public IActionResult ManuallyRequestEnginesLoaded(string owner, string repo)
{
// TODO: Add a threshold for how many repo engine loads are allowed
if (!owner.Equals(_owner, StringComparison.OrdinalIgnoreCase))
{
return(BadRequest($"Only predictions for {_owner} are supported"));
}
var modelHolder = _modelHolderFactory.CreateModelHolder(owner, repo);
if (modelHolder == null)
{
return(BadRequest($"Repo {_owner}/{repo} is not yet configured for label prediction."));
}
if (modelHolder.IsIssueEngineLoaded && (modelHolder.UseIssuesForPrsToo || modelHolder.IsPrEngineLoaded))
{
// queued hosted serrvice: task to only download and load models
Logger.LogInformation("! Checked to see if prediction engines were loaded: {Owner}/{Repo}", _owner, repo);
return(Ok($"Loaded {owner}/{repo}"));
}
return(Ok($"Prediction engines for {owner}/{repo} are still loading."));
}
public async Task <LabelSuggestion> PredictUsingModelsFromStorageQueue(string owner, string repo, int number)
{
if (_regex == null)
{
_regex = new Regex(@"@[a-zA-Z0-9_//-]+");
}
var modelHolder = _modelHolderFactory.CreateModelHolder(owner, repo);
if (modelHolder == null)
{
throw new InvalidOperationException($"Repo {owner}/{repo} is not yet configured for label prediction.");
}
if (!modelHolder.IsIssueEngineLoaded || (!modelHolder.UseIssuesForPrsToo && !modelHolder.IsPrEngineLoaded))
{
throw new InvalidOperationException("load engine before calling predict");
}
var iop = await _gitHubClientWrapper.GetIssue(owner, repo, number);
bool isPr = iop.PullRequest != null;
string body = iop.Body ?? string.Empty;
var userMentions = _regex.Matches(body).Select(x => x.Value).ToArray();
LabelSuggestion labelSuggestion = null;
if (isPr && !_useIssueLabelerForPrsToo)
{
var prModel = await CreatePullRequest(owner, repo, iop.Number, iop.Title, iop.Body, userMentions, iop.User.Login);
labelSuggestion = Predictor.Predict(prModel, _logger, modelHolder);
_logger.LogInformation("predicted with pr model the new way");
_logger.LogInformation(string.Join(",", labelSuggestion.LabelScores.Select(x => x.LabelName)));
return(labelSuggestion);
}
var issueModel = CreateIssue(iop.Number, iop.Title, iop.Body, userMentions, iop.User.Login);
labelSuggestion = Predictor.Predict(issueModel, _logger, modelHolder);
_logger.LogInformation("predicted with issue model the new way");
_logger.LogInformation(string.Join(",", labelSuggestion.LabelScores.Select(x => x.LabelName)));
return(labelSuggestion);
}