executive Summary\n"
+        "- Key Findings\n"
+        "- Critical Analysis\n"
+        "- Recommendations\n"
+        "- Next Steps\n\n"
+        "Coordinate your team effectively to deliver high-quality, comprehensive research."
+    ),
+    sub_agents=[summarizer_agent, critic_agent],
+    tools=[AgentTool(research_agent)]
+)

ai_agent_framework_crash_course/google_adk_crash_course/8_simple_multi_agent/requirements.txt

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+google-adk>=1.9.0
+python-dotenv>=1.1.1