Octogen Python SDK

Async Python SDK for the Octogen AI commerce API.

Install For Development

From this directory:

uv sync

Authentication

The client reads the API key from OCTOGEN_PLATFORM_API_KEY by default — the same variable the Octogen agent-onboarding skill and CLI use — and sends it as:

Authorization: Bearer <api-key>

You can also pass api_key explicitly when constructing the client.

OCTO_API_KEY is still read as a deprecated fallback: it raises a DeprecationWarning once and will be removed. Set OCTOGEN_PLATFORM_API_KEY.

Usage

import asyncio

from octogen_ai_sdk import OctogenClient


async def main() -> None:
    async with OctogenClient(base_url="https://api.storerouter.ai/v1") as client:
        results = await client.search_products(q="paisley jackets", limit=3)
        for product in results.items:
            print(product.title, product.product_url)


asyncio.run(main())

Product lookup

Look up a product URL directly. A missing product does not prove that its whole merchant domain is unsupported. Use get_me() to check credentials.

API

Every published /v1 operation has a method. tests/contract fails the build if that stops being true — see Contract conformance.

• get_me() returns the calling organization, key id and provenance, quotas, and rate-limit posture. Read-only and side-effect free: safe on startup and in CI.

• get_domain(url_or_host) returns one store's coverage snapshot (GET /v1/domains/{host}): every catalog serving the host, with product counts, populated facets and a price histogram. A URL is normalized to its host first. An uncovered host raises OctogenNotFoundError with detail == "domain_not_covered". There is no list of covered hosts.

• search_products(...) searches every active catalog by default, or only the catalogs in catalogs (1–500 keys) when it is provided. The query field is q, understood by default; understand, facets, exclude_facets, the price and brand-quality bounds, relax, and debug refine it (see below). Results come back as items + next_cursor, each item carrying product_url, plus effective_query with debug=True.

• more_like_this_products(...) finds products similar to a source product URL or UUID, or to a set of 1–20 product UUIDs passed as sources, optionally restricted to catalogs (1–100 keys). facets, exclude_facets and the price and brand-quality bounds work as on search. relax defaults to True on the server: a short page 1 is retried with Platform's generated facets dropped, never yours, and reported in effective_query.relaxation with debug=True. facets replaced include_facets in 0.8.0. omit_generated_facets and the embedding-column lists tune what is generated and how candidates are retrieved and ranked.

• lookup_product(url, match_mode=..., resolution_mode=..., on_demand_cache_policy=...) resolves a product URL from the index or on demand. resolution_mode and on_demand_cache_policy default to auto and prefer_cache; omitting match_mode leaves the server on its own default (loose).

• resolve_product_from_html(html=..., url=...) resolves a product from page HTML you already have — no index read, no outbound fetch.

• list_taxonomy_categories(parent=...), list_taxonomy_attributes(category) and list_taxonomy_attribute_values(handle) discover categories, their attributes and the attributes' value handles, paged with offset/limit. A category's facets and an attribute's facet_name plus value handle go back into search_products unchanged.

• count_product_facets(...) counts the products search_products would filter to — by categories, attributes and facet_names — under the same q, facets, bounds and catalogs.

• create_coverage_url_list(name=...), list_coverage_url_lists(...), get_coverage_url_list(url_list_id), and delete_coverage_url_list(url_list_id) manage coverage URL lists — named sets of product URLs that Octogen continuously joins against its crawled index and shares back as a BigQuery listing.

• add_coverage_url_list_urls(url_list_id, urls=[...]), remove_coverage_url_list_urls(url_list_id, urls=[...]), check_coverage_url_list_urls(url_list_id, urls=[...]), and list_coverage_url_list_urls(url_list_id, ...) mutate and inspect a list's membership with per-URL accepted/rejected outcomes.

async with OctogenClient(base_url="https://api.storerouter.ai/v1") as client:
    similar = await client.more_like_this_products(
        source_url="https://warrenlotas.com/products/black-hoodie",
        price_preference="any",
        limit=12,
    )
    for product in similar.items:
        print(product.title, product.product_url)

async with OctogenClient(base_url="https://api.storerouter.ai/v1") as client:
    url_list = await client.create_coverage_url_list(name="q3-campaign")
    result = await client.add_coverage_url_list_urls(
        url_list.url_list_id,
        urls=["https://warrenlotas.com/products/black-hoodie"],
    )
    print(result.url_count, [r.code for r in result.rejected])

async with OctogenClient() as client:
    children = await client.list_taxonomy_categories(
        parent="Apparel & Accessories > Clothing"
    )
    dresses = next(c for c in children.categories if c.name == "Dresses")
    counts = await client.count_product_facets(
        q="red",
        categories=[{"key": dresses.id, "facets": dresses.facets}],
        attributes=["neckline"],
    )
    print(counts.categories[0].count, counts.attributes[0].values[:3])

