lenz-io

Official Python SDK for the Lenz Fact Checking API for AI Product Teams.

Six API calls: one research-depth ladder, one call that runs it on a whole draft, and the citation check on its own.

• extract — pull verifiable claims out of any text, optionally narrowed with a focus. Free, 1000 calls/account/day (shared across your API keys).
• assess — fast 3-model panel verdict in ~15s. Sync, paid.
• verify — full multi-model pipeline with citations in ~90s. Async, paid.
• citecheck — the citation check on its own: does each source a draft cites say what the draft says? Async.
• ask — follow-up questions grounded on a verification. Sync, paid.
• review — the ladder on a draft in one call, its citations too if asked: issues and rewrites in 2-4 min. Async, paid.

Built for teams whose AI output is async or document-shaped: legal-memo generators, deep-research products, due-diligence platforms, vertical agents producing structured deliverables. Not chat AI, not voice AI, not real-time copilots — pipeline runs are the wrong shape for those.

First call

Get a free API key, with free credits to start, at lenz.io/api-credentials, then:

pip install lenz-io
export LENZ_API_KEY=lenz_...

from lenz_io import Lenz

client = Lenz()  # reads LENZ_API_KEY
row = client.assess(claim="The Great Wall of China is visible from space.").claims[0]
if row.status == "failed":  # no verdict for this row (not charged): failure says why
    print(row.failure.code, row.failure.hint)
else:
    print(row.verdict, row.confidence)  # e.g. False high  (about 15-20 s, 1 credit)

Using asyncio? AsyncLenz has the same methods, awaited (more): async with AsyncLenz() as client: row = (await client.assess(claim=...)).claims[0].

From there: the whole ladder on an LLM answer, a review of a draft, or the command-line tool.

Review a draft

One call runs the whole ladder on a draft: it pulls out the claims, gives each a quick assess verdict, and sends the ones that look wrong or uncertain through the full verify pipeline, up to five by default. It takes two to four minutes and hands back the issues, with suggested rewrites.

from lenz_io import Lenz

client = Lenz(api_key="lenz_...")

draft = """
The EU AI Act entered into force on 1 August 2024, and its obligations for
general-purpose models applied from 2 August 2025. Fines for prohibited
practices reach 7% of global annual turnover. About 40% of European
companies had started compliance work by the end of 2024.
"""

# One call: extract, assess, and verify the doubtful claims (async, 2-4 min)
review = client.review_and_wait(text=draft)
print(review.outcome)  # clean | issues_found | incomplete | unchecked
for i in review.issues:
    print(i.verdict, i.confidence, i.claim)
    if i.suggested_rewrite:
        print("  Suggested rewrite:", i.suggested_rewrite)

# Past the cap: send the remaining claims to /verify in one batch
capped = [{"claim": c.claim} for c in review.claims if c.escalation and c.escalation.disposition == "cap"]
results = client.verify_batch_and_wait(claims=capped) if capped else []

Which claims get the deep check. A claim is deep-checked when its quick verdict is False, Mostly False or Mixed, or its confidence is low, up to five of them. Change the rule with flat keyword arguments:

client.review_and_wait(
    text=draft,
    verdicts=["False", "Mostly False"],  # quick verdicts that get a deep check ([] = none)
    confidence=["low", "medium"],  # confidence bands that get one ([] = none)
    max_verifications=10,  # the deep-check cap (0 = quick checks only)
    max_assessments=20,  # how many of the draft's claims get a quick verdict
    depth="low",  # every deep check at half the credits
)

Reading the result. outcome is the one field to branch on. Each entry in issues is a claim whose final verdict is False, Mostly False or Mixed: source says whether that verdict comes from a deep check (verification, with key_finding, url and verification_id) or from the quick check alone (assessment, with the reviewers' rationale; escalation.disposition says why it was not deep-checked). suggested_rewrite comes from the deep check; an issue that stayed on the quick verdict has one only when the review asked for suggested edits (suggest_edits=True). It is not verified itself: review it, or run it through verify, before you use it. claims lists every claim with both checks; failures lists the ones whose work failed. The top-level types are importable from lenz_io; the nested ones (ReviewAssessment, ReviewVerification, ReviewSummary, …) from lenz_io.models.

Checking the draft's sources. max_citations=N (1-20) also checks the draft's first N citations, its links and DOIs: does each source say what the draft says it does? Links are read from text, so keep a link as a markdown link ([words](https://...)); a Word or Google document pasted as plain text loses them. With max_assessments=0 the review checks the sources and no claim.

review = client.review_and_wait(text=draft, max_citations=20, max_assessments=0)
s = review.summary
print(f"{s.citations_found} found, {s.citations_selected} checked")
for c in review.citation_issues:  # most serious first
    print(c.finding, c.cited_url or c.doi, c.statement)
    if c.snippet:
        print("  The source says:", c.snippet)

finding is one of doi_not_found, page_not_found, contradicted, quote_not_in_source, not_in_source or metadata_mismatch, most serious first. partly_supported (the source backs part of the statement) is reported in citations with its snippet, but it is not an issue: is_issue is false and it is not in citation_issues. citations lists every checked citation with its check; a row that could not be checked says why in check.unchecked_reason and what to do in check.hint, and citation_failures lists the ones that failed on our side. A citation issue makes outcome issues_found even when issues is empty. rationale is a reviewer's note, not a checked source; snippet is the passage from the page. more_claims and more_citations list what the draft holds past max_assessments and max_citations: found, not checked, to send in a later request. Leave max_citations out (or 0) and no citation is checked. Only claims traced directly back to the draft are checked. Each claim row's positions says where the draft makes it (a Position: start/end are code-point offsets into text, so text[start:end] is the passage, and text is the passage itself). For a URL draft start and end are None and text still carries the passage. more_claim_locations does the same for more_claims: one ClaimLocation (claim, positions) per string, same order, None until the draft is read. A citation's position is the same Position, with text None (the row carries the statement).

Suggested edits. suggest_edits=True also returns, for each claim with a suggested rewrite (from its deep check, or from its quick check when it stayed on the quick verdict), the smallest edits to the draft that make it say what the rewrite says, in the draft's own language. They cost no extra credits, and the review completes once they are settled. Each claim row (and its issue) carries suggested_edits: status "pending" or "completed", and edits, each a span of the text you sent (start/end in code points, text the exact slice) and its replacement. edits == [] means no edit could be made safely, or it could not be computed. They are not themselves verified. Two claims that share a passage can return overlapping edits: apply one of them.

