Endpoints

Every DirectInference request goes to one host with one key. This page is the full URL map across all three API surfaces plus the account & billing REST API. Each surface has a dedicated guide with request and response detail — the links are below each table.

Base URL and authentication

The advertised, API-only host is https://api.directinference.com. Every endpoint sits under the zero-knowledge DI base path /di. The authentication header is the one your client already uses for that vendor — point it at DirectInference and pass an llm_live_… key.

Surface	Base URL	Auth header
OpenAI-compatible	https://api.directinference.com/di/v1	Authorization: Bearer llm_live_…
Anthropic Messages	https://api.directinference.com/di — the SDK appends /v1/messages	x-api-key: llm_live_… (or Authorization: Bearer)
Gemini	https://api.directinference.com/di — the SDK appends /v1beta/models/…	x-goog-api-key: llm_live_… (or ?key= / Authorization: Bearer)

Full per-surface auth detail — including the header each SDK sets for you — is in Authentication.

Hosts and the legacy root path

api.directinference.com is the advertised host; use it for new integrations. The same API is also served at app.directinference.com for existing integrations. The surfaces also answer at the root (without the /di prefix) for older clients, but new integrations should use the …/di base shown here — it is the zero-knowledge surface where any model id resolves and is echoed back.

OpenAI-compatible

Method	Endpoint	Purpose
POST	https://api.directinference.com/di/v1/chat/completions	Chat Completions. Stream with "stream": true.
POST	https://api.directinference.com/di/v1/responses	Responses API (served statelessly).
GET	https://api.directinference.com/di/v1/models	List the DI Model — di-fusion, di-saver, di-max.

Request and response detail, including tools, vision, structured output, and supported parameters, is in the OpenAI-compatible guide.

Anthropic Messages

Method	Endpoint	Purpose
POST	https://api.directinference.com/di/v1/messages	Messages API. Stream with "stream": true.
POST	https://api.directinference.com/di/v1/messages/count_tokens	Count tokens for a Messages request.
GET	https://api.directinference.com/di/v1/models	List models. client.models.list() reads this in the Anthropic models shape.

Full detail — tool_use, streaming, cache_control, and the response envelope — is in the Anthropic Messages guide.

Gemini

The model and method live in the URL path — models/{model}:method — not the body. Any {model} id (for example gemini-2.5-flash) is accepted and echoed back as modelVersion.

Method	Endpoint	Purpose
POST	https://api.directinference.com/di/v1beta/models/{model}:generateContent	Generate content.
POST	https://api.directinference.com/di/v1beta/models/{model}:streamGenerateContent?alt=sse	Streaming generate content (SSE).
POST	https://api.directinference.com/di/v1beta/models/{model}:countTokens	Count tokens.
GET	https://api.directinference.com/di/v1beta/models	List models.

Full detail — function calling, streaming, and countTokens — is in the Gemini guide.

Model discovery

GET /di/v1/models lists the DI Model three ways: di-fusion (the default), plus di-saver and di-max — the same model with the effort knob pinned low and high, not separate models. Every entry carries root: "di-fusion". Listing requires authentication.

curl

curl https://api.directinference.com/di/v1/models \
  -H "Authorization: Bearer llm_live_..."

Python

from openai import OpenAI

client = OpenAI(
    api_key="llm_live_...",
    base_url="https://api.directinference.com/di/v1",
)

for m in client.models.list().data:
    print(m.id, "->", m.root)   # di-fusion -> di-fusion, di-saver -> di-fusion, ...

TypeScript

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "llm_live_...",
  baseURL: "https://api.directinference.com/di/v1",
});

for (const m of (await client.models.list()).data) {
  console.log(m.id, "->", (m as any).root); // di-fusion -> di-fusion, ...
}

A successful response (abridged):

{
  "object": "list",
  "data": [
    {
      "id": "di-fusion",
      "object": "model",
      "owned_by": "direct-inference",
      "root": "di-fusion",
      "context_length": 262144,
      "top_provider": { "context_length": 262144, "max_completion_tokens": 32768 },
      "supported_parameters": [
        "max_tokens", "temperature", "top_p", "stop", "stream",
        "response_format", "reasoning_effort", "reasoning", "tools", "tool_choice"
      ]
    },
    { "id": "di-saver", "object": "model", "root": "di-fusion", "...": "same shape" },
    { "id": "di-max",   "object": "model", "root": "di-fusion", "...": "same shape" }
  ]
}

Read the catalog at runtime

The token-limit fields — context_length and top_provider.max_completion_tokens — reflect the live model and can change, so read them from this endpoint rather than hardcoding the values shown above. There is nothing else to pin: there is no model to choose, and any other model id you send is treated as intent and echoed back unchanged. See Capabilities.

Account & billing

A small read-only REST API reports balance and usage. It is account-scoped to the calling key and zero-knowledge — costs come back in USD, and no backend model, provider, or upstream price is ever exposed.

Method	Endpoint	Purpose
GET	https://api.directinference.com/di/v1/credits	Prepaid balance and total used.
GET	https://api.directinference.com/di/v1/usage	Aggregate usage; group_by of day, request_type, application, or api_key, with optional start_date / end_date.
GET	https://api.directinference.com/di/v1/generation?id=<completion-id>	Cost and token usage for one request, keyed by its response id.

curl https://api.directinference.com/di/v1/credits \
  -H "Authorization: Bearer llm_live_..."
# {"balance":"9.800000","total_used":"0.200000"}

See Spend & limits for caps and the balance lifecycle, and Usage & analytics for the in-portal breakdown.

Response feedback

Rate a response your application received, keyed by the id on the completion your code already holds — the same id accepted by GET /v1/generation. It is one REST call, no SDK required.

Method	Endpoint	Purpose
POST	https://api.directinference.com/di/v1/feedback	Record a thumbs up / down (plus optional comment, labels, and an opaque end-user id) on one response.

curl https://api.directinference.com/di/v1/feedback \
  -H "Authorization: Bearer llm_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "id": "chatcmpl-abc123",
    "rating": "up",
    "comment": "resolved the ticket cleanly",
    "labels": {"category": "support", "helpful": true},
    "end_user": "acct_7f3a"
  }'
# {"object":"feedback","id":"chatcmpl-abc123","rating":"up","recorded":true,"end_user":"acct_7f3a"}

• id (required) is the response id you received; rating (required) is up or down.
• comment is free text; labels is a flat object of string / number / boolean annotations; end_user is any opaque string you use to attribute the rating — DI never learns who your users are.
• Re-submitting for the same (id, end_user) updates the existing rating rather than adding a duplicate.
• An unknown or foreign id returns 404; a response older than 30 days returns 409. The endpoint is zero-knowledge and does not count toward usage.

Errors

Each surface returns its native error envelope, and authentication, rate-limit, and spend-cap behavior is shared. Status codes (400, 401, 402, 413, 429, 5xx) and retry guidance are in Errors & limits; the observability headers every response carries are in Response headers.

Dive into a surface

OpenAI-compatible Chat Completions, Responses, tools, vision, structured output.

Anthropic Messages Messages API, tool_use, streaming, cache_control.

Gemini generateContent, streaming, function calling, countTokens.

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