如何使用 REST API 上传在 LangSmith 外部运行的实验

一些用户喜欢在 LangSmith 之外管理他们的数据集和运行他们的实验，但希望使用 LangSmith UI 来查看结果。这通过我们的/datasets/upload-experiment端点。

本指南将向您展示如何使用 REST API 上传评估，使用requests库。但是，相同的原则适用于任何语言。

请求正文架构

上传实验需要为实验和数据集指定相关的高级信息，以及示例中和运行的个人数据 实验。每个对象在results表示试验中的“行”，单个数据集示例以及关联的运行。请注意，dataset_id和dataset_name引用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。它们不应引用现有数据集 在 LangSmith 中（除非该数据集是通过此终端节点创建的）。

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 将是带有键的 dictexperiment和dataset，每个 ID 都是一个对象，其中包含有关所创建的实验和数据集的相关信息。

考虑

您可以通过在多个调用之间提供相同的dataset_id或dataset_name，将多个实验上传到同一数据集。您的实验将归为一组 ，您将能够使用 Comparison （比较） 视图来比较实验之间的结果。

确保各个行的开始和结束时间都介于实验的开始时间和结束时间之间。

您必须提供 dataset_id 或 dataset_name。如果您只提供了一个 ID，并且数据集尚不存在，我们将为您生成一个名称，反之亦然，如果 您只需提供一个名称。

您不能将实验上传到不是通过此终端节点创建的数据集。只有外部管理的数据集才支持上传实验。

示例请求

下面是一个对/datasets/upload-experiment.这是一个基本示例，仅使用最重要的字段作为说明。

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())

以下是收到的回复：

{
  "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 latency 和 feedback stats 为 null，因为运行还没有机会持久化，这可能需要几秒钟。 如果您保存实验 ID 并在几秒钟内再次查询，您将看到所有统计信息（尽管 tokens/cost 仍为 null，因为我们不要求这样做 信息）。

在 UI 中查看实验

现在，登录到 UI 并单击您新创建的数据集！您应该会看到一个实验：

您的示例将已上传：

点击您的实验将带您进入比较视图：

随着您向数据集上传更多实验，您将能够比较结果并在比较视图中轻松识别回归。