Search controls

Each search_products keyword controls one thing. q says what to find and is understood by default — rewritten for retrieval, with category, colour, brand, price, and attribute filters derived from it. facets, exclude_facets, and the bounds say what to keep; catalogs says where to look.

async with OctogenClient(base_url="https://api.storerouter.ai/v1") as client:
    page = await client.search_products(
        q="black hoodie",
        catalogs=["warrenlotas"],  # omit to search every catalog your key can access
        facets=[{"name": "color", "values": ["black"]}],
        exclude_facets=[{"name": "brand_name", "values": ["acme"]}],
        price_min=50,
        price_max=300,
        brand_quality_min=4,  # 1 (very poor) to 6 (exceptional)
        similar_to_brands=["Warren Lotas"],  # ranks, does not filter
        relax=True,  # drop understood filters in stages if nothing matches
        debug=True,
    )
    if page.effective_query is not None:
        for facet in page.effective_query.facets or []:
            print(facet.name, facet.values, facet.source)  # "caller" | "generated"

• understand=False matches q as written and filters only by what you send.
• omit_generated_facets=["fit"] drops an understood facet that is wrong when you have no value of your own for it; to replace one, send a facet of that name instead. Use the names effective_query reports.
• debug=True adds effective_query, the search that actually ran.

Contradictions the API would refuse — relax or understand=False without a q, a facet name sent twice, price_min above price_max — raise pydantic.ValidationError before any request.

Removed in 0.5.0 (the API now answers them with 422): catalog= → use catalogs=[key]; text_search_query= → use q with understand=False and your filters in facets and exclude_facets. See the CHANGELOG for the migration.

Prebuilt requests, timeouts, and errors

Every operation with a request body also takes request=, a prebuilt request model sent as is. A subclass's extra fields go out too, which bridges a field the API accepts before this SDK declares it. Passing request= together with the keyword form is a TypeError.

class MySearchRequest(ProgrammaticProductSearchRequest):
    new_control: bool | None = None

page = await client.search_products(
    request=MySearchRequest(q="linen dress", new_control=True),
    timeout=2.5,  # this call only; also works with an injected http_client
)

Every operation takes timeout (seconds or an httpx.Timeout). The SDK never retries, so map failures by type and retry what is safe for your call:

lookup_product_markdown(url) returns the product as LLM-ready Markdown (format: "markdown", Accept: text/markdown) in a ProductMarkdownLookupResult, with request_id, product_uuid, catalog, matched_via and normalized_url from the response's identity headers.

Every OctogenAPIError carries status_code, detail, and request_id (the response's x-request-id). OctogenTimeoutError subclasses OctogenConnectionError; a 504 is both an OctogenTimeoutError and an OctogenServerError.

Coverage URL lists CLI

octogen-url-lists manages coverage URL lists from the terminal, so the whole workflow — build a list, then subscribe to its BigQuery listing with octogen-bq-subscribe — stays on the command line. It uses OCTOGEN_PLATFORM_API_KEY (or --api-key), not Google credentials.

export OCTOGEN_PLATFORM_API_KEY=octo_live_...
uv run --project sdks/python octogen-url-lists create --base-url https://api.storerouter.ai/v1 --name q3-campaign --apply

Mutating commands are dry-run by default — matching octogen-bq-subscribe and octogen-bq-autosubscribe — so nothing changes until you pass --apply:

uv run --project sdks/python octogen-url-lists add-urls --base-url https://api.storerouter.ai/v1 cul_01... --file urls.txt
uv run --project sdks/python octogen-url-lists add-urls --base-url https://api.storerouter.ai/v1 cul_01... --file urls.txt --apply

--file reads one URL per line, skipping blank lines and # comments (pass - to read standard input), removes exact duplicates, and splits the result into requests of 1,000 URLs automatically. --url takes a single URL and can be repeated.

Add --json to any command for machine-readable output; dry-run JSON uses the same keys as the applied output so automation can parse both with one schema.

Deletion is permanent and has no restore, so delete --apply first shows what the list holds and then asks you to retype its name. Pass --yes to skip that prompt; without a TTY, --yes is required rather than assumed.

Because a large file becomes several requests, a failure partway through leaves the earlier requests applied. In that case the command exits 1 but still reports how many URLs landed — completedRequests and urlCount in JSON, and a stopped after N/M request(s) line on stderr — so automation never reads a partial update as a no-op. Re-running the same input is safe: adds and removes are idempotent.