Offsets all index the text you sent, so apply every claim's edits together, from the end of the text back:

review = client.review_and_wait(text=draft, suggest_edits=True)
edits = [e for c in review.claims if c.suggested_edits for e in c.suggested_edits.edits or []]
chars = list(draft)  # code points
taken_from = len(chars)
for e in sorted(edits, key=lambda e: e.start, reverse=True):
    if e.end <= taken_from and "".join(chars[e.start : e.end]) == e.text:  # no overlap, draft unchanged
        chars[e.start : e.end] = list(e.replacement)
        taken_from = e.start
edited = "".join(chars)

Waiting. review_and_wait polls on the review's own poll_after_seconds. Pass on_update= to see the quick verdicts as soon as they are in and each deep check as it lands; without it the helper is silent. It raises ReviewFailed when the review fails (review.failure.code and review.failure.hint say why; the exception's error_code keeps its 2.x spelling) and ReviewTimeout after timeout seconds (600 by default); the review keeps running, and the error carries its review_id and the last body read. To submit without waiting, client.review(draft) returns a review_id; read it with client.get_review(review_id), or only the issues with client.get_review(review_id, view="issues").

A runnable version, with the errors handled: examples/core/review_draft.py.

Credits. 1 per claim assessed, plus 10 (5 at depth="low") per deep check, plus 1 per checked citation; review.credits.charged says what the review cost. A resend with the same Idempotency-Key within 24 hours returns the same review; a new key is a new review.

From the terminal. lenz review draft.md prints the quick verdicts as they arrive and rewrites each row as its deep check lands. The exit code is the outcome, for CI: 0 clean, 1 issues found, 2 anything else (incomplete, unchecked, failed, timed out, or an error). --issues prints only the issues, --json the review body, --max-assessments N, --max-verifications N and --depth low set the policy, and --detach prints the review_id for lenz review --resume <id> (and exits 0: it submitted, it did not review). The draft's first 20 sources are checked too (1 credit per checked citation), and their count and their issues print after the claims; a source issue exits 1 like a claim one. --max-citations N checks the first N and --max-citations 0 none, and lenz review draft.md --max-assessments 0 checks the sources and no claim. This default is the CLI's: client.review() checks no citation unless you pass max_citations.

Check a draft's citations

citecheck runs the citation check on its own, without the rest of a review: does each cited source say what the draft says it does? Send a draft (its links are read from the text, as for review) or the statement-source pairs yourself.

check = client.citecheck_and_wait(draft, max_citations=10)
print(check.outcome)  # clean | issues_found | incomplete | unchecked
for c in check.citation_issues:  # most serious first
    print(c.finding, c.cited_url or c.doi, c.statement)

# Pairs: each checked as it is (max_citations does not apply)
check = client.citecheck_and_wait(
    pairs=[
        {
            "statement": "Water boils at 100 degrees Celsius at sea level.",
            "url": "https://en.wikipedia.org/wiki/Boiling_point",
        },
        {
            "statement": "Diamond sensors can measure temperature in a living cell.",
            "doi": "10.1038/nature12373",
            "cited_year": "2013",
        },
    ]
)

The body carries the same rows as a review's: citations, citation_issues, citation_failures, summary and more_citations (the draft's citations past max_citations, found but not checked). client.citecheck(...) returns a citecheck_id at once; read it with client.get_citecheck(citecheck_id). citecheck_and_wait raises CitecheckFailed when the check fails (or is cancelled elsewhere: failure_class cancelled) and CitecheckTimeout after timeout seconds. The citecheck.completed, citecheck.failed and citecheck.cancelled webhooks parse into a CitecheckEvent. A runnable version: examples/core/citecheck_draft.py.

From the terminal: lenz citecheck draft.md (or --pairs pairs.json, a JSON list of pairs) prints the count, the key numbers and each source issue, and exits 0 clean, 1 issues found, 2 anything else.

Command-line tool

The same primitives from your terminal — submit, poll, and read full reports. Ships inside this package behind the cli extra (quotes matter — bare brackets are a glob in zsh):

pipx install "lenz-io[cli]"      # isolated CLI install (recommended)
pip install "lenz-io[cli]"       # or into your current environment

lenz login                       # paste an API key (free — get one at lenz.io/api-credentials)
lenz extract "Einstein won the 1921 Nobel for relativity"   # free, 1000/day
lenz extract "$(cat deck.txt)" --focus "market size"        # only the claims you want
lenz extract "$(cat draft.txt)" --locate                    # where the text makes each claim
lenz assess  "The Great Wall is visible from space"          # fast verdict
lenz assess  "<claim 1>" "<claim 2>" "<claim 3>"              # one call, one verdict per claim (up to 20)
lenz verify  "Water boils at 90C at sea level"               # full pipeline (~90s)
lenz verify  "<claim>" --depth low                          # shallower, faster, half the credits
lenz verify  "<claim>" --json | jq .verdict                 # machine-readable
lenz status  <task_id>           # non-blocking: poll a verify task's progress
lenz show    <verification_id>   # full report — sources, warnings, panel + debate (-c for concise)
lenz ask <verification_id> "Which source is strongest?"
lenz review draft.md             # the whole draft: quick verdicts, deep checks, and up to 20 of its sources
lenz review draft.md --issues    # only the issues
lenz review draft.md --max-citations 0    # claims only, no source checked
lenz review draft.md --max-assessments 0  # only the sources, no claim
lenz citecheck draft.md          # the citation check on its own
lenz citecheck --pairs pairs.json   # statement-source pairs, each checked as it is
lenz usage                       # credits left, what they buy, and when they reset
lenz config                      # show which key/base URL is in use

Every command takes --json for a clean machine-readable object (also emitted automatically when stdout is not a TTY, so pipes Just Work). Errors in --json mode are {"error": {"code", "message", "status"}} on stdout with a nonzero exit (an out-of-credits run reports "code": "no_credits" and adds upgrade_url). lenz usage leads with the balance:

Lenz usage  (Pro plan)
  5070 credits left  (≈ 507 verifications · 5070 assessments)
  Verify:   507 left  (13 / 520 quota + 20 extra · 10 credits each · 5 at depth "low")
  Ask:      5070 left  (130 / 5200 quota + 200 extra · 1 credit each)
  Assess:   5070 left  (130 / 5200 quota + 200 extra · 1 credit each)
  Extract:  4 / 1000 today  (free — no credit charge)
  Credits reset in 3 days (Sep 1, 2026)

verify blocks with a progress spinner; Ctrl-C prints a lenz verify --resume <task_id> handle so a long run isn't lost. Key resolution order is --api-key flag → LENZ_API_KEY → ~/.config/lenz/config.json.

Scripting the lifecycle (no blocking). verify --detach returns a task_id immediately; poll it with status and read the full report with show once it completes:

tid=$(lenz verify "<claim>" --detach --json | jq -r .task_id)
lenz status "$tid" --json | jq -r .status          # processing → completed
lenz show <verification_id> --json                 # full report once done

If the input holds several claims, status reports needs_input and lists them; resolve it non-interactively by index (spawns one verification per pick):

lenz verify --resume "$tid" --claim 1,3 --detach --json   # → spawned task_ids

Quickstart — the canonical integration

from lenz_io import Lenz

client = Lenz(api_key="lenz_...")

