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‎PythonSampleAgent/getting_started_with_kairo_exporter/.env-NTT‎

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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__TYPE=AgenticUserAuthorization
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CONNECTIONSMAP_0_SERVICEURL=*
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CONNECTIONSMAP_0_CONNECTION=SERVICE_CONNECTION
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID=6eba289a-f3c2-4fed-ae31-e917548503ff
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET=rd.8Q~cMU2akle4M0tgsUCrHWpkFz9lzSO7L4b0-
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID=badf1f56-284d-4dc5-ac59-0dd53900e743
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__SCOPES=5a807f24-c9de-44ee-a3a7-329e88a00ffc/.default
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AZURE_OPENAI_API_KEY="9D0JCBGo9t8JttlbJRQAzoFP1oPNJ4U2VvWApq5jMrHv00CbdhpWJQQJ99BJACYeBjFXJ3w3AAABACOGYlrX"
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AZURE_OPENAI_ENDPOINT="https://a365-hw-openai-sentinel.openai.azure.com/"
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AZURE_OPENAI_DEPLOYMENT="gpt-4o-mini"
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ENABLE_A365_OBSERVABILITY=true
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ENABLE_A365_OBSERVABILITY_EXPORTER=false
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# PYTHON_ENVIRONMENT=production
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AGENT_ID=6eba289a-f3c2-4fed-ae31-e917548503ff
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__ALT_BLUEPRINT_NAME=SERVICE_CONNECTION
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__SCOPES=https://graph.microsoft.com/.default
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CONNECTIONSMAP__0__SERVICEURL=*
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CONNECTIONSMAP__0__CONNECTION=SERVICE_CONNECTION

‎PythonSampleAgent/getting_started_with_kairo_exporter/.env-Perplexity-preview70‎

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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__TYPE=AgenticUserAuthorization
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CONNECTIONSMAP_0_SERVICEURL=*
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CONNECTIONSMAP_0_CONNECTION=SERVICE_CONNECTION
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID=38987164-942b-4fea-97f9-c630b0ca523a
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET=uZY8Q~lyRSymXFu6JoVqL6fhs8Tb53P4nRlq~bpJ
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID=badf1f56-284d-4dc5-ac59-0dd53900e743
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__SCOPES=5a807f24-c9de-44ee-a3a7-329e88a00ffc/.default
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AZURE_OPENAI_API_KEY="9D0JCBGo9t8JttlbJRQAzoFP1oPNJ4U2VvWApq5jMrHv00CbdhpWJQQJ99BJACYeBjFXJ3w3AAABACOGYlrX"
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AZURE_OPENAI_ENDPOINT="https://a365-hw-openai-sentinel.openai.azure.com/"
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AZURE_OPENAI_DEPLOYMENT="gpt-4o-mini"
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ENABLE_A365_OBSERVABILITY=true
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ENABLE_A365_OBSERVABILITY_EXPORTER=true
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# PYTHON_ENVIRONMENT=production
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AGENT_ID=38987164-942b-4fea-97f9-c630b0ca523a
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__ALT_BLUEPRINT_NAME=SERVICE_CONNECTION
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__SCOPES=https://graph.microsoft.com/.default
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CONNECTIONSMAP__0__SERVICEURL=*
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CONNECTIONSMAP__0__CONNECTION=SERVICE_CONNECTION

