Jobs

{
  "run_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "status": "succeeded",
  "created_at": "2025-01-15T10:30:00Z",
  "started_at": "2025-01-15T10:30:02Z",
  "finished_at": "2025-01-15T10:31:14Z",
  "error_code": null,
  "error_message": null,
  "error_detail": null
}

{
  "run_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "status": "failed",
  "created_at": "2025-01-15T10:30:00Z",
  "started_at": "2025-01-15T10:30:02Z",
  "finished_at": "2025-01-15T10:30:08Z",
  "error_code": 50002,
  "error_message": "DATA_FETCH_ERROR",
  "error_detail": "Unable to fetch price data for ticker INVALIDTICKER.NSE"
}

curl https://api.foliolab.ai/jobs/a1b2c3d4-e5f6-7890-abcd-ef1234567890 \
  -H "Authorization: Bearer <YOUR_TOKEN>"

import requests

BASE_URL = "https://api.foliolab.ai"
TOKEN = "<YOUR_TOKEN>"
RUN_ID = "a1b2c3d4-e5f6-7890-abcd-ef1234567890"

headers = {"Authorization": f"Bearer {TOKEN}"}

response = requests.get(f"{BASE_URL}/jobs/{RUN_ID}", headers=headers)
response.raise_for_status()

job = response.json()
print(f"Status: {job['status']}")

if job["status"] == "failed":
    print(f"Error: {job['error_message']} - {job['error_detail']}")

{
  "items": [
    {
      "run_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "status": "succeeded",
      "created_at": "2025-01-15T10:30:00Z",
      "methods": ["MVO", "HRP"],
      "stock_count": 5
    },
    {
      "run_id": "f9e8d7c6-b5a4-3210-fedc-ba9876543210",
      "status": "running",
      "created_at": "2025-01-15T11:00:00Z",
      "methods": ["MinVol"],
      "stock_count": 8
    }
  ],
  "next_cursor": "eyJjIjoiMjAyNS0wMS0xNVQxMDozMDowMFoiLCJpIjoiYTFiMmMzZDQifQ=="
}

# First page
curl "https://api.foliolab.ai/jobs/history?limit=10" \
  -H "Authorization: Bearer <YOUR_TOKEN>"

# Next page (use next_cursor from previous response)
curl "https://api.foliolab.ai/jobs/history?limit=10&cursor=eyJjIjoiMjAyNS0wMS..." \
  -H "Authorization: Bearer <YOUR_TOKEN>"

import requests

BASE_URL = "https://api.foliolab.ai"
TOKEN = "<YOUR_TOKEN>"
headers = {"Authorization": f"Bearer {TOKEN}"}

# Fetch all jobs using cursor-based pagination
all_jobs = []
cursor = None

while True:
    params = {"limit": 20}
    if cursor:
        params["cursor"] = cursor

    resp = requests.get(f"{BASE_URL}/jobs/history", params=params, headers=headers)
    resp.raise_for_status()
    data = resp.json()

    all_jobs.extend(data["items"])
    cursor = data.get("next_cursor")

    if not cursor:
        break

print(f"Total jobs: {len(all_jobs)}")
for job in all_jobs:
    print(f"  {job['run_id'][:8]}...  {job['status']}  ({job['stock_count']} stocks)")

{
  "artifacts": [
    {
      "artifact_id": "art_001",
      "method": "MVO",
      "kind": "returns_dist",
      "label": "MVO Returns Distribution",
      "signed_url": "<presigned-url:art_001 - expires in 1h>",
      "content_type": "image/png"
    },
    {
      "artifact_id": "art_002",
      "method": "MVO",
      "kind": "max_drawdown",
      "label": "MVO Maximum Drawdown",
      "signed_url": "<presigned-url:art_002 - expires in 1h>",
      "content_type": "image/png"
    },
    {
      "artifact_id": "art_global_001",
      "method": null,
      "kind": "covariance_heatmap",
      "label": "Covariance Heatmap",
      "signed_url": "<presigned-url:art_global_001 - expires in 1h>",
      "content_type": "image/png"
    },
    {
      "artifact_id": "art_global_002",
      "method": null,
      "kind": "optimization_report",
      "label": "Optimization Report (Excel)",
      "signed_url": "<presigned-url:art_global_002 - expires in 1h>",
      "content_type": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
    }
  ],
  "data_parquets": {
    "benchmark_returns": "<presigned-url:benchmark_returns - expires in 1h>",
    "cumulative_returns": "<presigned-url:cumulative_returns - expires in 1h>",
    "stock_yearly_returns": "<presigned-url:stock_yearly_returns - expires in 1h>"
  },
  "data_files": {
    "chart_bundle": "<presigned-url:chart_bundle - expires in 1h>"
  }
}

curl https://api.foliolab.ai/jobs/a1b2c3d4-e5f6-7890-abcd-ef1234567890/artifacts \
  -H "Authorization: Bearer <YOUR_TOKEN>"

import requests
import os

BASE_URL = "https://api.foliolab.ai"
TOKEN = "<YOUR_TOKEN>"
RUN_ID = "a1b2c3d4-e5f6-7890-abcd-ef1234567890"

headers = {"Authorization": f"Bearer {TOKEN}"}

# Fetch artifact metadata
resp = requests.get(f"{BASE_URL}/jobs/{RUN_ID}/artifacts", headers=headers)
resp.raise_for_status()
data = resp.json()

# Download each artifact using its signed URL
output_dir = f"./results/{RUN_ID[:8]}"
os.makedirs(output_dir, exist_ok=True)

for artifact in data["artifacts"]:
    ext = "png" if "png" in artifact["content_type"] else "xlsx"
    filename = f"{artifact['kind']}_{artifact['method'] or 'global'}.{ext}"
    filepath = os.path.join(output_dir, filename)

    print(f"Downloading {artifact['label']}...")
    download = requests.get(artifact["signed_url"])
    download.raise_for_status()

    with open(filepath, "wb") as f:
        f.write(download.content)

# Download Parquet data files
for name, url in data["data_parquets"].items():
    filepath = os.path.join(output_dir, f"{name}.parquet")
    print(f"Downloading {name}.parquet...")
    download = requests.get(url)
    with open(filepath, "wb") as f:
        f.write(download.content)

print(f"\nAll artifacts saved to {output_dir}/")