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Documentation Index

Fetch the complete documentation index at: https://docs.opper.ai/llms.txt

Use this file to discover all available pages before exploring further.

Put an image or a PDF into a chat message and the model can read it. It’s the same messages array, with a richer content field. Not every model supports every input type. See the models catalog for which models accept images and which accept PDFs.

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Images

Two ways to send an image: a hosted URL or inline base64. 
import os, base64
from openai import OpenAI

client = OpenAI(
    base_url="https://api.opper.ai/v3/compat",
    api_key=os.environ["OPPER_API_KEY"],
)

# Hosted URL
r = client.chat.completions.create(
    model="openai/gpt-5-mini",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What's in this picture?"},
            {"type": "image_url", "image_url": {"url": "https://example.com/cat.jpg"}},
        ],
    }],
)
print(r.choices[0].message.content)

# Inline base64
with open("cat.jpg", "rb") as f:
    b64 = base64.b64encode(f.read()).decode()
r = client.chat.completions.create(
    model="openai/gpt-5-mini",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What's in this picture?"},
            {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64}"}},
        ],
    }],
)
Use the URL form when the image is already on the web. Use base64 for local files or anything not publicly reachable.

​
PDFs

PDFs work the same way. The model reads both the text and any embedded images (charts, diagrams, scanned pages).
Python
import base64

with open("contract.pdf", "rb") as f:
    b64 = base64.b64encode(f.read()).decode()

r = client.chat.completions.create(
    model="openai/gpt-5-mini",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Summarize the key clauses in this contract."},
            {"type": "file", "file": {"file_data": f"data:application/pdf;base64,{b64}"}},
        ],
    }],
)
print(r.choices[0].message.content)

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Chat vs JSON for media

NeedReach for
Show an image and ask a free-text question about itChat API (this page)
Extract structured fields from an image or PDF (a receipt, an invoice, a form)JSON API with output_schema
Run a multi-turn conversation about an uploaded documentChat API (this page)
Batch process documents into a databaseJSON API
Use the JSON API when you want structured JSON out of an image. Use Chat when the model needs to converse about the media.

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What’s next

JSON API: schemas

Multimodal input with typed JSON output.

Conversations

Multi-turn chat. Works with image and PDF messages too.

Models

Which models accept which input types.