# 1. extract — pull verifiable claims out of any text (free)
#    add focus="..." to narrow it to the claims you care about
out = client.extract(text=llm_output)
claims = [c.claim for c in out.claims]

# 2. assess — one call per 20 claims (extract finds up to 100), one row per claim, same order
quick = [row for i in range(0, len(claims), 20) for row in client.assess(claims=claims[i : i + 20]).claims]
for c in quick:
    if c.status == "failed":  # no verdict: failure.code says why, failure.hint what to send next
        print("failed", c.failure.code if c.failure else "", c.claim)
        continue
    print(c.verdict, c.confidence, c.claim)
    if c.rationale:
        print("  ", c.rationale)

# 3. verify — escalate the low-confidence rows to the full panel + citations
# verify_batch_and_wait takes up to 20 claims a call: the first 20 here
doubtful = [{"claim": c.claim} for c in quick if c.status == "completed" and c.confidence == "low"][:20]
results = client.verify_batch_and_wait(claims=doubtful) if doubtful else []
for r in results:
    if r.verification:
        print(r.verification.verdict, r.verification.lenz_score, r.verification.executive_summary)

# 4. ask — follow-up grounded on a verification (when a claim was escalated)
deep = next((r.verification for r in results if r.verification is not None), None)
if deep is not None:
    reply = client.ask.send(deep.verification_id, message="Which source is strongest?")
    print(reply.content)

assess(claims=[...]) takes up to 20 claims per call and always answers with exactly one row per claim, in the order sent. A row that could not be given a verdict comes back in position with status == "failed" and a failure block: failure.code (no_checkable_claim / framing_failed / upstream_unavailable / timeout — an open set; the last two are the ones worth resending as-is) and failure.hint, one sentence on what to send next; it is not charged. A compound item is assessed on its main claim and lists the other claims it found in more_claims — send those as their own items to check the rest. assess(claim="...") takes one text and answers with a row per claim found in it, up to 20, at 1 credit each; a text that makes more claims gets its 20 most check-worthy checked and the rest in more_claims, unchecked and free — send them back as claims, 20 a call.

Each verdict row also carries an optional note. rationale is the reasoning of a reviewer who agrees with the panel's verdict. It is a reviewer's note, not a checked source; for sourced evidence, call verify. Read it as optional: it can be None. (dissent is deprecated: it is always None and is kept only so code that reads it keeps working.)

Suggested rewrite. suggest_rewrite=True also writes, on each row the check found False or Mostly False with high confidence, the claim with its wrong part corrected (suggested_rewrite, else None), at no extra credit. It is not itself verified: review it, or run it through verify, before using it.

row = client.assess(claim="Venus is the closest planet to the Sun.", suggest_rewrite=True).claims[0]
if row.suggested_rewrite:
    print(row.suggested_rewrite)  # e.g. "Mercury is the closest planet to the Sun."

assess and verify share a result cache server-side: if a claim already has a deep verification, assess returns it via verification_url and you can skip the escalation. An answer served from that cache (a claim checked in the last hour) is free, so a tool that resends the same request is not charged twice.

How verification works

Framing → Research → Debate (2 models, 2 rounds) → Panel Review (3 reviewers running the same checks, 2 more when they disagree) → Conclusion. ~90 seconds wall-clock per claim. assess runs a leaner 3-model panel against the same framing for the ~15s pass.

Quickstart demo

from lenz_io import Lenz

client = Lenz(api_key="lenz_...")

v = client.verify_and_wait(claim="Sharks don't get cancer")
print(v.verdict, v.lenz_score)
# False 2

for source in v.sources[:3]:
    print(" -", source.title, source.url)

The demo claim is cached for an hour after anyone verifies it, so it can come back in seconds; otherwise it runs the full pipeline (~90s) like your own claims. Use webhooks for production async flows.

Get your webhook secret here → lenz.io/api-credentials

What you get on the client

• client.extract(text=...) → ExtractedClaims. Free, capped at 1000/account/day. Add focus= to narrow the list — see Steering extract — and locate=True to keep only the claims traced back to your text, with their positions (each out.claims[i].positions). Each attempt waits up to 150s by default (a timeout is retried like any transport error, and the call's idempotency key makes the retry replay the first answer); timeout= overrides it for that call.
• client.assess(claim=...) / client.assess(claims=[...]) → AssessResponse. Sync. One statement (~15s; text= is accepted as an alias: a document is text, a claim is claim) or a list of up to 20 claims in one call (~15s) — exactly one row per claim, in order; rows that got no verdict have status == "failed" and a failure block (failure.code, failure.hint), in position and free. A single text past 20 claims lists the rest in more_claims ([] otherwise). The two forms are mutually exclusive. timeout= overrides the client timeout for that call (both forms default to 100s: a long text can take up to 90s).
• client.verify(...) → TaskAccepted. Async submit; returns a task_id. Get the result by polling (client.wait(...) / client.get_status(...)) or via a webhook.
• client.verify_and_wait(...) → Verification. Submit + poll until the pipeline lands (sync ergonomic). Equivalent to wait(verify(...)).
• client.wait(task) → Verification. Block on a task_id (or a TaskAccepted) until it terminates. The polling counterpart to a webhook.
• client.verify_batch(claims=[...]) → BatchAccepted. Fan-out for multi-claim LLM outputs.
• client.verify_batch_and_wait(claims=[...]) → list[BatchItemResult]. Fan out a batch and poll every item to completion; one result per claim, in input order, never raises on a per-item failure.
• client.ask.{history,send,reset}(verification_id, ...) → Q&A on a verification. reply.content uses a small markdown subset (**bold**, *italic*, - or * bullets, blank-line paragraphs) — render with a minimal markdown library or display verbatim. See docs/quickstart#ask-reply-format.
• client.verifications.{list,iter,get,delete,related}(...) → manage past verifications. iter() walks every page lazily (for item in client.verifications.iter(): ...). All API claims are private; reference them by verification_id. Cache-hit on another customer's claim is transparent — you always see your own verification_id, never another customer's.
• client.library.list(...) / client.library.iter(...) → browse the public catalog (no API key needed); iter walks every page lazily and refuses sort="random", which is not exhaustive.
• client.usage() → the account's credit balance (usage.credits), the price list (usage.costs — verify 10, assess 1, ask 1, extract 0 — plus usage.cost_options for parameter-dependent prices such as depth), and per-capability projections of that one pool (usage.verify.remaining is how many verifications the balance still buys), plus the daily extract rate limit. Also reports has_webhook_secret — whether this key can receive signed webhook callbacks (verify with a webhook_url needs one); the secret value itself is never exposed.

Polling without webhooks

verify() returns immediately with a task_id; the pipeline runs async (~90s for a cold claim). You don't need webhooks to get the result — poll for it.