‎PythonSampleAgent/getting_started_with_kairo_exporter/README.md‎

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# Getting Started with Kairo Exporter Sample
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This sample demonstrates how to build an Agent365 Python agent with comprehensive observability using the Kairo SDK. It showcases telemetry tracking for agent invocation, AI inference calls, and tool execution, with telemetry exported to the Agent365 service.
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## 📋 Prerequisites
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- Python 3.11 or higher
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- Azure OpenAI service account
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- Agent365 service registration
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- Microsoft 365 developer tenant (for authentication)
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## 🛠️ Setup Instructions
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### 1. Clone and Navigate
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```bash
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cd Agent365/python/samples/getting_started_with_kairo_exporter
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```
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### 2. Create Virtual Environment
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```bash
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python -m venv .venv
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.venv\Scripts\activate # Windows
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# source .venv/bin/activate # macOS/Linux
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```
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### 3. Install Dependencies
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```bash
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pip install -r requirements.txt
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```
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### 4. Environment Configuration
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Copy the template and configure your environment:
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```bash
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cp env.TEMPLATE .env
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```
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Edit `.env` with your configuration:
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```properties
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# Service Connection (this is the azure bot credentials)
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID=your-service-client-id
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET=your-service-client-secret
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID=your-tenant-id
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# Agent Blueprint Connection (this is the agent credentials)
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CONNECTIONS__AGENTBLUEPRINT__SETTINGS__CLIENTID=your-agent-client-id
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CONNECTIONS__AGENTBLUEPRINT__SETTINGS__CLIENTSECRET=your-agent-client-secret
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CONNECTIONS__AGENTBLUEPRINT__SETTINGS__TENANTID=your-tenant-id
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# Agentic User Authorization
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__TYPE=AgenticUserAuthorization
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__ALT_BLUEPRINT_NAME=AGENTBLUEPRINT
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__SCOPES=https://graph.microsoft.com/.default
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# Connection Mapping
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CONNECTIONSMAP__0__SERVICEURL=*
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CONNECTIONSMAP__0__CONNECTION=SERVICE_CONNECTION
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# Azure OpenAI Configuration
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AZURE_OPENAI_API_KEY=your-openai-api-key
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AZURE_OPENAI_ENDPOINT=https://your-openai-resource.openai.azure.com/
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AZURE_OPENAI_DEPLOYMENT=gpt-4o-mini
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# Observability Settings
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ENABLE_OBSERVABILITY=true
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ENABLE_A365_OBSERVABILITY_EXPORTER=true # Canonical; enables Agent365 telemetry exporter
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PYTHON_ENVIRONMENT=development
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```
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```
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Legacy alias still accepted (deprecated):
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```properties
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ENABLE_KAIRO_EXPORTER=true
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```
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### 5. Run the Agent
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**Using Python directly:**
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```bash
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python -m src.main
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```
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## Install Agents Playground
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### Quick Install (Windows via winget)
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```
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winget install agentsplayground
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```
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### Start Agents Playground
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Add agentsplayground to your PATH
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After installation run:
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```
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agentsplayground
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```
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This launches a web browser with the Microsoft 365 Agents Playground UI where you can configure and chat with your local agent.
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Use the Playground UI to send a message (e.g. "What is the weather in Seattle?").
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Send a custom activity with the message and correct recipient object. Other fields can be left as is
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```json
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{
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"id": "94a8b018-7365-43b9-b9a9-bc7fc67be329",
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"timestamp": "2025-09-18T22:21:54.612Z",
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"channelId": "msteams",
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"serviceUrl": "http://localhost:56150/_connector",
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"recipient":
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{
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"id": "a365testingagent@testcsaaa.onmicrosoft.com",
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"name": "A365 Testing Agent",
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"agenticUserId": "ea1a172b-f443-4ee0-b8a1-27c7ab7ea9e5",
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"agenticAppId": "933f6053-d249-4479-8c0b-78ab25424002",
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"tenantId": "5369a35c-46a5-4677-8ff9-2e65587654e7",
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"role": "agenticUser"
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},
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"from":
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{
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"id": "29:1sH5NArUwkWAX-VmfHH3cfem2S89f2nB0N6aJ5zEjBoxT17fhSMdlYu_55ZyR8_OKFxS3BMnaGldHH3wdf_9K4Q",
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"name": "UserName",
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"aadObjectId": "03f4dd93-7e1e-41d6-bf7c-f211f9e96a13",
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"role": "user"
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},
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"conversation": {
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"id": "__PERSONAL_CHAT_ID__",
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"conversationType": "personal",
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"tenantId": "00000000-0000-0000-0000-0000000000001"
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},
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"type": "message",
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"text": "what can you do"
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}
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```
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## 🏗️ Architecture Overview
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### Observability Flow
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1. **User Message** → `InvokeAgentScope` starts
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2. **Token Exchange** → Agentic token obtained for telemetry export
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3. **AI Processing** → `InferenceScope` tracks OpenAI calls
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4. **Tool Execution** → `ExecuteToolScope` monitors tool operations
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5. **Response** → All telemetry exported to Agent365 service
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### Authentication Flow
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1. **Agent Registration**: Service connects using service connection credentials
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2. **User Authentication**: Agentic user authorization for each conversation
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3. **Token Exchange**: Tokens exchanged for proper audience/scopes
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4. **Telemetry Export**: Cached tokens used for Agent365 service authentication
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## 🔧 Configuration Options
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### Kairo Exporter Settings
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In `start_server.py`, you can configure:
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```python
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success = configure(
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service_name="AzureOpenAiKairoTracing", # Service identifier
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service_namespace="AzureOpenAiKairoTesting", # Namespace
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logger_name="kairo", # Logger name
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token_resolver=token_resolver_func, # Token resolution function
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cluster_category="preprod", # Target cluster (preprod/prod)
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)
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```

