Read, build, inspect

GenAI Studio capability guides

Seven detailed implementation guides: what each GenAI Studio capability does, how to call it, and how to verify its output.

Prepared September 14, 2026 · SDK source reviewed at c9e8b34 · Examples are teaching adaptations; authenticated gateway calls were not run for these pages.

Guide library

Choose the next capability to understand

Start with the knowledge-base walkthrough to learn how to upload documents, verify indexing, and query a reference collection. The other guides cover the neighboring capabilities that turn model access into a reviewable application.

For a new implementation, use this order: access → structured extraction → reference ingestion → retrieval → exact tools → evaluation → interface. Evaluate the examples against the quality criteria for your own application.

Use a small complete example. Carry one synthetic case through the stages, retain its evidence, and show the result to a reviewer. Add more tools only when the next experiment needs them.
CAPABILITY 01

Model access, chat & conversations

Connect Python to GenAI Studio, compare models, stream drafts, and manage conversation history.

1,177 words · Code examples and source links

CAPABILITY 02

Structured extraction & evidence

Turn résumé text into typed facts, check supporting passages, and preserve human corrections.

1,135 words · Code examples and source links

CAPABILITY 03

Create & use a knowledge base

Upload documents, ingest Markdown bundles, verify indexing, and reuse a saved reference collection.

1,518 words · Code examples and source links

CAPABILITY 04

Retrieval, embeddings & sources

Inspect retrieved passages, understand vector similarity, and choose built-in or custom retrieval.

1,183 words · Code examples and source links

CAPABILITY 05

Tools & database lookups

Expose narrow Python functions for exact crosswalk queries and understand how tool calls execute.

1,240 words · Code examples and source links

CAPABILITY 06

Workflows, tracing & evaluation

Coordinate bounded stages, inspect traces, compare repeated runs, and evaluate model-based review.

1,117 words · Code examples and source links

CAPABILITY 07

Build a Streamlit review interface

Connect a deliberate submit action to GenAI Studio, handle drafts and errors, and plan persistence.

1,196 words · Code examples and source links

What every guide provides

  • A plain-language explanation and a small workflow diagram.
  • Source-checked SDK methods, examples, and setup assumptions.
  • Copyable code with explanations of inputs, outputs, and failure cases.
  • Practical checks for understanding behavior and verifying results.
  • Descriptive resource links with visible full URLs for copying into a console.

How to use the examples

Configure credentials privately and choose currently available models through the access guide. Code blocks are starter scripts or explicitly labelled continuations. The HTML pages do not execute Python or call GenAI Studio. The knowledge-base guide documents a readiness-check mismatch found in the reviewed SDK; it does not silently patch the repository.

Shared records, exact mappings, and reviewer edits belong in deliberate database storage. The reference collection supplies context. Preserve that distinction throughout the application.

Primary resources