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openapi sample (#44025)
* Add OpenAPI samples for weather data and TripAdvisor API integration - Introduced `weather_openapi.json` to define an OpenAPI specification for retrieving current weather data from wttr.in. - Created `sample_agent_openapi.py` to demonstrate the creation of an AI agent that utilizes the weather OpenAPI tool. - Developed `sample_agent_openapi_with_project_connection.py` to showcase an AI agent using the TripAdvisor API with project connection authentication. - Updated documentation for openapi. - Remove indentaiton from doc since it isn't supported by code snipper * added change log * Resolved comment * resolve comment
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‎sdk/ai/azure-ai-projects/.env.template‎

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@@ -54,4 +54,5 @@ BING_CUSTOM_SEARCH_PROJECT_CONNECTION_ID=
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BING_CUSTOM_SEARCH_INSTANCE_NAME=
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SHAREPOINT_PROJECT_CONNECTION_ID=
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A2A_PROJECT_CONNECTION_ID=
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BROWSER_AUTOMATION_PROJECT_CONNECTION_ID=
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BROWSER_AUTOMATION_PROJECT_CONNECTION_ID=
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OPENAPI_PROJECT_CONNECTION_ID=

‎sdk/ai/azure-ai-projects/CHANGELOG.md‎

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### Sample updates
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* Added OpenAPI tool sample. See `sample_agent_openapi.py`.
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* Added OpenAPI with Project Connection sample. See `sample_agent_openapi_with_project_connection.py`.
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* Added SharePoint grounding tool sample. See `sample_agent_sharepoint.py`.
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## 2.0.0b2 (2025-11-14)
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### Features Added

‎sdk/ai/azure-ai-projects/README.md‎

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‎sdk/ai/azure-ai-projects/samples/agents/assets/tripadvisor_openapi.json‎

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‎sdk/ai/azure-ai-projects/samples/agents/assets/weather_openapi.json‎

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{
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"openapi": "3.1.0",
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"info": {
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"title": "get weather data",
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"description": "Retrieves current weather data for a location based on wttr.in.",
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"version": "v1.0.0"
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},
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"servers": [
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{
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"url": "https://wttr.in"
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}
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],
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"auth": [],
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"paths": {
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"/{location}": {
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"get": {
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"description": "Get weather information for a specific location",
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"operationId": "GetCurrentWeather",
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"parameters": [
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{
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"name": "location",
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"in": "path",
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"description": "City or location to retrieve the weather for",
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"required": true,
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"schema": {
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"type": "string"
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}
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},
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{
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"name": "format",
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"in": "query",
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"description": "Always use j1 value for this parameter",
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"required": true,
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"schema": {
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"type": "string",
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"default": "j1"
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}
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}
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],
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"responses": {
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"200": {
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"description": "Successful response",
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"content": {
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"text/plain": {
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"schema": {
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"type": "string"
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}
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}
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}
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},
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"404": {
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"description": "Location not found"
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}
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},
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"deprecated": false
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}
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}
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},
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"components": {
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"schemes": {}
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}
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}

‎sdk/ai/azure-ai-projects/samples/agents/tools/sample_agent_openapi.py‎

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# ------------------------------------
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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# ------------------------------------
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"""
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DESCRIPTION:
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This sample demonstrates how to create an AI agent with OpenAPI tool capabilities
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using the OpenApiAgentTool and synchronous Azure AI Projects client. The agent can
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call external APIs defined by OpenAPI specifications.
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USAGE:
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python sample_agent_openapi.py
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Before running the sample:
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pip install "azure-ai-projects>=2.0.0b1" azure-identity openai python-dotenv jsonref
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Set these environment variables with your own values:
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1) AZURE_AI_PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
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page of your Microsoft Foundry portal.
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2) AZURE_AI_MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
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the "Models + endpoints" tab in your Microsoft Foundry project.
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"""
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import os
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import jsonref
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from dotenv import load_dotenv
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from azure.identity import DefaultAzureCredential
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from azure.ai.projects import AIProjectClient
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from azure.ai.projects.models import (
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PromptAgentDefinition,
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OpenApiAgentTool,
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OpenApiFunctionDefinition,
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OpenApiAnonymousAuthDetails,
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)
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load_dotenv()
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endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
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with (
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DefaultAzureCredential() as credential,
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AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
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project_client.get_openai_client() as openai_client,
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):
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weather_asset_file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../assets/weather_openapi.json"))
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# [START tool_declaration]
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with open(weather_asset_file_path, "r") as f:
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openapi_weather = jsonref.loads(f.read())
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tool = OpenApiAgentTool(
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openapi=OpenApiFunctionDefinition(
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name="get_weather",
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spec=openapi_weather,
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description="Retrieve weather information for a location",
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auth=OpenApiAnonymousAuthDetails(),
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)
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)
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# [END tool_declaration]
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agent = project_client.agents.create_version(
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agent_name="MyAgent",
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definition=PromptAgentDefinition(
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model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
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instructions="You are a helpful assistant.",
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tools=[tool],
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),
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)
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print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
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response = openai_client.responses.create(
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input="What is the name and population of the country that uses currency with abbreviation THB?",
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extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
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)
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print(f"Response created: {response.output_text}")
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print("\nCleaning up...")
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project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
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print("Agent deleted")

