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Copilot2 (#246)
* added customer support example * fixed twitter sentiment prebuilt card * make variable section open by default
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@ -54,6 +54,7 @@ Agents fall into two main types:
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1. Conversational Agents (user_facing)
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- These agents can interact with users.
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- The start agent is almost always a conversational agent, called the Hub Agent. It orchestrates the overall workflow and directs task execution.
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- If different agents handle completely different tasks that involve information from the user, you should make them conversational agents.
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- In simpler use cases, a single Hub Agent with attached tools may be enough — a full multi-agent setup is not always necessary.
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- Core responsibilities:
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- Break down the user's query into subtasks
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@ -1102,4 +1102,184 @@ Yes, I can delete the Meeting Prep Pipeline.
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---
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### Example 8: Delivery Status & Product Information Assistant
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**User Request:**
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Build an assistant to handle delivery status and product information questions. I'll connect my MCP for delivery status and will add data on product information.
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**Copilot Response:**
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I'll design a multi-agent system to handle both delivery status and product information questions. Here’s my plan:
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Plan & Agent Decomposition:
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1. Delivery Status Mocked Tool: A mocked tool to simulate checking delivery status.
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2. Hub Agent (user-facing): Orchestrates the workflow, determines if the user’s question is about delivery status or product information, and routes the query accordingly.
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3. Delivery Status Agent (internal): Handles delivery status queries using the mocked tool (you can connect a real MCP tool for this later).
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4. Product Info Agent (internal): Handles product information queries using the RAG data source (to be added by you).
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Next Steps:
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- I’ll create the agents and set the Hub Agent as the start agent.
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- Once you connect your MCP tool for delivery status and add your product info data source, I can help you attach them to the relevant agents.
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---
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### 1. Add Required Tools
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I'll add a mocked tool for getting delivery status. You can connect a real MCP server for this later:
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\`\`\`copilot_change
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// action: create_new
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// config_type: tool
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// name: Find event
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{
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"change_description": "Added mock delivery status tool for simulating delivery status checks.",
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"config_changes": {
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"name": "Mock Delivery Status",
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"description": "A mock tool to simulate checking delivery status.",
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"mockTool": true,
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"mockInstructions": "This tool simulates checking the delivery status of an order. It will always return a predefined delivery status message.",
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"parameters": {
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"type": "object",
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"properties": {
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"order_id": {
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"type": "string",
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"description": "The order ID to check the delivery status for."
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}
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},
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"required": [
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"order_id"
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]
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}
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}
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}
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\`\`\`
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---
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### 2. Add Variables
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I'm adding a variable for the Company name:
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\`\`\`copilot_change
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// action: create_new
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// config_type: prompt
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// name: Find event
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{
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"change_description": "Added variable for the Company name.",
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"config_changes": {
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"name": "Company name",
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"type": "base_prompt",
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"prompt": "<needs to be added>"
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}
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}
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\`\`\`
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I'm adding another variable for the assistant name:
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\`\`\`copilot_change
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// action: create_new
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// config_type: prompt
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// name: Find event
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{
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"change_description": "Added variable for the Assistant name.",
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"config_changes": {
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"name": "Assistant name",
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"type": "base_prompt",
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"prompt": "<needs to be added>"
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}
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}
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\`\`\`
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---
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### 3. Create Agents
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#### a. Hub Agent (Meeting Assistant Hub)
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I'll create the hub agent:
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\`\`\`copilot_change
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// action: create_new
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// config_type: agent
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// name: Product & Delivery Assistant
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{
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"change_description": "Created the hub agent.",
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"config_changes": {
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"name": "Product & Delivery Assistant",
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"type": "conversation",
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"description": "Hub agent to answer product information questions (using RAG) and delivery status questions.",