BigQuery subscribe (optional)

Once Octogen grants your organization access to a catalog's BigQuery Analytics Hub listing, subscribe to it — creating the linked dataset in your GCP project — without leaving the terminal. Install the extra and authenticate with Application Default Credentials:

pip install "octogen-ai-sdk[bigquery]"
gcloud auth application-default login

CLI (dry-run by default; --apply to subscribe):

octogen-bq-subscribe --listing <listing-resource> --project my-gcp-project --apply

Or programmatically:

from octogen_ai_sdk import subscribe_to_listing

result = subscribe_to_listing(
    listing_resource="projects/octogen-prod/locations/us/dataExchanges/oneoff/listings/farfetch",
    destination_project="my-gcp-project",
)
print(result.linked_dataset, result.state)

Copy <listing-resource> from the Platform UI BigQuery sharing page or from the Catalog Partner MCP list_bigquery_listing_resources tool. It's idempotent, and raises OctogenBigQueryAccessPendingError if Octogen's IAM grant hasn't landed yet (it's asynchronous — retry in a few minutes).

Auto-subscribe new listings

For cron jobs, use the higher-level autosubscribe command. It calls Octogen MCP to register your Reader if needed, finds every ready listing that is not active yet, creates linked datasets in your GCP project, then refreshes Octogen's status.

Bootstrap Octogen MCP credentials once from an interactive terminal:

uv run --project sdks/python octogen-mcp-login \
  --authkit-domain https://auth.storerouter.ai \
  --resource https://mcp.storerouter.ai \
  --client-id-file /secure/octogen-mcp.client-id \
  --refresh-token-file /secure/octogen-mcp.refresh

Dry-run first:

OCTOGEN_MCP_CLIENT_ID_FILE=/secure/octogen-mcp.client-id \
OCTOGEN_MCP_REFRESH_TOKEN_FILE=/secure/octogen-mcp.refresh \
uv run --project sdks/python --extra bigquery \
  octogen-bq-autosubscribe \
  --mcp-url https://mcp.storerouter.ai/mcp/ \
  --mcp-token-endpoint https://auth.storerouter.ai/oauth2/token \
  --project my-gcp-project \
  --principal serviceAccount:bq-reader@my-gcp-project.iam.gserviceaccount.com \
  --json

Apply from cron:

*/15 * * * * cd /path/to/octogen-dev && OCTOGEN_MCP_CLIENT_ID_FILE=/secure/octogen-mcp.client-id OCTOGEN_MCP_REFRESH_TOKEN_FILE=/secure/octogen-mcp.refresh uv run --project sdks/python --extra bigquery octogen-bq-autosubscribe --mcp-url https://mcp.storerouter.ai/mcp/ --mcp-token-endpoint https://auth.storerouter.ai/oauth2/token --project my-gcp-project --principal serviceAccount:bq-reader@my-gcp-project.iam.gserviceaccount.com --apply --json

OCTOGEN_MCP_REFRESH_TOKEN_FILE should contain an Octogen MCP OAuth refresh token. If WorkOS rotates that refresh token during exchange, the command writes the replacement back to the same file. The command also accepts OCTOGEN_MCP_CLIENT_ID instead of OCTOGEN_MCP_CLIENT_ID_FILE, OCTOGEN_MCP_TOKEN_COMMAND for custom token brokers, or OCTOGEN_MCP_ACCESS_TOKEN for short-lived manual runs. BigQuery subscription still uses your local Google Application Default Credentials.

Tests

Run the mocked SDK tests:

uv run pytest

Run linting:

uv run ruff check

Run type checking:

uv run ty check

Run all configured git hooks:

uv run --project sdks/python prek run --all-files

Example

From the repository root:

OCTOGEN_PLATFORM_API_KEY=... uv run --project sdks/python python examples/python/search_clothes.py

Generated versus hand-written

src/octogen_ai_sdk/generated/models.py is emitted from the published contract by npm run codegen (at the repository root) and committed, so a contract change arrives as a reviewable diff. Response models are re-exported from it under the contract's own names.

Response models are forward compatible, generated or hand-written: they keep unknown fields (extra="allow", read them from model_extra or model_dump(by_alias=True)), and their enums are open (Literal[...] | str), so a value the server adds after this release parses instead of failing the response. Request models keep closed enums and extra="forbid".

Request models stay hand-written in models.py, for two reasons: rules the contract cannot express (extra="forbid" catches a misspelled key, but not "exactly one of url or uuid"), and constructor ergonomics — the generator turns a length-constrained string into a root-model alias, so a generated request body would not accept a plain str.

operations.py is the routing table; tests/contract fails when it and the published contract disagree in either direction.