‎sdk/ai/azure-ai-projects/samples/agents/tools/sample_agent_openapi_with_project_connection.py‎

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# ------------------------------------
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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# ------------------------------------
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"""
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DESCRIPTION:
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This sample demonstrates how to create an AI agent with OpenAPI tool capabilities
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using the OpenApiAgentTool with project connection authentication. The agent can
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call external APIs defined by OpenAPI specifications, using credentials stored in
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an Azure AI Project connection.
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USAGE:
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python sample_agent_openapi_with_project_connection.py
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Before running the sample:
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pip install "azure-ai-projects>=2.0.0b1" azure-identity openai python-dotenv jsonref
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Set these environment variables with your own values:
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1) AZURE_AI_PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
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page of your Microsoft Foundry portal.
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2) AZURE_AI_MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
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the "Models + endpoints" tab in your Microsoft Foundry project.
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3) OPENAPI_PROJECT_CONNECTION_ID - The OpenAPI project connection ID,
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as found in the "Connections" tab in your Microsoft Foundry project.
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"""
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import os
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import jsonref
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from dotenv import load_dotenv
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from azure.identity import DefaultAzureCredential
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from azure.ai.projects import AIProjectClient
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from azure.ai.projects.models import (
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PromptAgentDefinition,
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OpenApiAgentTool,
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OpenApiFunctionDefinition,
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OpenApiAnonymousAuthDetails,
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OpenApiManagedAuthDetails,
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OpenApiProjectConnectionAuthDetails,
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OpenApiProjectConnectionSecurityScheme,
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)
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load_dotenv()
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endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
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with (
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DefaultAzureCredential() as credential,
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AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
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project_client.get_openai_client() as openai_client,
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):
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tripadvisor_asset_file_path = os.path.abspath(
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os.path.join(os.path.dirname(__file__), "../assets/tripadvisor_openapi.json")
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)
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# [START tool_declaration]
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with open(tripadvisor_asset_file_path, "r") as f:
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openapi_tripadvisor = jsonref.loads(f.read())
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tool = OpenApiAgentTool(
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openapi=OpenApiFunctionDefinition(
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name="tripadvisor",
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spec=openapi_tripadvisor,
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description="Trip Advisor API to get travel information",
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auth=OpenApiProjectConnectionAuthDetails(
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security_scheme=OpenApiProjectConnectionSecurityScheme(
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project_connection_id=os.environ["OPENAPI_PROJECT_CONNECTION_ID"]
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)
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),
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)
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)
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# [END tool_declaration]
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agent = project_client.agents.create_version(
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agent_name="MyAgent",
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definition=PromptAgentDefinition(
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model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
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instructions="You are a helpful assistant.",
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tools=[tool],
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),
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)
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print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
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response = openai_client.responses.create(
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input="Recommend me 5 top hotels in paris, France",
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extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
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)
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print(f"Response created: {response.output_text}")
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print("\nCleaning up...")
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project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
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print("Agent deleted")

‎sdk/ai/azure-ai-projects/samples/agents/tools/sample_agent_sharepoint.py‎

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)
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print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
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user_input = input("Enter your question corresponded to the documents in SharePoint:\n")
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# Send initial request that will trigger the SharePoint tool
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stream_response = openai_client.responses.create(
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stream=True,
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input="Please summarize the last meeting notes stored in SharePoint.",
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input=user_input,
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extra_body={"agent": {"name": agent.name, "type": "agent_reference"}},
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)
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