[Beta] Bulk Exporting Trace Data

Note

Please note that the Data Export functionality is in Beta and only supported for LangSmith Plus or Enterprise tiers.

LangSmith's bulk data export functionality allows you to export your traces into an external destination. This can be useful if you want to analyze the data offline in a tool such as BigQuery, Snowflake, RedShift, Jupyter Notebooks, etc.

An export can be launched to target a specific LangSmith project and date range. Once a batch export is launched, our system will handle the orchestration and resilience of the export process. Please note that exporting your data may take some time depending on the size of your data. We also have a limit on how many of your exports can run at the same time. Bulk exports also have a runtime timeout of 24 hours.

Destinations

Currently we support exporting to an S3 bucket or S3 API compatible bucket that you provide. The data will be exported in Parquet columnar format. This format will allow you to easily import the data into other systems. The data export will contain equivalent data fields as the Run data format.

Exporting Data

Destinations - Providing a S3 bucket

To export LangSmith data, you will need to provide an S3 bucket where the data will be exported to.

The following information is needed for the export:

• Bucket Name: The name of the S3 bucket where the data will be exported to.
• Prefix: The root prefix within the bucket where the data will be exported to.
• S3 Region: The region of the bucket - this is needed for AWS S3 buckets.
• Endpoint URL: The endpoint URL for the S3 bucket - this is needed for S3 API compatible buckets.
• Access Key: The access key for the S3 bucket.
• Secret Key: The secret key for the S3 bucket.

We support any S3 compatible bucket, for non AWS buckets such as GCS or MinIO, you will need to provide the endpoint URL.

Preparing the Destination

The following example demonstrates how to create a destination using cURL. Replace the placeholder values with your actual configuration details. Note that credentials will be stored securely in an encrypted form in our system.

curl --request POST \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports/destinations' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID' \
  --data '{
    "destination_type": "s3",
    "display_name": "My S3 Destination",
    "config": {
      "bucket_name": "your-s3-bucket-name",
      "prefix": "root_folder_prefix",
      "region": "your aws s3 region",
      "endpoint_url": "your endpoint url for s3 compatible buckets"
    },
    "credentials": {
      "access_key_id": "YOUR_S3_ACCESS_KEY_ID",
      "secret_access_key": "YOUR_S3_SECRET_ACCESS_KEY"
    }
  }'

Use the returned id to reference this destination in subsequent bulk export operations.

If you receive an error while creating a destination, see debug destination errors for details on how to debug this.

AWS S3 bucket

For AWS S3, you can leave off the endpoint_url and supply the region that matches the region of your bucket.

curl --request POST \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports/destinations' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID' \
  --data '{
    "destination_type": "s3",
    "display_name": "My AWS S3 Destination",
    "config": {
      "bucket_name": "my_bucket",
      "prefix": "data_exports",
      "region": "us-east-1",
    },
    "credentials": {
      "access_key_id": "YOUR_S3_ACCESS_KEY_ID",
      "secret_access_key": "YOUR_S3_SECRET_ACCESS_KEY"
    }
  }'

Google GCS XML S3 compatible bucket

When using Google's GCS bucket, you need to use the XML S3 compatible API, and supply the endpoint_url which is typically https://storage.googleapis.com.
Here is an example of the API request when using the GCS XML API which is compatible with S3:

curl --request POST \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports/destinations' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID' \
  --data '{
    "destination_type": "s3",
    "display_name": "My GCS Destination",
    "config": {
      "bucket_name": "my_bucket",
      "prefix": "data_exports",
      "endpoint_url": "https://storage.googleapis.com"
    },
    "credentials": {
      "access_key_id": "YOUR_S3_ACCESS_KEY_ID",
      "secret_access_key": "YOUR_S3_SECRET_ACCESS_KEY"
    }
  }'

See Google documentation for more info

Create an export job

To export data, you will need to create an export job. This job will specify the destination, the project, and the date range of the data to export.

You can use the following cURL command to create the job:

curl --request POST \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID' \
  --data '{
    "bulk_export_destination_id": "your_destination_id",
    "session_id": "project_uuid",
    "start_time": "2024-01-01T00:00:00Z",
    "end_time": "2024-01-02T23:59:59Z"
  }'

Use the returned id to reference this export in subsequent bulk export operations.

Monitoring the Export Job

Monitor Export Status

To monitor the status of an export job, use the following cURL command:

curl --request GET \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports/{export_id}' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID'

Replace {export_id} with the ID of the export you want to monitor. This command retrieves the current status of the specified export job.