‎PythonSampleAgent/getting_started_with_kairo_exporter/a365.config.json‎

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{
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"tenantId": "badf1f56-284d-4dc5-ac59-0dd53900e743",
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"subscriptionId": "964de8b4-c259-4d89-a809-697ef73502f6",
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"resourceGroup": "nikhilc-rg",
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"location": "eastus",
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"environment": "prod",
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"needDeployment": true,
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"graphBaseUrl": "https://graph.microsoft.com",
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"clientAppId": "217fa152-bd72-431a-8329-82b6fbc2db95",
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"appServicePlanName": "nikhilc-rg-plan",
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"appServicePlanSku": "B1",
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"webAppName": "nikhilcagent0416-webapp",
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"agentIdentityDisplayName": "nikhilcagent0416 Identity",
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"agentBlueprintDisplayName": "nikhilcagent0416 Blueprint",
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"agentUserPrincipalName": "nikhilcagent0416@a365preview070.onmicrosoft.com",
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"agentUserDisplayName": "nikhilcagent0416 Agent User",
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"managerEmail": "Nikhilc@a365preview070.onmicrosoft.com",
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"agentUserUsageLocation": "US",
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"deploymentProjectPath": "C:\\Users\\nikhilc\\repos\\Agent365SDK\\Agent365-python\\build\\getting_started_with_kairo_exporter",
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"agentDescription": "nikhilcagent0416 - Agent 365 Agent"
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}

‎PythonSampleAgent/getting_started_with_kairo_exporter/devTools/m365agentsplayground.log‎

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debug Telemetry: agents-playground-cli/cliStart {"cleanProperties":{"isExec":"true","argv":"<REDACTED: user-file-path>,<REDACTED: user-file-path>,-e,http://localhost:3978/api/messages,-c,emulator"}}
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log Listening on 56150
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log Microsoft 365 Agents Playground is being launched for you to debug the app: http://localhost:56150
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debug started web socket client
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debug started web socket client
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log Waiting for connection of endpoint: http://localhost:3978/api/messages
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log waiting for 1 resources: http://localhost:3978/api/messages
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log wait-on(42708) complete
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log Events recording disabled.
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debug Telemetry: agents-playground-server/eventsRecording {"cleanProperties":{"enabled":"false"}}
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debug Telemetry: agents-playground-server/getConfig {"cleanProperties":{"internalConfig":"{\"locale\":\"en-US\",\"localTimezone\":\"America/Los_Angeles\",\"channelId\":\"emulator\",\"debugConfig\":{\"eventsRecordingEnabled\":false}}"}}
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debug Telemetry: agents-playground-server/error {"cleanProperties":{"stack":"\"Error: Request failed with status code 500\\n at UserBotError (<REDACTED: user-file-path> (<REDACTED: user-file-path> (<REDACTED: user-file-path> (node:internal/process/task_queues:95:5)\\n at async ConversationUpdateUserBotAccessor.sendInstallationMemberAddedActivity (<REDACTED: user-file-path>)\"","message":"\"Request failed with status code 500\"","code":"\"UserBotError\"","innerHttpError":"{\"statusCode\":500,\"body\":\"500 Internal Server Error\\n\\nServer got itself in trouble\"}"}}
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log InternalServiceError: Request failed with status code 500
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at UserBotError (C:\snapshot\packages\cli\dist\bundled.js)
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at ConversationUpdateUserBotAccessor.handleAxiosError (C:\snapshot\packages\cli\dist\bundled.js)
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at ConversationUpdateUserBotAccessor.sendActivity (C:\snapshot\packages\cli\dist\bundled.js)
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at process.processTicksAndRejections (node:internal/process/task_queues:95:5)
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at async ConversationUpdateUserBotAccessor.sendInstallationMemberAddedActivity (C:\snapshot\packages\cli\dist\bundled.js) {
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code: 'UserBotError',
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innerHttpError: {
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statusCode: 500,
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body: '500 Internal Server Error\n\nServer got itself in trouble'
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}
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}