The one-liner is verify_and_wait(). If you already hold a task_id (or want to submit and wait separately), use wait():

task = client.verify(claim="Sharks don't get cancer")  # async, returns a task_id
verification = client.wait(task)  # blocks until it lands
print(verification.verdict, verification.lenz_score)

To run several claims in parallel, submit a batch and wait on all of them. verify_batch_and_wait returns one BatchItemResult per claim, in input order, and never raises on a single claim failing — inspect each item's status:

results = client.verify_batch_and_wait(
    claims=[
        {"text": "Sharks don't get cancer"},
        {"text": "The Eiffel Tower is 330m tall"},
    ]
)
for r in results:
    if r.status == "completed":
        print(r.claim, "→", r.verification.verdict)
    else:
        print(r.claim, "→", r.status)  # needs_input | failed | timeout

A failed item with status_detail is None is a verification its account's retention period has removed (HTTP 410, see Retention), a task id nothing was found under (404) or an answer in another API version; every other failure carries a status_detail. A 401 / 403 on a poll (the key itself refused) raises from the whole call.

A verify takes ~90 seconds, so show your users where it is. on_progress fires once per poll while the run is going — it takes the task_id as well, because the batch helper round-robins several ids in one loop:

client.verify_and_wait(
    claim="Sharks don't get cancer",
    on_progress=lambda task_id, p: print(f"{p.step} — step {p.index} of {p.total}"),
)
# framing — step 1 of 5
# research — step 2 of 5
# ...

p.step is one of starting / framing / research / debate / adjudication / conclusion. p.index is stage position, not elapsed work — the stages are uneven, so a bar driven by it sits on research for roughly half the run. An exception raised inside your callback never breaks the poll.

Prefer webhooks for production async flows (no long-lived HTTP connection); prefer polling for scripts, notebooks, and request/response handlers where blocking is fine. If you want full control over the loop, call get_status(task_id) yourself — it's a single non-blocking poll.

Response shape — the unified vocabulary

Every claim-shaped response shares these fields at top level:

The accepted values are exported as Literal aliases for comparisons and exhaustive matching: Verdict (the five labels and "Error"), VerdictLabel (the five labels), Confidence and Depth ("standard" or "low"). The fields themselves stay str, so a value a later API adds still reads.

from lenz_io import Verdict

NEEDS_A_LOOK: set[Verdict] = {"False", "Mostly False", "Mixed"}
flagged = [row for row in quick if row.verdict in NEEDS_A_LOOK]

Field names: the current names, and the deprecated 2.x ones

The API's current response shape gives each field one name across every endpoint. Since 3.0 the SDK asks for it (X-Lenz-API-Version: 2026-10-11) and reads only that shape from its own calls (webhooks of both shapes are still parsed). The current names are attributes already. The 2.x names are deprecated and still work, with the value they had in 2.x (except the few values the API no longer sends, listed under "What reads differently" in the changelog); they will be removed in a future major release. Move to the current names when convenient:

"Nothing checkable" is no_checkable_claim in the current names; the 2.x fields keep their own spelling (not_a_claim, no_claim). The current names are read-only properties. The full list, with the aliases that have no replacement, is in the changelog.

What model_dump() and --json return. Not the response body as sent: a model's model_dump() (and the CLI's --json, which prints it) holds the 2.x-compatible fields, computed from the response, plus the current-shape keys the server sent (failure, more_claims, claims, completed_at, ...). The body exactly as sent is exc.body on an error and event.raw on a webhook event.

A suggested rewrite (suggested_rewrite)

A verification can carry suggested_rewrite: a suggested rewrite of its claim that the verification's findings support, to use in place of the original sentence.

v = client.verifications.get("a1b2c3d4")

if v.suggested_rewrite is not None:
    print(v.suggested_rewrite)  # the rewritten sentence

• It has not been verified itself. Before using it, review it or run it through client.verify(...).
• None for a true claim, when no correction is established, and on verifications that predate the field.
• On every verification, single or listed: verifications.get, verifications.list, library.list, verify_and_wait, wait, a completed get_status, and the result of a verification.completed webhook. assess rows carry their own with suggest_rewrite=True.

The warranty (coverage)

Qualifying verdicts on paid Pro and Scale plans carry a contractual warranty from Lenz. Every verification tells you where it stands:

v = client.verifications.get("a1b2c3d4")

if v.coverage is None:
    ...  # Lenz is not operating the warranty, or you called without a key
elif v.coverage.status == "covered":
    cert = client.verifications.get_certificate(v.verification_id)
    # cert.leaf / cert.signature / cert.anchors — verifiable WITHOUT Lenz,
    # with the script at cert.verifier_url and the keys at cert.keys_url.
else:
    print(v.coverage.reasons)  # e.g. ["plan"] or ["verdict"]

Three things worth getting right:

• coverage is None and status == "uncovered" are different facts. The first means Lenz is not operating the warranty, or the call was unauthenticated; the second means it IS, and this verdict did not qualify.
• The money fields are three, not two. currency is ISO 4217, and cap / aggregate are integers in major units — cap=10000 means ten thousand, not a hundred. Read currency; do not assume EUR.
• A 404 from get_certificate() does not mean "not covered" — check coverage.status for that.
• reasons == ["account"] means the account turned certificates off. An account on Pro or Scale can switch them off on the API credentials page; checks submitted from then on carry no certificate. A verification that already carries a certificate keeps it.

Retention

By default a verification stays available for as long as the account exists. An account on Pro or Scale can set a retention period on the API credentials page. Once a verification is older than that period, reading it raises LenzGoneError (HTTP 410, code == "purged", with purged_at), and wait() raises it at once instead of polling to its deadline. It also disappears from verifications.list(). A certificate issued for it stays available from verifications.get_certificate().

from lenz_io import LenzGoneError

try:
    v = client.verifications.get("a1b2c3d4")
except LenzGoneError as exc:
    print(exc.purged_at)  # "2026-10-25T10:00:00+00:00"

Webhooks

from lenz_io import LenzWebhooks, VerificationCompleted, VerificationFailed, VerificationNeedsInput

webhooks = LenzWebhooks(secret="whsec_...")

# In your web handler:
event = webhooks.parse(raw_body=request.body, headers=request.headers)
if isinstance(event, VerificationCompleted):
    # event.verification is the verification as client.get_status returns it
    # (a TaskStatus); the verdict is under .result, a typed Verification.
    v = event.verification.result if event.verification else None
    if v is not None:
        print(v.verification_id, v.verdict, v.lenz_score, v.confidence)
elif isinstance(event, VerificationNeedsInput):
    options = [c.claim for c in event.claims]  # pick, then client.select(event.task_id, claims=[...])
elif isinstance(event, VerificationFailed):
    # failure.code is WHAT stopped it; failure_class is WHY (closed set) and
    # retryable tells you what to do about it.
    if event.failure and event.failure.retryable:
        resubmit_later(event.task_id)  # transient provider outage
    else:
        log_permanent_failure(event.task_id, event.failure.code if event.failure else "")

.verification (since 3.0) is built from either payload shape, and is None only when a payload cannot be read as one. The flat event.result dict (and error, failure_class, retryable on a failed event) are kept with their 2.x values; prefer .verification and .failure.

