如何通过 REST API 上传在 LangSmith 之外运行的实验

有些用户倾向于在 LangSmith 之外管理他们的数据集并运行实验，但希望使用 LangSmith UI 来查看结果。我们的 /datasets/upload-experiment 端点支持此功能。

本指南将向您展示如何使用 REST API 上传评估，以 Python 中的 requests 库为例。然而，同样的原则适用于任何语言。

请求体架构

上传实验需要指定实验和数据集的相关高级信息，以及实验中示例和运行的单独数据。results 中的每个对象都代表实验中的“行”——一个单独的数据集示例，以及相关的运行。请注意，dataset_id 和 dataset_name 指的是您在外部系统中的数据集标识符，并将用于将外部实验分组到单个数据集中。它们不应指 LangSmith 中已有的数据集（除非该数据集是通过此端点创建的）。

您可以使用以下架构将实验上传到 /datasets/upload-experiment 端点

{
  "experiment_name": "string (required)",
  "experiment_description": "string (optional)",
  "experiment_start_time": "datetime (required)",
  "experiment_end_time": "datetime (required)",
  "dataset_id": "uuid (optional - an external dataset id, used to group experiments together)",
  "dataset_name": "string (optional - must provide either dataset_id or dataset_name)",
  "dataset_description": "string (optional)",
  "experiment_metadata": { // Object (any shape - optional)
    "key": "value"
  },
  "summary_experiment_scores": [ // List of summary feedback objects (optional)
    {
      "key": "string (required)",
      "score": "number (optional)",
      "value": "string (optional)",
      "comment": "string (optional)",
      "feedback_source": { // Object (optional)
        "type": "string (required)"
      },
      "feedback_config": { // Object (optional)
        "type": "string enum: continuous, categorical, or freeform",
        "min": "number (optional)",
        "max": "number (optional)",
        "categories": [ // List of feedback category objects (optional)
            "value": "number (required)",
            "label": "string (optional)"
        ]
      },
      "created_at": "datetime (optional - defaults to now)",
      "modified_at": "datetime (optional - defaults to now)",
      "correction": "Object or string (optional)"
    }
  ],
  "results": [ // List of experiment row objects (required)
    {
      "row_id": "uuid (required)",
      "inputs": {     // Object (required - any shape). This will
        "key": "val"  // be the input to both the run and the dataset example.
      },
      "expected_outputs": { // Object (optional - any shape).
        "key": "val"        // These will be the outputs of the dataset examples.
      },
      "actual_outputs": { // Object (optional - any shape).
        "key": "val       // These will be the outputs of the runs.
      },
      "evaluation_scores": [ // List of feedback objects for the run (optional)
        {
            "key": "string (required)",
            "score": "number (optional)",
            "value": "string (optional)",
            "comment": "string (optional)",
            "feedback_source": { // Object (optional)
                "type": "string (required)"
            },
            "feedback_config": { // Object (optional)
                "type": "string enum: continuous, categorical, or freeform",
                "min": "number (optional)",
                "max": "number (optional)",
                "categories": [ // List of feedback category objects (optional)
                    "value": "number (required)",
                    "label": "string (optional)"
                ]
            },
            "created_at": "datetime (optional - defaults to now)",
            "modified_at": "datetime (optional - defaults to now)",
            "correction": "Object or string (optional)"
        }
      ],
      "start_time": "datetime (required)", // The start/end times for the runs will be used to
      "end_time": "datetime (required)",   // calculate latency. They must all fall between the
      "run_name": "string (optional)",     // start and end times for the experiment.
      "error": "string (optional)",
      "run_metadata": { // Object (any shape - optional)
        "key": "value"
      }
    }
  ]
}

响应 JSON 将是一个字典，包含 experiment 和 dataset 两个键，每个键都是一个对象，其中包含有关已创建实验和数据集的相关信息。

注意事项

您可以通过在多次调用之间提供相同的 dataset_id 或 dataset_name 来将多个实验上传到同一数据集。您的实验将分组到单个数据集下，您将能够使用比较视图比较不同实验的结果。

确保您的每个行的开始时间和结束时间都在实验的开始时间和结束时间之间。

您必须提供 dataset_id 或 dataset_name。如果您只提供 ID 且数据集尚不存在，我们将为您生成一个名称；反之，如果您只提供名称，则会生成一个 ID。

