क्विकस्टार्ट

msy_dummy_api_key_for_test_mode_12345678

import requests
import os
import time

headers = {
  "Authorization": f"Bearer {os.environ['MESHY_API_KEY']}"
}

# 1. Generate a preview model and get the task ID

generate_preview_request = {
  "mode": "preview",
  "prompt": "a monster mask",
  "should_remesh": True,
}

generate_preview_response = requests.post(
  "https://api.meshy.ai/openapi/v2/text-to-3d",
  headers=headers,
  json=generate_preview_request,
)

generate_preview_response.raise_for_status()

preview_task_id = generate_preview_response.json()["result"]

print("Preview task created. Task ID:", preview_task_id)

# 2. Poll the preview task status until it's finished

preview_task = None

while True:
  preview_task_response = requests.get(
    f"https://api.meshy.ai/openapi/v2/text-to-3d/{preview_task_id}",
    headers=headers,
  )

  preview_task_response.raise_for_status()

  preview_task = preview_task_response.json()

  if preview_task["status"] == "SUCCEEDED":
    print("Preview task finished.")
    break

  print("Preview task status:", preview_task["status"], "| Progress:", preview_task["progress"], "| Retrying in 5 seconds...")
  time.sleep(5)

# 3. Download the preview model in glb format

preview_model_url = preview_task["model_urls"]["glb"]

preview_model_response = requests.get(preview_model_url)
preview_model_response.raise_for_status()

with open("preview_model.glb", "wb") as f:
  f.write(preview_model_response.content)

print("Preview model downloaded.")

# 4. Generate a refined model and get the task ID

generate_refined_request = {
  "mode": "refine",
  "preview_task_id": preview_task_id,
}

generate_refined_response = requests.post(
  "https://api.meshy.ai/openapi/v2/text-to-3d",
  headers=headers,
  json=generate_refined_request,
)

generate_refined_response.raise_for_status()

refined_task_id = generate_refined_response.json()["result"]

print("Refined task created. Task ID:", refined_task_id)

# 5. Poll the refined task status until it's finished

refined_task = None

while True:
  refined_task_response = requests.get(
    f"https://api.meshy.ai/openapi/v2/text-to-3d/{refined_task_id}",
    headers=headers,
  )

  refined_task_response.raise_for_status()

  refined_task = refined_task_response.json()

  if refined_task["status"] == "SUCCEEDED":
    print("Refined task finished.")
    break

  print("Refined task status:", refined_task["status"], "| Progress:", refined_task["progress"], "| Retrying in 5 seconds...")
  time.sleep(5)

# 6. Download the refined model in glb format

refined_model_url = refined_task["model_urls"]["glb"]

refined_model_response = requests.get(refined_model_url)
refined_model_response.raise_for_status()

with open("refined_model.glb", "wb") as f:
  f.write(refined_model_response.content)

print("Refined model downloaded.")

import requests
import os
import time

headers = {
  "Authorization": f"Bearer {os.environ['MESHY_API_KEY']}"
}

# 1. Generate a preview model and get the task ID

generate_preview_request = {
  "mode": "preview",
  "prompt": "a monster mask",
  "should_remesh": True,
}

generate_preview_response = requests.post(
  "https://api.meshy.ai/openapi/v2/text-to-3d",
  headers=headers,
  json=generate_preview_request,
)

generate_preview_response.raise_for_status()

preview_task_id = generate_preview_response.json()["result"]

print("Preview task created. Task ID:", preview_task_id)

# 2. Poll the preview task status until it's finished

preview_task = None

while True:
  preview_task_response = requests.get(
    f"https://api.meshy.ai/openapi/v2/text-to-3d/{preview_task_id}",
    headers=headers,
  )

  preview_task_response.raise_for_status()

  preview_task = preview_task_response.json()

  if preview_task["status"] == "SUCCEEDED":
    print("Preview task finished.")
    break

  print("Preview task status:", preview_task["status"], "| Progress:", preview_task["progress"], "| Retrying in 5 seconds...")
  time.sleep(5)

# 3. Download the preview model in glb format

preview_model_url = preview_task["model_urls"]["glb"]

preview_model_response = requests.get(preview_model_url)
preview_model_response.raise_for_status()

with open("preview_model.glb", "wb") as f:
  f.write(preview_model_response.content)

print("Preview model downloaded.")

# 4. Generate a refined model and get the task ID

generate_refined_request = {
  "mode": "refine",
  "preview_task_id": preview_task_id,
}

generate_refined_response = requests.post(
  "https://api.meshy.ai/openapi/v2/text-to-3d",
  headers=headers,
  json=generate_refined_request,
)

generate_refined_response.raise_for_status()

refined_task_id = generate_refined_response.json()["result"]

print("Refined task created. Task ID:", refined_task_id)

# 5. Poll the refined task status until it's finished

refined_task = None

while True:
  refined_task_response = requests.get(
    f"https://api.meshy.ai/openapi/v2/text-to-3d/{refined_task_id}",
    headers=headers,
  )

  refined_task_response.raise_for_status()

  refined_task = refined_task_response.json()

  if refined_task["status"] == "SUCCEEDED":
    print("Refined task finished.")
    break

  print("Refined task status:", refined_task["status"], "| Progress:", refined_task["progress"], "| Retrying in 5 seconds...")
  time.sleep(5)

# 6. Download the refined model in glb format

refined_model_url = refined_task["model_urls"]["glb"]

refined_model_response = requests.get(refined_model_url)
refined_model_response.raise_for_status()

with open("refined_model.glb", "wb") as f:
  f.write(refined_model_response.content)

print("Refined model downloaded.")

python api_request.py