Bystro Think Python API
The Think SDK submits durable agent workloads, streams visible output and structured progress, handles human-input pauses, uploads large files in chunks, reuses Bystro datasets and conversations as context, and downloads protected results.
Install
Bystro 2.1.2 supports CPython 3.11 and 3.12:
python --version
python -m pip install "bystro>=2.1.2,<2.2"
Production uses publicly trusted HTTPS certificates. Customers do not need a custom CA bundle or TLS override; those are only for local development servers using a private certificate authority.
Authenticate once, then use the cached login
Use getpass for the one-time interactive login so secrets do not appear in
source code, notebook output, shell history, or environment listings:
from getpass import getpass
from bystro.api import auth
email = input("Bystro email: ").strip()
site_access_code = getpass("Site access code (leave blank if not required): ")
auth.login(
email,
getpass("Bystro password: "),
site_access_code=site_access_code or None,
)
The login JWT is stored in ~/.bystro/bystro_authentication_token.json; the
directory is mode 0700 and the atomically replaced file is mode 0600. The
site-access code is used only for that login session and is not cached.
Normal scripts then use the cached login without handling a password:
from bystro.think import ThinkClient
client = ThinkClient.from_cached_login()
New accounts must accept the current legal assertions once. Use
LegalConsent.accepted(name) with auth.signup(...), or complete signup in the
dashboard before running the login snippet above.
Canonical interactive workflow
This is the recommended customer experience. It prints lifecycle changes,
backend-owned phases such as web search and source verification, visible answer
chunks, and an elapsed heartbeat if no server frame arrives for 30 seconds.
interact() prompts for any number of clarification or plan-review pauses.
from bystro.think import NeedsInput, RunResult, ThinkClient, show_progress
with ThinkClient.from_cached_login(on_event=show_progress) as client:
run = client.submit_with_progress(
"Research the latest CAR-T therapies and cite primary sources."
)
outcome = run.interact(timeout=3600)
if isinstance(outcome, NeedsInput):
# interact() handles clarification and plan-review pauses itself.
# A returned NeedsInput is a billing pause that must be resolved in
# the dashboard, followed by run.refresh(). Unlimited accounts should
# not enter this branch.
print(outcome)
else:
assert isinstance(outcome, RunResult)
print("\nFinal Markdown is also available as outcome.output")
submit_with_progress() installs a progress renderer automatically. Supplying
show_progress on the client also includes connection and reconnect events.
Do not pass the same callback again to run.wait(on_event=...).
Think uses authenticated Socket.IO transport. It normally upgrades to WebSocket and retains HTTP polling as a compatibility fallback. Output frames are cumulative short snapshots, not necessarily one event per tokenizer token; the SDK turns them into exact append/replace/retract updates and never exposes internal reasoning text.
To require native WebSocket and fail rather than fall back to polling:
with ThinkClient.from_cached_login(
on_event=show_progress,
transports=("websocket",),
) as client:
result = client.submit_with_progress("Draw a duck.").interact(timeout=3600)
Non-interactive input callbacks
Applications can answer pauses without calling input(). Manual wait() and
respond() remain available when the application needs complete control.
from bystro.think import NeedsInput, ThinkClient
def answer_clarification(request: NeedsInput) -> str:
print("Clarification:", request.prompt)
return "Cover all disease areas and the last 24 months."
def review_plan(request: NeedsInput) -> str:
print("Proposed plan:", request.prompt)
return "accept"
with ThinkClient.from_cached_login() as client:
run = client.submit_with_progress("Research recent CAR-T therapies.")
result = run.interact(
timeout=3600,
on_clarification=answer_clarification,
on_plan_review=review_plan,
)
For manual control:
from bystro.think import InputKind, NeedsInput
outcome = run.wait(timeout=3600)
if isinstance(outcome, NeedsInput):
if outcome.kind is InputKind.PLAN_REVIEW:
run.respond("accept")
elif outcome.kind is InputKind.CLARIFICATION:
run.respond("Use case_control as the phenotype column")
The first live pause can precede its durable checkpoint commit. respond()
waits for the checkpoint replay before uploading attachments or dispatching the
answer, and ignores stale replayed checkpoints after reconnect.
Choose a mode
The default mode is base. Pass RunOptions per submitted conversation:
from bystro.think import RunOptions
run = client.submit_with_progress(
"Research the latest CAR-T therapies and cite primary sources.",
options=RunOptions(mode="plus2"),
)
| Value | Dashboard name | Intended use |
|---|---|---|
base |
Base | Faster, token-efficient work with lighter research. |
plus |
Plus v1 | Verified analysis with deep research. |
plus2 |
Plus v2 | Stronger experimental research workflow. |
phd |
PhD | Deepest reasoning for demanding analyses. |
Other controls are typed fields on RunOptions: advanced_planning,
auto_compact, fast, verify, verify_sources, and
zero_data_retention. Availability and billing follow the authenticated
account and deployment configuration.
