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Merge pull request #3462 from MicrosoftDocs/main
3/11/2025 11:00 AM IST Publish
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.github/policies/disallow-edits.yml

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@@ -10,12 +10,58 @@ configuration:
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- payloadType: Pull_Request
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- isAction:
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action: Opened
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- or:
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- filesMatchPattern:
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matchAny: true
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pattern: articles/index.*
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- filesMatchPattern:
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matchAny: true
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pattern: articles/index.*
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then:
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- addReply:
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reply: >-
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@${issueAuthor} - You tried to add an index file to this repository; this is not permitted so your pull request will be closed automatically.
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@${issueAuthor} - You tried to add an index file to this repository; this is not permitted so your pull request will be closed automatically.
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- closePullRequest
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- description: Close PRs to the "ai-services/personalizer" folder where the author isn't a member of the MicrosoftDocs org (i.e. PRs in public repo).
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if:
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- payloadType: Pull_Request
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- isAction:
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action: Opened
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- filesMatchPattern:
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matchAny: true
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pattern: articles/ai-services/personalizer/*
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- not:
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activitySenderHasAssociation:
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association: Member
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then:
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- addReply:
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reply: >-
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@${issueAuthor} - Pull requests that modify files in this folder aren't accepted from public contributors.
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- closePullRequest
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- description: \@mention specific people when a PR is opened in the "ai-services/personalizer" folder.
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if:
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- payloadType: Pull_Request
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- isAction:
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action: Opened
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- filesMatchPattern:
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matchAny: true
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pattern: articles/ai-services/personalizer/*
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- activitySenderHasAssociation:
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association: Member
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- not:
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or:
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- isActivitySender:
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user: eric-urban
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- isActivitySender:
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user: nitinme
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- isActivitySender:
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user: mrbullwinkle
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then:
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- addReply:
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reply: >-
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@${issueAuthor} - Please don't sign off on this PR. The area owners will sign off once they've reviewed your contribution.
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- mentionUsers:
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mentionees:
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- eric-urban
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- nitinme
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- mrbullwinkle
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replyTemplate: ${mentionees} - Please review this PR and sign off when you're ready to merge it.
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assignMentionees: True # This part probably won't work since the bot doesn't have write perms.

articles/ai-services/agents/how-to/tools/azure-functions.md

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@@ -232,7 +232,7 @@ agent = project_client.agents.create_agent(
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```
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# [REST API](#tab/rest)
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Follow the [REST API Quickstart](../../quickstart.md?pivots=rest-api) to set the right values for the environment variables `AZURE_AI_AGENTS_TOKEN` and `AZURE_AI_AGENTS_ENDPOINT`. The create the agent using:
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Follow the [REST API Quickstart](../../quickstart.md?pivots=rest-api) to set the right values for the environment variables `AZURE_AI_AGENTS_TOKEN` and `AZURE_AI_AGENTS_ENDPOINT`. Then create the agent using:
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```console
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curl $AZURE_AI_AGENTS_ENDPOINT/assistants?api-version=2024-12-01-preview \
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-H "Authorization: Bearer $AZURE_AI_AGENTS_TOKEN" \
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print(f"Created message, message ID: {message.id}")
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# Run the agent
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run = project_client.agents.create_run(thread_id=thread.id, assistant_id=agent.id)
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run = project_client.agents.create_run(thread_id=thread.id, agent_id=agent.id)
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# Monitor and process the run status. The function call should be placed on the input queue by the Agent Service for the Azure Function to pick up when requires_action is returned
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while run.status in ["queued", "in_progress", "requires_action"]:
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time.sleep(1)

articles/ai-services/agents/how-to/tools/bing-grounding.md

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@@ -344,7 +344,7 @@ Create a run and observe that the model uses the Grounding with Bing Search tool
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```python
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# Create and process agent run in thread with tools
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run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
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run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
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print(f"Run finished with status: {run.status}")
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# Retrieve run step details to get Bing Search query link

articles/ai-services/agents/how-to/tools/code-interpreter.md

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@@ -260,7 +260,7 @@ message = project_client.agents.create_message(
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print(f"Created message, message ID: {message.id}")
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# create and execute a run
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run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
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run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
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print(f"Run finished with status: {run.status}")
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if run.status == "failed":

articles/ai-services/agents/how-to/tools/function-calling.md

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@@ -369,7 +369,7 @@ curl $AZURE_AI_AGENTS_ENDPOINT/threads/thread_abc123/messages?api-version=2024-1
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```python
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# Create and process agent run in thread with tools
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run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
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run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
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print(f"Run finished with status: {run.status}")
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if run.status == "failed":

articles/ai-services/agents/how-to/tools/openapi-spec.md

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@@ -321,7 +321,7 @@ Create a run and observe that the model uses the OpenAPI Spec tool to provide a
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print(f"Created message, ID: {message.id}")
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# Create and process agent run in thread with tools
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run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
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run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
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print(f"Run finished with status: {run.status}")
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327327
if run.status == "failed":

articles/ai-services/agents/how-to/virtual-networks.md

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@@ -246,7 +246,7 @@ with project_client:
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print(f"Created message, message ID: {message.id}")
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# Run the agent
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run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
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run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
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print(f"Run finished with status: {run.status}")
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if run.status == "failed":

articles/ai-services/agents/includes/azure-search/code-examples.md

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@@ -262,7 +262,7 @@ message = project_client.agents.create_message(
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print(f"Created message, message ID: {message.id}")
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# Run the agent
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run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)
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run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
266266
print(f"Run finished with status: {run.status}")
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if run.status == "failed":

articles/ai-services/agents/includes/file-search/azure-blob-storage-code-examples.md

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@@ -78,7 +78,7 @@ message = project_client.agents.create_message(
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)
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print(f"Created message, message ID: {message.id}")
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81-
run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent_1.id)
81+
run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent_1.id)
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project_client.agents.delete_vector_store(vector_store.id)
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print("Deleted vector store")

articles/ai-services/agents/includes/file-search/deep-dive.md

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Original file line numberDiff line numberDiff line change
@@ -38,7 +38,7 @@ batch = project_client.agents.create_vector_store_file_batch_and_poll(
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Files can be removed from a vector store by either:
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4040
* Deleting the vector store file object or,
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* Deleting the underlying file object, which removes the file it from all vector_store and code_interpreter configurations across all agents and threads in your organization
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* Deleting the underlying file object, which removes the file from all vector_store and code_interpreter configurations across all agents and threads in your organization
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The maximum file size is 512 MB. Each file should contain no more than 5,000,000 tokens per file (computed automatically when you attach a file).
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@@ -52,7 +52,7 @@ file_search_tool.remove_vector_store(vector_store.id)
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print(f"Removed vector store from file search, vector store ID: {vector_store.id}")
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5454
project_client.agents.update_agent(
55-
assistant_id=agent.id, tools=file_search_tool.definitions, tool_resources=file_search_tool.resources
55+
agent_id=agent.id, tools=file_search_tool.definitions, tool_resources=file_search_tool.resources
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)
5757
print(f"Updated agent, agent ID: {agent.id}")
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