Foundry 代理服务代码解释器

使用代码解释器创建代理

code_interpreter = CodeInterpreterTool()

# An agent is created with the Code Interpreter capabilities:
agent = project_client.agents.create_agent(
    model=os.environ["MODEL_DEPLOYMENT_NAME"],
    name="my-agent",
    instructions="You are helpful agent",
    tools=code_interpreter.definitions,
    tool_resources=code_interpreter.resources,
)

附加文件供代码解释器使用

如果希望文件与代码解释器一起使用，可以使用该 upload_and_poll 函数。

file = agents_client.files.upload_and_poll(file_path=asset_file_path, purpose=FilePurpose.AGENTS)
print(f"Uploaded file, file ID: {file.id}")

code_interpreter = CodeInterpreterTool(file_ids=[file.id])

使用代码解释器创建代理

var projectEndpoint = System.Environment.GetEnvironmentVariable("ProjectEndpoint");
var modelDeploymentName = System.Environment.GetEnvironmentVariable("ModelDeploymentName");

PersistentAgentsClient client = new(projectEndpoint, new DefaultAzureCredential());

PersistentAgent agent = client.Administration.CreateAgent(
    model: modelDeploymentName,
    name: "My Friendly Test Agent",
    instructions: "You politely help with math questions. Use the code interpreter tool when asked to visualize numbers.",
    tools: [new CodeInterpreterToolDefinition()]
);

附加文件供代码解释器使用

如果希望文件与代码解释器一起使用，可以将其附加到邮件中。

PersistentAgentFileInfo uploadedAgentFile = client.Files.UploadFile(
    filePath: "sample_file_for_upload.txt",
    purpose: PersistentAgentFilePurpose.Agents);
var fileId = uploadedAgentFile.Id;

var attachment = new MessageAttachment(
    fileId: fileId,
    tools: tools
);

// attach the file to the message
PersistentThreadMessage message = client.Messages.CreateMessage(
    threadId: thread.Id,
    role: MessageRole.User,
    content: "Can you give me the documented information in this file?",
    attachments: [attachment]
);

使用代码解释器创建代理

// Create the code interpreter tool
const codeInterpreterTool = ToolUtility.createCodeInterpreterTool();

// Enable the code interpreter tool during agent creation
const agent = await client.createAgent("gpt-4o", {
  name: "my-agent",
  instructions: "You are a helpful agent",
  tools: [codeInterpreterTool.definition],
  toolResources: codeInterpreterTool.resources,
});
console.log(`Created agent, agent ID: ${agent.id}`);

附加文件供代码解释器使用

如果希望文件与代码解释器一起使用，可以将其附加到该工具。

// Upload file and wait for it to be processed
const filePath = "./examplefile.csv";
const localFileStream = fs.createReadStream(filePath);
const localFile = await client.files.upload(localFileStream, "assistants", {
  fileName: "localFile",
});
// Create code interpreter tool
const codeInterpreterTool = ToolUtility.createCodeInterpreterTool([localFile.id]);

使用代码解释器工具创建代理

curl --request POST \
  --url $AZURE_AI_FOUNDRY_PROJECT_ENDPOINT/assistants?api-version=$API_VERSION \
  -H "Authorization: Bearer $AGENT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "instructions": "You are an AI assistant that can write code to help answer math questions.",
    "tools": [
      { "type": "code_interpreter" }
    ],
    "model": "gpt-4o-mini",
    "tool_resources"{
      "code interpreter": {
      }
    }
  }'

String agentName = "code_interpreter_agent";
CodeInterpreterToolDefinition ciTool = new CodeInterpreterToolDefinition();
CreateAgentOptions createAgentOptions = new CreateAgentOptions(modelName).setName(agentName).setInstructions("You are a helpful agent").setTools(Arrays.asList(ciTool));
PersistentAgent agent = administrationClient.createAgent(createAgentOptions);

附加文件供代码解释器使用

如果希望文件与代码解释器一起使用，可以将其附加到该工具。

FileInfo uploadedFile = filesClient.uploadFile(new UploadFileRequest(
    new FileDetails(BinaryData.fromFile(htmlFile))
    .setFilename("sample.html"), FilePurpose.AGENTS));

MessageAttachment messageAttachment = new MessageAttachment(Arrays.asList(BinaryData.fromObject(ciTool))).setFileId(uploadedFile.getId());

PersistentAgentThread thread = threadsClient.createThread();
ThreadMessage createdMessage = messagesClient.createMessage(
    thread.getId(),
    MessageRole.USER,
    "What does the attachment say?",
    Arrays.asList(messageAttachment),
    null);