Submit files with the question
A path passed in files is uploaded to the authenticated user's personal
artifacts and attached to the same message. Large inputs use resumable bounded
10 MiB chunks, SHA-256 checksums, idempotent retries, and asynchronous
finalization polling.
from bystro.think import ThinkClient, UploadProgress
def upload_progress(progress: UploadProgress) -> None:
print(
f"[upload:{progress.phase.value}] {progress.fraction:.0%}",
flush=True,
)
with ThinkClient.from_cached_login() as client:
run = client.submit_with_progress(
"Analyze the cohort using the attached phenotype table.",
files=["cohort.vcf.gz", "phenotypes.tsv"],
on_upload_progress=upload_progress,
)
result = run.interact(timeout=3600)
A single path can be passed directly:
run = client.submit_with_progress(
"Summarize this study protocol.",
files="protocol.pdf",
)
Create a reusable artifact before submission with upload_artifact() (or its
short alias upload()):
artifact = client.upload_artifact(
"cohort.vcf.gz",
artifact_path="study/cohort.vcf.gz",
on_progress=upload_progress,
)
run = client.submit_with_progress("Run QC on this cohort.", files=[artifact])
Artifact paths are relative, have at most 64 components, and must end with the local file's exact name. Invalid paths fail locally before upload.
Compose genetic, conversation, and artifact context
The context helpers accept either a string or an immutable
MessageWithContext, so they compose without constructing XML manually. The
SDK serializes an escaped XML preview with message.to_xml(), while the live
request keeps ownership-bearing references in structured metadata.
from bystro.think import (
add_artifact_context,
add_genetic_context,
add_previous_conversation_context,
)
message = "Re-evaluate the strongest phenotype associations."
message = add_genetic_context(
"annotation-job-id",
message,
name="Case cohort",
assembly="hg38",
)
message = add_previous_conversation_context(
"prior-thread-id",
message,
name="Earlier analysis",
)
message = add_artifact_context(artifact, message)
run = client.submit_with_progress(message)
Reusable higher-order transforms are available:
from bystro.think import (
artifact_context,
compose_context,
genetic_context,
previous_conversation_context,
)
study_context = compose_context(
genetic_context("annotation-job-id", assembly="hg38"),
previous_conversation_context("prior-thread-id"),
artifact_context("existing-artifact-id"),
)
run = client.submit_with_progress(
study_context("Compare the strongest signals.")
)
Think resolves every dataset, conversation, and artifact under the authenticated user's ownership. User-authored XML is never an authorization boundary.
Structured progress and custom presentation
ThinkEvent.progress contains the server's current phase snapshot. Typical
phase kinds are search, verify, compute, query, and think.
ThinkEvent.stream_update contains safe visible-output deltas.
from bystro.think import EventKind, ThinkEvent
def on_event(event: ThinkEvent) -> None:
if event.progress is not None:
phase = event.progress.active_phase
if phase is not None:
print(phase.kind, phase.label, phase.completed, phase.total)
return
update = event.stream_update
if event.kind is EventKind.STREAM and update is not None:
if update.operation == "append":
print(update.delta, end="", flush=True)
elif update.operation == "replace":
print("\n[corrected output]\n", update.delta)
elif update.operation == "retract":
print(f"\n[removed message {update.message_id}]")
ProgressRenderer(heartbeat_interval=30) provides the canonical terminal
presentation. Generic Thinking... and Processing... states print at most
once per turn; meaningful phase/count changes print immediately; and the renderer emits
Still working... (… elapsed) during complete transport silence. Heartbeat
workers stop on input, completion, failure, cancellation, or local detach.
Results, conversations, and downloads
Generated files are available directly on a successful RunResult. The
listing is authenticated and loaded once, on first access, so access it while
the client context is open:
from pathlib import Path
from bystro.think import RunResult, ThinkClient
with ThinkClient.from_cached_login() as client:
run = client.submit_with_progress("Draw and save a cartoon duck.")
result = run.interact(timeout=3600)
if not isinstance(result, RunResult):
raise RuntimeError("The run paused for billing")
for output_file in result.files: # result.artifacts is the same tuple
print(output_file.path, output_file.size)
if result.files:
first = run.download_file(
result.files[0],
Path("downloads") / result.files[0].path,
)
print("Downloaded:", first)
archive = run.download_all(Path("downloads") / f"{run.id}.tar")
print("Archive:", archive)
download_file() and download_all() stream to a temporary file and publish
the destination only after the authenticated download completes. Existing
targets are never replaced unless overwrite=True is explicit.
