Large Codebase Indexing Best Practices
For efficient indexing of large code repositories on GitHub (e.g. microsoft/vscode projects), the following process is recommended:
- Choosing the right branch: It is recommended to prioritize the indexing of main/primary branches to ensure code integrity.
- Preparing API requests: Submit JSON requests to the /v2/repositories endpoint using standard HTTP POST methods
Sample request code:
import requests
url = "https://api.trynia.ai/v2/repositories"
headers = {
"Authorization": "Bearer <您的密钥> ",
"Content-Type": "application/json"
}
response = requests.post(
url,
json={"repository":"microsoft/vscode","branch":"main"},
headers=headers
)
Once indexing is complete, the status can be verified via the check_repository_status interface. Large projects take an average of 10-15 minutes.
This answer comes from the articleNia: Intelligent Tools to Help Developers Understand and Manage Code BasesThe
May not be reproduced without permission:AI productivity tools " What preparation is required for Nia AI to index against large codebases?
