LLM & agent access
Read these docs by machine: Markdown views, llms.txt, llms-full.txt, and the OpenAPI specification.
LLM & agent access
Everything on this site is designed to be read by an LLM as easily as by a person. If you are wiring up a coding agent — or you are the coding agent — use the surfaces below instead of scraping HTML.
Markdown views
Any docs page is available as Markdown by appending .md to its URL:
curl https://sference.com/docs/quickstart.md
curl https://sference.com/docs/agents/langchain.md
curl https://sference.com/docs/api-reference/inference-api/V1ChatCompletionsCreateChatCompletion.mdYou can also ask for Markdown on the plain URL with content negotiation:
curl -H "Accept: text/markdown" https://sference.com/docs/quickstartBoth work for guide pages and for every API-reference page. Blog posts have the same treatment (/blog/<slug>.md), as do the legal pages (/legal/dpa.md, /legal/subprocessors.md, /privacy.md, /terms.md).
Indexes for one-shot loading
| File | Contents |
|---|---|
/llms.txt | Curated index: what sference is, capabilities, pricing, and a link per docs page. The right entry point for an agent deciding what to read. |
/llms-full.txt | Every prose page concatenated into one file, with each page's Markdown twin linked. For loading the whole documentation into context at once. |
/openapi.json | The machine-readable API specification behind the API reference. |
# Load the whole documentation
curl https://sference.com/llms-full.txt
# Or just the index, then fetch what you need
curl https://sference.com/llms.txtOpenAPI specification
https://sference.com/openapi.json is the complete spec: every inference route, every control-plane route, and every schema. Point a code generator or an agent at it to produce a client without reading prose.
A prompt for a coding agent
Paste this into your agent to give it a working understanding of the API:
You are writing code against the sference inference API.
- Base URL: https://api.sference.com/v1
- Auth: `Authorization: Bearer sk_...` (also accepts `x-api-key` on /v1/messages)
- Surfaces: the OpenAI Chat API, the OpenAI Responses API, and the Anthropic Messages API
- Model ids are catalog ids, e.g. "zai-org/GLM-5.3". There are no gpt-* or claude-* aliases.
- Windows: realtime (default), flex (`service_tier: "flex"`, 0.7x), batch
(`background: true` + `metadata.completion_window: "24h"`, 0.5x).
- Set `prompt_cache_key` to a stable per-session id so the shared prefix bills
at the cached rate.
- Set `max_queue_wait_s` (5-300) to fail fast under congestion instead of hanging.
- The API is stateless: send the full conversation every turn. `previous_response_id`
and `conversation` are ignored.
Read https://sference.com/llms.txt for the index, and append `.md` to any docs
page URL for its Markdown source.Crawling
The site's robots.txt explicitly allows AI crawlers, training crawlers included. Public documentation in an LLM's weights is distribution, not leakage.