Python: added code sample to download file from code interpreter

python/samples/02-agents/providers/openai/client_with_code_interpreter_files_download.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import os
+from pathlib import Path
+
+from agent_framework import Agent
+from agent_framework.openai import OpenAIChatClient
+from dotenv import load_dotenv
+from openai import AsyncOpenAI
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+OpenAI Chat Client — Code Interpreter Graph Generation from CSV
+
+This sample demonstrates using code interpreter with the Responses API to:
+  1. Upload a local CSV file via the Files API
+  2. Pass the file to code interpreter via get_code_interpreter_tool(file_ids=[...])
+  3. Ask the model to generate matplotlib charts from the data
+  4. Download generated chart images from container file citations
+  5. Clean up the uploaded file
+
+The generated images are saved to the current working directory.
+"""
+
+
+def extract_file_citations(result) -> list[dict[str, str]]:
+    """Extract container file citation metadata from an AgentResponse.
+
+    Returns a list of dicts with 'container_id', 'file_id', and 'filename' keys.
+    """
+    citations = []
+    for message in result.messages:
+        for content in message.contents:
+            if not content.annotations:
+                continue
+            for ann in content.annotations:
+                if ann.get("type") == "citation" and ann.get("file_id"):
+                    props = ann.get("additional_properties", {})
+                    container_id = props.get("container_id")
+                    if not container_id:
+                        continue
+                    citations.append({
+                        "container_id": container_id,
+                        "file_id": ann["file_id"],
+                        "filename": ann.get("url") or "",
+                    })
+    return citations
+
+
+async def upload_csv(openai_client: AsyncOpenAI, csv_path: str) -> str:
+    """Upload a local CSV file for code interpreter use.
+
+    Args:
+        openai_client: The underlying AsyncOpenAI client.
+        csv_path: Local path to the CSV file.
+
+    Returns:
+        The uploaded file ID.
+    """
+    with open(csv_path, "rb") as f:
+        uploaded = await openai_client.files.create(file=f, purpose="assistants")
+    print(f"Uploaded {csv_path} → {uploaded.id}")
+    return uploaded.id
+
+
+async def cleanup_uploaded_file(openai_client: AsyncOpenAI, file_id: str) -> None:
+    """Delete an uploaded file."""
+    await openai_client.files.delete(file_id)
+    print(f"Deleted uploaded file: {file_id}")
+
+
+async def download_container_file(
+    openai_client: AsyncOpenAI,
+    container_id: str,
+    file_id: str,
+    output_path: str,
+) -> str:
+    """Download a file from an OpenAI container and save it locally.
+
+    Args:
+        openai_client: The underlying AsyncOpenAI client.
+        container_id: The container ID from the citation metadata.
+        file_id: The file ID from the citation metadata.
+        output_path: Local path to save the downloaded file.
+
+    Returns:
+        The output path where the file was saved.
+    """
+    response = await openai_client.containers.files.content.retrieve(
+        file_id=file_id,
+        container_id=container_id,
+    )
+    with open(output_path, "wb") as f:
+        f.write(response.content)
+    print(f"Downloaded {output_path} ({len(response.content)} bytes)")
+    return output_path
+
+
+async def main() -> None:
+    model = os.environ["AZURE_OPENAI_MODEL"]
+    endpoint = os.environ["AZURE_OPENAI_ENDPOINT"]
+    api_key = os.environ["AZURE_OPENAI_API_KEY"]
+
+    client = OpenAIChatClient(
+        model=model,
+        azure_endpoint=endpoint,
+        api_key=api_key,
+    )
+
+    # Upload the CSV and configure code interpreter with the file
+    csv_path = str(Path(__file__).parents[3] / "shared" / "sample_assets" / "sample_city_populations.csv")
+    openai_client = client.client
+    uploaded_file_id = await upload_csv(openai_client, csv_path)
+
+    agent = Agent(
+        client=client,
+        instructions=(
+            "You are a data visualization assistant. "
+            "When asked to create charts or graphs, use matplotlib to generate them. "
+            "Always save charts with plt.savefig before plt.show."
+        ),
+        tools=client.get_code_interpreter_tool(file_ids=[uploaded_file_id]),
+    )
+
+    query = (
+        "Read the uploaded CSV file and create two charts: "
+        "1) A horizontal bar chart of the top 10 cities by population, "
+        "2) A pie chart showing population distribution by continent. "
+        "Use a nice color palette, add titles and labels."
+    )
+    print(f"\nUser: {query}\n")
+
+    result = await agent.run(query)
+
+    # Print the text response
+    print(f"Assistant: {result.text}\n")
+
+    # Print any generated Python code
+    for message in result.messages:
+        for content in message.contents:
+            if content.type == "code_interpreter_tool_call" and content.inputs:
+                print("Generated code:")
+                print(content.inputs[0].text)
+                print()
+
+    # Download generated chart images from container file citations
+    citations = extract_file_citations(result)
+    for i, cite in enumerate(citations):
+        filename = cite["filename"] or f"output_{i}.png"
+        await download_container_file(
+            openai_client,
+            container_id=cite["container_id"],
+            file_id=cite["file_id"],
+            output_path=filename,
+        )
+
+    # Clean up
+    await cleanup_uploaded_file(openai_client, uploaded_file_id)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/shared/sample_assets/sample_city_populations.csv

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+city,country,population_millions,area_sq_km,density_per_sq_km,continent
+Tokyo,Japan,37.4,2194,17049,Asia
+Delhi,India,32.9,1484,22177,Asia
+Shanghai,China,29.2,6341,4607,Asia
+São Paulo,Brazil,22.6,1521,14862,South America
+Mumbai,India,21.7,603,36003,Asia
+Cairo,Egypt,21.3,3085,6906,Africa
+Beijing,China,20.9,16411,1274,Asia
+Mexico City,Mexico,21.8,1485,14680,North America
+Dhaka,Bangladesh,22.4,306,73275,Asia
+Osaka,Japan,19.1,225,84889,Asia
+New York,USA,18.8,783,24009,North America
+Lagos,Nigeria,15.9,1171,13578,Africa
+Istanbul,Turkey,15.6,5461,2856,Europe
+Buenos Aires,Argentina,15.4,4758,3237,South America
+Kolkata,India,15.1,1887,8003,Asia