Integrations
FastAPI integration
Create a small FastAPI endpoint that forwards prompts to abliteration.ai.
Keep your ABLIT_KEY in an environment variable and return the JSON response.
Quick start
Base URL
Example request
from fastapi import FastAPI
from pydantic import BaseModel
import httpx
import os
app = FastAPI()
class ChatIn(BaseModel):
prompt: str
@app.post("/chat")
async def chat(payload: ChatIn):
async with httpx.AsyncClient() as client:
res = await client.post(
"https://api.abliteration.ai/v1/chat/completions",
headers={
"Authorization": f"Bearer {os.environ['ABLIT_KEY']}",
"Content-Type": "application/json",
},
json={
"model": "abliterated-model",
"messages": [{"role": "user", "content": payload.prompt}],
},
)
return res.json()Free preview for 5 messages. Sign up to continue.
Service notes
- Pricing model: Usage-based pricing (~$5 per 1M tokens) billed on total tokens (input + output). See the API pricing page for current plans.
- Data retention: No prompt/output retention by default. Operational telemetry (token counts, timestamps, error codes) is retained for billing and reliability.
- Compatibility: OpenAI-style /v1/chat/completions request and response format with a base URL switch.
- Latency: Depends on model size, prompt length, and load. Streaming reduces time-to-first-token.
- Throughput: Team plans include priority throughput. Actual throughput varies with demand.
- Rate limits: Limits vary by plan and load. Handle 429s with backoff and respect any Retry-After header.
Common errors & fixes
- 401 Unauthorized: Check that your API key is set and sent as a Bearer token.
- 404 Not Found: Make sure the base URL ends with /v1 and you call /chat/completions.
- 400 Bad Request: Verify the model id and that messages are an array of { role, content } objects.
- 429 Rate limit: Back off and retry. Use the Retry-After header for pacing.