POST
/api/v1/exports/fine-tuneExport 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/settings/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)
500Internal Server Error — DB_ERROR.
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
// The TypeScript SDK (@evalguard/sdk) exposes TYPED methods — runEval,
// getEval, runSecurityScan, checkFirewall, … — not a generic request().
// For an arbitrary endpoint, call it directly:
const res = await fetch("https://evalguard.ai/api/v1/exports/fine-tune", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.EVALGUARD_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"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(res.status, await res.json());Python
# The Python SDK (pip install evalguardai) exposes TYPED methods on
# EvalGuardClient — run_eval, get_eval, … — not a generic request().
# For an arbitrary endpoint, call it directly:
import os
import requests
headers = {"Authorization": f"Bearer {os.environ['EVALGUARD_API_KEY']}"}
headers["Content-Type"] = "application/json"
response = requests.request(
"POST",
"https://evalguard.ai/api/v1/exports/fine-tune",
headers=headers,
json={
"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.status_code, response.json())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
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