List and resume past conversations:
conversations = client.list_conversations(search="CAR-T", limit=20)
for conversation in conversations:
print(conversation.id, conversation.name, conversation.created_at)
previous = client.resume(conversations[0].id)
print(previous.messages)
print(previous.output_files())
Omit limit to traverse all cursor pages. run.messages excludes internal
reasoning and progress-card messages; run.history is bounded SDK event
history. A resumed run restores its submitted mode and other RunOptions, so
run.follow_up(...) continues with the original settings.
In Jupyter, RunResult and NeedsInput implement _repr_markdown_(), so
placing either object at the end of a cell renders its Markdown naturally.
Cancellation, detach, and reconnect
Cancellation is distinct from closing a local client:
from bystro.think import RunCancelledError
run.cancel(timeout=60) # waits for durable server cleanup to be released
try:
run.wait()
except RunCancelledError:
print("Cancelled")
cancel() sends the active task ID when available, ignores delayed lifecycle
events from older tasks, and reissues an interrupted stop after reconnect until
the server emits its durable release event.
Use run.detach() (or close the ThinkClient) to disconnect locally while the
server keeps working. Reattach from another process later:
run_id = run.id
run.detach()
with ThinkClient.from_cached_login() as client:
resumed = client.resume(run_id)
outcome = resumed.wait(timeout=3600)
A ThinkClient owns one foreground conversation at a time. Use separate
clients for concurrently controlled conversations.
Async applications
The submission API is synchronous; the live event iterator and terminal wait also have event-loop-friendly async forms:
import asyncio
from bystro.think import ThinkClient
async def main() -> None:
with ThinkClient.from_cached_login() as client:
run = client.submit("Research recent CAR-T approvals.")
async for event in run.aevents(timeout=3600):
print(event.kind.value)
result = await run.await_result(timeout=30)
print(result)
asyncio.run(main())
aevents() never blocks the event loop while waiting for Socket.IO events;
durable refreshes run outside the loop.
Cloudflare configuration
No Cloudflare change is needed when the installed SDK connects, uploads, and downloads successfully. If browser-only challenges intercept Python traffic, create a zone-level custom rule with action Skip and match only the API hosts/routes used by the SDK. Select only:
- All Super Bot Fight Mode rules
- Browser Integrity Check
- Security Level
Keep Log matching requests enabled. Do not select all remaining custom rules, rate limiting rules, or managed WAF rules unless a specific logged false positive proves one of those components is responsible. Cloudflare documents that Skip can target these products independently, leaving other security layers active: Skip action and available skip options.
For ai.bystro.cloud, the complete SDK transport surface is:
/auth/cookie
/set-session-cookie
/ws/socket.io
/project/threads
/user/files/*
/api/user-output/*
For bystro.cloud, one-time programmatic login uses:
/api/site-gate/authenticate
/api/user/auth/local
If customers also need to discover existing genetic-analysis jobs with
bystro.api.annotation.get_jobs, include the narrow /api/jobs* path prefix
on bystro.cloud. This route is optional when the caller already knows the
genetic job ID. It remains protected by Bystro authentication and authorization;
the Cloudflare rule skips only the selected browser-oriented checks.
Keep the route expression narrow rather than bypassing by user agent or a shared customer token. Application authentication and ownership checks still run at the origin, while Cloudflare DDoS protection, managed WAF, and rate limits remain available.
An easy verification is to install the wheel in a clean environment, unset
REQUESTS_CA_BUNDLE and SSL_CERT_FILE, require
transports=("websocket",), submit a small run, list conversations, upload a
file larger than 10 MiB, and download one result plus the tar archive. A
Cloudflare HTML challenge or cf-ray 403 indicates the route rule still does
not match; a typed JSON/application error means the request reached Bystro.
Errors
Transport, HTTP, authentication, billing, admission, cancellation, timeout, and
protocol failures have typed exceptions under bystro.think. In particular:
ThinkAuthenticationError: cached dashboard login is missing or expired.ThinkBillingRequiredError: initial admission requires plan/credit action.RunRejectedError: submission was rejected before dispatch.RunTimeoutError: a local wait deadline elapsed; the durable run may continue.RunCancelledError: server-side cancellation completed.RunProtocolError: the server returned contradictory or incomplete state.
Closing a client never implies cancellation.
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