The Python client for the Pipelex hosted API.
pipelex-sdk is the Python counterpart of @pipelex/sdk, exactly as mthds (the mthds-python package) is the Python counterpart of the mthds npm package. It is the hosted superset: the five normative MTHDS Protocol routes (inherited from mthds) plus the durable run lifecycle plus the Pipelex product surface (methods, organizations, billing, API keys, onboarding, storage, run records).
One-way dependency: pipelex-sdk → mthds.
pip install pipelex-sdkThe API key resolves, in order: explicit api_key argument → PIPELEX_API_KEY → anonymous. The token is optional — anonymous access works against the protocol routes (e.g. a local bare runner); the product routes return 401.
The base URL resolves, in order: explicit base_url argument → PIPELEX_BASE_URL → the hosted default https://api.pipelex.com. The base URL is host-only (no path/query/fragment); every endpoint composes as {base}/v1/{endpoint}.
The SDK never reads the mthds resolver (MTHDS_API_KEY / MTHDS_BASE_URL / ~/.mthds/config) — those settings configure the vendor-neutral mthds tooling and whichever runner it targets, not this Pipelex client.
request_timeout_seconds (constructor argument, default 20 min) sets the per-instance blocking-execute ceiling the inherited protocol routes (execute / start / validate / models / version) use.
app_info (constructor argument, an AppInfo from pipelex_sdk.user_agent) puts your application's name in front of the SDK's own tokens in the User-Agent that every request carries — acme-invoicer/1.4.0 pipelex-sdk-python/0.11.0 mthds-python/0.15.0 python/3.12.4 (linux; x86_64) — which the platform uses to attribute traffic in its analytics. The header follows the workspace spec docs/specs/client-identification.md; see docs/client-identification.md.
The client is async-only (httpx AsyncClient) and is an async context manager.
from pipelex_sdk.client import PipelexAPIClient
from pipelex_sdk.validation_models import VALIDATION_VIEW_INPUT_FORM
async def main() -> None:
async with PipelexAPIClient() as client:
# 1. Validate an MTHDS bundle. The verdict is always returned (never raised):
# a 200 discriminated on `is_valid`, carrying `rendered_markdown`.
# Structured views are opt-in: asking for `input_form` here is what populates
# `report.input_form` (the per-pipe input-form descriptors); omit `views` and the
# request body carries no `views` key at all.
report = await client.validate([bundle_text], views=[VALIDATION_VIEW_INPUT_FORM])
print(report.rendered_markdown)
if not report.is_valid:
return
# 2. Run a method end-to-end. `start_and_wait` self-heals across runner kinds:
# durable start+poll on the hosted API, blocking execute on a bare runner.
result = await client.start_and_wait(
pipe_code="my_pipe",
inputs={"topic": "quantum computing"},
)
# 3. Read the output. Every completed run delivers a resolved `main_stuff`
# (the full working memory also rides `pipe_output` on the blocking path).
print(result.main_stuff)A method reaches every method-taking call in exactly one of three forms: inline source, a method_ref address (github.com/<owner>/<repo>[/<selector>][@<tag>], resolved by the server — pipelex-api >= 0.21.0; on api.pipelex.com availability follows the platform deploy that forwards it), or a hosted method_id (mt_…, resolved by the platform). A method_ref pairs with nothing — it is a complete run source — and its runs carry typed provenance:
ack = await client.start(method_ref="github.com/Pipelex/methods/documents@v0.1.0", inputs={...})
print(ack.method_provenance.commit_sha) # the SHA actually fetched — stable even if the tag moves
result = await client.wait_for_result(ack.pipeline_run_id)
# The tooling routes take the same selectors under a strict XOR (exactly one, no pairing):
report = await client.validate(method_ref="github.com/Pipelex/methods/documents@v0.1.0")
report = await client.validate(method_id="mt_123")codegen() projects a method into stamped typed artifacts plus their codegen.lock, and write_codegen_tree writes that response to disk verbatim, so the tree is byte-identical to a local pipelex codegen types run and no pipelex install is needed:
from pathlib import Path
from pipelex_sdk.codegen_writer import write_codegen_tree
from pipelex_sdk.crate_models import CodegenRequest, CodegenValidReport
report = await client.codegen(CodegenRequest(method_ref="github.com/Pipelex/methods/documents@v0.1.0", target="python-pydantic"))
if not isinstance(report, CodegenValidReport):
raise SystemExit(report.message)
written = write_codegen_tree(report, output_dir=Path("src/generated/documents"))
print(written.written, written.removed)It never overwrites a file codegen does not own, rewrites only what changed, and prunes stamped artifacts that dropped out of the set. Commit the tree; do not run a formatter over it.
