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Divinci AI SDK

Fine-tuning & Training Data

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Two cooperating clients turn your existing content into a fine-tuned model:

  • divinci.trainingData synthesizes question/answer pairs from RAG documents or audio transcripts.
  • divinci.fineTune manages the fine-tuning jobs and their files.

Generating training data

Section titled “Generating training data”

Estimate cost first, then generate:

const estimate = await divinci.trainingData.estimateCost(
  "ws_123",
  "RagFile",
  ragFileId,
  { qaPerChunk: 3 },
);
console.log(estimate.costs.totalCostUSD);


const job = await divinci.trainingData.generateFromRag("ws_123", ragFileId, {
  qaPerChunk: 3,
  qualityThreshold: 0.7,
});


// Wait for the async job to finish
const done = await divinci.trainingData.waitFor("ws_123", job._id, {
  onProgress: (j) => console.log(j.progress?.qaPairsGenerated),
});


const pairs = await divinci.trainingData.results("ws_123", job._id);

You can also generate from audio: generateFromAudio("ws_123", audioId, options).

Exporting generated data

Section titled “Exporting generated data”

The same training-data job can flow into fine-tuning, QA suites, or back into RAG:

// → fine-tune file
await divinci.trainingData.exportToFineTune("ws_123", job._id, { approvedOnly: true });


// → QA test suites
await divinci.trainingData.exportToQA("ws_123", job._id, {
  targetSuiteIds: ["suite_a"],
  samplingStrategy: "diverse",
  maxTests: 50,
});


// → a RAG vector (synthesize declarative passages)
await divinci.trainingData.exportToRag("ws_123", job._id, {
  synthesisMode: "auto",
  enableRoundTripFilter: true,
});

Fine-tuning jobs

Section titled “Fine-tuning jobs”
const job = await divinci.fineTune.create({
  workspaceId: "ws_123",
  name: "support-tuned-v1",
  baseModel: "gemini-2.5-flash",
  trainingData: fineTuneFile,
});


await divinci.fineTune.start(job._id);


const status = await divinci.fineTune.status(job._id);
console.log(status.status, status.progress);


await divinci.fineTune.cancel(job._id);

Reusing files across workspaces

Section titled “Reusing files across workspaces”
const result = await divinci.fineTune.copyFilesFrom({
  sourceWhitelabelId: "ws_source",
  // optional: sourceFileIds, copyCachedIds
});
console.log(result.fileIdMap);

Method reference

Section titled “Method reference”
ClientMethods
trainingDataestimateCost, generateFromRag, generateFromAudio, list, get, results, exportToFineTune, exportToQA, exportToRag, cancel, waitFor
fineTunelist, get, create, delete, start, status, cancel, copyFilesFrom, exportFileToQA