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Enterprise Jurassic API family.

Developer
AI21 Labs
Release date
Mar 9, 2023
Parameters
Undisclosed
Corpus size
Undisclosed
License
Proprietary
Context window
128K tokens
Modalities
text

Learn this model

Tutorial tailored to Jurassic-2 Ultra—cost, capabilities, API setup, and production patterns based on this model's specs (not generic copy for every LLM).

Cost & access

Jurassic-2 Ultra is proprietary via AI21 Labs. Typical billing: input + output tokens; ChatGPT-style subscriptions are separate from API access. With a 128K tokens context window, long PDFs or chat histories increase input tokens quickly—trim history or summarize older turns in production.

Functional understanding

  • Enterprise Jurassic API family.
  • Modalities: text · License: Proprietary · Released 2023-03-09.
  • Best-fit workflows for this model:
  • • Drafting, summarization, and structured extraction from long documents.

Technical foundation

  • AI21 Labs reports Undisclosed parameters; training data: Undisclosed.
  • Context: 128K tokens. Open weights: no.
  • Jurassic-2 Ultra is positioned as a general-purpose model in the AI21 Labs lineup.

First API call

Follow AI21 Labs's official SDK for Jurassic-2 Ultra; use model id "jurassic-2-ultra" from their docs.

# See https://example.com/jurassic-2-ultra
# Model id: jurassic-2-ultra

Important technical topics

  • Prompting Jurassic-2 Ultra: be explicit about output format. Weak: "Analyze this." Better: "Return JSON with fields id, total, date for AI21 Labs billing data."
  • Temperature: use 0–0.3 for extraction and compliance on Jurassic-2 Ultra; 0.7–1.0 for brainstorming.
  • Tokens: Jurassic-2 Ultra bills by tokens (~¾ word each). Undisclosed parameters affect capability; your bill is driven by context length and call volume.
  • Context window (128K tokens): everything in one request—system prompt, tools, RAG chunks, and history—must fit. Truncate or summarize when approaching the limit for Jurassic-2 Ultra.

Real enterprise patterns

  • RAG with Jurassic-2 Ultra: retrieve from your vector DB, cite sources in the prompt.
  • Tool calling: define JSON schemas; let Jurassic-2 Ultra request functions, not free-form SQL.
  • Eval suite: regression prompts before each model or prompt change.
  • Cost routing: default to Jurassic-2 Ultra for hard tasks; smaller sibling model for triage.

Production & security

  • Secrets: never commit keys for Jurassic-2 Ultra; use vault + per-environment rotation.
  • PII: mask before inference; log redacted prompts only.
  • Observability: trace id per request; log model=jurassic-2-ultra, tokens in/out, latency.
  • Rate limits: handle AI21 Labs 429/5xx with exponential backoff and circuit breakers.
  • Guardrails: schema-validate JSON; block disallowed topics; cross-check numbers against source docs.

Mini projects with this model

  • Support copilot: Jurassic-2 Ultra drafts replies from KB snippets.
  • Contract clause extractor with human approval.
  • Weekly metrics narrative from SQL + CSV exports.
  • Agent that files expenses from receipt photos (if multimodal).

Suggested stack

  • Language: Python 3.11+
  • LLM: Jurassic-2 Ultra (AI21 Labs official SDK)
  • UI: Streamlit or Next.js for internal tools
  • APIs: FastAPI
  • Vector DB (RAG): Pinecone / Chroma / pgvector

Learning path

  • Python basics
  • HTTP/REST and environment variables
  • AI21 Labs authentication and Jurassic-2 Ultra model id (jurassic-2-ultra)
  • First successful call to Jurassic-2 Ultra
  • Prompt design and JSON / structured outputs
  • RAG
  • Tool use / function calling
  • Evals and regression sets
  • Production deploy + monitoring