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Developer access / lower refusal

An uncensored LLM API with a visible contract

Build with BrokenGPT’s direct chat-completions API: no gateway prompt filter, private open-source model routing, JSON or SSE streaming, and token metering.

UPDATED 18 Jul 20268 MIN READTECHNICAL GUIDE
01

The endpoint is familiar. The supported subset is explicit.

BrokenGPT exposes POST /v1/chat/completions at https://brokengpt.com. Requests use a bearer API key, a public model alias, and an ordered array of role-based messages. Responses return JSON by default or server-sent events when stream is true.

“Uncensored” means the gateway does not block prompts before inference. “Compatible” describes a request and response shape. Neither word should be stretched into a claim that the endpoint implements every feature of another provider. The exact public contract is the API documentation.

AUTH / 01

Revocable bearer keys

Keys are authenticated server-side and can be managed independently from the browser session.

FORMAT / 02

JSON or SSE

Use a normal completion response or stream incremental chunks over server-sent events.

TRACE / 03

Request identifiers

Response and rate-limit headers make a live request easier to trace and diagnose.

USAGE / 04

Input + output metering

API calls spend credits and are labelled as API usage instead of chat usage in the dashboard.

02

One cURL request to the first streamed token.

Create an API key in the dashboard, keep it on the server, and send the public model alias shown in the live docs. The example below requests SSE streaming without adding an output-token cap, so the model can finish naturally.

POST /v1/chat/completions

curl https://brokengpt.com/v1/chat/completions \
  -H "Authorization: Bearer $BROKENGPT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "broken-one",
    "messages": [
      {"role": "user", "content": "Explain the tradeoff directly."}
    ],
    "stream": true,
    "temperature": 0.7
  }'
03

Know what the current chat-completions route accepts.

Current public request surface
FieldCurrent behaviorNotes
modelRequired public model aliasA mismatched alias returns a model-not-found error.
messagesRequired array of system, user, and assistant messagesContent is a string; one to 100 messages per request.
streamOptional booleanTrue returns text/event-stream chunks and a final DONE event.
temperature / top_pOptional sampling controlsTemperature accepts 0–2; top_p accepts 0–1.
max_tokensOptional caller-chosen capOmit it for natural completion; max_completion_tokens is accepted as an alias.
stop / userOptionalStop accepts one string or up to four strings; user is a short identifier.
tools / tool_choiceOptional function callingClients execute returned calls unless they build a separate hosted-tool workflow.
response_formatOptional validated JSONJSON object and JSON Schema formats complete before delivery and do not stream.
seed / Idempotency-KeyOptional reproducibility controlsSeeds depend on route support; idempotency applies to non-streamed calls.

Responses, batch inference, token counting, and usage reports have their own documented endpoints. Multimodal message parts, embeddings, image generation, hosted assistants, and private-route extensions are not implied by chat compatibility.

04

API usage costs credits—and remains separately visible.

A direct API request first checks the account’s credit balance and request-rate allowance. Successful completions record input tokens, output tokens, model alias, latency, API-key identifier, and request status. Streamed requests are recorded when the stream completes; failed inference records a failed status without fabricated output usage.

The account uses one prepaid balance across browser chat and API calls, while the usage view separates the two sources by color and totals. Current token prices belong on the pricing page, where they can change without making an old guide misleading.

05

The router selects capability, not permission.

Every valid API request is sent to the configured open-source model mixture. The gateway can select a specialist inference tier, but it does not return a platform-authored censorship response or stop prompts with a keyword gate.

The system page defines the stable public alias, private mixture, limits, and data flow. Build application-specific validation and human review on top; generated output can still be false, biased, insecure, or incomplete.

STRAIGHT ANSWERS

Frequently asked questions

01What makes this an uncensored LLM API?

BrokenGPT does not use a gateway moderation filter to block prompts. Every request reaches the configured open-source model mixture, though individual models can still choose how to answer.

02Is every OpenAI API feature supported?

No. BrokenGPT documents focused compatibility surfaces, not an entire third-party platform. The public API supports text chat, function tools, structured JSON, Responses, persisted batches, token counting, usage reports, and SSE streaming.

03Does API-key usage spend credits?

Yes. Successful direct API calls are metered for input and output tokens and spend from the same prepaid credit balance as chat. The dashboard separates API usage from chat usage for inspection.

04Does BrokenGPT impose a default output cap?

No. When you omit max_tokens, BrokenGPT does not inject a token ceiling. The model finishes naturally, subject to its context boundary and normal service runtime constraints.

BUILD AGAINST THE CONTRACT

Start with one request.

Create a key, send the chat-completions shape, then verify usage and response metadata in the dashboard.

Open API docs