If you're on Python 3.10+ a match statement reads even cleaner — events are plain dataclasses, so structural pattern matching works.

If you rely on the warranty, publish on CertificateTimestamped, not on VerificationCompleted. Cover requires the certificate's qualified timestamp to precede what you publish or send, so a pipeline keyed on completed races the anchor and can put the statement out before cover exists:

from lenz_io import CertificateTimestamped

if isinstance(event, CertificateTimestamped):
    # The timestamp landed; cover is in force. Safe to publish now.
    publish(event.verification_id, certificate=event.coverage["certificate_url"])

It carries coverage instead of result — it reports a timestamp landing, not a verdict being produced.

A task cancelled elsewhere (the website's Stop button, another process) sends verification.cancelled, parsed as VerificationCancelled (event.verification.status is "cancelled"), review.cancelled and citecheck.cancelled. These are sent for work submitted with the API version this SDK uses; a cancellation of work submitted by an older client keeps arriving as the *.failed event with failure_class cancelled.

A review sends review.completed or review.failed, parsed as ReviewEvent with the final review on event.review. Deduplicate on event.event_id: it is the same on every retry of one delivery. The deep checks a review runs send no verification.* events of their own, and events this SDK version does not know parse as a plain WebhookEvent: ignore them. event.review is None if the body could not be read (event.raw keeps it).

from lenz_io import ReviewEvent

if isinstance(event, ReviewEvent) and event.review and not already_seen(event.event_id):
    for issue in event.review.issues:
        flag(issue.claim, issue.verdict, issue.suggested_rewrite)

parse_webhook(body) parses a body whose signature you have already checked (or one you stored) into the same events.

Signature verification is HMAC-SHA256 over the raw body; the SDK does it for you and rejects tampered or replayed payloads.

See examples/core/fastapi_webhook.py for a runnable FastAPI receiver, and examples/core/verify_llm_output.py for the headline extract → assess → escalate pattern.

Credits

One pool per account funds every billable call, at a fixed weight:

u = client.usage()
print(u.credits.remaining, "credits")  # the balance — the authoritative number
print(u.costs["verify"], "credits per verification")  # the price list
print(u.cost_options["verify"]["depth"]["low"], "at depth low")  # 5 — half price
print(u.credits.remaining // u.costs["verify"], "verifications left")  # that balance in verifications
print(u.credits.extra, "of them non-expiring")  # grants + top-ups

The verify / ask / assess blocks on Usage are deprecated (kept, with their 2.x values) projections of the one balance into each capability's unit — how many of those calls the remaining credits would buy — not separate allowances. Spending on any one of them moves all of them. Derive the same number from credits and costs, as above.

credits.extra is the non-expiring part of the balance. Its old name, credits.bonus, is deprecated: the same number, it emits a DeprecationWarning when read and is kept for existing code.

Per-capability bonus is that capability's share of credits.extra, so 200 extra credits read as assess.bonus == 200 and verify.bonus == 20. The old capability.credits field is a deprecated alias of bonus (it never meant the pool); reading it emits a DeprecationWarning and it is kept for existing code.

Depth pricing

cost_options["verify"]["depth"]["low"] is the price of a depth="low" verification — half a standard one. low caps research breadth (fewer discovery queries, a hard extraction ceiling, no recovery fetch tiers) while every reasoning step runs the same models; it is not a model downgrade.

It is a price, not a capability, which is why it is nested under cost_options rather than sitting in costs beside the four capability names. There is deliberately no usage.verify_low block beside usage.verify — it would report the same balance in a second unit. Divide the balance yourself when you want the count:

# Every level is optional: a server predating this field sends `{}`, and
# the capability's default price in `costs` is the right fallback.
low = u.cost_options.get("verify", {}).get("depth", {}).get("low") or u.costs["verify"]
low_depth_left = u.credits.remaining // low  # 1014

You are charged for the depth you requested, not the one you were served. The depth echoed on the completed verification is what the verdict was produced with, so it can read standard on a low request — the echo describes the evidence behind the answer, the charge follows the request. A batch may mix depths and is billed per item.

A verdict served from the last hour's cache is free, on verify, assess and review alike. The one exception is a verify that issues your business plan a new warranty certificate, charged at the depth you requested.

Errors

Every error subclass is typed and carries a request_id you can quote on support tickets:

from lenz_io import (
    LenzAuthError,
    LenzConnectionError,
    LenzNotFoundError,
    LenzQuotaExceededError,
    LenzRateLimitError,
    LenzUpstreamUnavailableError,
    LenzValidationError,
)

try:
    client.verify_and_wait(claim="...")
except LenzQuotaExceededError as exc:
    # HTTP 402. Out of credits — retrying will not clear it.
    print(exc.remaining)  # 0 verifications, or None if the server didn't say
    print(exc.credit_balance)  # 4 — credits left in the pool, or None
    print(exc.cost)  # 10 — credits this call would have taken, or None
    # `cost` is depth-aware: a rejected depth="low" verify reports 5, and a
    # rejected batch mixing depths reports its real summed total. Read it
    # rather than multiplying `requested` by a price you assumed.
    print(exc.resets_at)  # "2026-09-01T00:00:00+00:00", or None
    print(exc.upgrade_url)  # https://lenz.io/plans
except LenzAuthError as exc:
    print(exc)
    # Unauthorized
    #   Cause:  Invalid api key
    #   Fix:    Your credential is missing, invalid or expired. Check the key you passed, or get a new one at https://lenz.io/api-credentials.
    #   Docs:   https://lenz.io/docs/auth
    #   Request ID: req_abc123
except LenzRateLimitError as exc:
    # Waits up to 60s are already retried for you, so reaching here means
    # either the ladder ran out or the wait is long. Don't sleep it — the
    # /extract daily cap can be hours away.
    schedule_retry_in(exc.retry_after)
except LenzValidationError as exc:
    for field_err in exc.errors:
        print(field_err["loc"], field_err["msg"])
except LenzUpstreamUnavailableError as exc:
    # HTTP 503, code "upstream_unavailable" (model/search providers
    # exhausted) or "capacity" (submissions shed at the door). Nothing was
    # charged. Waits up to 60s are already slept through by the automatic
    # retry ladder; reaching here means the server stated a longer one.
    schedule_retry_in(exc.retry_after)  # typically 90-120s
except LenzNotFoundError as exc:
    # HTTP 404. The id (or key) the request names finds nothing: retrying
    # will not change that. A LenzError, as in 2.x.
    print(exc.fix)
except LenzConnectionError as exc:
    # No answer at all, after the SDK's own retries: the network, DNS, TLS,
    # or (LenzRequestTimeoutError, a subclass) one request's timeout. A
    # LenzAPIError, as in 2.x; exc.__cause__ is the httpx exception. The
    # request may have reached the server: resend with the SAME key
    # (idempotency_key=exc.idempotency_key), never as a plain new call.
    schedule_retry_in(30)

retryable (since 3.0, on every error): whether sending the same request again can succeed. True for a connection failure, a request timeout, a 429, a 5xx and a 409 that means "not yet" (idempotency_conflict: the first request with that key is still running; verification_not_ready); False for any other 4xx and a version error; None when there was no HTTP status (a missing key, a *_and_wait timeout). A failed verification, review or citation check carries the server's own value (None when it sent none).