run_codegen_check is the writer's counterpart: pure hashing over the tree and its lock, so it boots no engine, reaches no network and needs no API key. Point it at the directory you generated into:
from pathlib import Path
from pipelex_sdk.codegen_check import run_codegen_check
report = run_codegen_check(root=Path("src/generated/documents"))
if not report.is_current:
for drift in report.drifts:
print(f"{drift.path}: {drift.category} — {drift.detail}")
raise SystemExit(1)The drift categories are pipelex codegen check's, and so are the sentences: an artifact edited below its stamp is hand-edited, one off the locked hash is modified, one the lock tracks and disk has lost is missing, and a stamped file the lock does not track is an orphan — the stale-artifact class a per-file stamp cannot catch alone. The two readers reach the same verdict over the same bytes apart from two deliberate divergences, both documented in docs/architecture.md: this one accepts a projection line whose axes are outside its own vocabulary, where the CLI calls such a tree hand-edited, and it refuses a Python artifact that declares a PEP 263 source encoding, where the CLI calls that one current. Regeneration stays a developer action, because it needs the engine; the check is the CI action, because it needs only hashes, so an upstream template improvement never reddens your pipeline. Whether the tree still matches what the method resolves to is a separate question the engine alone can answer — compare report.crate_fingerprint against a live codegen() response to close it.
Behind the hosted gateway, a synchronous execute() is cut off at ~30s and surfaces a PipelineExecuteTimeoutError pointing here. For long methods, drive the durable lifecycle yourself — the run survives client disconnects and is resumable by pipeline_run_id:
ack = await client.start(pipe_code="long_pipe", inputs={...})
result = await client.wait_for_result(ack.pipeline_run_id)A method the plane will not run — a bundle naming a model the deck does not serve, a pipe whose output cannot be assembled — is refused before any result exists: start, execute and start_and_wait raise ApiResponseError on the 422. Its message names the request, gives the reason and, on its own line, the next step the plane advises, so printing the error is already actionable:
API POST /v1/start failed (422): Pipe 'draft_pitch' (PipeLLM), field 'model': Model handle 'gpt-5.1' was not found in the model deck
Did you mean: gpt-5.5, gpt-5.4, gpt-5.6-sol, gpt-5.4-pro, gpt-5.6-luna
Next step: Edit the bundle as each validation error says: apply its suggested fix where it has one, after confirming an unsafe one
A program reads the same thing as fields:
from pipelex_sdk.errors import ApiResponseError
try:
result = await client.start_and_wait(pipe_code="pitch_product", mthds_contents=[bundle])
except ApiResponseError as exc:
if exc.error_domain == "input":
for item in exc.validation_errors or []:
print(f"{item.pipe_code}: {item.message}") # the failing pipe, typed as ValidationErrorItem
if exc.user_action is not None:
print(f"Next step: {exc.user_action.detail}")
raisevalidation_errors is set when the runner itemized its refusal at load; a run that failed during execution carries the pipe in server_message instead (Pipe 'analyze_topics' failed (review_topics → analyze_topics): …).
A run that ends without a result — FAILED, CANCELLED, TERMINATED or TIMED_OUT — makes wait_for_result, start_and_wait and download_artifacts raise RunFailedError. Its message already names the status and the reason (Run finished with status FAILED: <message>), status is the typed RunStatus, and error is the run's stored error report, typed whole as RunErrorReport (pipelex_sdk.error_models): the runner's error_type, message, title, type_uri, error_domain, error_category, retryable, user_action, model, provider, provider_metadata, validation_errors, and anything newer on model_extra. error is None for a run that ended with no report, such as a cancelled one.
from pipelex_sdk.errors import RunFailedError
try:
result = await client.wait_for_result(run_id)
except RunFailedError as exc:
report = exc.error
if report is None:
print(f"Run {exc.run_id} ended {exc.status} without a report.")
else:
print(f"{report.title}: {report.user_action.detail if report.user_action else report.message}")
if report.retryable:
... # the same run may succeed if started againBranch on error_domain (input, config, runtime), type_uri and retryable, never on the wording of message. The report is the runner's verbose one, so message and provider_metadata can hold a model provider's raw text: what a person should see of it is your application's decision. The same report is on RunRead.error when you read the run's status, on RunResultFailed.error from get_run_result, and on PipelineRun.error in the run lists.
Every /v1 route raises a typed ApiResponseError on a non-2xx answer, carrying the members of the RFC 9457 problem document: the protocol routes (execute, start, validate, models, version), the run status and results reads, and the product routes — the account, methods, organization, billing, API-key, onboarding, storage and upload methods, codegen and resolve, and the run records (list_runs, iterate_runs, get_run_detail, update_run). It is mthds's own ApiResponseError narrowed, so except mthds.runners.api.exceptions.ApiResponseError catches it too; health raises PipelineRequestError, and docs/architecture.md lists the error regimes. The branch fields are type_uri, the problem's type, a stable URI naming the error class that every problem carries, and error_domain, the coarse class (input means the caller can fix it, config that a configuration change is needed, runtime that execution failed). error_domain is carried only by the problems the runner renders — a run route's refusal, and those of codegen and resolve, which the hosted API relays from the runner — and is None on the platform's own problems, such as those of the account, billing and API-key routes, which name their class by type_uri alone:
from pipelex_sdk.errors import ApiResponseError
try:
created = await client.create_pipelex_api_key(label="ci")
print(created.api_key) # plaintext — returned only once
except ApiResponseError as exc:
if exc.type_uri == "https://pipelex.com/errors/pipelex_api_key_limit_reached":
print("Per-account key limit reached — revoke an old key first.")
