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LlamaIndex integration

LlamaIndex's OpenAI LLM supports OpenAI-compatible endpoints. Set api_base to the abliteration.ai base URL.

Use the standard LlamaIndex interfaces while keeping your model and prompt logic intact.

Quick start

Example request
from llama_index.llms.openai import OpenAI

llm = OpenAI(
    model="abliterated-model",
    api_base="https://api.abliteration.ai/v1",
    api_key="YOUR_ABLIT_KEY",
)

response = llm.complete("Summarize this in one sentence.")
print(response.text)

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.

Related links