List Runs for an Export

An export is typically broken up into multiple runs which correspond to a specific date partition to export. To list all runs associated with a specific export, use the following cURL command:

curl --request GET \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports/{export_id}/runs' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID'

This command fetches all runs related to the specified export, providing details such as run ID, status, creation time, rows exported, etc.

List All Exports

To retrieve a list of all export jobs, use the following cURL command:

curl --request GET \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID'

This command returns a list of all export jobs along with their current statuses and creation timestamps.

Stop an Export

To stop an existing export, use the following cURL command:

curl --request PATCH \
  --url 'https://api.smith.langchain.com/api/v1/bulk-exports/{export_id}' \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: YOUR_API_KEY' \
  --header 'X-Tenant-Id: YOUR_WORKSPACE_ID' \
  --data '{
    "status": "Cancelled"
}'

Replace {export_id} with the ID of the export you wish to cancel. Note that a job cannot be restarted once it has been cancelled, you will need to create a new export job instead.

Partitioning Scheme

Data will be exported into your bucket into the follow Hive partitioned format:

<bucket>/<prefix>/export_id=<export_id>/tenant_id=<tenant_id>/session_id=<session_id>/runs/year=<year>/month=<month>/day=<day>

Importing Data into other systems

Importing data from S3 and Parquet format is commonly supported by the majority of analytical systems. See below for documentation links:

BigQuery

To import your data into BigQuery, see Loading Data from Parquet and also Hive Partitioned loads.

Snowflake

You can load data into Snowflake from S3 by following the Load from Cloud Document.

RedShift

You can COPY data from S3 / Parquet into RedShift by following the AWS COPY Instructions.

Clickhouse

You can directly query data in S3 / Parquet format in Clickhouse. As an example, if using GCS, you can query the data as follows:

SELECT count(distinct id) FROM s3('https://storage.googleapis.com/<bucket>/<prefix>/export_id=<export_id>/**',
 'access_key_id', 'access_secret', 'Parquet')

See Clickhouse S3 Integration Documentation for more information.

DuckDB

You can query the data from S3 in-memory with SQL using DuckDB. See S3 import Documentation.

Error Handling

Debugging Destination Errors

The destinations API endpoint will validate that the destination and credentials are valid and that write access is is present for the bucket.

If you receive an error, and would like to debug this error, you can use the AWS CLI to test the connectivity to the bucket. You should be able to write a file with the CLI using the same data that you supplied to the destinations API above.

AWS S3:

aws configure

# set the same access key credentials and region as you used for the destination
> AWS Access Key ID: <access_key_id>
> AWS Secret Access Key: <secret_access_key>
> Default region name [us-east-1]: <region>

# List buckets
aws s3 ls /

# test write permissions
touch ./test.txt
aws s3 cp ./test.txt s3://<bucket-name>/tmp/test.txt

GCS Compatible Buckets:

You will need to supply the endpoint_url with --endpoint-url option.
For GCS, the endpoint_url is typically https://storage.googleapis.com:

aws configure

# set the same access key credentials and region as you used for the destination
> AWS Access Key ID: <access_key_id>
> AWS Secret Access Key: <secret_access_key>
> Default region name [us-east-1]: <region>

# List buckets
aws s3 --endpoint-url=<endpoint_url> ls /

# test write permissions
touch ./test.txt
aws s3 --endpoint-url=<endpoint_url> cp ./test.txt s3://<bucket-name>/tmp/test.txt

Monitoring Runs

You can monitor your runs using the List Runs API. If this is a known error, this will be added to the errors field of the run.

Common Errors

Here are some common errors:

Error	Description
Access denied	The blob store credentials or bucket are not valid. This error occurs when the provided access key and secret key combination doesn't have the necessary permissions to access the specified bucket or perform the required operations.
Bucket is not valid	The specified blob store bucket is not valid. This error is thrown when the bucket doesn't exist or there is not enough access to perform writes on the bucket.
Key ID you provided does not exist	The blob store credentials provided are not valid. This error occurs when the access key ID used for authentication is not a valid key.
Invalid endpoint	The endpoint_url provided is invalid. This error is raised when the specified endpoint is an invalid endpoint. Only S3 compatible endpoints are supported, for example https://storage.googleapis.com for GCS, https://play.min.io for minio, etc. If using AWS, you should omit the endpoint_url.