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Migrating code-interpreter module to the samples folder.
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‎scenarios/Agents/samples/code-interpreter/python-code-interpreter.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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FILE: python-sample.py
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DESCRIPTION:
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This sample demonstrates how to use agent operations with code interpreter from
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the Azure Agents service using a synchronous client.
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USAGE:
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python python-sample.py
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Before running the sample:
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pip install azure-ai-projects azure-identity
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Set this environment variables with your own values:
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PROJECT_CONNECTION_STRING - the Azure AI Project connection string, as found in your AI Studio Project.
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"""
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import os
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from azure.ai.projects import AIProjectClient
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from azure.ai.projects.models import CodeInterpreterTool
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from azure.ai.projects.models import FilePurpose
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from azure.identity import DefaultAzureCredential
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from pathlib import Path
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# Create an Azure AI Client from a connection string, copied from your AI Studio project.
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# At the moment, it should be in the format "<HostName>;<AzureSubscriptionId>;<ResourceGroup>;<HubName>"
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# Customer needs to login to Azure subscription via Azure CLI and set the environment variables
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project_client = AIProjectClient.from_connection_string(
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credential=DefaultAzureCredential(), conn_str=os.environ["PROJECT_CONNECTION_STRING"]
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)
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with project_client:
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# upload a file and wait for it to be processed
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file = project_client.agents.upload_file_and_poll(
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file_path="../../data/nifty_500_quarterly_results.csv", purpose=FilePurpose.AGENTS
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)
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print(f"Uploaded file, file ID: {file.id}")
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# instantiate the CodeInterpreterTool with the necessary files
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code_interpreter = CodeInterpreterTool(file_ids=[file.id])
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# notice that CodeInterpreter must be enabled in the agent creation, otherwise the agent will not be able to see the file attachment
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agent = project_client.agents.create_agent(
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model="gpt-4o-mini",
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name="my-agent",
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instructions="You are helpful agent",
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tools=code_interpreter.definitions,
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tool_resources=code_interpreter.resources,
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)
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print(f"Created agent, agent ID: {agent.id}")
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# create a thread
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thread = project_client.agents.create_thread()
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print(f"Created thread, thread ID: {thread.id}")
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# create a message
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message = project_client.agents.create_message(
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thread_id=thread.id,
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role="user",
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content="Could you please create bar chart in the TRANSPORTATION sector for the operating profit from the uploaded csv file and provide file to me?",
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)
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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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print(f"Run finished with status: {run.status}")
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if run.status == "failed":
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# Check if you got "Rate limit is exceeded.", then you want to get more quota
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print(f"Run failed: {run.last_error}")
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# delete the original file from the agent to free up space (note: this does not delete your version of the file)
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project_client.agents.delete_file(file.id)
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print("Deleted file")
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# print the messages from the agent
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messages = project_client.agents.get_messages(thread_id=thread.id)
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print(f"Messages: {messages}")
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# get the most recent message from the assistant
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last_msg = messages.get_last_text_message_by_sender("assistant")
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if last_msg:
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print(f"Last Message: {last_msg.text.value}")
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# save the newly created file
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for image_content in messages.image_contents:
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print(f"Image File ID: {image_content.image_file.file_id}")
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file_name = f"{image_content.image_file.file_id}_image_file.png"
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project_client.agents.save_file(file_id=image_content.image_file.file_id, file_name=file_name)
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print(f"Saved image file to: {Path.cwd() / file_name}")
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# iterates through file_path_annotations in messages and prints details for each annotation
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for file_path_annotation in messages.file_path_annotations:
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print(f"File Paths:")
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print(f"Type: {file_path_annotation.type}")
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print(f"Text: {file_path_annotation.text}")
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print(f"File ID: {file_path_annotation.file_path.file_id}")
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print(f"Start Index: {file_path_annotation.start_index}")
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print(f"End Index: {file_path_annotation.end_index}")
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# delete the agent once done
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project_client.agents.delete_agent(agent.id)
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print("Deleted agent")

‎scenarios/Agents/samples/code-interpreter/readme.md‎

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# Code interpreter
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Code Interpreter allows the Agent to write and run Python code in a sandboxed execution environment. With Code Interpreter enabled, your Agent can run code iteratively to solve more challenging code, math, and data analysis problems.
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## Examples
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Run the code samples below and view the output.
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>[!NOTE]
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> Be sure that you've [installed the SDK](../../quickstart.md#install-the-sdk-package) for your language.
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* [Python](./python-code-interpreter.py)
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# Additional samples
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* [Math tutor](https://github.com/openai/openai-cookbook/blob/main/examples/data/oai_docs/tool-code-interpreter.txt)
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## Supported file types
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|File format|MIME Type|
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|---|---|
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|.c| text/x-c |
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|.cpp|text/x-c++ |
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|.csv|application/csv|
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|.docx|application/vnd.openxmlformats-officedocument.wordprocessingml.document|
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|.html|text/html|
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|.java|text/x-java|
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|.json|application/json|
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|.md|text/markdown|
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|.pdf|application/pdf|
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|.php|text/x-php|
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|.pptx|application/vnd.openxmlformats-officedocument.presentationml.presentation|
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|.py|text/x-python|
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|.py|text/x-script.python|
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|.rb|text/x-ruby|
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|.tex|text/x-tex|
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|.txt|text/plain|
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|.css|text/css|
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|.jpeg|image/jpeg|
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|.jpg|image/jpeg|
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|.js|text/javascript|
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|.gif|image/gif|
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|.png|image/png|
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|.tar|application/x-tar|
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|.ts|application/typescript|
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|.xlsx|application/vnd.openxmlformats-officedocument.spreadsheetml.sheet|
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|.xml|application/xml or "text/xml"|
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|.zip|application/zip|

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