Get the prompt content with given prompt id.

Create a prompt with given content, system instruction, model and display name.

Update a prompt with given prompt_id and new content, system instruction, model, and display name.

Delete a prompt with given prompt_id.

Lists Vertex prompts matching a given display name.

Constructs a JSON configuration for Data-Driven Optimize and uploads it to GCS.

This tool generates a JSON configuration file based on the provided parameters and uploads it to the specified Google Cloud Storage URI. This configuration file is required to run data-driven prompt optimization.

Args: gcs_config_uri: The GCS URI where the generated VAPO config JSON file will be saved (e.g., 'gs://my-bucket/vapo/config.json'). prompt_optimizer_method: The method for prompt optimization. Either 'VAPO' or 'OPTIMIZATION_TARGET_GEMINI_NANO'. target_model_endpoint_url: The custom endpoint URL for the target model. Required for Gemini Nano target. base_config: Optional. A dictionary representing the base configuration. modifications: Optional. A dictionary representing the modifications to apply to the base config. base_config_path: Optional. Path to a base config file. If provided and base_config is None, this config will be loaded.

Returns: A string containing a success message and details about the uploaded configuration file, including a link to the Vertex AI console.

Starts a data-driven prompt optimization job on Vertex AI.

This method uses a dataset and configurable metrics. The config_gcs_path must point to a JSON file in Google Cloud Storage.

Args: config_gcs_path: The Google Cloud Storage URI (e.g., "gs://your-bucket/config.json") to a JSON file containing the Prompt Optimizer configuration. This is required. service_account: The service account email to run the job. This is required. prompt_optimizer_method: The method for prompt optimization. Either 'VAPO' or 'OPTIMIZATION_TARGET_GEMINI_NANO'. wait_for_completion: If True, the tool will block until the Vertex AI CustomJob completes. Defaults to False.

Returns: A string indicating the status and details of the optimization job, including a link to the Vertex AI console.

Applies few shot prompt optimization to a prompt using user provided dataset and method.

Args: prompt_to_optimize: The zero-based index of the prompt to improve. example_path: GCS path to the csv file containg few-shot examples method: The optimization method to use for few shot prompt improvement. The method should be one of the following: - TARGET_RESPONSE: Optimize the prompt to match the target response. - RUBRICS: Optimize the prompt to improve the rubrics scores.

Returns: Optimized prompt.

Analyzes results and saves the detailed data to files.

Generates a comprehensive HTML report from Data-Driven Optimize analysis results.

获取 MCP 服务的 token 使用统计信息。

调用 DashScope 的远程 MCP 服务并获取结果。

Args: tool_name: DashScope MCP 中的工具名称 arguments: 传递给工具的参数字典