您不能将实验上传到不是通过此端点创建的数据集。上传实验仅支持外部管理的数据集。

请求示例

下面是调用 /datasets/upload-experiment 的一个简单示例。这是一个基本示例，仅使用最重要的字段进行说明。

import os
import requests

body = {
  "experiment_name": "My external experiment",
  "experiment_description": "An experiment uploaded to LangSmith",
  "dataset_name": "my-external-dataset",
  "summary_experiment_scores": [
    {
      "key": "summary_accuracy",
      "score": 0.9,
      "comment": "Great job!"
    }
  ],
  "results": [
    {
      "row_id": "<<uuid>>",
      "inputs": {
        "input": "Hello, what is the weather in San Francisco today?"
      },
      "expected_outputs": {
        "output": "Sorry, I am unable to provide information about the current weather."
      },
      "actual_outputs": {
        "output": "The weather is partly cloudy with a high of 65."
      },
      "evaluation_scores": [
        {
          "key": "hallucination",
          "score": 1,
          "comment": "The chatbot made up the weather instead of identifying that "
                     "they don't have enough info to answer the question. This is "
                     "a hallucination."
        }
      ],
      "start_time": "2024-08-03T00:12:39",
      "end_time": "2024-08-03T00:12:41",
      "run_name": "Chatbot"
    },
    {
      "row_id": "<<uuid>>",
      "inputs": {
        "input": "Hello, what is the square root of 49?"
      },
      "expected_outputs": {
        "output": "The square root of 49 is 7."
      },
      "actual_outputs": {
        "output": "7."
      },
      "evaluation_scores": [
       {
          "key": "hallucination",
          "score": 0,
          "comment": "The chatbot correctly identified the answer. This is not a "
                     "hallucination."
        }
      ],
      "start_time": "2024-08-03T00:12:40",
      "end_time": "2024-08-03T00:12:42",
      "run_name": "Chatbot"
    }
  ],
  "experiment_start_time": "2024-08-03T00:12:38",
  "experiment_end_time": "2024-08-03T00:12:43"
}

resp = requests.post(
    "https://api.smith.langchain.com/api/v1/datasets/upload-experiment", # Update appropriately for self-hosted installations or the EU region
    json=body,
    headers={"x-api-key": os.environ["LANGSMITH_API_KEY"]}
)
print(resp.json())

下面是收到的响应

{
  "dataset": {
    "name": "my-external-dataset",
    "description": null,
    "created_at": "2024-08-03T00:36:23.289730+00:00",
    "data_type": "kv",
    "inputs_schema_definition": null,
    "outputs_schema_definition": null,
    "externally_managed": true,
    "id": "<<uuid>>",
    "tenant_id": "<<uuid>>",
    "example_count": 0,
    "session_count": 0,
    "modified_at": "2024-08-03T00:36:23.289730+00:00",
    "last_session_start_time": null
  },
  "experiment": {
    "start_time": "2024-08-03T00:12:38",
    "end_time": "2024-08-03T00:12:43+00:00",
    "extra": null,
    "name": "My external experiment",
    "description": "An experiment uploaded to LangSmith",
    "default_dataset_id": null,
    "reference_dataset_id": "<<uuid>>",
    "trace_tier": "longlived",
    "id": "<<uuid>>",
    "run_count": null,
    "latency_p50": null,
    "latency_p99": null,
    "first_token_p50": null,
    "first_token_p99": null,
    "total_tokens": null,
    "prompt_tokens": null,
    "completion_tokens": null,
    "total_cost": null,
    "prompt_cost": null,
    "completion_cost": null,
    "tenant_id": "<<uuid>>",
    "last_run_start_time": null,
    "last_run_start_time_live": null,
    "feedback_stats": null,
    "session_feedback_stats": null,
    "run_facets": null,
    "error_rate": null,
    "streaming_rate": null,
    "test_run_number": 1
  }
}

请注意，实验结果中的延迟和反馈统计信息为空，因为运行尚未有机会持久化，这可能需要几秒钟。如果您保存实验 ID 并在几秒钟后再次查询，您将看到所有统计信息（尽管 token/成本仍为空，因为我们在请求体中没有要求这些信息）。

在用户界面中查看实验

现在，登录用户界面并点击您新创建的数据集！您应该会看到一个实验：

您的示例已上传：

点击您的实验将带您进入比较视图：

随着您上传更多实验到数据集中，您将能够在比较视图中比较结果并轻松识别回归问题。