Install sphinx_learn, submit your first documents with .fit, and follow the ingest job in Sphinx.
Use this quickstart to submit a document to your Sphinx knowledge base with .fit and open the resulting ingest job. The example supplies its own text, so you do not need a local document to get started.
Set SPHINX_API_KEY and SPHINX_PROJECT_ID in your environment, then run:
import osfrom sphinx_ai import File, createKnowledgeBaseClientknowledge_base = createKnowledgeBaseClient( api_key=os.environ["SPHINX_API_KEY"], project_id=os.environ["SPHINX_PROJECT_ID"],)ingestion = knowledge_base.fit( prompt=( "Learn a knowledge graph that helps us understand how metrics are defined at our company." ), docs=[ File( path="metrics/active-customers.txt", content=( "An active customer is an account with at least one paid order " "in the last 30 days. Exclude test accounts and canceled orders." ).encode("utf-8"), ), ],)print(ingestion.job_url())
File(...) validates each document’s path and content immediately. .fit(...) checks the prompt and batch limits before uploading. See input constraints when preparing your own documents.The script prints a URL with this structure:
Open the URL to check the job’s progress and results. The prompt tells the ingest job what you want to do with the documents; it is not a guarantee of a particular output.
.fit returns after uploading the documents and submitting the job. Ingestion continues separately. Check the job in Sphinx to confirm it completed successfully and review the results.
See Using .fit library for the API reference, supported formats, exact input limits, and failure handling.
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