OpenAI-compatible clinical model

Build clinical software on Olive

Olive is Avey's clinical language model. It reasons before it answers, reads the documents you upload, and runs behind the OpenAI API. Change three values in the SDK you already use, and call it.

Make your first call Get an API key

first_call.py

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.avey.ai/llm",  
    api_key=os.environ["AVEY_API_KEY"],  
)

response = client.chat.completions.create(
    model="olive",  
    messages=[{"role": "user", "content": "Red flags for headache in primary care?"}],
)

message = response.choices[0].message
print(getattr(message, "reasoning_content", None))  # how Olive worked it through
print(message.content)  # the answer

Start here

Three pages answer most first questions

QuickstartCreate an API key, send your first request to Olive, and read the response.OpenAI compatibilityWhich OpenAI endpoints, request fields, and response fields Avey Olive supports, and which it does not.ErrorsStatus codes, what each one means and what to do, and the shape of the error body.

The model

The numbers to size a request against

Model id

olive

Text in, text out. Reasoning comes back in reasoning_content.

Context window: 65,536tokens, prompt and output
Max output: 16,384tokens, reasoning included
File uploads: 5MB, up to 100 pages
Model calls: 60per minute, 10,000 per day

Every limit and the model list response are on Models and limits. The effort budgets are on Reasoning.

Guides

What you can build

ReasoningRead Olive's reasoning apart from its answer, and set how much it reasons.StreamingReceive Olive's answer as it is generated, as server-sent events.Structured outputsParse and validate Olive's JSON before your code stores or acts on it.ToolsLet Olive call your functions, or search your vector stores, in a Responses request.FilesUpload a document or image, then ask Olive about it by file ID.Vector storesIndex documents too large for the prompt, then search them, or let Olive search them while it answers.Conversation stateContinue a conversation with previous_response_id, and keep a long conversation inside the context window.Web searchComing soonLet Olive search the web while it answers. Coming soon.

Clinical use

A clinician reviews every output

Olive supports clinical work. It does not replace clinical judgement. A qualified clinician reviews every output that affects care before it is acted on, and that holds for the reasoning too. Olive can be confidently wrong.

Do not send protected health information. Remove names, contact details, identifiers and dates of birth before text or files reach the API.

Use casesThe clinical tasks Olive is built for, what each request carries, and what to check before the output is used.Build with AI toolsGive a coding assistant these docs in a form it reads well, so the code it writes uses the right model id, key header and reasoning field.