Capture file IDs from code interpreter in streaming responses (#2741)

python/samples/getting_started/agents/azure_ai/README.md

@@ -14,6 +14,7 @@ This folder contains examples demonstrating different ways to create and use age
 | [`azure_ai_with_bing_custom_search.py`](azure_ai_with_bing_custom_search.py) | Shows how to use Bing Custom Search with Azure AI agents to search custom search instances and provide responses with relevant results. Requires a Bing Custom Search connection and instance configured in your Azure AI project. |
 | [`azure_ai_with_browser_automation.py`](azure_ai_with_browser_automation.py) | Shows how to use Browser Automation with Azure AI agents to perform automated web browsing tasks and provide responses based on web interactions. Requires a Browser Automation connection configured in your Azure AI project. |
 | [`azure_ai_with_code_interpreter.py`](azure_ai_with_code_interpreter.py) | Shows how to use the `HostedCodeInterpreterTool` with Azure AI agents to write and execute Python code for mathematical problem solving and data analysis. |
+| [`azure_ai_with_code_interpreter_file_generation.py`](azure_ai_with_code_interpreter_file_generation.py) | Shows how to retrieve file IDs from code interpreter generated files using both streaming and non-streaming approaches. |
 | [`azure_ai_with_existing_agent.py`](azure_ai_with_existing_agent.py) | Shows how to work with a pre-existing agent by providing the agent name and version to the Azure AI client. Demonstrates agent reuse patterns for production scenarios. |
 | [`azure_ai_with_existing_conversation.py`](azure_ai_with_existing_conversation.py) | Demonstrates how to use an existing conversation created on the service side with Azure AI agents. Shows two approaches: specifying conversation ID at the client level and using AgentThread with an existing conversation ID. |
 | [`azure_ai_with_application_endpoint.py`](azure_ai_with_application_endpoint.py) | Demonstrates calling the Azure AI application-scoped endpoint. |

python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py

@@ -0,0 +1,111 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import (
+    CitationAnnotation,
+    HostedCodeInterpreterTool,
+    HostedFileContent,
+    TextContent,
+)
+from agent_framework._agents import AgentRunResponseUpdate
+from agent_framework.azure import AzureAIClient
+from azure.identity.aio import AzureCliCredential
+
+"""
+Azure AI V2 Code Interpreter File Generation Sample
+
+This sample demonstrates how the V2 AzureAIClient handles file annotations
+when code interpreter generates text files. It shows both non-streaming
+and streaming approaches to verify file ID extraction.
+"""
+
+QUERY = (
+    "Write a simple Python script that creates a text file called 'sample.txt' containing "
+    "'Hello from the code interpreter!' and save it to disk."
+)
+
+
+async def test_non_streaming() -> None:
+    """Test non-streaming response - should have annotations on TextContent."""
+    print("=== Testing Non-Streaming Response ===")
+
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIClient(credential=credential).create_agent(
+            name="V2CodeInterpreterFileAgent",
+            instructions="You are a helpful assistant that can write and execute Python code to create files.",
+            tools=HostedCodeInterpreterTool(),
+        ) as agent,
+    ):
+        print(f"User: {QUERY}\n")
+
+        result = await agent.run(QUERY)
+        print(f"Agent: {result.text}\n")
+
+        # Check for annotations in the response
+        annotations_found: list[str] = []
+        # AgentRunResponse has messages property, which contains ChatMessage objects
+        for message in result.messages:
+            for content in message.contents:
+                if isinstance(content, TextContent) and content.annotations:
+                    for annotation in content.annotations:
+                        if isinstance(annotation, CitationAnnotation) and annotation.file_id:
+                            annotations_found.append(annotation.file_id)
+                            print(f"Found file annotation: file_id={annotation.file_id}")
+
+        if annotations_found:
+            print(f"SUCCESS: Found {len(annotations_found)} file annotation(s)")
+        else:
+            print("WARNING: No file annotations found in non-streaming response")
+
+
+async def test_streaming() -> None:
+    """Test streaming response - check if file content is captured via HostedFileContent."""
+    print("\n=== Testing Streaming Response ===")
+
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIClient(credential=credential).create_agent(
+            name="V2CodeInterpreterFileAgentStreaming",
+            instructions="You are a helpful assistant that can write and execute Python code to create files.",
+            tools=HostedCodeInterpreterTool(),
+        ) as agent,
+    ):
+        print(f"User: {QUERY}\n")
+        annotations_found: list[str] = []
+        text_chunks: list[str] = []
+        file_ids_found: list[str] = []
+
+        async for update in agent.run_stream(QUERY):
+            if isinstance(update, AgentRunResponseUpdate):
+                for content in update.contents:
+                    if isinstance(content, TextContent):
+                        if content.text:
+                            text_chunks.append(content.text)
+                        if content.annotations:
+                            for annotation in content.annotations:
+                                if isinstance(annotation, CitationAnnotation) and annotation.file_id:
+                                    annotations_found.append(annotation.file_id)
+                                    print(f"Found streaming annotation: file_id={annotation.file_id}")
+                    elif isinstance(content, HostedFileContent):
+                        file_ids_found.append(content.file_id)
+                        print(f"Found streaming HostedFileContent: file_id={content.file_id}")
+
+        print(f"\nAgent response: {''.join(text_chunks)[:200]}...")
+
+        if annotations_found or file_ids_found:
+            total = len(annotations_found) + len(file_ids_found)
+            print(f"SUCCESS: Found {total} file reference(s) in streaming")
+        else:
+            print("WARNING: No file annotations found in streaming response")
+
+
+async def main() -> None:
+    print("AzureAIClient Code Interpreter File Generation Test\n")
+    await test_non_streaming()
+    await test_streaming()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/getting_started/agents/azure_ai_agent/README.md