idempotency_key (since 3.0, on every error): the Idempotency-Key the failed call sent, or None when it sent none. A resend is safe only with the same key: pass idempotency_key=exc.idempotency_key back, and the server replays the first answer (or reports the first request still running) instead of running it again. A plain new call sends a new key, and can run (and charge) the work twice.

from lenz_io import LenzError

try:
    client.assess(claim="...")
except LenzError as exc:
    if exc.retryable:
        # Later, the same request with the same key:
        # client.assess(claim="...", idempotency_key=exc.idempotency_key)
        schedule_retry_in(getattr(exc, "retry_after", None) or 30)
    else:
        raise

Local argument mistakes (an empty id, two exclusive arguments) raise ValueError, never a LenzError.

A *_and_wait helper that reaches its own timeout raises LenzTimeoutError (ReviewTimeout, CitecheckTimeout): the job keeps running server-side, so read it later by its id rather than resubmitting. A poll answered 401, 403, 404 or 410 (or in another API version) ends the wait at once with that error; in verify_batch_and_wait a 404, a 410 or a version error fails that item only (the others keep going), while a 401 / 403 raises. A 5xx, a 429 or a network failure is polled again. Each poll is bounded by what is left of the timeout (each phase at most the client's own), and no poll starts once it is spent; timeout=0 reads each status once, as in 2.x. ReviewFailed, ReviewTimeout, CitecheckFailed and CitecheckTimeout are also importable as ReviewFailedError, ReviewTimeoutError, CitecheckFailedError and CitecheckTimeoutError (the same classes).

LenzApiVersionError (a LenzError) is raised when a response names an API version other than the one this SDK reads. Every response carries the version that served it in X-Lenz-API-Version; lenz-io 3.x asks for 2026-10-11 and reads that version's shape only, so an answer in 2026-05-13 (a server still on the older version, or a reply replayed from an idempotent request stored before the change) is refused rather than misread. It carries api_version (what the response named), status_code and body as sent. If it persists, contact support with the request id; lenz-io 2.x reads both versions. A response without the header is read as usual, and webhook payloads are never refused (they are parsed in either shape).

Replays of requests made before the switch. An idempotent request first sent before lenz.io served 2026-10-11, and replayed with the same Idempotency-Key afterwards, answers with the stored reply in 2026-05-13, which 3.x refuses with LenzApiVersionError. Replays are kept for 24 hours and replies stored since 2026-10-09 are kept in both versions, so in practice none remain when 3.0 ships. If you meet one, finish that work with lenz-io 2.x; never change the key to get past it, which would run (and charge) the request a second time.

from lenz_io import LenzApiVersionError

try:
    client.assess("The Earth is round.")
except LenzApiVersionError as exc:
    print(exc.api_version)  # "2026-05-13"

A failed verification (as opposed to a failed HTTP call) raises LenzPipelineError from verify_and_wait / wait. Since 2.8.0 it carries failure_class (closed set: upstream_unavailable | insufficient_evidence | invalid_input | cancelled | internal) and retryable — True means a transient provider-side exhaustion where resubmitting the same claim is the right move; older servers leave it None. A verification cancelled elsewhere (the website's Stop button, another process) raises the same error with failure_class == "cancelled" and retryable False; review_and_wait and citecheck_and_wait do the same with ReviewFailed and CitecheckFailed.

LenzQuotaExceededError is a sibling of LenzAuthError, not a subclass — "fix your key" and "top up your account" are different actions. So if you were catching LenzAuthError to handle an empty balance, that branch stops firing; add a LenzQuotaExceededError handler.

Resuming a verification

If a verify_and_wait call exceeds its timeout (default 300s) or your process dies mid-poll, the pipeline keeps running. The exception carries the task_id:

from lenz_io import LenzTimeoutError

try:
    client.verify_and_wait(claim="...", timeout=30)
except LenzTimeoutError as exc:
    print("resume later via:", exc.task_id)

# Later (different process / restart) — block on the same task_id:
verification = client.wait("tsk_abc123")
print(verification.verdict, verification.lenz_score)

# ...or do a single non-blocking poll yourself:
status = client.get_status("tsk_abc123")
if status.status == "completed":
    print(status.result.verdict, status.result.lenz_score)

Stopping a run

A verification, a review or a citation check that is still running can be stopped. Each has its own method, and each answers 200 whatever the state of the run, so losing a race is not an error:

result = client.cancel("tsk_abc123")  # a verification -> CancelResult
if result.cancelled:
    print("stopped:", result.status)  # "cancelled"
else:
    print("already ended:", result.status)  # "completed" or "failed"

review = client.cancel_review("d6b2bd72")  # the full view, like get_review
print(review.status, review.credits.charged)  # "cancelled", what it cost

check = client.cancel_citecheck("12bbbf65")  # like get_citecheck
print(check.status, check.credits.charged)

• cancel(task_id) returns a CancelResult. cancelled=True with status == "cancelled" means the run is cancelled, by this call or an earlier one, so a repeated or retried cancel answers True too. cancelled=False means it is not cancelled, and status is the run's status, normally "completed" (the verification exists and was charged as usual) or "failed". A run waiting on select is cancelled too. A task that select already resolved answers cancelled=False with needs_input: cancel the task ids select returned.
• cancel_review(review_id) stops the review and everything in it: its quick checks, its deep checks and its citation checks. It returns the review as it stands, status == "cancelled"; a review that had already ended is returned unchanged (completed or failed).
• cancel_citecheck(citecheck_id) returns the check the same way.
• A review's deep checks are cancelled through the review. Calling cancel(task_id) with the task_id of one raises a LenzError with code == "use_review_cancel" (HTTP 409); call cancel_review instead. The SDK sends that request once and does not wait or resend.
• An unknown id, another account's, or (for cancel) a task started on the website raises LenzNotFoundError.
• A cancelled verification is not charged and saves nothing. A cancelled review or citation check is charged only for what it delivered before the cancel (quick checks served, deep checks that finished, citations checked); the rest is refunded or never charged. credits.charged on the result is what the review or check cost.
• Cancelling twice is safe, so the calls send no Idempotency-Key. They are retried on a 5xx, a 429 or a dropped connection, like any call that is safe to repeat.
• Afterwards get_status, get_review and get_citecheck return the cancelled status, and wait, review_and_wait and citecheck_and_wait raise the failed error with failure_class == "cancelled". A webhook_url receives verification.cancelled, review.cancelled or citecheck.cancelled.