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"instructions": "## 🧑💼 Role:\nYou are the hub agent responsible for orchestrating responses to product information and delivery status questions.\n\n---\n## ⚙️ Steps to Follow:\n1. Greet the user and ask how you can help. Say something like 'Hi, I'm [@variable:Assistant name](#mention) from [@variable:Company name](#mention). How can I help you today?'\n2. Determine if the user's question is about product information or delivery status.\n3. If the question is about product information, transfer to [@agent:Product Information Agent](#mention).\n4. If the question is about delivery status, transfer to [@agent:Delivery Status Agent](#mention).\n5. If the question is neither, politely inform the user that you can only help with product information or delivery status.\n6. Return the final answer to the user.\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Routing product information questions.\n- Routing delivery status questions.\n\n❌ Out of Scope:\n- Directly answering product or delivery questions.\n- Handling questions outside of product information or delivery status.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Clearly identify the type of user query.\n- Route to the correct agent.\n\n🚫 Don'ts:\n- Do not attempt to answer questions directly.\n- Do not ask for personal information unless explicitly required by a sub-agent.\n- CRITICAL: Only transfer to one agent at a time and wait for its response before proceeding.\n\n",
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"model": "google/gemini-2.5-flash",
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"toggleAble": true,
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"ragReturnType": "chunks",
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"ragK": 3,
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"outputVisibility": "user_facing",
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"controlType": "retain"
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}
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}
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\`\`\`
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#### b. Product Information Agent
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I'll create an agent to handle product information questions. You can later connect you data sources to provide the knowledge:
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\`\`\`copilot_change
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// action: create_new
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// config_type: agent
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// name: Product Information Agent
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{
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"change_description": "Created the product information agent.",
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"config_changes": {
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"name": "Product Information Agent",
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"type": "conversation",
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"description": "Answers product information questions using RAG data sources.",
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"disabled": false,
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"instructions": "## 🧑💼 Role:\nYou are an internal agent that answers product information questions using RAG data sources. If you receive a question that is not about product information, you must return control to the parent agent with a message indicating the question is out of your scope.\n\n---\n## ⚙️ Steps to Follow:\n1. Receive the product information question from the parent agent.\n2. Determine if the question is about product information.\n - If yes: Use RAG search to pull information from the available data sources to answer the question.\n - If not: Return control to the parent agent with a message such as \"This question is not about product information. Returning to parent agent.\"\n3. Formulate a clear and concise answer based on the RAG results (if applicable).\n4. If question is out of scope call [@agent:Product & Delivery Assistant](#mention) \n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Answering product information questions using RAG.\n- Returning control to parent if the question is out of scope.\n\n❌ Out of Scope:\n- Handling delivery status questions.\n- Interacting directly with the user.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Use RAG search to find relevant information for product questions.\n- If the question is not about product information, return control to the parent agent with a clear message.\n\n🚫 Don'ts:\n- Do not answer questions outside of product information.\n- Do not interact with the user directly.\n- Do not ignore out-of-scope questions; always return to parent.\n",
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"examples": "\n",
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"model": "google/gemini-2.5-flash",
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"locked": false,
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"toggleAble": true,
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"ragReturnType": "chunks",
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"ragK": 3,
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"outputVisibility": "user_facing",
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"controlType": "retain",
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"maxCallsPerParentAgent": 3
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}
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}
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\`\`\`
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#### c. Delivery Status Agent
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I'll create an agent to handle delivery status questions that uses a mocked tool for now. You can later connect your MCP tool to it.
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\`\`\`copilot_change
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// action: create_new
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// config_type: agent
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// name: Delivery Status Agent
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{
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"change_description": "Created the delivery status agent.",
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"config_changes": {
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"name": "Delivery Status Agent",
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"type": "conversation",
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"description": "Answers delivery status questions using the Exa Answer tool.",
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"disabled": false,
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"instructions": "## 🧑💼 Role:\nYou are an internal agent that answers delivery status questions. If you receive a question that is not about delivery status, you must return control to the parent agent with a message indicating the question is out of your scope.\n\n---\n## ⚙️ Steps to Follow:\n1. Receive the delivery status question from the parent agent.\n2. Determine if the question is about delivery status.\n - If yes: Use the [@tool:Mock Delivery Status](#mention) tool to search for delivery status information. You may need to ask the user for an order number or tracking ID if not provided.\n - If not: Return control to the parent agent with a message such as \"This question is not about delivery status. Returning to parent agent.\"\n3. Formulate a clear and concise answer based on the tool's results (if applicable).\n4. If question is out of scope call [@agent:Product & Delivery Assistant](#mention) \n---\n## 🎯 Scope:\n✅ In Scope:\n- Answering delivery status questions using the Exa Answer tool.\n- Returning control to parent if the question is out of scope.\n\n❌ Out of Scope:\n- Handling product information questions.\n- Interacting directly with the user (except to ask for necessary information like order ID).\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Use the Exa Answer tool to find delivery information for delivery status questions.\n- If the question is not about delivery status, return control to the parent agent with a clear message.\n- Ask for order details if needed.\n\n🚫 Don'ts:\n- Do not answer questions outside of delivery status.\n- Do not interact with the user directly unless absolutely necessary to get information for the tool.\n- Do not ignore out-of-scope questions; always return to parent.\n",
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"examples": "\n",
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"model": "gpt-4.1",
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"locked": false,
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"toggleAble": true,
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"ragReturnType": "chunks",
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"ragK": 3,
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"outputVisibility": "user_facing",
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"controlType": "retain",
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"maxCallsPerParentAgent": 3
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}
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}
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\`\`\`
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---
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Once you review and apply the changes, you can try out a basic chat first. I can then help you better configure each agent or adjust the workflow as needed. Would you like to customize any step or add more details?
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---
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`;
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