@@ -9,6 +9,7 @@ This folder contains examples demonstrating different ways to create and use age
 | [`azure_ai_basic.py`](azure_ai_basic.py) | The simplest way to create an agent using `ChatAgent` with `AzureAIAgentClient`. It automatically handles all configuration using environment variables. |
 | [`azure_ai_with_bing_custom_search.py`](azure_ai_with_bing_custom_search.py) | Shows how to use Bing Custom Search with Azure AI agents to find real-time information from the web using custom search configurations. Demonstrates how to set up and use HostedWebSearchTool with custom search instances. |
 | [`azure_ai_with_bing_grounding.py`](azure_ai_with_bing_grounding.py) | Shows how to use Bing Grounding search with Azure AI agents to find real-time information from the web. Demonstrates web search capabilities with proper source citations and comprehensive error handling. |
+| [`azure_ai_with_code_interpreter_file_generation.py`](azure_ai_with_code_interpreter_file_generation.py) | Shows how to retrieve file IDs from code interpreter generated files using both streaming and non-streaming approaches. |
 | [`azure_ai_with_code_interpreter.py`](azure_ai_with_code_interpreter.py) | Shows how to use the HostedCodeInterpreterTool with Azure AI agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks. |
 | [`azure_ai_with_existing_agent.py`](azure_ai_with_existing_agent.py) | Shows how to work with a pre-existing agent by providing the agent ID to the Azure AI chat client. This example also demonstrates proper cleanup of manually created agents. |
 | [`azure_ai_with_existing_thread.py`](azure_ai_with_existing_thread.py) | Shows how to work with a pre-existing thread by providing the thread ID to the Azure AI chat client. This example also demonstrates proper cleanup of manually created threads. |

python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_code_interpreter_file_generation.py

@@ -0,0 +1,102 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import AgentRunResponseUpdate, ChatAgent, HostedCodeInterpreterTool, HostedFileContent
+from agent_framework.azure import AzureAIAgentClient
+from azure.identity.aio import AzureCliCredential
+
+"""
+Azure AI Agent Code Interpreter File Generation Example
+
+This sample demonstrates using HostedCodeInterpreterTool with AzureAIAgentClient
+to generate a text file and then retrieve it.
+
+The test flow:
+1. Create an agent with code interpreter tool
+2. Ask the agent to generate a txt file using Python code
+3. Capture the file_id from HostedFileContent in the response
+4. Retrieve the file using the agents_client.files API
+"""
+
+
+async def main() -> None:
+    """Test file generation and retrieval with code interpreter."""
+
+    async with AzureCliCredential() as credential:
+        client = AzureAIAgentClient(credential=credential)
+
+        try:
+            async with ChatAgent(
+                chat_client=client,
+                instructions=(
+                    "You are a Python code execution assistant. "
+                    "ALWAYS use the code interpreter tool to execute Python code when asked to create files. "
+                    "Write actual Python code to create files, do not just describe what you would do."
+                ),
+                tools=[HostedCodeInterpreterTool()],
+            ) as agent:
+                # Be very explicit about wanting code execution and a download link
+                query = (
+                    "Use the code interpreter to execute this Python code and then provide me "
+                    "with a download link for the generated file:\n"
+                    "```python\n"
+                    "with open('/mnt/data/sample.txt', 'w') as f:\n"
+                    "    f.write('Hello, World! This is a test file.')\n"
+                    "'/mnt/data/sample.txt'\n"  # Return the path so it becomes downloadable
+                    "```"
+                )
+                print(f"User: {query}\n")
+                print("=" * 60)
+
+                # Collect file_ids from the response
+                file_ids: list[str] = []
+
+                async for chunk in agent.run_stream(query):
+                    if not isinstance(chunk, AgentRunResponseUpdate):
+                        continue
+
+                    for content in chunk.contents:
+                        if content.type == "text":
+                            print(content.text, end="", flush=True)
+                        elif content.type == "hosted_file":
+                            if isinstance(content, HostedFileContent):
+                                file_ids.append(content.file_id)
+                                print(f"\n[File generated: {content.file_id}]")
+
+                print("\n" + "=" * 60)
+
+                # Attempt to retrieve discovered files
+                if file_ids:
+                    print(f"\nAttempting to retrieve {len(file_ids)} file(s):")
+                    for file_id in file_ids:
+                        try:
+                            file_info = await client.agents_client.files.get(file_id)
+                            print(f"  File {file_id}: Retrieved successfully")
+                            print(f"    Filename: {file_info.filename}")
+                            print(f"    Purpose: {file_info.purpose}")
+                            print(f"    Bytes: {file_info.bytes}")
+                        except Exception as e:
+                            print(f"  File {file_id}: FAILED to retrieve - {e}")
+                else:
+                    print("No file IDs were captured from the response.")
+
+                # List all files to see if any exist
+                print("\nListing all files in the agent service:")
+                try:
+                    files_list = await client.agents_client.files.list()
+                    count = 0
+                    for file_info in files_list.data:
+                        count += 1
+                        print(f"  - {file_info.id}: {file_info.filename} ({file_info.purpose})")
+                    if count == 0:
+                        print("  No files found.")
+                except Exception as e:
+                    print(f"  Failed to list files: {e}")
+
+        finally:
+            await client.close()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())