Idempotency

Every call that charges or starts work sends an auto-generated Idempotency-Key by default: verify, verify_and_wait, verify_batch, verify_batch_and_wait, select, assess, extract and ask.send (one random key per call, reused across that call's own retries), so a network drop after submit doesn't spawn a duplicate or charge a second time. Override with idempotency_key="..." to pin a specific key (it also makes a retry from another process replay), or idempotency=False to opt out. review and citecheck always send one (pin it with idempotency_key=). The batch and ask.send keys are new in 3.0; 2.x sent one there only when you passed it.

The key is never derived from the request: asking the same question again on ask.send is a new call, with a new key, and is asked again. Pin a key when your retry means "the same question, once" — the reply, the credit and the conversation history are then all the first call's:

reply = client.ask.send(
    v.verification_id,
    message="Which source is strongest?",
    idempotency_key="deal-42-followup-1",
)

A retry that arrives while the first call with that key is still running is answered 409 idempotency_conflict. The SDK sends the same key and body again inside the same call, after the wait the server states (or its usual backoff), within the call's retries; if the first call is still running after them, it raises that LenzError with retryable=True. It never mints a second key to get past it. Every error of a call that sent a key carries it as exc.idempotency_key: resend with that key, never as a plain new call, which would send a new key and could run (and charge) the work twice.

Steering extract

extract returns every major factual claim it finds, ranked most-check-worthy first. On a long document that is often more than you want to verify. Pass focus= to narrow it:

out = client.extract(
    text=pitch_deck,
    focus="market size, growth and competitors",
)

A focus can only select from the claims the extractor found. It cannot add a claim, reword one, reorder them, change the output language, or change what counts as a claim — selection runs over the claim list, not over your document, so a claim you get back is one an unfocused call would have returned too, verbatim.

At most 300 characters. A longer focus is rejected with a 422 rather than truncated, so you never get a subset you did not ask for.

When the document has claims but none fall within your focus, status is "no_match" and claims is empty. The unfocused list is never substituted — widen the focus and call again.

if out.status == "no_match":
    ...  # nothing in this document matched; broaden the focus

A focused call costs the same single unit of the daily cap as an unfocused one.

On the CLI:

lenz extract "$(cat deck.txt)" --focus "market size and competitors"

Locating claims in your text

Pass locate=True to keep only the claims that can be traced directly back to your text, and to learn where the text makes each one:

out = client.extract(text=draft, locate=True)
for c in out.claims:
    for pos in c.positions or []:
        print(c.claim, "->", pos.text)
        if pos.start is not None:
            assert draft[pos.start : pos.end] == pos.text

A claim found nowhere in the text, or found with a different figure, is left out; if that leaves no claim, status is "not_a_claim". Each entry of claims has its positions (every place the text makes it, in text order, at least one and at most 10). Each is a Position: start and end index the text you sent in Unicode code points, so text[start:end] works natively; end is exclusive. Both are None when the input was a URL, since the page is not returned; pos.text carries the passage.

positions is None when locate was not set, or when the claims could not be located — the list is then returned unfiltered. Locating adds a few seconds. locate defaults to off; leave it None to use the server default, or pass False to turn it off explicitly.

On the CLI:

lenz extract "$(cat draft.txt)" --locate

Multi-language output

The Lenz API returns prose fields (atomic claim, executive summary, debate, panel reasoning) in any of 12 languages. Pass language= on verify, verify_and_wait, verify_batch, assess, extract, or ask.send. Verdict labels stay English regardless of language. On extract, language and focus are independent — a focus written in any language selects claims emitted in language.

v = client.verify_and_wait(
    claim="La Tierra es plana",
    language="es",  # Spanish output
)
print(v.verdict, v.language)
# False es

Supported codes: en (default), es, de, fr, it, pt, nl, sv, da, no, fi, bg. To ask for another language, contact us at https://lenz.io/contact.

Answer in the language of the text

language="auto" on assess, verify / verify_and_wait and ask.send answers in the language of the text you submitted (on ask.send, the language of the claim being discussed). A concrete code always wins, and leaving language out still means English. The other methods (extract, verify_batch, citecheck, review) take the codes above, not auto.

r = client.assess(claim="Die Erde ist flach.", language="auto")
print(r.claims[0].verdict, r.claims[0].language)
# False de

On assess with a claims list, one language is chosen for the whole request: the one most items are written in, otherwise English. For a list that mixes languages, name the code you want instead.

Per-item override on verify_batch:

batch = client.verify_batch(
    claims=[
        {"claim": "Coffee causes cancer."},  # en (batch default)
        {"claim": "El café causa cáncer.", "language": "es"},  # overrides
    ],
    language="en",
)

Using Lenz from async code

AsyncLenz (since 3.1) is the client for asyncio: the same methods, parameters, defaults, results and errors as Lenz, awaited. It never blocks the event loop.

from lenz_io import AsyncLenz

async with AsyncLenz() as client:  # reads LENZ_API_KEY
    row = (await client.assess(claim="The Great Wall of China is visible from space.")).claims[0]
    review = await client.review_and_wait(draft)
    async for item in client.verifications.iter():
        print(item.verification_id, item.verdict)

In a web app, create one AsyncLenz in the app's lifespan and close it on shutdown. FastAPI does not cancel a handler when the caller goes away, so a long wait behind a request runs as a task that you cancel on request.is_disconnected(); with cancel_on_abort=True that also stops the job on the server (full example):

import asyncio
from collections.abc import AsyncIterator
from contextlib import asynccontextmanager
from fastapi import FastAPI, Request, Response
from lenz_io import AsyncLenz


@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncIterator[None]:
    async with AsyncLenz() as client:
        app.state.lenz = client
        yield


app = FastAPI(lifespan=lifespan)


@app.post("/review", response_model=None)
async def review(text: str, request: Request) -> dict[str, object] | Response:
    client: AsyncLenz = request.app.state.lenz
    wait = asyncio.ensure_future(client.review_and_wait(text, cancel_on_abort=True))
    try:
        while not wait.done():
            await asyncio.wait({wait}, timeout=1)
            if not wait.done() and await request.is_disconnected():
                wait.cancel()  # cancel_on_abort: the review is asked to stop on the server too
                await asyncio.gather(wait, return_exceptions=True)
                return Response(status_code=499)
    finally:
        wait.cancel()  # no-op once it is done; stops it if this handler is cancelled
    result = wait.result()
    return {"outcome": result.outcome, "issues": [issue.claim for issue in result.issues]}

To check many claims at once, send them in one call (assess(claims=[...]), verify_batch_and_wait), or fan out with asyncio.gather behind a semaphore. A 429 is retried by the SDK; the semaphore keeps the burst (and the connection pool, 100 connections by default) in bounds:

limit = asyncio.Semaphore(8)


async def one(claim: str) -> str:
    async with limit:
        return (await client.assess(claim=claim)).claims[0].verdict


verdicts = await asyncio.gather(*(one(c) for c in claims))

verify_batch_and_wait polls its items one after another, as the sync client does; to poll items in parallel, asyncio.gather(*(client.wait(item) for item in batch.items)).

