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September 20: Paid subscription plans; support for custom observed entities & Azure OpenAI GPT-4

New Features

  • 🔥
    Graphlit now supports paid Hobby, Starter and Growth tiers for projects, in addition to the existing Free tier. Starting at $49/mo, plus $0.10/credit for usage, we now support higher quota based on your subscribed tier. By providing a payment method for your organization in the Developer Portal, you can upgrade each project individually to the tier that fits your application's needs.
  • 💡
    Added GraphQL mutations for the creation, update and deletion of observed entities (i.e. Person, Organization, Place, Product, Event, Label, Category).
  • 💡
    Added new observed entity types to knowledge graph: Repo (i.e. Git repo), Software.
  • 💡
    Added searchType and numberSimilar fields to Specification object for configuring semantic search in conversations. In situations where the user prompt is limited in length, HYBRID search type can provide better semantic search results for the prompt context.
  • 💡
    Added support for the Azure OpenAI GPT-4 model.
  • Added support for project quota field. Project quotas are based on the subscribed pricing tier. Quota limits are now applied as content is ingested, and as feeds and conversations are created.
  • Added contentLimit to conversation strategy object to limit the number of semantic search content results which are formatted into prompt context.
  • Better relevance ranking on semantic search results when formatting prompt context in conversations.
  • ℹ️
    Free tier has updated quota: 1GB storage, 100 contents, 3 feeds and 10 conversations.
  • Now using the Deepgram Nova-2 audio transcription model, which is 18% more accurate, and 5-40x faster.

Bugs Fixed

  • GPLA-1373: Failed to extract multiple text pages from DOCX without page breaks. Now we support token-aware page chunking.
  • GPLA-1377: Failed during semantic search with no content results, when prompting conversation.
  • GPLA-1415: Failed when user prompt couldn't generate text embeddings.