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POST/api/v1/exports/fine-tune

Export data in fine-tune format (JSONL)

Synchronously generates a JSONL attachment of cases/rows in openai (messages[]), anthropic (prompt/completion), or generic jsonl format, sourced from a dataset and/or an eval run (at least one required). Optional filters select by score/passed/tags. Both sources are project-ownership-verified (403 otherwise). requiredRole: editor.

Authentication

Send Authorization: Bearer YOUR_API_KEY on every request. Generate API keys at /dashboard/api-keys.

Request body required

Example

{
  "projectId": "00000000-0000-0000-0000-000000000000",
  "format": "openai",
  "datasetId": "00000000-0000-0000-0000-000000000000",
  "evalRunId": "00000000-0000-0000-0000-000000000000",
  "filters": {
    "minScore": 0,
    "maxScore": 0,
    "passedOnly": false,
    "tags": [
      "string"
    ]
  }
}
Schema
{
  "application/json": {
    "schema": {
      "type": "object",
      "properties": {
        "projectId": {
          "type": "string",
          "format": "uuid",
          "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$"
        },
        "format": {
          "type": "string",
          "enum": [
            "openai",
            "anthropic",
            "jsonl"
          ]
        },
        "datasetId": {
          "type": "string",
          "format": "uuid",
          "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
          "description": "Source dataset. At least one of datasetId/evalRunId required."
        },
        "evalRunId": {
          "type": "string",
          "format": "uuid",
          "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
          "description": "Source eval run (passing cases used). At least one of datasetId/evalRunId required."
        },
        "filters": {
          "type": "object",
          "properties": {
            "minScore": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "maxScore": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "passedOnly": {
              "type": "boolean"
            },
            "tags": {
              "maxItems": 50,
              "type": "array",
              "items": {
                "type": "string",
                "maxLength": 60
              }
            }
          },
          "additionalProperties": false
        }
      },
      "required": [
        "projectId",
        "format"
      ],
      "additionalProperties": false
    }
  }
}

Response

All status codes

200JSONL attachment (X-Export-Count / X-Export-Format headers).
400(no description)
401(no description)
403FORBIDDEN — source does not belong to this project.
404NOT_FOUND / EMPTY_EXPORT — project/source not found or no data matched filters.
429(no description)

Code samples

cURL

curl -X POST \
  https://evalguard.ai/api/v1/exports/fine-tune \
  -H "Authorization: Bearer $EVALGUARD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "projectId": "00000000-0000-0000-0000-000000000000", "format": "openai", "datasetId": "00000000-0000-0000-0000-000000000000", "evalRunId": "00000000-0000-0000-0000-000000000000", "filters": { "minScore": 0, "maxScore": 0, "passedOnly": false, "tags": [ "string" ] } }'

TypeScript

import { EvalGuard } from "@evalguard/sdk";

const client = new EvalGuard({ apiKey: process.env.EVALGUARD_API_KEY });

const response = await client.request({
  method: "POST",
  path: "/api/v1/exports/fine-tune",
  body: {
    "projectId": "00000000-0000-0000-0000-000000000000",
    "format": "openai",
    "datasetId": "00000000-0000-0000-0000-000000000000",
    "evalRunId": "00000000-0000-0000-0000-000000000000",
    "filters": {
      "minScore": 0,
      "maxScore": 0,
      "passedOnly": false,
      "tags": [
        "string"
      ]
    }
  },
});
console.log(response);

Python

from evalguard import EvalGuard
import os

client = EvalGuard(api_key=os.environ["EVALGUARD_API_KEY"])

response = client.request(
    method="POST",
    path="/api/v1/exports/fine-tune",
    body={
    "projectId": "00000000-0000-0000-0000-000000000000",
    "format": "openai",
    "datasetId": "00000000-0000-0000-0000-000000000000",
    "evalRunId": "00000000-0000-0000-0000-000000000000",
    "filters": {
        "minScore": 0,
        "maxScore": 0,
        "passedOnly": False,
        "tags": [
            "string"
        ]
    }
},
)
print(response)

Go

package main

import (
	"context"
	"fmt"
	"net/http"
	"os"
	"strings"
)

func main() {
	body := strings.NewReader(`{"projectId":"00000000-0000-0000-0000-000000000000","format":"openai","datasetId":"00000000-0000-0000-0000-000000000000","evalRunId":"00000000-0000-0000-0000-000000000000","filters":{"minScore":0,"maxScore":0,"passedOnly":false,"tags":["string"]}}`)
	req, _ := http.NewRequestWithContext(context.Background(), "POST", "https://evalguard.ai/api/v1/exports/fine-tune", body)
	req.Header.Set("Authorization", "Bearer "+os.Getenv("EVALGUARD_API_KEY"))
	req.Header.Set("Content-Type", "application/json")
	resp, err := http.DefaultClient.Do(req)
	if err != nil { panic(err) }
	defer resp.Body.Close()
	fmt.Println(resp.Status)
}

Errors

400401403404429

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