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FEAT: Support PDF and file inputs via `binary_path` in OpenAI chat and response targets

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Seit 16.10.2026.

Bewertung

Schwierigkeit
4/5
Geschätzter Aufwand
3-5 Tage
Anfängerfreundlichkeit
35/100
Issue-Typ
Feature
Klarheit
Größtenteils klar
Aktivitätsstatus
Aktiv
Tech-Stack
python
Bereich
ai, api

Rechercherichtung

Start from the binary_path message pieces that PDFConverter already produces, then read how OpenAIChatTarget and OpenAIResponseTarget build their request payloads and declare input capabilities. Reading the storage abstraction used to load files is also needed. Done means a request containing a PDF plus text serializes correctly for both targets, passes capability validation, survives history rebuilding, and has regression tests and a documented example.

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Beschreibung

feature-request help wanted
Is your feature request related to a problem? Please describe.

PyRIT represents files such as PDFs using binary_path, and converters such as PDFConverter already produce this type. However, OpenAIChatTarget and OpenAIResponseTarget do not currently support sending these files as native file inputs.

This leaves a gap between generating a file and submitting it to a model for document-based testing.

Describe the solution you'd like

Support binary_path message pieces in both targets, starting with PDFs and extending to other file formats where the selected API and model support them.

Expected behavior:

  • Read the referenced file through PyRIT's storage abstraction and serialize it into the appropriate Chat Completions or Responses API file-input format.
  • Support file-only messages, files alongside text instructions, and multiple files where supported by the API.
  • Update target input capabilities so requests containing binary_path pass validation.
  • Preserve file inputs when rebuilding conversation history.
  • Surface clear errors for unreadable files and unsupported inputs. Document API/model-specific format and size restrictions rather than implying that all binary files are supported.

Include request-serialization and regression tests for both targets, plus a documented example that sends a PDF with a text instruction.

Describe alternatives you've considered, if relevant

Extracting text from the PDF or converting its pages to images can work for some use cases, but changes how the model receives the document and does not exercise native file handling.

Manually building API requests outside these targets requires users to duplicate request-building logic.

Additional context

Related issues #423, #415, and #541 cover file generation and injection. This request covers the separate target responsibility of sending those files to the model.

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Python
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