turoeducate-biobank 0.1.0

CLI and Python SDK for the TuroEducate Biobank — query specimens, build cohorts, and chat with Turo from the terminal.

turoeducate-biobank

Programmatic access to the TuroEducate Biobank — a CLI plus a Python SDK for querying specimens, building cohorts, exporting CSV, and chatting with Turo (the biobank assistant) from your terminal or scripts.

$ pip install turoeducate-biobank
$ biobank login
$ biobank specimens list -f "Stain Types contains Ki-67" -f "Diagnosis Category eq Breast"
$ biobank ai

Built for pathology research workflows. Currently in beta.

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Install

pip install turoeducate-biobank

Python ≥ 3.10. Installs a biobank command + the turoeducate_biobank Python package.

Auth

biobank login

login walks you through host + email + password, then mints a long-lived API token (bb_live_…) and stores it under ~/.config/turoeducate-biobank/credentials.json at 0600.

You can also point at a backend with environment variables (CI-friendly):

export TUROEDUCATE_BIOBANK_HOST=https://app.turoeducate.com
export TUROEDUCATE_BIOBANK_TOKEN=bb_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Token scopes

biobank tokens create --name ci-readonly --scope read --expires-in-days 30
biobank tokens list
biobank tokens revoke <id>

Scopes are read, write, admin. A read token can list/get/search/export but can't mint new tokens or modify data.

CLI cookbook

Schema

biobank schema

Lists every field in your org's biobank schema, with type + enum choices + which fields are part of the keyword-search index.

Specimens

# list with filters (multi-field)
biobank specimens list \
  -f "Gender eq female" \
  -f "Age at Collection between 40,70" \
  -f "Stain Types contains Ki-67"

# fetch one
biobank specimens get <specimen-id>

# keyword search
biobank specimens search "MMR-deficient"

# export the matching cohort to CSV
biobank specimens export \
  -f "Diagnosis Category eq Breast" \
  -f "Report Date between 2026-04-01,2026-04-30" \
  -o breast-april.csv

Filter mini-DSL

field op value — ops: eq ne gt gte lt lte in contains between.

• in and between take comma-separated values: --filter "Diagnosis Category in Breast,GI", --filter "Age between 40,60".
• Field names that contain spaces (e.g. Stain Types) are fine — the parser matches the rightmost op token.

Cohorts

biobank cohorts list
biobank cohorts create --name "Breast Ki-67" \
  -f "Diagnosis Category eq Breast" \
  -f "Stain Types contains Ki-67"
biobank cohorts apply <cohort-id>          # show matching specimens
biobank cohorts apply <cohort-id> --json
biobank cohorts delete <cohort-id>

# export a saved cohort
biobank specimens export --cohort <cohort-id> -o cohort.csv

Slides

biobank slides list <specimen-id>

Notes

biobank notes list <specimen-id>
biobank notes add  <specimen-id> "needs re-cut for IHC panel"
biobank notes delete <note-id>

Chat (one-shot)

biobank chat ask "histogram of TAT days by diagnosis category"
biobank chat ask "now only the breast cases" --thread-id <id>
biobank chat threads list
biobank chat threads delete <id>

Interactive AI mode

biobank ai

A REPL with rich Markdown rendering, dim-cyan tool-use chips, inline chart summaries, and slash commands:

Command	What it does
/threads	list saved chats
/open <id-prefix>	switch to a chat (resumes its filters)
/new	start a fresh thread
/cohort	show the active filter context
/clear	clear the cohort context
/save <name>	persist the current filters as a named cohort
/export	write the current cohort to ./cohort.csv
/help	print all slash commands
/exit	leave (Ctrl+D works too)

Each turn carries the cohort context so multi-turn narrowing works the same as in the web app:

you »  describe the cohort by age and grade
→ filter_specimens(filters=[1 clauses])
→ aggregate(metric=count, group_by=Grade, chart_type=bar)
[Markdown summary + ASCII bar chart]

you  [3 filters] »  now only her2 positive
→ filter_specimens(filters=[3 clauses])
[narrowed cohort + chart]

Self-check

biobank validate

Verifies auth + schema fetch + a single specimen read.

Python SDK

from turoeducate_biobank import BiobankClient

client = BiobankClient.from_env()                # uses env vars
# or
client = BiobankClient(host="https://app.turoeducate.com",
                       token="bb_live_xxxxxxxx…")

# Browse
schema = client.schema()
for spec in client.specimens.iter_all(filters=[
    {"field": "Stain Types", "op": "contains", "value": "Ki-67"},
    {"field": "Diagnosis Category", "op": "eq", "value": "Breast"},
]):
    print(spec.slide_id_value, spec.metadata.get("Test Code"))

# Save a cohort
ch = client.cohorts.create(
    name="Breast Ki-67",
    filters=[
        {"field": "Stain Types", "op": "contains", "value": "Ki-67"},
        {"field": "Diagnosis Category", "op": "eq", "value": "Breast"},
    ],
)
print(ch.matching_count, "matching")

# Ask Turo programmatically
turn = client.chat.send("describe this cohort", cohort_filters=[
    {"field": "Diagnosis Category", "op": "eq", "value": "Breast"},
])
for m in turn.new_messages:
    if m.role == "assistant":
        for block in m.content:
            if block.get("type") == "text":
                print(block["text"])

Config locations

Path	Purpose
~/.config/turoeducate-biobank/credentials.json	host + API token
~/.config/turoeducate-biobank/history/ai.history	biobank ai REPL history

Override the root with TUROEDUCATE_BIOBANK_HOME=/some/dir.

Versioning + changelog

Semver. Breaking CLI/SDK changes only on a major bump. See the project root CHANGELOG.md.

License

Proprietary — © Turocrates AI.