elif exc.type_uri == "https://pipelex.com/errors/validation_failed":
print(f"Fix the request: {exc.server_message}")
else:
print(f"Unexpected failure, request id {exc.request_id}")
raiseOn a problem the runner rendered, branch on error_domain for the class — if exc.error_domain == "input": shows the caller what to fix, whatever the exact error. The rest of the document rides beside them: server_message (the detail), title, instance, retryable, user_action (the mthds UserAction, kept only when it has a kind and a non-empty detail), error_category, the platform's field-level errors, validation_errors for a bundle fault, and request_id for a support request, read from the body or from the X-Request-ID header. The answer itself stays reachable as plain data: status, headers (lower-case names, so exc.headers.get("retry-after") reads a 429's delay) and request_url. code (the platform's closed code, such as conflict) and error_type (the runner's exception class name) are each surface's own finer code — useful for display and support, not the field to branch on. problem is the decoded document whole, for any member the SDK does not name.
There is no barrel import — package __init__.py files stay empty. Import each symbol from its module:
- Client & construction —
from pipelex_sdk.client import PipelexAPIClient, DEFAULT_API_BASE_URL, MthdsFile - Run lifecycle types —
from pipelex_sdk.runs import RunStatus, RunPublic, RunRead, RunResults, RunResultState, WaitForResultOptions, PollInfo - Error reports —
from pipelex_sdk.error_models import RunErrorReport, UserAction, ProviderErrorMetadata, MigrationErrorBlock, FieldError - Product wire models —
from pipelex_sdk.product_models import UserProfile, MethodData, MethodWriteInput, Membership, MembershipsResponse, SubscriptionResponse, PlanView, InvoiceView, OnboardingSubmission, UploadInput, UploadedFile, PipelineRun, ..., with the catalog-source readers beside them:method_source_to_contentsturns a fetchedMethodData.mthdsinto themthds_contentsa run or a validate takes, andMethodFile/parse_method_files/serialize_method_filesare the codec for a method's custom PipeFuncpython. - Validation verdict types —
from pipelex_sdk.validation_models import PipelexValidationResult, PipelexValidationReport, PipelexInvalidReport, ValidationErrorItem, SuggestedFix, VALIDATION_VIEW_INPUT_FORM, ... - Codegen tree —
from pipelex_sdk.codegen_writer import write_codegen_tree, CodegenTreeWriteReportto write one,from pipelex_sdk.codegen_check import run_codegen_check, CodegenCheckReport, CodegenDrift, DriftCategoryto verify one, with the format primitives inpipelex_sdk.codegen_lock(CodegenLock,parse_lock,load_lock,validate_artifact_path, ...) andpipelex_sdk.codegen_stamp(STAMPABLE_SUFFIXES,is_stampable_artifact_path,compute_content_hash,parse_stamped, ...) - Typed errors —
from pipelex_sdk.errors import ApiResponseError, ApiUnreachableError, PipelineExecuteTimeoutError, PagingNotTerminatingError, RunFailedError, RunTimeoutError, RunLifecycleUnavailableError, RunStillRunningError, CodegenError, CodegenLockError, ... - Version —
from pipelex_sdk.version import __version__ - Client identification —
from pipelex_sdk.user_agent import AppInfo, build_user_agent, is_token - Protocol surface (the MTHDS standard's wire types) comes from the
mthdsdependency — e.g.from mthds.protocol.exceptions import PipelineRequestError,from mthds.protocol.models import ValidationResult(the neutral verdict union thatPipelexValidationResultnarrows). - Input-form descriptors and pipe I/O contracts come from
mthdstoo, because they are the standard's artifacts and this SDK only carries them:from mthds.protocol.input_form import InputForm, InputFormField, ListField, TextField, ...andfrom mthds.protocol.pipe_io_contracts import PipeIOContracts, PipeInputContract, PresenceMarker, IOMultiplicity, ....PipelexValidationReport.input_formand.pipe_io_contractsare typed with them, so a node narrows on itskindand a slot's presence and multiplicity read as enums — butpipelex_sdkdoes not re-export the vocabulary, and importing it from here is the one supported path.
make install # create the venv and install all extras
make agent-check # fix-imports + format + lint + pyright + mypy
make agent-test # run the test suite quietly (prints only on failure)
make check # full gate: agent-check aggregate + unused-imports + pylintSee CLAUDE.md for the coding standards and docs/architecture.md for the design (including the parity map against @pipelex/sdk).
MIT — see LICENSE.