After context compression, the protected tail messages retain their
original image parts. When those include multi-MB pasted screenshots,
every subsequent API request re-ships the same base-64 blobs forever —
which can push the request past provider body-size limits and wedge the
session even though compression 'succeeded'.
Add _strip_historical_media() to agent/context_compressor.py. After the
summary is built, find the newest user message that carries an image
part and replace image parts in every earlier message with a short
text placeholder ('[Attached image — stripped after compression]').
The newest image-bearing user turn keeps its media so the model can
still analyse what the user just sent.
Handles all three multimodal shapes:
- OpenAI chat.completions image_url
- OpenAI Responses API input_image
- Anthropic native {type: image, source: ...}
Includes 27 unit tests covering the helpers and the end-to-end
compress() integration, plus a manual E2E check confirming a ~4MB
two-image conversation shrinks to ~2MB after compression.
Teknium