Multimodal Input¶
FastAIAgent agents accept images, PDFs, and any file/bytes as first-class inputs alongside text. The same code works against OpenAI, Azure, Anthropic, Gemini, Bedrock, and Ollama — the SDK handles the provider-specific wire formatting and forwards files natively (never stringified, never rendered locally when the provider can parse them).
from fastaiagent import Agent, LLMClient, Image, PDF, File
agent = Agent(
name="claims",
llm=LLMClient(provider="anthropic", model="claude-sonnet-4-6"),
)
result = agent.run(
[
"Compare the photo to the policy and assess the claim.",
Image.from_file("damage.jpg"),
PDF.from_file("policy.pdf"),
]
)
print(result.output)
Or just hand the agent bytes / a path — the type is sniffed and wrapped in a
File automatically:
What's supported¶
| Capability | Status |
|---|---|
| Image input (JPEG, PNG, GIF, WebP) | Yes |
| PDF input (text / vision / native modes) | Yes |
Native PDF (OpenAI/Azure file, Anthropic/Bedrock document, Gemini inlineData) |
Yes |
Generic File input (any bytes, mime-routed) |
Yes |
Auto-detect bare bytes / Path |
Yes |
| Documents (csv/txt/html/md, docx/xlsx via Bedrock/Gemini) | Yes |
| Audio (wav/mp3 on OpenAI/Gemini) | Yes |
Tool returns Image / PDF |
Yes |
| Multimodal in Chain state (checkpointed) | Yes |
| Multimodal in Swarm shared context | Yes |
| Multimodal in eval JSONL datasets | Yes |
| Multimodal in trace inspector + Replay | Yes |
Input-only: image/audio generation and OCR-as-a-feature are out of scope. Which file types a given provider accepts natively varies — see the File routing matrix.
Read next¶
- When to use it — read this first if you're weighing the abstraction against just base64-encoding the file yourself. Honest decision rubric for when the layer earns its keep and when it's overkill.
- Images —
Imageconstructors, supported formats, sizes, the OpenAIdetailparameter. - PDFs —
PDFconstructors, text vs vision vs native modes. - Files (any type) — the generic
Fileinput, auto-detect, and the per-provider routing matrix. - Provider Support — capability matrix and auto-detection rules.
- Multimodal Eval — JSONL syntax for image/PDF references.