Cancellation. Cancelling the task that awaits a call (a timeout, a caller that left) raises CancelledError and closes the request in flight. It only stops waiting: the verification, review or citation check keeps running on the server and is charged as usual if it completes. Unless the wait was called with cancel_on_abort=True (wait, verify_and_wait, verify_batch_and_wait, review_and_wait, citecheck_and_wait): then the SDK also sends the matching cancel / cancel_review / cancel_citecheck (one request per job, at most 5 seconds) and then re-raises the CancelledError unchanged. Call aclose() (or leave async with) before the event loop ends, so pending cancels go out: a cancel cut off by the loop closing is logged at WARNING and never sent. A cancelled verification is not charged; a cancelled review or citation check refunds what it had not delivered. A cancel that fails, or that loses the race to the end of the job (which is then charged as usual), is logged at WARNING with the job id. asyncio.timeout() and asyncio.wait_for() around a wait are cancellations; the wait's own timeout= running out is not, and never stops the job. wait(task_id, cancel_on_abort=True) knows the id up front: a cancellation already requested when it starts cancels the run without polling. A task cancelled before it ever runs never enters the call, so nothing is sent.

A submit cancelled after its request left may still have started the job, and a fresh call would start (and charge) a second one. If you may cancel a submit, pin idempotency_key= and resend with the same key to get the same job back (within 24 hours); to keep the task_id across a cancelled wait, call verify() and then wait().

What differs from Lenz:

• the methods are coroutines (iter() returns an async iterator, with_options() stays a plain method); close with await client.aclose() or async with (no close(), no with);
• http_client= takes an httpx.AsyncClient;
• on_progress / on_update may be async def (awaited before the next poll);
• the waits take cancel_on_abort (above);
• the User-Agent ends ; async).

One AsyncLenz belongs to one event loop (like the httpx.AsyncClient inside it): create it where it is used, never at import time. asyncio only; trio is not supported. In tests, pass http_client=httpx.AsyncClient(transport=httpx.MockTransport(handler)) to answer every request yourself.

For a long check you do not need to wait for, verify(..., webhook_url=...) returns at once and Lenz posts the result to you when it is done (see Webhooks).

On lenz-io 3.0 and earlier (no AsyncLenz), run the sync client in a worker thread (await asyncio.to_thread(client.assess, claim=claim)); cancelling such a task does not stop the call.

Configuration

Lenz(
    api_key="lenz_...",  # or set LENZ_API_KEY env var
    base_url="https://lenz.io/api/v1",  # override for staging / local
    timeout=30.0,  # seconds per request; also None or an httpx.Timeout
    max_retries=3,
)

AsyncLenz(...) takes the same arguments, with an httpx.AsyncClient as http_client=.

Environment variables:

• LENZ_API_KEY — read if api_key= is not passed
• LENZ_BASE_URL — read if base_url= is not passed

An OAuth access token for the Lenz API works wherever the API key goes: pass it as api_key or in LENZ_API_KEY.

timeout must be a number of seconds greater than 0 and at most 2,147,483, None (no timeout), an httpx.Timeout or httpx's (connect, read, write, pool) tuple; max_retries a whole number, 0 or more. Anything else raises ValueError when the client is built.

Per-call options

Every method takes three keyword-only request options, for that call only:

client.assess(claim="...", timeout=20)  # one HTTP attempt, in seconds
client.usage(max_retries=0)  # no retries for this call
client.verify("...", extra_headers={"X-Trace-Id": trace})  # added to the request

• timeout: one HTTP attempt, a number of seconds greater than 0 or an httpx.Timeout. httpx applies it per phase (connect, read, write, pool), and the read limit to each chunk of the answer: it limits inactivity, not the whole call, and each retry gets its own.
• max_retries: how often a request that failed in a way worth retrying (a 5xx, a 429, a dropped connection) is sent again: a whole number, 0 or more.
• extra_headers: headers added to the request. Names are header tokens and values visible ASCII, with spaces and tabs allowed inside but not at either end (an empty value is fine); anything else raises ValueError. The SDK's own headers are refused (X-Lenz-API-Version, Idempotency-Key, Authorization, Content-Type, Content-Length, Host, Transfer-Encoding): use idempotency_key= and api_key= for the first two. A header with the name of a default one (User-Agent, Accept), in any casing, replaces the default instead of being sent next to it.

What each option reaches:

A bad value raises ValueError before anything is sent (for the iterators, when the iterator is created). Precedence, per option: the call's keyword, then the copy's (with_options), then the client's; headers merge, the call's over the copy's.

extract and assess wait at least 150 s and 100 s when the timeout comes from a copy or the client, as they always did. A timeout passed to the call is used as given, even below that: it can time out a call the server is still running, so retry it with the same idempotency_key to get its answer.

None means different things in two places:

For no timeout on one call, pass timeout=httpx.Timeout(None).

A client with other defaults: with_options

client.with_options(...) returns a copy with its own defaults, sharing the connection pool, key and base URL. It is cheap, so you can make one per request or per job, and the client it was made from does not change:

fast = client.with_options(timeout=10, max_retries=0)
fast.assess(claim="...")

for job in jobs:
    scoped = client.with_options(extra_headers={"X-Job-Id": job.id})
    scoped.review_and_wait(job.draft)

A copy of a copy starts from the copy's options (timeout, retries and headers), and changes only what it is given. The pool belongs to the client that created it: close() and with on a copy do nothing, closing the original closes the pool for every copy (a copy then raises httpx's closed-client error), and a client given http_client= never closes it. A copy is as safe to share across threads as the client. The copy is shallow: attributes a subclass of Lenz adds are shared with the client it was made from.

Compatibility

• Python 3.10, 3.11, 3.12
• Works in CI/CD (no interactive prompts, no global state)
• Mockable for tests: every HTTP call goes through httpx; use respx or inject your own httpx.Client via Lenz(..., http_client=...) (an httpx.AsyncClient for AsyncLenz)
• AsyncLenz: asyncio (not trio)

Contributing

git clone https://github.com/lenzhq/lenz-io-python && cd lenz-io-python
uv sync --extra dev
git config core.hooksPath scripts/hooks   # one-time: enables pre-commit

The pre-commit hook mirrors CI exactly (ruff check, ruff format --check, mypy, pytest). Runs ~10s per commit on a warm cache. Skip once with git commit --no-verify when you must.

Bug reports + feature requests

github.com/lenzhq/lenz-io-python/issues

For commercial use, volume pricing, or onboarding support, get in touch.

License

MIT. See LICENSE.

Maintainer

@Pavel12431432