‎PythonSampleAgent/getting_started_with_kairo_exporter/env.TEMPLATE‎

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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID=
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET=
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID=
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CONNECTIONS__SERVICE_CONNECTION__SETTINGS__ALT_BLUEPRINT_NAME=AGENTBLUEPRINT
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CONNECTIONS__AGENTBLUEPRINT__SETTINGS__CLIENTID=
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CONNECTIONS__AGENTBLUEPRINT__SETTINGS__CLIENTSECRET=
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CONNECTIONS__AGENTBLUEPRINT__SETTINGS__TENANTID=
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__TYPE=AgenticUserAuthorization
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__ALT_BLUEPRINT_NAME=AGENTBLUEPRINT
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AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__AGENTIC__SETTINGS__SCOPES=https://graph.microsoft.com/.default
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CONNECTIONSMAP__0__SERVICEURL=*
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CONNECTIONSMAP__0__CONNECTION=SERVICE_CONNECTION
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AZURE_OPENAI_API_KEY=
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AZURE_OPENAI_ENDPOINT="https://a365-hw-openai-sentinel.openai.azure.com/"
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AZURE_OPENAI_DEPLOYMENT="gpt-4o-mini"
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#Kairo SDK Specific keys
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ENABLE_OBSERVABILITY=true
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ENABLE_KAIRO_EXPORTER=true
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PYTHON_ENVIRONMENT=production/development

‎PythonSampleAgent/getting_started_with_kairo_exporter/manifest/agenticUserTemplateManifest.json‎

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{
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"id": "7b0926a6-c4ee-445a-a913-bd054594bd09",
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"schemaVersion": "0.1.0-preview",
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"agentIdentityBlueprintId": "6eba289a-f3c2-4fed-ae31-e917548503ff",
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"communicationProtocol": "activityProtocol"
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}

‎PythonSampleAgent/getting_started_with_kairo_exporter/manifest/color.png‎

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‎PythonSampleAgent/getting_started_with_kairo_exporter/manifest/manifest.json‎

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{
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"$schema": "https://developer.microsoft.com/en-us/json-schemas/teams/vdevPreview/MicrosoftTeams.schema.json",
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"id": "6eba289a-f3c2-4fed-ae31-e917548503ff",
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"name": {
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"short": "nikhilcpermtest Blueprint",
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"full": "nikhilcpermtest Blueprint"
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},
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"description": {
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"short": "A brief description of what your agent does.",
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"full": "A comprehensive description of your agent\u0027s capabilities and purpose. Explain what problems it solves, what data it can access, and how users will interact with it. This description helps users understand when and how to use your agent effectively."
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},
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"icons": {
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"outline": "outline.png",
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"color": "color.png"
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},
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"accentColor": "#9ec9d9",
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"version": "1.1.5",
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"manifestVersion": "devPreview",
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"developer": {
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"name": "Microsoft Corporation",
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"mpnId": "",
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"websiteUrl": "https://go.microsoft.com/fwlink/?LinkId=518028",
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"privacyUrl": "https://go.microsoft.com/fwlink/?LinkId=518028",
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"termsOfUseUrl": "https://shares.datatransfer.microsoft.com/assets/Microsoft_Terms_of_Use.html"
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},
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"agenticUserTemplates": [
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{
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"id": "7b0926a6-c4ee-445a-a913-bd054594bd09",
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"file": "agenticUserTemplateManifest.json"
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}
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]
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}

‎PythonSampleAgent/getting_started_with_kairo_exporter/manifest/manifest.zip‎

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